Biomechanical analysis of the Maxillary Sinus Floor Membrane During internal Sinus Floor Elevation With Implants at Different angles of the Maxillary Sinus angles

OBJECTIVE: This study analyzed and compared the biomechanical properties of maxillary sinus floor mucosa with implants at three different maxillary sinus angles during a modified internal sinus floor elevation procedure. METHODS: 3D reconstruction of the implant, maxillary sinus bone, and membrane were performed. The maxillary sinus model was set at three different angles. Two internal maxillary sinus elevation models were established, and finite element analysis was used to simulate the modified maxillary sinus elevation process. The implant was elevated to 10 mm at three maxillary sinus angles when the maxillary sinus floor membrane was separated by 0 and 4 mm. The stress of the maxillary sinus floor membrane was analyzed and compared. RESULTS: When the maxillary sinus floor membrane was separated by 0 mm and elevated to 10 mm, the peak stress values of the implant on the maxillary sinus floor membrane at three different angles were as follows: maxillary sinus I: 5.14-78.32 MPa; maxillary sinus II: 2.81-73.89 MPa; and maxillary sinus III: 2.82-51.87 MPa. When the maxillary sinus floor membrane was separated by 4 mm and elevated to 10 mm, the corresponding values were as follows: maxillary sinus I: 0.50-7.25 MPa; maxillary sinus II: 0.81-16.55 MPa; and maxillary sinus III: 0.49-22.74 MPa. CONCLUSION: The risk of sinus floor membrane rupture is greatly reduced after adequate dissection of the maxillary sinus floor membrane when performing modified internal sinus elevation in a narrow maxillary sinus. In a wide maxillary sinus, the risk of rupture or perforation of the wider maxillary sinus floor is reduced, regardless of whether traditional or modified internal sinus elevation is performed at the same height

Amino acid Formula induces Microbiota Dysbiosis and Depressive-Like Behavior in Mice

Amino acid formula (AAF) is increasingly consumed in infants with cow\u27s milk protein allergy; however, the long-term influences on health are less described. In this study, we established a mouse model by subjecting neonatal mice to an amino acid diet (AAD) to mimic the feeding regimen of infants on AAF. Surprisingly, AAD-fed mice exhibited dysbiotic microbiota and increased neuronal activity in both the intestine and brain, as well as gastrointestinal peristalsis disorders and depressive-like behavior. Furthermore, fecal microbiota transplantation from AAD-fed mice or AAF-fed infants to recipient mice led to elevated neuronal activations and exacerbated depressive-like behaviors compared to that from normal chow-fed mice or cow\u27s-milk-formula-fed infants, respectively. Our findings highlight the necessity to avoid the excessive use of AAF, which may influence the neuronal development and mental health of children

Seizing the window of opportunity to mitigate the impact of climate change on the health of Chinese residents

The health threats posed by climate change in China are increasing rapidly. Each province faces different health risks. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate and even prevent the achievement of the Healthy and Beautiful China initiatives. The 2021 China Report of the Lancet Countdown on Health and Climate Change is the first annual update of China’s Report of the Lancet Countdown. It comprehensively assesses the impact of climate change on the health of Chinese households and the measures China has taken. Invited by the Lancet committee, Tsinghua University led the writing of the report and cooperated with 25 relevant institutions in and outside of China. The report includes 25 indicators within five major areas (climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement) and a policy brief. This 2021 China policy brief contains the most urgent and relevant indicators focusing on provincial data: The increasing health risks of climate change in China; mixed progress in responding to climate change. In 2020, the heatwave exposures per person in China increased by 4.51 d compared with the 1986–2005 average, resulting in an estimated 92% increase in heatwave-related deaths. The resulting economic cost of the estimated 14500 heatwave-related deaths in 2020 is US$176 million. Increased temperatures also caused a potential 31.5 billion h in lost work time in 2020, which is equivalent to 1.3% of the work hours of the total national workforce, with resulting economic losses estimated at 1.4% of China’s annual gross domestic product. For adaptation efforts, there has been steady progress in local adaptation planning and assessment in 2020, urban green space growth in 2020, and health emergency management in 2019. 12 of 30 provinces reported that they have completed, or were developing, provincial health adaptation plans. Urban green space, which is an important heat adaptation measure, has increased in 18 of 31 provinces in the past decade, and the capacity of China’s health emergency management increased in almost all provinces from 2018 to 2019. As a result of China’s persistent efforts to clean its energy structure and control air pollution, the premature deaths due to exposure to ambient particulate matter of 2.5 μm or less (PM2.5) and the resulting costs continue to decline. However, 98% of China’s cities still have annual average PM2.5 concentrations that are more than the WHO guideline standard of 10 μg/m3. It provides policymakers and the public with up-to-date information on China’s response to climate change and improvements in health outcomes and makes the following policy recommendations. (1) Promote systematic thinking in the related departments and strengthen multi-departmental cooperation. Sectors related to climate and development in China should incorporate health perspectives into their policymaking and actions, demonstrating WHO’s and President Xi Jinping’s so-called health-in-all-policies principle. (2) Include clear goals and timelines for climate-related health impact assessments and health adaptation plans at both the national and the regional levels in the National Climate Change Adaptation Strategy for 2035. (3) Strengthen China’s climate mitigation actions and ensure that health is included in China’s pathway to carbon neutrality. By promoting investments in zero-carbon technologies and reducing fossil fuel subsidies, the current rebounding trend in carbon emissions will be reversed and lead to a healthy, low-carbon future. (4) Increase awareness of the linkages between climate change and health at all levels. Health professionals, the academic community, and traditional and new media should raise the awareness of the public and policymakers on the important linkages between climate change and health.</p

Dynamic Bayesian models for modelling environmental space-time fields

This thesis addresses spatial interpolation and temporal prediction using air pollution data by several space-time modelling approaches. Firstly, we implement the dynamic linear modelling (DLM) approach in spatial interpolation and find various potential problems with that approach. We develop software to implement our approach. Secondly, we implement a Bayesian spatial prediction (BSP) approach to model spatio-temporal ground-level ozone fields and compare the accuracy of that approach with that of the DLM. Thirdly, we develop a Bayesian version empirical orthogonal function (EOF) method to incorporate the uncertainties due to temporally varying spatial process, and the spatial variations at broad- and fine- scale. Finally, we extend the BSP into the DLM framework to develop a unified Bayesian spatio-temporal model for univariate and multivariate responses. The result generalizes a number of current approaches in this field.Science, Faculty ofStatistics, Department ofGraduat

Dynamical analysis in dual-memristor-based FitzHugh–Nagumo circuit and its coupling finite-time synchronization

This paper presents an improved dual-memristor-based FitzHugh–Nagumo (DM-FHN) system, which is a non-autonomous circuit derived from FitzHugh–Nagumo (FHN) neuron circuit by substituting the tunnel diode with hyperbolic tangent memductance and connecting an active charge-controlled memristor in series with an inductor. The analysis model of the system is established first, and the rich dynamic behaviors of the system, varying with the circuit component parameters, are studied via the phase diagram, bifurcation diagram and Lyapunov exponential spectrum. Some interesting phenomena, such as bifurcation, periodic-chaotic state transition, periodic-chaotic bubbles, multistability phenomenon, and symmetrical behaviors, are observed. The finite-time synchronization of two coupled DM-FHN neurons for different behaviors due to different initial conditions is also studied. The cubic flux-controlled memristor is used as a synapse between the coupling circuits. The sufficient synchronization conditions for the unidirectional and bidirectional coupling DM-FHN circuits are derived respectively and the influence of the system initial values on the coupling synchronization is also investigated. The rich synchronous dynamics of the coupled DM-FHN systems are illustrated by the numerical simulations, the result of which also validates the presented analysis model

Temporal Forecasting with a Bayesian Spatial Predictor: Application to Ozone

This paper develops and empirically compares two Bayesian and empirical Bayes space-time approaches for forecasting next-day hourly ground-level ozone concentrations. The comparison involves the Chicago area in the summer of 2000 and measurements from fourteen monitors as reported in the EPA's AQS database. One of these approaches adapts a multivariate method originally designed for spatial prediction. The second is based on a state-space modeling approach originally developed and used in a case study involving one week in Mexico City with ten monitoring sites. The first method proves superior to the second in the Chicago Case Study, judged by several criteria, notably root mean square predictive accuracy, computing times, and calibration of 95% predictive intervals