Periodontal health and quality of life in patients with chronic obstructive pulmonary disease

SummaryObjectiveTo evaluate the association of periodontal health and parameters of quality of life assessed in 306 Chinese patients with chronic obstructive pulmonary disease (COPD).MethodsPeriodontal status and respiratory function in 306 COPD patients were clinically evaluated and their quality of life was assessed using the standardized St George’s Respiratory Questionnaire (SGRQ).ResultsThe SGRQ scores were all significantly correlated with major lung function parameters (r2 = −0.37 to −0.28; all p < 0.0001) and Medical Research Council dyspnoea scale (r2 = 0.23 to 0.30; all p < 0.0001). The SGRQ scores also correlated with the 6-min walk test (r2 = −0.15 to −0.13; all p < 0.05). Of periodontal health parameters, missing tooth number and plaque index appeared to be related to the scores of quality of life. The age- and gender-adjusted Pearson’s correlation coefficients between missing teeth and total score, symptoms score, and activity score were 0.09, 0.12, and 0.12, respectively (all p < 0.05). The Pearson’s correlation coefficients between plaque index and symptoms score and activity score were 0.09 and 0.09 (p < 0.05). After adjusting for age, gender, body mass index, and smoking status, missing teeth remained significantly associated with symptom score (p = 0.030) and activity score (p = 0.033) while plaque index was significantly associated with symptom score (p = 0.007).ConclusionsPoor periodontal health as reflected by missing teeth and plaque index was significantly associated with lower quality of life in COPD patients. Our findings indicate the importance of promoting dental care in current public health strategies to improve the quality of life in COPD patients

Contrasting responses of soil microbial biomass and extracellular enzyme activity along an elevation gradient on the eastern Qinghai-Tibetan Plateau

Soil microbial community composition and extracellular enzyme activity are two main drivers of biogeochemical cycling. Knowledge about their elevational patterns is of great importance for predicting ecosystem functioning in response to climate change. Nevertheless, there is no consensus on how soil microbial community composition and extracellular enzyme activity vary with elevation, and little is known about their elevational variations on the eastern Qinghai-Tibetan Plateau, a region sensitive to global change. We therefore investigated the soil microbial community composition using phospholipid fatty acids (PLFAs) analysis, and enzyme activities at 2,820 m (coniferous and broadleaved mixed forest), 3,160 m (dark coniferous forest), 3,420 m (alpine dwarf forest), and 4,280 m (alpine shrubland) above sea level. Our results showed that soil microbial community composition and extracellular enzyme activities changed significantly along the elevational gradient. Biomass of total microbes, bacteria, and arbuscular mycorrhizal fungi at the highest elevation were the significantly lowest among the four elevations. In contrast, extracellular enzyme activities involved in carbon (C)-, nitrogen (N)-, and phosphorus (P)- acquiring exhibited the maximum values at the highest elevation. Total nutrients and available nutrients, especially P availability jointly explained the elevational pattern of soil microbial community, while the elevational variation of extracellular enzyme activities was dependent on total nutrients. Microbial metabolism was mainly C- and P-limited with an increasing C limitation but a decreasing P limitation along the elevational gradient, which was related significantly to mean annual temperature and total P. These results indicated a vital role of soil P in driving the elevational patterns of soil microbial community and metabolism. Overall, the study highlighted the contrasting responses of soil microbial biomass and extracellular enzyme activities to elevation, possibly suggesting the differences in adaption strategy between population growth and resource acquisition responding to elevation. The results provide essential information for understanding and predicting the response of belowground community and function to climate change on the eastern Qinghai-Tibetan Plateau

Cytidine-phosphate-guanosine oligodeoxynucleotides in combination with CD40 ligand decrease periodontal inflammation and alveolar bone loss in a TLR9-independent manner

Local administration of toll-like receptor 9 (TLR9), agonist cytidine-phosphate-guanosine oligodeoxynucleotide (CpG ODNs), and CD40 ligand (CD40L) can decrease ligature-induced periodontal inflammation and bone loss in wild type (WT) mouse. Objective: This study aimed to explore whether such effect is dependent on TLR9 signaling. Material and Methods: Purified spleen B cells isolated from WT C57BL/6J mice and TLR9 knockout (KO) mice were cultured for 48 hours under the following conditions: CD40L, CpG+CD40L, CpG at low, medium and high doses. We determined B cell numbers using a hemocytometer at 24 h and 48 h. Percentages of CD1dhiCD5+ B cells were detected by flow cytometry. Interleukin-10 (IL-10) mRNA expression and protein secretion were measured by quantitative real-time polymerase chain reaction (qRT-PCR) and by ELISA, respectively. The silk ligature was tied around the maxillary second molars for 14 days, during which the CpG+CD40L mixture or PBS was injected into palatal gingiva on days 3, 6, and 9. Results: For both WT and TLR9 KO mice, CpG significantly induced B cell proliferation, increased IL-10 mRNA expression and protein secretion of IL-10 but reduced CD1dhiCD5+ B cells population; local injection of CpG+CD40L mixture significantly decreased alveolar bone loss and the number of TRAP-positive cells adjacent to the alveolar bone surface, and significantly increased the gingival mRNA expression of IL-10 and decreased RANKL and IFN-γ mRNA expression. Conclusions: These results indicated that CpG plus CD40L decreased periodontal inflammation and alveolar bone loss in a TLR9-independent manner in ligature-induced experimental periodontitis

Periodontal health: A national cross‐sectional study of knowledge, attitudes and practices for the public oral health strategy in China

Aim To assess the status of periodontal health knowledge, attitudes and practices (KAP) among Chinese adults. Materials and Methods A cross‐sectional study was conducted in a nationally representative sample of adults (N = 50,991) aged 20 years or older from ten provinces, autonomous regions, and municipalities. Percentages of Chinese adults with correct periodontal knowledge, positive periodontal attitudes, and practices were estimated. Multiple logistic regression analyses were used to examine the related factors. Results Less than 20% of Chinese adults were knowledgeable about periodontal disease. Very few (2.6%) of Chinese adults use dental floss ≥once a day and undergo scaling ≥once a year and visit a dentist (6.4%) in the case of gingival bleeding. Periodontal health KAP was associated with gender, age, body mass index, marital status, place of residence, education level, income, smoking status, and history of periodontal disease. Conclusions Periodontal health KAP are generally poor among the Chinese adult population. Community‐based health strategies to improve periodontal health KAP need to be implemented. Increasing knowledge of periodontal disease, the cultivation of correct practices in response to gingival bleeding, and the development of good habits concerning the use of dental floss and regular scaling should be public oral health priorities

Microinjection Manipulation Resulted in the Increased Apoptosis of Spermatocytes in Testes from Intracytoplasmic Sperm Injection (ICSI) Derived Mice

The invention of intracytoplasmic sperm injection (ICSI) has possibly been the most important development in reproductive medicine, one that has given hope to thousands of infertile couples worldwide. However, concerns remain regarding the safety of this method since it is a more invasive procedure than in vitro fertilization (IVF), since a spermatozoon is injected into the oocyte cytoplasm. Using mice derived from IVF technology as a control, we assessed the influence of invasive microinjection in the process of transferring sperm into oocyte cytoplasm in ICSI procedure on the development and physiologic function of resultant offspring. Our results demonstrated that mice produced from ICSI and IVF had no significant difference in phenotypic indices including body weight, forelimb physiology, and learning and memory ability. However, increased spermatocyte apoptosis was observed in the testis of adult ICSI mice, when compared with IVF mice. And, decreased testis weight and marked damage of spermatogenic epithelia were found in aged ICSI mice. Furthermore, proteomic analysis verified that most of the differentiated proteins in testes between adult ICSI and IVF mice were those involved in regulation of apoptosis pathways. Our results demonstrated that the microinjection manipulation used in the ICSI procedure might pose potential risks to the fertility of male offspring. The changed expression of a series of proteins relating to apoptosis or proliferation might contribute to it. Further studies are necessary to better understand all the risks of ICSI

Data-Driven Degradation Modeling and SOH Prediction of Li-Ion Batteries

Electrified vehicles (EV) and marine vessels represent promising clean transportation solutions to reduce or eliminate petroleum fuel use, greenhouse gas emissions and air pollutants. The presently commonly used electric energy storage system (ESS) is based on lithium-ion batteries. These batteries are the electrified or hybridized powertrain&rsquo;s most expensive component and show noticeable performance degradations under different use patterns. Therefore, battery life prediction models play a key role in realizing globally optimized EV design and energy control strategies. This research studies the data-driven modelling and prediction methods for Li-ion batteries&rsquo; performance degradation behaviour and the state of health (SOH) estimation. The research takes advantage of the increasingly available battery test and data to reduce prediction errors of the widely used semi-empirical modelling methods. Several data-driven modelling techniques have been applied, improved, and compared to identify their advantages and limitations. The data-driven approach and Kalman Filter (KF) algorithm are used to estimate and predict the degradation of the battery during operation. The combined algorithm of Gaussian Process Regression (GPR) and Extended Kalman Filter (EKF) showed higher accuracy than other algorithms

Data-Driven Degradation Modeling and SOH Prediction of Li-Ion Batteries

Electrified vehicles (EV) and marine vessels represent promising clean transportation solutions to reduce or eliminate petroleum fuel use, greenhouse gas emissions and air pollutants. The presently commonly used electric energy storage system (ESS) is based on lithium-ion batteries. These batteries are the electrified or hybridized powertrain’s most expensive component and show noticeable performance degradations under different use patterns. Therefore, battery life prediction models play a key role in realizing globally optimized EV design and energy control strategies. This research studies the data-driven modelling and prediction methods for Li-ion batteries’ performance degradation behaviour and the state of health (SOH) estimation. The research takes advantage of the increasingly available battery test and data to reduce prediction errors of the widely used semi-empirical modelling methods. Several data-driven modelling techniques have been applied, improved, and compared to identify their advantages and limitations. The data-driven approach and Kalman Filter (KF) algorithm are used to estimate and predict the degradation of the battery during operation. The combined algorithm of Gaussian Process Regression (GPR) and Extended Kalman Filter (EKF) showed higher accuracy than other algorithms

Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems

Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs