Association between occlusal support and cognitive impairment in older Chinese adults: a community-based study

IntroductionThe loss of occlusal support due to tooth loss is associated with systemic diseases. However, there was little about the association between occlusal support and cognitive impairment. The cross-sectional study aimed to investigate their association.MethodsCognitive function was assessed and diagnosed in 1,225 community-dwelling adults aged 60 years or older in Jing’an District, Shanghai. Participants were diagnosed with mild cognitive impairment (MCI) by Peterson’s criteria, or dementia, according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. We determined the number of functional occlusal supporting areas according to Eichner classifications. We used multivariate logistic regression models to analyze the relationship between occlusal support and cognitive impairment and mediation effect models to analyze the mediation effect of age.ResultsSix hundred sixty participants were diagnosed with cognitive impairment, averaging 79.92 years old. After adjusting age, sex, education level, cigarette smoking, alcohol drinking, cardiovascular disease, and diabetes, individuals with poor occlusal support had an OR of 3.674 (95%CI 1.141–11.829) for cognitive impairment compared to those with good occlusal support. Age mediated 66.53% of the association between the number of functional occlusal supporting areas and cognitive impairment.DiscussionIn this study, cognitive impairment was significantly associated with the number of missing teeth, functional occlusal areas, and Eichner classifications with older community residents. Occlusal support should be a significant concern for people with cognitive impairment

Online Prediction of the Enzymatic Hydrolysis Efficiency of Crop Straw

The extent of removal of lignin and hemicellulose are crucial indicators for evaluating the efficiency of enzymatic hydrolysis of crop straw. Numerous factors influence these two indices. Establishing a quantitative model that correlates these factors with hydrolysis efficiency is essential, as it can guide efficient hydrolysis. In this study, a predictive method for enzymatic hydrolysis efficiency in crop straw was proposed using Grey relational analysis (GRA), Kernel principal component analysis (KPCA), and a least squares support vector machine (LSSVM). The authors collected a dataset from actual production data and developed an efficiency predictive model using GRA for variable selection, KPCA for dimensionality reduction, and LSSVM for model training. This model allows for the direct estimation of the final enzymatic hydrolysis efficiency based on production condition variables, which can include enzyme amount, temperatures, pH, time, agitation, and straw dimensions. Extensive experimental testing validated the effectiveness of the proposed method, resulting in minimal errors, a high degree of fit, and exceptional performance. The methodology described in this study can serve as a foundation for optimising the design of efficient enzymatic hydrolysis production processes for crop straw. Additionally, it offers valuable soft measurements to support efficient control of the enzymatic hydrolysis process

Online Prediction of the Enzymatic Hydrolysis Efficiency of Crop Straw

The extent of removal of lignin and hemicellulose are crucial indicators for evaluating the efficiency of enzymatic hydrolysis of crop straw. Numerous factors influence these two indices. Establishing a quantitative model that correlates these factors with hydrolysis efficiency is essential, as it can guide efficient hydrolysis. In this study, a predictive method for enzymatic hydrolysis efficiency in crop straw was proposed using Grey relational analysis (GRA), Kernel principal component analysis (KPCA), and a least squares support vector machine (LSSVM). The authors collected a dataset from actual production data and developed an efficiency predictive model using GRA for variable selection, KPCA for dimensionality reduction, and LSSVM for model training. This model allows for the direct estimation of the final enzymatic hydrolysis efficiency based on production condition variables, which can include enzyme amount, temperatures, pH, time, agitation, and straw dimensions. Extensive experimental testing validated the effectiveness of the proposed method, resulting in minimal errors, a high degree of fit, and exceptional performance. The methodology described in this study can serve as a foundation for optimising the design of efficient enzymatic hydrolysis production processes for crop straw. Additionally, it offers valuable soft measurements to support efficient control of the enzymatic hydrolysis process

Online Prediction of the Enzymatic Hydrolysis Efficiency of Crop Straw

The extent of removal of lignin and hemicellulose are crucial indicators for evaluating the efficiency of enzymatic hydrolysis of crop straw. Numerous factors influence these two indices. Establishing a quantitative model that correlates these factors with hydrolysis efficiency is essential, as it can guide efficient hydrolysis. In this study, a predictive method for enzymatic hydrolysis efficiency in crop straw was proposed using Grey relational analysis (GRA), Kernel principal component analysis (KPCA), and a least squares support vector machine (LSSVM). The authors collected a dataset from actual production data and developed an efficiency predictive model using GRA for variable selection, KPCA for dimensionality reduction, and LSSVM for model training. This model allows for the direct estimation of the final enzymatic hydrolysis efficiency based on production condition variables, which can include enzyme amount, temperatures, pH, time, agitation, and straw dimensions. Extensive experimental testing validated the effectiveness of the proposed method, resulting in minimal errors, a high degree of fit, and exceptional performance. The methodology described in this study can serve as a foundation for optimising the design of efficient enzymatic hydrolysis production processes for crop straw. Additionally, it offers valuable soft measurements to support efficient control of the enzymatic hydrolysis process

Engineering Versatile Nanomedicines for Ultrasonic Tumor Immunotherapy

Abstract Due to the specific advantages of ultrasound (US) in therapeutic disease treatments, the unique therapeutic US technology has emerged. In addition to featuring a low‐invasive targeted cancer‐cell killing effect, the therapeutic US technology has been demonstrated to modulate the tumor immune landscape, amplify the therapeutic effect of other antitumor therapies, and induce immunosensitization of tumors to immunotherapy, shedding new light on the cancer treatment. Tremendous advances in nanotechnology are also expected to bring unprecedented benefits to enhancing the antitumor efficiency and immunological effects of therapeutic US, as well as therapeutic US‐derived bimodal and multimodal synergistic therapies. This comprehensive review summarizes the immunological effects induced by different therapeutic US technologies, including ultrasound‐mediated micro‐/nanobubble destruction (UTMD/UTND), sonodynamic therapy (SDT), and focused ultrasound (FUS), as well as the main underlying mechanisms involved. It is also discussed that the recent research progress of engineering intelligent nanoplatform in improving the antitumor efficiency of therapeutic US technologies. Finally, focusing on clinical translation, the key issues and challenges currently faced are summarized, and the prospects for promoting the clinical translation of these emerging nanomaterials and ultrasonic immunotherapy in the future are proposed

Exosomal circSHKBP1 promotes gastric cancer progression via regulating the miR-582-3p/HUR/VEGF axis and suppressing HSP90 degradation

Abstract Background Circular RNAs (circRNAs) play important regulatory roles in the development of various cancers. However, biological functions and the underlying molecular mechanism of circRNAs in gastric cancer (GC) remain obscure. Methods Differentially expressed circRNAs were identified by RNA sequencing. The biological functions of circSHKBP1 in GC were investigated by a series of in vitro and in vivo experiments. The expression of circSHKBP1 was evaluated using quantitative real-time PCR and RNA in situ hybridization, and the molecular mechanism of circSHKBP1 was demonstrated by western blot, RNA pulldown, RNA immunoprecipitation, luciferase assays and rescue experiments. Lastly, mouse xenograft and bioluminescence imaging were used to exam the clinical relevance of circSHKBP1 in vivo. Results Increased expression of circSHKBP1(hsa_circ_0000936) was revealed in GC tissues and serum and was related to advanced TNM stage and poor survival. The level of exosomal circSHKBP1 significantly decreased after gastrectomy. Overexpression of circSHKBP1 promoted GC cell proliferation, migration, invasion and angiogenesis in vitro and in vivo, while suppression of circSHKBP1 plays the opposite role. Exosomes with upregulated circSHKBP1 promoted cocultured cells growth. Mechanistically, circSHKBP1 sponged miR-582-3p to increase HUR expression, enhancing VEGF mRNA stability. Moreover, circSHKBP1 directly bound to HSP90 and obstructed the interaction of STUB1 with HSP90, inhibiting the ubiquitination of HSP90, resulting in accelerated GC development in vitro and in vivo. Conclusion Our findings demonstrate that exosomal circSHKBP1 regulates the miR-582-3p/HUR/VEGF pathway, suppresses HSP90 degradation, and promotes GC progression. circSHKBP1 is a promising circulating biomarker for GC diagnosis and prognosis and an exceptional candidate for further therapeutic exploration. </jats:sec

Prevalence and influencing factors of malocclusion in adolescents in Shanghai, China

Abstract Background The main purpose of the study was to investigate the prevalence and related risk factors of malocclusion in permanent dentition among adolescents in Shanghai, and provide basic data for government’s preventive strategies and intervention plans. Methods 1799 adolescents aged 11–15 years old from 18 middle schools in 6 districts of Shanghai were recruited to investigate oral health status and related risk factors using cluster random sampling method in 2021. Malocclusion and caries were examined by on-site inspection. The investigation criteria referred to Bjoerk and the recommendation of the WHO. The malocclusion inspection items included molars relationship, canine relationship, overbite, overjet, midline displacement, anterior crossbite, posterior crossbite, scissors bite, crowding and spacing. The subjects were asked to fill in a questionnaire including parents’ education level, oral health behaviors and dietary habits. The chi-square test and logistic regression analysis were used to analyze the relationship between malocclusion and risk factors. Results 1799 adolescents were included in the study and the prevalence of malocclusion in adolescents in Shanghai was 83.5%, and the proportion of molar relationship class I, class II, and class III was 48.9%, 14.7%, and 19.0%, respectively. The most common occlusal characteristic of malocclusion was anterior crowding, followed by midline irregularities and deep overbite, with prevalence rates of 44.8%, 39.0% and 38.6%, respectively. The prevalence rate of adolescents with caries was 34.3%. Those who had dental caries and preferred soft food were more likely to have abnormal occlusal characteristics (p < 0.05). Conclusion The prevalence of malocclusion in adolescents in Shanghai is high, so it is of great significance to strengthen oral health education, allocate proper preventive strategies and carry out the early correction if necessary