Integrated correlation analysis of the thickness of buccal bone and gingiva of maxillary incisors.

OBJECTIVE: This study aimed to validate the integrated correlation between the buccal bone and gingival thickness of the anterior maxilla, and to gain insight into the reference plane selection when measuring these two tissues before treatment with implants. METHODOLOGY: Cone beam computed tomography (CBCT) and model scans of 350 human subjects were registered in the coDiagnostiX software to obtain sagittal maxillary incisor sections. The buccal bone thickness was measured at the coronal (2, 4, and 6 mm apical to the cementoenamel junction [CEJ]) and apical (0, 2, and 4 mm coronal to the apex plane) regions. The buccal gingival thickness was measured at the supra-CEJ (0, 1mm coronal to the CEJ) and sub-CEJ regions (1, 2, 4, and 6 mm apical to the CEJ). Canonical correlation analysis was performed for intergroup correlation analysis and investigation of key parameters. RESULTS: The mean thicknesses of the buccal bone and gingiva at different levels were 0.64~1.88 mm and 0.66~1.37 mm, respectively. There was a strong intergroup canonical correlation between the thickness of the buccal bone and that of the gingiva (r=0.837). The thickness of the buccal bone and gingiva at 2 mm apical to the CEJ are the most important indices with the highest canonical correlation coefficient and loadings. The most and least prevalent subgroups were the thin bone and thick gingiva group (accounting for 47.6%) and the thick bone and thick gingiva group (accounting for 8.6%). CONCLUSION: Within the limitations of this retrospective study, the thickness of the buccal bone is significantly correlated with that of the buccal gingiva, and the 2 mm region apical to the CEJ is a vital plane for quantifying the thickness of these two tissues.

The development and training effect of innovative undergraduate dental talents training project: A 6-year retrospective study.

INTRODUCTION: To summarize the development of Innovative Undergraduate Dental Talents Training Project (IUDTTP) and investigate the training effect of this extracurricular dental basic research education activity from 2015 to 2020 to obtain educational implications. MATERIALS AND METHODS: The Guanghua School of Stomatology established the IUDTTP in 2015. The authors recorded the development process and analysed the participation situation, training effect, academic performance and overall satisfaction during 2015-2020 through documental analysis, questionnaire and quiz. The t-test, chi-square test and ANOVA were used to test the difference. RESULTS: The educational goal, education module and assessment system of IUDTTP evolved and developed every year. A total of 336 students and 79 mentors attended the IUDTTP from 2015 to 2020, with the participation rate increasing from 45.1% to 73.5%. The participants exhibited favourable basic research abilities, manifesting as the increase of funded projects and published papers and satisfying quiz scores. Almost all students (94.94%) admitted their satisfaction with the IUDTTP. Moreover, the attended students surpassed the non-participants in terms of GPA, the number of acquired scholarships and outstanding graduates (p < .05). Likewise, the enrolment rate of postgraduate participants was significantly higher than non-participants. CONCLUSIONS: To date, the training effect indicated that the IUDTTP has fulfilled the education aim. It brought positive effects on promoting research interest, cultivating research capacities and enhancing academic performance. The potential deficiencies of extracurricular educational activities, including inflexibility in schedule and insufficiency in systematisms, may be remedied by more systematic educational settings in the future.

Integrated correlation analysis of the thickness of buccal bone and gingiva of maxillary incisors

Abstract Objective This study aimed to validate the integrated correlation between the buccal bone and gingival thickness of the anterior maxilla, and to gain insight into the reference plane selection when measuring these two tissues before treatment with implants. Methodology Cone beam computed tomography (CBCT) and model scans of 350 human subjects were registered in the coDiagnostiX software to obtain sagittal maxillary incisor sections. The buccal bone thickness was measured at the coronal (2, 4, and 6 mm apical to the cementoenamel junction [CEJ]) and apical (0, 2, and 4 mm coronal to the apex plane) regions. The buccal gingival thickness was measured at the supra-CEJ (0, 1mm coronal to the CEJ) and sub-CEJ regions (1, 2, 4, and 6 mm apical to the CEJ). Canonical correlation analysis was performed for intergroup correlation analysis and investigation of key parameters. Results The mean thicknesses of the buccal bone and gingiva at different levels were 0.64~1.88 mm and 0.66~1.37 mm, respectively. There was a strong intergroup canonical correlation between the thickness of the buccal bone and that of the gingiva (r=0.837). The thickness of the buccal bone and gingiva at 2 mm apical to the CEJ are the most important indices with the highest canonical correlation coefficient and loadings. The most and least prevalent subgroups were the thin bone and thick gingiva group (accounting for 47.6%) and the thick bone and thick gingiva group (accounting for 8.6%). Conclusion Within the limitations of this retrospective study, the thickness of the buccal bone is significantly correlated with that of the buccal gingiva, and the 2 mm region apical to the CEJ is a vital plane for quantifying the thickness of these two tissues

Measuring the binary thickness of buccal bone of anterior maxilla in low-resolution cone-beam computed tomography via a bilinear convolutional neural network.

Background: The thickness of the buccal bone of the anterior maxilla is an important aesthetic-determining factor for dental implant, which is divided into the thick (≥1 mm) and thin type (<1 mm). However, as a micro-scale structure that is evaluated through low-resolution cone-beam computed tomography (CBCT), its thickness measurement is error-prone under the circumstance of enormous patients and relatively inexperienced primary dentists. Further, the challenges of deep learning-based analysis of the binary thickness of buccal bone include the substantial real-world variance caused by pixel error, the extraction of fine-grained features, and burdensome annotations. Methods: This study built bilinear convolutional neural network (BCNN) with 2 convolutional neural network (CNN) backbones and a bilinear pooling module to predict the binary thickness of buccal bone (thick or thin) of the anterior maxilla in an end-to-end manner. The methods of 5-fold cross-validation and model ensemble were adopted at the training and testing stages. The visualization methods of Gradient Weighted Class Activation Mapping (Grad-CAM), Guided Grad-CAM, and layer-wise relevance propagation (LRP) were used for revealing the important features on which the model focused. The performance metrics and efficacy were compared between BCNN, dentists of different clinical experience (i.e., dental student, junior dentist, and senior dentist), and the fusion of BCNN and dentists to investigate the clinical feasibility of BCNN. Results: Based on the dataset of 4,000 CBCT images from 1,000 patients (aged 36.15±13.09 years), the BCNN with visual geometry group (VGG)16 backbone achieved an accuracy of 0.870 [95% confidence interval (CI): 0.838-0.902] and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.924 (95% CI: 0.896-0.948). Compared with the conventional CNNs, BCNN precisely located the buccal bone wall over irrelevant regions. The BCNN generally outperformed the expert-level dentists. The clinical diagnostic performance of the dentists was improved with the assistance of BCNN. Conclusions: The application of BCNN to the quantitative analysis of binary buccal bone thickness validated the model's excellent ability of subtle feature extraction and achieved expert-level performance. This work signals the potential of fine-grained image recognition networks to the precise quantitative analysis of micro-scale structures.

Quantification of the apical palatal bone index for maxillary incisor immediate implant assessment: A retrospective cross-sectional study.

BACKGROUND: Apical palatal bone is important in immediate implant evaluation. Current consensus gives qualitative suggestions regarding it, limiting its clinical decision-making value. OBJECTIVES: To quantify the apical palatal bone dimension in maxillary incisors and reveal its quantitative correlation with other implant-related hard tissue indices to give practical advice for pre-immediate implant evaluation and design. MATERIAL AND METHODS: A retrospective analysis of immediate implant-related hard tissue indices in maxillary incisors obtained by cone beam computed tomography (CBCT) was conducted. Palatal bone thickness at the apex level (Apical-P) on the sagittal section was selected as a parameter reflecting the apical palatal bone. Its quantitative correlation with other immediate implant-related hard tissue indices was revealed. Clinical advice of pre-immediate implant assessment was given based on the quantitative classification of Apical-P and its other correlated immediate implant-related hard tissue indices. RESULTS: Apical-P positively correlated with cervical palatal bone, whole cervical buccal-palatal bone, sagittal root angle, and basal bone width indices. while negatively correlated with apical buccal bone, cervical buccal bone, and basal bone length indices. Six quantitative categories of Apical-P are proposed. Cases with Apical-P below 4 mm had an insufficient apical bone thickness to accommodate the implant placement, while Apical-P beyond 12 mm should be cautious about the severe implant inclination. Cases with Apical-P of 4-12 mm can generally achieve satisfying immediate implant outcomes via regulating the implant inclination. CONCLUSIONS: Quantification of the apical palatal bone index for maxillary incisor immediate implant assessment can be achieved, providing a quantitative guide for immediate implant placement in the maxillary incisor zone.

Abnormal maxillary sinus diagnosing on CBCT images via object detection and 'straight-forward' classification deep learning strategy.

BACKGROUND: Pathological maxillary sinus would affect implant treatment and even result in failure of maxillary sinus lift and implant surgery. However, the maxillary sinus abnormalities are challenging to be diagnosed through CBCT images, especially for young dentists or dentists in grassroots medical institutions without systematical education of general medicine. OBJECTIVES: To develop a deep-learning-based screening model incorporating object detection and 'straight-forward' classification strategy to screen out maxillary sinus abnormalities on CBCT images. METHODS: The large area of background noise outside maxillary sinus would affect the generalisation and prediction accuracy of the model, and the diversity and imbalanced distribution of imaging manifestations may bring challenges to intellectualization. Thus we adopted an object detection to limit model's observation zone and 'straight-forward' classification strategy with various tuning methods to adapt to dental clinical need and extract typical features of diverse manifestations so that turn the task into a 'normal-or-not' classification. RESULTS: We successfully constructed a deep-learning model consist of well-trained detector and diagnostor module. This model achieved ideal AUROC and AUPRC of 0.953 and 0.887, reaching more than 90% accuracy at optimal cut-off. McNemar and Kappa test verified no statistical difference and high consistency between the prediction and ground truth. Dentist-model comparison test showed the model's statistically higher diagnostic performance than dental students. Visualisation method confirmed the model's effectiveness in region recognition and feature extraction. CONCLUSION: The deep-learning model incorporating object detection and straightforward classification strategy could achieve satisfying predictive performance for screening maxillary sinus abnormalities on CBCT images.

Nanotopographic micro-nano forces finely tune the conformation of macrophage mechanosensitive membrane protein integrin ß2 to manipulate inflammatory responses.

Finely tuning mechanosensitive membrane proteins holds great potential in precisely controlling inflammatory responses. In addition to macroscopic force, mechanosensitive membrane proteins are reported to be sensitive to micro-nano forces. Integrin ß2, for example, might undergo a piconewton scale stretching force in the activation state. High-aspect-ratio nanotopographic structures were found to generate nN-scale biomechanical force. Together with the advantages of uniform and precisely tunable structural parameters, it is fascinating to develop low-aspect-ratio nanotopographic structures to generate micro-nano forces for finely modulating their conformations and the subsequent mechanoimmiune responses. In this study, low-aspect-ratio nanotopographic structures were developed to finely manipulate the conformation of integrin ß2. The direct interaction of forces and the model molecule integrin αXß2 was first performed. It was demonstrated that pressing force could successfully induce conformational compression and deactivation of integrin αXß2, and approximately 270 to 720 pN may be required to inhibit its conformational extension and activation. Three low-aspect-ratio nanotopographic surfaces (nanohemispheres, nanorods, and nanoholes) with various structural parameters were specially designed to generate the micro-nano forces. It was found that the nanorods and nanohemispheres surfaces induce greater contact pressure at the contact interface between macrophages and nanotopographic structures, particularly after cell adhesion. These higher contact pressures successfully inhibited the conformational extension and activation of integrin ß2, suppressing focal adhesion activity and the downstream PI3K-Akt signaling pathway, reducing NF-κB signaling and macrophage inflammatory responses. Our findings suggest that nanotopographic structures can be used to finely tune mechanosensitive membrane protein conformation changes, providing an effective strategy for precisely modulating inflammatory responses. Electronic Supplementary Material: Supplementary material (primer sequences of target genes in RT-qPCR assay; the results of solvent accessible surface area during equilibrium simulation, the ligplut results of hydrogen bonds, and hydrophobic interactions; the density of different nanotopographic structures; interaction analysis of the downregulated leading genes of "focal adhesion" signaling pathway in nanohemispheres and nanorods groups; and the GSEA results of "Rap 1 signaling pathway" and "regulation of actin cytoskeleton" in different groups) is available in the online version of this article at 10.1007/s12274-023-5550-0.

Novel Muscle-Homing Peptide FGF1 Conjugate Based on AlphaFold for Type 2 Diabetes Mellitus.

Drugs for metabolic diseases usually require systemic administration and act on multiple tissues, which may produce some unpredictable side effects. There have been many successful studies on targeted drugs, especially antitumor drugs. However, there is still little research on metabolic disease drugs targeting specific tissues. Fibroblast growth factor 1 (FGF1) is a potential therapy for type 2 diabetes (T2D) without the risk of hypoglycemia. However, the major impediment to the clinical application of FGF1 is its mitogenic potential. We previously engineered an FGF1 variant (named FGF1ΔHBS) to tune down its mitogenic activity via reducing the heparin-binding ability. However, other notable side effects still remained, including severe appetite inhibition, pathogenic loss of body weight, and increase in fatality rate. In this study, we used AlphaFold2 and PyMOL visualization tools to construct a novel FGF1ΔHBS conjugate fused with skeletal muscle-targeted (MT) peptide through a flexible peptide linker termed MT-FGF1ΔHBS. We found that MT-FGF1ΔHBS specifically homed to skeletal muscle tissue after systemic administration and induced a potent glucose-lowering effect in T2D mice without hypoglycemia. Mechanistically, MT-FGF1ΔHBS elicits the glucose-lowering effect via AMPK activation to promote the GLUT4 expression and translocation in skeletal muscle cells. Notably, compared with native FGF1ΔHBS, MT-FGF1ΔHBS had minimal effects on food intake and body weight and did not induce any hyperplasia in major tissues of both T2D and normal mice, indicating that this muscle-homing protein may be a promising candidate for T2D treatment. Our targeted peptide strategy based on computer-aided structure prediction in this study could be effectively applied for delivering agents to functional tissues to treat metabolic or other diseases, offering enhanced efficacy and reducing systemic off-target side effects.

"Brain-inspired intelligence" in dental implant decision-making / 口腔疾病防治

@#At present, implant surgery robots have basically achieved "surgical intelligence", but "brain-inspired intelligence" of robots is still in the stage of theory and exploration. The formulation of a clinical implantation plan depends on the timing of implantation, implantation area, bone condition, surgical procedure, patient factors, etc., which need to evaluate the corresponding clinical decision indicators and clinical pathways. Inspired by evidence-based medicine and the potential of big data and deep learning, combined with the data characteristics of clinical decision indicators and clinical pathways that can be quantitatively or qualitatively analyzed, this review simulates the cognitive behavior and neural mechanisms of the human brain and proposes a feasible brain-inspired intelligence scheme by predicting the decision indices and executing clinical pathways intelligently, that is, "select clinical indicators and clarify clinical pathways -- construct database -- use deep learning to intelligently predict decision indicators -- intelligent execution of clinical pathways -- brain-inspired intelligence of implant decision-making". Combined with the previous research results of our team, this review also describes the process of realization of brain-inspired intelligence for immediate implant timing decisions, providing an example of the comprehensive realization of brain-inspired intelligence of implant surgery robots in the future. In the future, how to excavate and summarize other clinical decision factors and select the best way to realize the automatic prediction of evidence-based clinical indicators and pathways and finally realize the complete intellectualization of clinical diagnosis and treatment processes will be one of the directions that dental clinicians need to strive for.

Guvermectin, a novel plant growth regulator, can promote the growth and high temperature tolerance of maize.

Guvermectin is a recently discovered microbial N9-glucoside cytokinin compound extracted from Streptomyces sanjiangensis NEAU6. Although some research has reported that N9-glucoside cytokinin compounds do not have the activity of cytokinin, it has been noted that guvermectin can promote growth and antifungal activity in Arabidopsis. Maize is an important food crop in the world and exploring the effect of guvermectin on this crop could help its cultivation in regions with adverse environmental conditions such as a high temperature. Here, we investigated the effects of guvermectin seed soaking treatment on the growth of maize at the seedlings stage and its yield attributes with different temperature stresses. The maize (cv. Zhengdan 958) with guvermectin seed soaking treatment were in two systems: paper roll culture and field conditions. Guvermectin seed soaking treated plants had increased plant height, root length, and mesocotyl length at the seedlings stage, and spike weight at maturity in the field. But only root length was increased at the paper roll culture by guvermectin seed soaking treatment. Guvermectin seed soaking treatment reduced the adverse effects on maize seedling when grow at a high temperature. Further experiments showed that, in high temperature conditions, guvermectin treatment promoted the accumulation of heat shock protein (HSP) 17.0, HSP 17.4 and HSP 17.9 in maize roots. Comparative transcriptomic profiling showed there were 33 common differentially expressed genes (DEGs) in guvermectin treated plants under high temperature and room temperature conditions. The DEGs suggested that guvermectin treatment led to the differential modulation of several transcripts mainly related with plant defense, stress response, and terpenoid biosynthesis. Taken together, these results suggested that the guvermectin treatment promoted the growth and tolerance of high temperature stresses, possibly by activation of related pathways. These results show that guvermectin is a novel plant growth regulator and could be developed as an application to maize seeds to promote growth in high temperature environments.

Host-induced gene silencing of PcCesA3 and PcOSBP1 confers resistance to Phytophthora capsici in Nicotiana benthamiana through NbDCL3 and NbDCL4 processed small interfering RNAs.

Host-induced gene silencing (HIGS) is a RNA-based system depend on the biological macromolecules generated in plants to control diseases. However, the effector proteins active in the HIGS are uncertain, which impedes its further application, especially for oomycete that lack efficient HIGS targets. Phytophthora capsici is an important oomycete causes blight in over 70 crops. Here, we comprehensively screened efficient HIGS vectors targeting PcCesA3 or PcOSBP1 in P. capsici to better control it and explore the characteristics of efficient HIGS vectors. Among the 26 vectors with different lengths and structures, we found that hairpin vectors with a 70 nt loop and ~ 500 bp stem showed the highest control efficacy, with the expressing of the screened vectors, the infection and fertility of P. capsici were greatly inhibited in transgenic Nicotiana benthamiana. Based on these efficient vectors, we demonstrated that the amount of HIGS vector generated small interfering RNAs (siRNAs) was positively related to gene silencing efficiency and resistance, and that NbDCL3 and NbDCL4 were the key effectors producing siRNAs. This work discovers the principles for efficient HIGS vectors design, and elucidates the molecular mechanism of HIGS, which could benefit the control of many other plant diseases based on HIGS.

Monitoring and characterization of prochloraz resistance in Fusarium fujikuroi in China.

Rice bakanae disease, caused by Fusarium fujikuroi, is a destructive seed-borne disease throughout the world. Prochloraz, a DMI (C-14α-demethylase inhibitor) fungicide, has been registered in China for >20 years. Prochloraz resistance in F. fujikuroi was severe in China with resistance frequencies of 34.56%, 45.33%, and 48.45% from 2019 to 2021. The fitness of prochloraz-resistant population was lower than that of sensitive population, with an average CFI of 2.86 × 106 and 4.56 × 106, respectively. No cross-resistance was detected between prochloraz and tebuconazole or hexaconazole, and the prochloraz-resistant isolates were still sensitive to fludioxonil, phenamacril, and pydiflumetofen. S312T mutation in Ffcyp51b or overexpression of Ffcyp51a and Ffcyp51b was detected in the highly resistant isolates. AS-PCR primers were designed to detect the prochloraz-resistant isolates with S312T mutation in the field. Resistant isolates carrying S312T mutation were the dominant group in prochloraz-resistant population with frequencies of 43.26%, 23.59%, and 71.20% from 2019 to 2021, which indicated that more attention should be paid to this genotype when monitoring and managing the prochloraz resistance in F. fujikuroi.

Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination.

BACKGROUND: Immediate implant placement in the esthetic area requires comprehensive assessments with nearly 30 quantitative indexes. Most artificial intelligence (AI)-driven measurements of quantitative indexes depend on segmentation or landmark detection, which require extra labeling of images and contain possible intraclass errors. METHODS: For the initial attempt, the method was tested on sagittal root inclination measurement. This study had developed an accurate and efficient end-to-end model incorporating a convolutional neural network (CNN) based on unlabeled cone-beam computed tomography (CBCT) images for immediate implant placement diagnosis and treatment. The model took pretrained ResNeXt101 as the backbone and was constructed based on 2,920 CBCT images with corresponding angles of the tooth axis and bone axis. The performance of our CNN model was evaluated on a separate test set. RESULTS: Our model exhibited high prediction accuracy in sagittal root inclination measurements, as evidenced by the low mean average error of 2.16°, the high correlation coefficient of 0.915 to manual measurement, and the narrow 95% confidence interval shown by Bland-Altman plots. The intraclass correlation coefficient further confirmed the measurement accuracy of our model was comparable with that of junior clinicians. The model took merely 0.001 seconds for each CBCT image, making it highly efficient. To better understand the model's quality, we visualized our end-to-end CNN model through Guided Backpropagation, Grad-CAM, and Guided Grad-CAM, and confirmed its effectiveness in region recognition. CONCLUSIONS: We succeeded in taking the first step in constructing the end-to-end immediate implant placement AI tool through sagittal root inclination measurements without intermediate steps and extra labeling on images.

A practical guide to promote informatics-driven efficient biotopographic material development.

Micro/nano topographic structures have shown great utility in many biomedical areas including cell therapies, tissue engineering, and implantable devices. Computer-assisted informatics methods hold great promise for the design of topographic structures with targeted properties for a specific medical application. To benefit from these methods, researchers and engineers require a highly reusable "one structural parameter - one set of cell responses" database. However, existing confounding factors in topographic cell culture devices seriously impede the acquisition of this kind of data. Through carefully dissecting the confounding factors and their possible reasons for emergence, we developed corresponding guideline requirements for topographic cell culture device development to remove or control the influence of such factors. Based on these requirements, we then suggested potential strategies to meet them. In this work, we also experimentally demonstrated a topographic cell culture device with controlled confounding factors based on these guideline requirements and corresponding strategies. A "guideline for the development of topographic cell culture devices" was summarized to instruct researchers to develop topographic cell culture devices with the confounding factors removed or well controlled. This guideline aims to promote the establishment of a highly reusable "one structural parameter - one set of cell responses" database that could facilitate the application of informatics methods, such as artificial intelligence, in the rational design of future biotopographic structures with high efficacy.

Successful targeting of the NRG1 fusion reveals durable response to afatinib in lung adenocarcinoma: a case report.

The treatments for advanced non-small cell lung cancer (NSCLC) patients have been improved by developing tyrosine kinase inhibitors (TKIs) as targeted therapies. Oncogenic gene fusions resulting from structural DNA rearrangements have been proposed as a unique class of oncogenic drivers and therapeutic targets. Currently approved TKIs mainly focused on a few well-known fusion genes such as anaplastic lymphoma kinase (ALK) and ROS proto-oncogene 1 (ROS1). Fusions involving neuregulin 1 gene (NRG1) have been recently described in a small portion of solid tumors as actionable oncogenic drivers, leading to the activation of the erythroblastic leukemia viral oncogene homolog (ErbB)-mediated pathway. Therefore, gene fusions containing NRG1 could serve as a therapeutic candidate for ErbB-targeted treatment. In the present study, we report a lung adenocarcinoma patient harboring the CD74-NRG1 fusion, which was identified by next-generation sequencing (NGS). The patient received the irreversible pan-ErbB inhibitor, afatinib, as first-line treatment and showed a significant treatment response with a progression-free survival of 8 months. After progressive disease (PD), the second NGS did not identify novel genetic alterations that emerged after afatinib resistance. Our case supports the use of ErbB-targeted treatment for NRG1 fusion-positive NSCLC. Further studies are warranted to understand treatment effects and acquired resistance of afatinib in NGR1 fusion-positive patients.

Analysis of the sagittal root angle and its correlation with hard and soft tissue indices in anterior teeth for immediate implant evaluation: a retrospective study.

BACKGROUND: To assess the root angle characteristics of maxillary incisors, and to analyze the relationship between the root angle and other implant-related anatomical indices to use the sagittal root angle as an index for immediate implant evaluation and design. METHODS: A random sample consisting of 400 cone-beam computed tomography (CBCT) images and 65 maxillary plaster models were selected for the present study. CBCT and stereolithography (STL) scan images were imported as DICOM files into coDiagnostiX software for matching the hard and soft tissue. The angle between the long axis of the anterior tooth and the corresponding alveolar bone and implant-related hard and soft tissue indices were measured in the sagittal section. Descriptive statistics, frequency analysis, multi-level comparisons, and correlation analyses were performed. RESULTS: The average sagittal root angles were 15° at the central incisor and 19° at the lateral incisor. The root angle in males was significantly larger than that in females, and increased with age. The largest angle, 22.35°, was found in the lateral incisors of the oldest (> 50 years old) male group. The root angle was found to correlate with coronal buccal bone thickness, coronal palatal bone thickness, apical buccal bone thickness, palatal bone thickness, and the below apex bone thickness. CONCLUSIONS: The sagittal root angle could reflect the distribution of other implant-related anatomical indices, which may provide additional reference for the evaluation of immediate implant placement.

Urinary exosomal long noncoding RNAs serve as biomarkers for early detection of non-small cell lung cancer.

OBJECTIVE: Increasing the efficiency of early diagnosis using noninvasive biomarkers is crucial for enhancing the survival rate of lung cancer patients. We explore the differential expression of non-small cell lung cancer (NSCLC)-related long noncoding RNAs (lncRNAs) in urinary exosomes in NSCLC patients and normal controls to diagnose lung cancer. METHODS: A differential expression analysis between NSCLC patients and healthy controls was performed using microarrays. Gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to predict potential functions of lncRNAs in NSCLC. quantitative real-time PCR (QT-PCR) was used to verify microarray results. RESULTS: A total of 640 lncRNAs (70 up- and 570 down-regulated) were differentially expressed in NSCLC patients in comparison to healthy controls. Six lncRNAs were detected by QT-PCR. GO term and KEGG pathway analyses showed that differential lncRNAs were enriched in cellular component organization or biogenesis, as well as other biological processes and signaling pathways, such as the PI3K-AKT, FOXO, p53, and fatty acid biosynthesis. CONCLUSIONS: The differential lncRNAs in urinary exosomes are potential diagnostic biomarkers of NSCLC. The lncRNAs enriched in specific pathways may be associated with tumor cell proliferation, tumor cell apoptosis, and the cell cycle involved in the pathogenesis of NSCLC.

Response mechanisms to joint exposure of triclosan and its chlorinated derivatives on zebrafish (Danio rerio) behavior.

Triclosan (TCS), 2,4,6-trichlorophenol (2,4,6-TCP) and 2,4-dichlorophenol (2,4-DCP) frequently co-exist in real-world aquatic environments; the latter two contaminants contributing to TCS photolytic products or chlorinated derivatives. There is a paucity of information regarding their joint toxicity to aquatic organisms leading us to study their effects on the swimming behavior of zebrafish (Danio rerio). Herein, we reported that 0.28 mg/L TDT exposure (mixtures of TCS, 2,4,6-TCP and 2,4-DCP) enhanced 24-hpf embryonic spontaneous movement frequency, 96-hpf larval activity; however, the 0.56 and 1.12 mg/L TDT treatments decreased all of these behavioral endpoints. All adult behavioral tests demonstrated that chronic TDT exposure (0.14 mg/L) led to hyperactivity and restlessness in adult zebrafish. A 0.14 mg/L TD DATE /@ "M/d/yyyy" 11/21/2017T treatment led to anxiety-like behavior in a bottom dwelling test and excessive panic and low hedging capacity in a conditioned place preference test. Social interaction test demonstrated that zebrafish preferred quiet and isolated space in response to TDT stress. Zebrafish memory was significantly decreased in a T-maze experiment. Whole mount in situ hybridization of pax2a and bcl2l11 genes revealed that their differential expression in the brain and skeleton were related to the corresponding phenotypic behavioral abnormality. A series of biomarker and estrogen receptor assays demonstrated that TDT acute exposure caused abnormal energy metabolism and neurological diseases. AO staining revealed that TDT exposure produced vascular ablation in the head, as well as the occurrence of massive apoptosis in the brain. TEM observation showed pyknosis of nucleus following TDT exposure. These results allow assessment of mechanisms for zebrafish abnormal behavior in response to TDT exposure, and are useful for early intervention and gene therapy of contaminant-induced diseases.

Effects of methylglyoxal and glyoxalase I inhibition on breast cancer cells proliferation, invasion, and apoptosis through modulation of MAPKs, MMP9, and Bcl-2.

Emerging evidence indicates that methylglyoxal (MG) can inhibit tumorigenesis. Glyoxalase I (GLOI), a MG degradation enzyme, is implicated in the progression of human malignancies. However, little is known about the roles of MG and GLOI in breast cancer. Our purpose was to investigate the anticancer effects of MG and inhibition of GLOI on breast cancer cells and the underlying mechanisms of these effects. Our findings demonstrate that cell viability, migration, invasion, colony formation, and tubule formation were significantly restrained by addition of MG or inhibition of GLOI, while apoptosis was significantly increased. Furthermore, the expression of p-JNK, p-ERK, and p-p38 was markedly upregulated by addition of MG or inhibition of GLOI, whereas MMP-9 and Bcl-2 expression levels were dramatically decreased. These effects were augmented by combined treatment with MG and inhibition of GLOI. Collectively, these data indicate that MG or inhibition of GLOI induces anticancer effects in breast cancer cells and that these effects are potentiated by combination of the 2. These effects were modulated by activation of the MAPK family and downregulation of Bcl-2 and MMP-9. These findings may provide a new approach for the treatment of breast cancer.

Toxicity assessment of combined fluoroquinolone and tetracycline exposure in zebrafish (Danio rerio).

Fluoroquinolones (FQs) and tetracyclines (TCs), the two ß-diketone antibiotics (DKAs), are two frequently detected pollutants in the environment; however, little data are available on their combined toxicity to zebrafish (Danio rerio). This study reports that toxicologic effects of combined DKA (FQs-TCs) exposure on zebrafish were comparable with or slightly less than those of TCs alone, showing that TCs played a major toxicologic role in the mixtures. The effects of FQs, TCs, and DKAs on malformation rates of zebrafish were dose dependent, with EC50 values of 481.3, 16.4, and 135.1 mg/L, respectively. According to the combined effects of DKAs on zebrafish hatching, mortality, and malformation rates, the interaction between FQs and TCs was shown to be antagonistic based on three assessment methods: Toxic Unit, Additional Index, and Mixture Toxic Index. The 1.56 mg/L TC and 9.38 mg/L DKA treatments resulted in higher zebrafish basal swimming rate compared with the control group at 120 hours postfertilization (hpf). in both light and light-to-dark photoperiod experiments. Under conditions of no obvious abnormality in cardiac development, the heart beats were decreased significantly because of DKA exposure, such as decreasing by ∼20% at 150 mg/L DKAs. Transmission electron microscopy observation of myocytes from DKA-exposed hearts displayed prominent interruptions and myofibrillar disorganization of the normal parallel alignment of thick and thin filaments, and partial edematous and dissolved membranes of cell nuclear tissues. At 90 mg/L DKAs, the transcriptional levels of the acta1a, myl7, and gle1b genes, related to heart development and skeletal muscle formation, were significantly changed. This is consistent with the swimming behavior and histopathologic results obtained by transmission electron microscopy. In summary, the toxicity of the combined DKAs to zebrafish was comparable with or less than that of TCs alone and had the ability to impair individual behaviors that are of great importance in the assessment of their ecologic fitness. © 2014 Wiley Periodicals, Inc. Environ Toxicol 31: 736-750, 2016.