Adolescents and Children Age Estimation Using Machine Learning Based on Pulp and Tooth Volumes on CBCT Images.

OBJECTIVES: To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography (CBCT) images, and to compare and analyze the estimation results. METHODS: A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected. The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated. Three machine learning algorithms (K-nearest neighbor, ridge regression, and decision tree) and stepwise regression were used to establish four age estimation models. The coefficient of determination, mean error, root mean square error, mean square error and mean absolute error were computed and compared. A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed. RESULTS: The K-nearest neighbor model (R2=0.779) and the ridge regression model (R2=0.729) outperformed stepwise regression (R2=0.617), while the decision tree model (R2=0.494) showed poor fitting. The correlation heatmap demonstrated a monotonically negative correlation between age and the parameters including pulp volume, the ratio of pulp volume to hard tissue volume, and the ratio of pulp volume to tooth volume. CONCLUSIONS: Pulp volume and pulp volume proportion are closely related to age. The application of CBCT-based machine learning methods can provide more accurate age estimation results, which lays a foundation for further CBCT-based deep learning dental age estimation research.

[Responses of radial growth of Larix principis-rupprechtii at different densities to drought events]. / 不同密度华北落叶松径向生长对干旱事件的响应.

In recent years, a surge in drought occurrences has dramatically impacted tree growth worldwide. We examined the ecological resilience of Larix principis-rupprechtii plantations with varying densities (1950, 2355, and 2595 trees·hm-2) at the Saihanba Mechanical Forest Farm, by extracting the increment cores using the standard dendrochronological method to measure individual-tree basal area increments (BAI) as part of our assessment of ecological resilience, including resistance (Rt), recovery (Rc), and resilience (Rs). The results showed that drought events occurred in 2006-2010, 2015, and 2018. The Rt for L. principis-rupprechtii plantations varied from 0.76 to 2.01 across three drought events, indicating generally high resistance, except for the plantation with 2355 trees·hm-2 during the second dry year (Rt=0.69). The Rt for the plantation with 2595 trees·hm-2 significantly decreased across all drought events, while no significant change was observed in the plantations with 1950 and 2355 trees·hm-2. The Rc showed no differences in response to a single drought event across plantation densities, with a significant upward trend for all the densities with each occurrence of drought event. There was no significant difference in the resilience of different densities of L. principis-rupprechtii to the first drought event, whereas the plantation with 2595 trees·hm-2 exhibited significantly lower Rs during the second and third drought events compared with 1950 and 2355 trees·hm-2, respectively. During the 2015 drought event, plantation with 2595 trees·hm-2 experienced a significant growth decline (radial growth change rate was -26.5%), while no such decline was observed in the plantations with 1950 and 2355 trees·hm-2. Overall, the plantation with 2595 trees·hm-2 demonstrated the lowest resilience to drought events.

The dorsal hippocampal CA3 regulates spatial reference memory through the CtBP2/GluR2 pathway.

The dorsal hippocampus plays a pivotal role in spatial memory. However, the role of subregion-specific molecular pathways in spatial cognition remains unclear. We observed that the transcriptional coregulator C-terminal binding protein 2 (CtBP2) presented CA3-specific enrichment in expression. RNAi interference of CtBP2 in the dorsal CA3 (dCA3) neurons, but not the ventral CA3 (vCA3), specifically impaired spatial reference memory and reduced the expression of GluR2, the calcium permeability determinant subunit of AMPA receptors. Application of an antagonist for GluR2-absent calcium permeable AMPA receptors rescued spatial memory deficits in dCA3 CtBP2 knockdown animals. Transcriptomic analysis suggest that CtBP2 may regulate GluR2 protein level through post-translational mechanisms, especially by the endocytosis pathway which regulates AMPA receptor sorting. Consistently, CtBP2 deficiency altered the mRNA expression of multiple endocytosis-regulatory genes, and CtBP2 knockdown in primary hippocampal neurons enhanced GluR2-containing AMPA receptor endocytosis. Together, our results provide evidence that the dCA3 regulates spatial reference memory by the CtBP2/GluR2 pathway through the modulation of calcium permeable AMPA receptors.

Health Informatics on Adolescents Smoking Based on the Miryoku Engineering Analysis Framework.

Smoking among young people has aroused widespread concern in society. The number of young people who smoke has increased year by year, which has largely affected their health. Therefore, how to improve the prevention and control rate of tobacco harm, thereby reducing the smoking rate of young people has become an important issue. Based on the glamour engineering research method that can specifically solve the problem of attractiveness between users and products, the user preference of young people's smoking behavior is studied through the evaluation structure method and quantitative type I analysis, and the potential attractive factors are analyzed. Among them, there are 7 important attractive characteristics that affect the first attempt to smoke. These seven factors are divided into two aspects, namely, personal preference factors and environmental factors. The statistical data obtained through data analysis will be tested in the KMO field. The KMO values are 0.827 and 0.687, respectively, and the statistical results have obvious scores, so this study is effective. By quantifying one category, the partial correlation coefficients of different categories can be found, that is, specific solutions. This method provides a reference for ways and means to curb smoking behavior and also provides a case study for studying user perception. According to the research results, we seek ways to influence the smoking preferences of young people and then adopt some artificial methods to intervene in the generation of these factors, so as to achieve the purpose of reducing smoking among young people.

Rehabilitation Educational Design for Children with Autism Based on the Radial Basis Function Neural Network.

Children with autism need appropriate educational toys to assist rehabilitation training, so as to inhibit the development of autism. Toys and related treatments for children with autism can alleviate some of the deficits of children with autism. By using toys as stimuli and various sensations obtained by children with autism or toys as a result of reinforcement, the improvement of certain capabilities expected by related therapies can be achieved through the process of stimulation and reinforcement. However, in the process of pediatrics toy development, it is difficult for toy designers to assess whether the purpose of stimulation and reinforcement can be achieved. There are many factors that affect the design of rehabilitation toys. The industry has not formed a unified design evaluation standard, and the effects of product rehabilitation training are uneven. A method based on the radial basis function (RBF) neural network was proposed in this research to study the rehabilitation design and evaluation of rehabilitation toys for children with autism. Firstly, according to the three demand indicators for the evaluation of rehabilitation training for children with autism, that is, "useful, educational, and entertaining," the analytic network process (ANP) method was chosen as the weighting method for determining each indicator in the overall evaluation. The RBF neural network rehabilitation model for children with autism was designed and evaluated. The maximum error of the model was less than 10%. The evaluation method was objective and reasonable, so as to provide a reference for the more accurate design evaluation, purchase, and development of rehabilitation toys for children with autism.

ErbB4 regulate extracellular dopamine through the p38 MAPK signaling pathway.

ErbB4 loss-of-function in catecholaminergic neurons induces catecholamine dyshomeostasis. Despite ErbB4's significant role in neuropathology, the signaling pathways that regulate these changes are still widely unknown. In this study, we attempt to identify the downstream pathway of ErbB4 that regulates catecholamine homeostasis. The SH-SY5Y human neuroblastoma cell line was used as the in vitro model for catecholaminergic neurons. Western blotting, enzyme-linked immunosorbent assay, and pharmacological and genetic manipulations by agonist/antagonist or small interference RNA were used to investigate the relationship between ErbB4 and extracellular catecholamines. We confirmed that ErbB4 is abundantly expressed in undifferentiated and retinoic acid-differentiated catecholaminergic cells from the SH-SY5Y cell line. ErbB4 inhibition increase the ratio of phosphorylated p38 to total p38 in SH-SY5Y human neuroblastoma cells. Consistent with previous in vivo observations in mice, ErbB4 deficiency led to increases in extracellular dopamine and norepinephrine levels. However, the resulting increase in extracellular dopamine, but not norepinephrine, could be suppressed by p38 inhibitor SB202190. Our results suggest that both extracellular dopamine and norepinephrine homeostasis could be regulated by ErbB4 in human catecholaminergic cells, and ErbB4 may regulate extracellular dopamine, but not norepinephrine, through the p38 MAPK signaling pathway, thus indicating different regulatory pathways of dopamine and norepinephrine by ErbB4 in catecholaminergic neurons.

Genome-wide identification, phylogeny, and expression analysis of the SWEET gene family in tomato.

The SWEET (Sugars Will Eventually Be Exported Transporters) gene family encodes membrane-embedded sugar transporters containing seven transmembrane helices harboring two MtN3 and saliva domain. SWEETs play important roles in diverse biological processes, including plant growth, development, and response to environmental stimuli. Here, we conducted an exhaustive search of the tomato genome, leading to the identification of 29 SWEET genes. We analyzed the structures, conserved domains, and phylogenetic relationships of these protein-coding genes in detail. We also analyzed the transcript levels of SWEET genes in various tissues, organs, and developmental stages to obtain information about their functions. Furthermore, we investigated the expression patterns of the SWEET genes in response to exogenous sugar and adverse environmental stress (high and low temperatures). Some family members exhibited tissue-specific expression, whereas others were more ubiquitously expressed. Numerous stress-responsive candidate genes were obtained. The results of this study provide insights into the characteristics of the SWEET genes in tomato and may serve as a basis for further functional studies of such genes.