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Should we report Breslow density, a new concept in cutaneous melanoma?

Secinti IE, Gursoy D, Erturk T, Dede I, Ozgur T, Dogan E

Malays J Pathol, 2021 Dec;43(3):397-404.
PMID: 34958061

INTRODUCTION: Breslow density is a newly defined biomarker, independent of Breslow thickness. We aimed to investigate the relationship of Breslow density with other clinicopathological prognostic factors and its effect on the overall survival and disease-free survival in patients with cutaneous melanomas.
MATERIALS & METHODS: This was a single-centre retrospective study of patients (n = 19) diagnosed with cutaneous malignant melanomas in our hospital between 2011 and 2019 were included in the study. The exclusion criteria were in situ melanomas, punch or incisional biopsies and metastasis at the time of the diagnosis. Breslow density was determined by reevaluating slides obtained at the time of the initial diagnoses. The effect of Breslow density on survival was determined using univariate and multivariate Cox proportional risk analyses.
RESULTS: In terms of the overall survival, mortality risk increased as Breslow density increased (p = 0.044). Breslow density was not significantly associated with the overall survival in the multivariate model (p = 0.078). In terms of disease-free survival, the risk of metastasis or recurrence increased 1.229- fold in accordance with an increase in Breslow thickness (CI: 1.057-1.428), whereas increased Breslow density increased the metastasis or recurrence risk 1.059-fold (CI: 1.008-1.112). In the multivariate model, only Breslow density was statistically significant (p = 0.046).
CONCLUSIONS: As a semi-quantitative and subjective measurement, Breslow density is not a completely accurate representation of the invasive tumour load. However, the measurement is practical and low cost and requires no additional equipment. Therefore, Breslow density can be measured in every laboratory. Considering the value of Breslow density in predicting the prognosis in patients with cutaneous melanomas and strong inter-observer compliance observed in the present study, we believe that it would be useful to include this measurement in pathology reports.
Ecological footprints and sustainable environmental management: A critical view of China's economy

Li M, Badeeb RA, Dogan E, Gu X, Zhang H

J Environ Manage, 2023 Dec 01;347:118994.
PMID: 37722155 DOI: 10.1016/j.jenvman.2023.118994

Global economies have recently been concerned about sustainable environmental management by reducing emissions and tackling ecological footprints. The rapid economic expansion and investment in traditional manufacturing further raises environmental degradation. China surpasses other emerging economies in the economic growth race yet has remained the top pollution-emitting economy for the last few decades, necessitating scholarly attention. This study examines the influencing factors of ecological footprints in China from the perspective of COP27. Using the extended dataset from 1988 to 2021, this study uses several time series diagnostic tests and verifies the existence of the long-run association between the study variables. Consequently, the non-linear scattered data leads to non-parametric (method of moment quantile regression) adoption. The empirical results indicate that only economic growth is a significant factor in environmental quality degradation in China. However, improving renewable energy usage, research and development, and foreign direct investment reduces the country's ecological footprint. Hence, the latter variables substantially lead to environmental sustainability. The robustness of the results is confirmed via a robust non-parametric estimator and causality test. Based on the empirical results, this study recommends increased investment in research and development, renewable production, and foreign direct investment enhancement.
Fulltext Analyzing the nexus between environmental sustainability and clean energy for the USA

Dogan E, Mohammed KS, Khan Z, Binsaeed RH

Environ Sci Pollut Res Int, 2024 Apr;31(19):27789-27803.
PMID: 38517628 DOI: 10.1007/s11356-024-32765-5

Environmental sustainability is a key target to achieve sustainable development goals (SDGs). However, achieving these targets needs tools to pave the way for achieving SDGs and COP28 targets. Therefore, the primary objective of the present study is to examine the significance of clean energy, research and development spending, technological innovation, income, and human capital in achieving environmental sustainability in the USA from 1990 to 2022. The study employed time series econometric methods to estimate the empirical results. The study confirmed the long-run cointegrating relationship among CO2 emissions, human capital, income, R&D, technological innovation, and clean energy. The results are statistically significant in the short run except for R&D expenditures. In the long run, the study found that income and human capital contribute to further aggravating the environment via increasing CO2 emissions. However, R&D expenditures, technological innovation, and clean energy help to promote environmental sustainability by limiting carbon emissions. The study recommends investment in technological innovation, clean energy, and increasing R&D expenditures to achieve environmental sustainability in the USA.
How does technological innovation moderate the environmental impacts of economic growth, natural resource rents and trade openness?

Ehigiamusoe KU, Dogan E, Ramakrishnan S, Binsaeed RH

J Environ Manage, 2024 Dec;371:123229.
PMID: 39522189 DOI: 10.1016/j.jenvman.2024.123229

The objective of this study is to unravel the linear impacts of economic growth, technological innovation, natural resource rents and trade openness on carbon emissions in Malaysia during 1980-2021. It also unveils the moderating role of technological innovation on the impacts of economic growth, natural resource rents and trade openness on carbon emissions. It further analyses the nonlinear relationship between technological innovation and carbon emissions. It estimates the parameters with the Autoregressive Distributed Lag model technique. The results of the linear model reveal that economic growth, natural resource rents and trade openness contributes to carbon emissions while technological innovation mitigates carbon emissions. The disaggregated analysis of natural resource rents indicates that oil rents, natural gas rents and coal rents intensify carbon emissions while mineral rents and forest rents do not contribute to carbon emissions. The disaggregated analysis of trade openness shows that exports worsen carbon emissions while imports have tenuous effect. The disaggregated analysis of technological innovation indicates that innovation by non-residents mitigate carbon emissions while innovation by residents do not alleviate carbon emissions. Moreover, evidence from the interaction model reveals that technological innovation can favourably mitigate the adverse impacts of economic growth and trade openness on carbon emissions albeit it cannot alleviate the impact of natural resource rents on carbon emissions. Besides, the nonlinear model indicates a U-shaped relationship between technological innovation and carbon emissions. Unlike previous studies that typically focused on the direct impacts of these variables, this study unravels the impacts of the disaggregated components as well as provides insights into the moderating and nonlinear effects of technological innovation on carbon emissions. The implication of this study is that efforts to achieve a carbon-neutral economy should consider the direct and indirect impacts of economic growth, technological innovation, natural resource rents and trade openness. It is recommended for Malaysia to encourage technological innovation in her quest to abate the adverse environmental impacts of economic activities.