Assessment of the correlation between supracrestal gingival tissue dimensions and other periodontal phenotypes components via the digital registration method: a cross­sectional study in a Chinese population.

BACKGROUND: Supracrestal gingival tissue dimensions (SGTDs) has been considered to be an essential element of periodontal phenotype (PP) components. This study aimed to explore the relationship between SGTDs and other PP components by digital superposition method that integrated cone beam computed tomography (CBCT) with intraoral scanning. METHODS: This cross-sectional study was conducted at the Stomatology Hospital of Fujian Medical University. Participants were recruited based on the inclusion and exclusion criteria. The data obtained from the digital scanner (TRIOS 3, 3Shape, Denmark) and CBCT images were imported into the TRIOS software (Implant Studio, 3Shape, Denmark) for computing relevant parameters. The significant level was set at 0.05. RESULTS: A total of 83 participants with 498 maxillary anterior teeth were finally included. The mean values of supracrestal gingival height (SGH) and the distance from the cementoenamel junction (CEJ) to the crest of the alveolar ridge (CEJ-ABC) on the buccal site were significantly higher than palatal SGH (SGH-p) and palatal CEJ-ABC (CEJ-ABC-p). Men exhibited taller CEJ-ABC and SGH-p than women. Additionally, tooth type was significantly associated with the SGH, SGH-p and CEJ-ABC-p. Taller SGH was associated with wider crown, smaller papilla height (PH), flatter gingival margin, thicker bone thickness (BT) and gingival thickness (GT) at CEJ, the alveolar bone crest (ABC), and 2 mm apical to the ABC. Smaller SGH-p displayed thicker BT and GT at CEJ, the ABC, and 2 and 4 mm apical to the ABC. Higher CEJ-ABC showed lower interproximal bone height, smaller PH, flatter gingival margin, thinner GT and BT at CEJ, and 2 mm apical to the ABC. Smaller CEJ-ABC-p displayed thicker BT at CEJ and 2 and 4 mm apical to the ABC. On the buccal, thicker GT was correlated with thicker BT at 2 and 4 mm below the ABC. CONCLUSION: SGTDs exhibited a correlation with other PP components, especially crown shape, gingival margin and interdental PH. The relationship between SGTDs and gingival and bone phenotypes depended on the apico-coronal level evaluated. TRIAL REGISTRATION: This study was approved by the Biomedical Research Ethics Committee of Stomatology Hospital of Fujian Medical University (approval no. 2023-24).

Changes in disease burden and global inequalities in bladder, kidney and prostate cancers from 1990 to 2019: a comparative analysis based on the global burden of disease study 2019.

BACKGROUND: Bladder, kidney and prostate cancers make significant contributors to cancer burdens. Exploring their cross-country inequalities may inform equitable strategies to meet the 17 sustainable development goals before 2030. METHODS: We analyzed age-standardized disability-adjusted life-years (ASDALY) rates for the three cancers based on Global Burden of Diseases Study 2019. We quantified the inequalities using slope index of inequality (SII, absolute measure) and concentration index (relative measure) associated with national sociodemographic index. RESULTS: Varied ASDALY rates were observed in the three cancers across 204 regions. The SII decreased from 35.15 (95% confidence interval, CI: 29.34 to 39.17) in 1990 to 15.81 (95% CI: 7.99 to 21.79) in 2019 for bladder cancers, from 78.94 (95% CI: 75.97 to 81.31) in 1990 to 59.79 (95% CI: 55.32 to 63.83) in 2019 for kidney cancer, and from 192.27 (95% CI: 137.00 to 241.05) in 1990 to - 103.99 (95% CI: - 183.82 to 51.75) in 2019 for prostate cancer. Moreover, the concentration index changed from 12.44 (95% CI, 11.86 to 12.74) in 1990 to 15.72 (95% CI, 15.14 to 16.01) in 2019 for bladder cancer, from 33.88 (95% CI: 33.35 to 34.17) in 1990 to 31.13 (95% CI: 30.36 to 31.43) in 2019 for kidney cancer, and from 14.61 (95% CI: 13.89 to 14.84) in 1990 to 5.89 (95% CI: 5.16 to 6.26) in 2019 for prostate cancer. Notably, the males presented higher inequality than females in both bladder and kidney cancer from 1990 to 2019. CONCLUSIONS: Different patterns of inequality were observed in the three cancers, necessitating tailored national cancer control strategies to mitigate disparities. Priority interventions for bladder and kidney cancer should target higher socioeconomic regions, whereas interventions for prostate cancer should prioritize the lowest socioeconomic regions. Additionally, addressing higher inequality in males requires more intensive interventions among males from higher socioeconomic regions.

Enhancing economic competitiveness analysis through machine learning: Exploring complex urban features.

Urban economic competitiveness is a fundamental indicator for assessing the level of urban development and serves as an effective approach for understanding regional disparities. Traditional economic competitiveness research that relies solely on traditional regression models and assumes feature relationship theory tends to fall short in fully exploring the intricate interrelationships and nonlinear associations among features. As a result, the study of urban economic disparities remains limited to a narrow range of urban features, which is insufficient for comprehending cities as complex systems. The ability of deep learning neural networks to automatically construct models of nonlinear relationships among complex features provides a new approach to research in this issue. In this study, a complex urban feature dataset comprising 1008 features was constructed based on statistical data from 283 prefecture-level cities in China. Employing a machine learning approach based on convolutional neural network (CNN), a novel analytical model is constructed to capture the interrelationships among urban features, which is applied to achieve accurate classification of urban economic competitiveness. In addition, considering the limited number of samples in the dataset owing to the fixed number of cities, this study developed a data augmentation approach based on deep convolutional generative adversarial network (DCGAN) to further enhance the accuracy and generalization ability of the model. The performance of the CNN classification model was effectively improved by adding the generated samples to the original sample dataset. This study provides a precise and stable analytical model for investigating disparities in regional development. In the meantime, it offers a feasible solution to the limited sample size issue in the application of deep learning in urban research.

Accuracy assessment and climatology of MODIS aerosol optical properties over North Africa.

In this study, the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) product was compared with ground-based measurements at five sites of the Aerosol Robotic Network (AERONET) in North Africa. The MODIS AOD showed a good correlation coefficient of ~0.78, a very small mean bias error of 0.009, and a root mean square error of 0.126 with AERONET. The Dark Target/Deep Blue (DT/DB) algorithm showed better performance at low aerosol loading while underestimating AOD at higher aerosol loading, mainly for coarse-dominated aerosol types. This work also showed the benefits of using MODIS retrievals as a reliable data source for aerosols and providing a long-term aerosol type classification. The primary aerosol type is dust emitted from the Sahara Desert, and the dusty atmosphere becomes gradually mixed with pollution aerosols approaching the coastal region. The annual mean MODIS AOD at 550 nm and Ångström exponent at 412-650 nm (AE) ranged from 0.17 to 0.45 and from 0.13 to 1.25, respectively, in Algeria between 2001 and 2019. Lower AOD (< 0.22) and higher AE (> 1) were found in the northern region, while the highest AOD (0.35 to 0.45) and the lowest AE (< 0.25) were observed over the Tanezrouft desert in southern Algeria. The seasonal mean AOD was highest in summer, while the lowest was in winter due to very high easterly and northeasterly Harmattan surface wind over Zone of Chotts and the Tidikelt Depression, respectively. The negative AOD trends observed over Algeria could be partially connected to the decline (increase) in surface (850 hPa) winds over potential dust source areas in southern Algeria.

Spatial evolution of cultivated land in the Heilongjiang Province in China from 1980 to 2015.

Sustaining cultivated land is critically important for food security, economic development, and social stability in China. China has been developing rapidly since the adoption of the Chinese Economic Reform of 1978, revealing the spatial evolution characteristics of cultivated land can provide valuable information for estimating and sustaining Chinese food security. In this study, we analyzed the spatial evolution of cultivated land from 1980 to 2015 in the Heilongjiang Province, one of the most important grain production regions in China, by combining five land-use databases, a geographic information system, and mathematical models. The results showed that cultivated land in the Heilongjiang Province increased by 33,234 km2 (23%) from 1980 to 2015. The increase primarily resulted from land conversion from the forest (11,511 km2), grassland (9780 km2), and unused land (9696 km2). Additionally, cultivated land-use change's spatial characteristics differed among decadal periods. Spatial changes were stronger during 1990-2000 than in the other periods (1980-1990, 2000-2010, and 2010-2015). The landscape shape index indicated that cultivated land development had a regular changing pattern but showed a trend toward irregular development over the study period. The spatial expansion of cultivated land showed a strong directional trend, which was further found to be associated with geomorphological factors, indicating the prominent controls of abiotic factors on cultivated land expansion. This study provides an overview of the long-term spatial evolution characteristics of cultivated land and the key abiotic controls on cultivated land use change. This information can help local government policymakers effectively balance regional development, environmental protection, and food security.

Global, regional, and national burden of kidney, bladder, and prostate cancers and their attributable risk factors, 1990-2019.

BACKGROUND: The burden of kidney, bladder, and prostate cancers has changed in recent decades. This study aims to investigate the global and regional burden of, and attributable risk factors for genitourinary cancers during the past 30 years. METHODS: We extracted data of kidney, bladder, and prostate cancers from the Global Burden of Disease 2019 database, including incidence, mortality, disability-adjusted life-years (DALYs), and attributable risk factors from 1990 to 2019. Estimated annual percentage changes (EAPC) were calculated to assess the changes in age-standardized incidence rate, age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR). The associations between cancers burden and socio-demographic index (SDI) were also analyzed. RESULTS: Compared with 1990, the global incident cases in 2019 were higher by 154.78%, 123.34%, and 169.11% for kidney, bladder, and prostate cancers, respectively. During the 30-year study period, there was a downward trend in ASMR and ASDR for bladder cancer (EAPC = - 0.68 and - 0.83, respectively) and prostate cancer (EAPC = - 0.75 and - 0.71, respectively), but an upward trend for kidney cancer (EAPC = 0.35 and 0.12, respectively). Regions and countries with higher SDI had higher incidence, mortality, and DALYs for all three types of cancers. The burden of bladder and prostate cancers was mainly distributed among older men, whereas the burden of kidney cancer increased among middle-aged men. Smoking related mortality and DALYs decreased, but high body mass index (BMI) and high fasting plasma glucose (FPG) related mortality and DALYs increased among kidney, bladder, and prostate cancers during the study period. CONCLUSIONS: Kidney, bladder, and prostate cancers remain major global public health challenges, but with distinct trend for different disease entity across different regions and socioeconomic status. More proactive intervention strategies, at both the administrative and academic levels, based on the dynamic changes, are needed.

Global, Regional, and National Incidence and Year Lived with Disability for Benign Prostatic Hyperplasia from 1990 to 2019.

The objective of this study is to provide comprehensive and up-to-date estimates on the disease burden of BPH in 204 countries and territories between 1990 and 2019. Data about incidence, year lived with disability (YLD), and their age-standardized rates (ASRs) for 21 regions, 5 Socio-demographic Index (SDI) quintiles, 204 countries and territories, and 12 age categories from 1990 to 2019 were obtained from the Global Burden of Disease 2019 study. Estimated annual percentage changes (EAPCs) of the ASRs and the associations between SDI and the ASRs were estimated. The effects of population growth, population aging, and age-specific rate on the changes in the absolute numbers of incidence and YLD were quantified. Globally, there were 11.26 million (95% uncertainty interval [UI]: 8.79, 14.46) new cases and 1.86 million (95%UI: 1.13, 2.78) YLD due to BPH in 2019. The global ASRs of incidence (EAPC: -0.031, 95% CI: -0.050, -0.012) and YLD (EAPC: -0.058, 95% CI: -0.084, -0.031) decreased slightly from 1990 to 2019, whereas the absolute numbers increased dramatically from 1990 (incidence by 105.7% and YLD by 110.6%), mainly driven by the population growth (53.5% for incidence and 54.4% for YLD) and population aging (55.7% for incidence and 63.2% for YLD). The burden of BPH varied markedly among different regions, socioeconomic status, and countries. As the population is growing and aging, great efforts are required to develop effective prevention, treatment and management strategies to meet the high and increasing burden of BPH worldwide.

Impact of subsidies on innovations of environmental protection and circular economy in China.

Technological innovations in China's energy conservation and environmental protection industry (EEPI) are capital-intensive and useful to mitigate environmental externality, thus they need policy support and government subsidies (GSs) at the emerging stage. Nevertheless, research is limited on the influence of GSs onto innovation performance of China's EEPI, with particular to the effect of GSs from enterprise level. This study investigated 62 listed energy conservation and environmental protection enterprises (EEPEs) in China's market in 2013-2018. The innovation performance of these enterprises was quantitatively evaluated, and multivariate regression models were devised to examine GSs and other potential drivers that might influence the innovation. Key findings include (1) EEPEs' investment in R&D and protection of intellectual properties played a positive intermediary and regulatory role between GSs and enterprise innovation performance (correlation at the significance level of 0.05 (p = 0.045; p = 0.036)). (2) There is a significant positive correlation at the significance level of 0.05 (p = 0.011), which indicates that the strongest positive relation between GSs and innovation performance was identified in an environment of low external regulation and high internal regulation, and the effects were more significant for non-state-owned EEPEs(correlation at the significance level of 0.05 (p = 0.018)). (3) The promotion of GSs to innovation was found less effective in the three most developed regions in China, i.e., the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Area. Nonetheless it was more effective for enterprise engaged in the circular economy and resource recycling (correlation at a significant level of 0.05 (P = 0.048)). These findings may shed lights on decision making of green technology development for environmental conservation and circular economy.

Automated Brain Region Segmentation for Single Cell Resolution Histological Images Based on Markov Random Field.

The brain consists of massive regions with different functions and the precise delineation of brain region boundaries is important for brain region identification and atlas illustration. In this paper we propose a hierarchical Markov random field (MRF) model for brain region segmentation, where a MRF is applied to the downsampled low-resolution images and the result is used to initialize another MRF for the original high-resolution images. A fractional differential feature and a gray level co-occurrence matrix are extracted as the observed vector for the MRF and a new potential energy function, which can capture the spatial characteristic of brain regions, is proposed as well. A fuzzy entropy criterion is used to fine-tune the boundary from the hierarchical MRF model. We test the model both on synthetic images and real histological mouse brain images. The result suggests that the model can accurately identify target regions and even the whole mouse brain outline as a special case. An interesting observation is that the model cannot only segment regions with different cell density but also can segment regions with similar cell density and different cell morphology texture. Thus this model shows great potential for building the high-resolution 3D brain atlas.

North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget.

The terrestrial ecosystems of North America have been identified as a sink of atmospheric CO2 though there is no consensus on the magnitude. However, the emissions of non-CO2 greenhouse gases (CH4 and N2O) may offset or even overturn the climate cooling effect induced by the CO2 sink. Using a coupled biogeochemical model, in this study, we have estimated the combined global warming potentials (GWP) of CO2, CH4 and N2O fluxes in North American terrestrial ecosystems and quantified the relative contributions of environmental factors to the GWP changes during 1979-2010. The uncertainty range for contemporary global warming potential has been quantified by synthesizing the existing estimates from inventory, forward modeling, and inverse modeling approaches. Our "best estimate" of net GWP for CO2, CH4 and N2O fluxes was -0.50 ± 0.27 Pg CO2 eq/year (1 Pg = 1015 g) in North American terrestrial ecosystems during 2001-2010. The emissions of CH4 and N2O from terrestrial ecosystems had offset about two thirds (73 %±14 %) of the land CO2 sink in the North American continent, showing large differences across the three countries, with offset ratios of 57 % ± 8 % in US, 83 % ± 17 % in Canada and 329 % ± 119 % in Mexico. Climate change and elevated tropospheric ozone concentration have contributed the most to GWP increase, while elevated atmospheric CO2 concentration have contributed the most to GWP reduction. Extreme drought events over certain periods could result in a positive GWP. By integrating the existing estimates, we have found a wide range of uncertainty for the combined GWP. From both climate change science and policy perspectives, it is necessary to integrate ground and satellite observations with models for a more accurate accounting of these three greenhouse gases in North America.