The Use of 810 and 1064 nm Lasers on Dental Implants: In Vitro Analysis of Temperature, Surface Alterations, and Biological Behavior in Human Gingival Fibroblasts.

Objective: The primary objective of this study was to evaluate the safety of 810 and 1064 nm laser treatment on dental implants. Background: Peri-implantitis is a challenge for clinicians and researchers. Methods: A pig mandible model was used to evaluate temperature increases during laser irradiation. Surface alterations on processed pure titanium discs were analyzed via scanning electron microscopy and measurement of surface contact angles. Processed titanium discs were cocultured in vitro with human gingival fibroblasts; subsequently, cell proliferation was measured. Results: The maximum temperature and time to reach each threshold were comparable. No surface alterations were detected after 810 nm laser irradiation, whereas surface cracks were observed after 1064 nm laser irradiation under the parameter setting of 31.84 W/cm2. Compared with unaltered processed pure titanium discs, the proliferation of human gingival fibroblasts was significantly greater on altered processed pure titanium discs. Conclusions: The use of either 810 or 1064 nm laser treatments may increase the risk of thermal damage in terms of increased temperature if the parameter setting is not warranted. In addition, the use of 1064 nm laser treatment could lead to changes in pure titanium discs that do not negatively affect cell proliferation. Further investigations of laser-assisted therapy are necessary to improve guidelines concerning the treatment of peri-implantitis. Clinical trial registration number: 2021-P2-098-01.

Bisphenol S induces oxidative stress-mediated impairment of testosterone synthesis by inhibiting the Nrf2/HO-1 signaling pathway.

Bisphenol S (BPS) is an environmental endocrine disruptor widely used in industrial production. BPS induces oxidative stress and exhibits male reproductive toxicity in mice, but the mechanisms by which BPS impairs steroid hormone synthesis are not fully understood. Nuclear factor erythroid 2-related factor 2(Nrf2)/HO-1 signaling is a key pathway in improving cellular antioxidant defense capacities. Therefore, this study explored the effects of exposure to BPS on testosterone synthesis in adult male mice and its mechanisms with regard to the Nrf2/HO-1 signaling pathway. Adult male C57BL/6 mice were orally exposed to BPS (2, 20, and 200 mg/kg BW) with sesame oil as a vehicle (0.1 ml/10 g BW) per day for 28 consecutive days. The results showed that compared with the control group, serum testosterone levels were substantially reduced in the 20 and 200 mg/kg BPS treatment groups, and testicular testosterone levels were reduced in all BPS treatment groups. These changes were accompanied by a prominent decrease in the expression levels of testosterone synthesis-related enzymes (STAR, CYP11A1, CYP17A1, HSD3B1, and HSD17B3) in the mouse testis. In addition, BPS induced oxidative stress in the testis by upregulating the messenger RNA and protein levels of Keap1 and downregulating the levels of Nrf2, HO-1, and downstream antioxidant enzymes (CAT, SOD1, and Gpx4). In summary, our results indicate that exposure of adult male mice to BPS can inhibit Nrf2/HO-1 signaling and antioxidant enzyme activity, which induces oxidative stress and thereby may impair testosterone synthesis in testicular tissues, leading to reproductive damage.

The BDNF-TrkB-CREB Signalling Pathway Is Involved in Bisphenol S-Induced Neurotoxicity in Male Mice by Regulating Methylation.

Bisphenol S (BPS), the most common substitute for bisphenol A in manufacturing, is associated with neurotoxicity, but its molecular mechanisms are unclear. Here, we studied the role of the BDNF-TrkB-CREB (brain-derived neurotrophic factor-tropomyosin-related kinase B-CAMP response element-binding protein) signalling pathway in bisphenol S-induced neurotoxicity via methylation regulation in male C57BL/6 mice. The mice were treated with sesame oil or 2, 20 and 200 mg/kg body weight BPS for 28 consecutive days, and the hippocampus was extracted. We recorded the body weight, organ index, and hippocampal pathology and ultrastructure of the mice. The BDNF, TrkB, CREB, phosphorylated (p)-CREB, DNMTs (DNA methyltransferases) levels were determined by qRT-PCR and/or Western blotting. BDNF promoter IV methylation level was detected by bisulfite sequencing PCR. BPS damaged the mouse hippocampus ultrastructure and reduced the number of synapses. Further, it increased the methylation rate of BDNF promoter IV; downregulated BDNF, CREB, p-CREB/CREB and DNMT1 expression; and upregulated DNMT3a and DNMT3b expression. Therefore, we speculate that the BDNF-TrkB-CREB pathway may be involved in BPS-induced neurotoxicity in male mice by regulating methylation.

Geranyl phenyl ethers from Illicium micranthum and their anti-HBV activity.

Fourteen new geranyl phenyl ethers (1-14) along with three known compounds (15-17) were isolated from Illicium micranthum, and their structures were elucidated by comprehensive spectroscopic methods. Illimicranins A-H (1-8) were characterized as geranyl vanillin ethers, while 9 and 10 were dimethyl acetal derivatives. Illimicranins I and J (11 and 12) were rare geranyl isoeugenol ethers. Illimicranins K and L (13 and 14) represented the first example of geranyl guaiacylacetone ether and geranyl zingerone ether, respectively. Compounds 1, 2 and 15 exhibited anti-HBV (hepatitis B virus) activity against HBsAg (hepatitis B surface antigen) and HBeAg (hepatitis B e antigen) secretion, and HBV DNA replication.

[A Sampling Survey of the Oral Health Status and Awareness among Primary School Students in Lhasa].

Objective To investigate the oral health status and awareness of urban children in Lhasa,aiming to provide a data basis for the prevention and treatment of children's caries and the promotion of oral health education. Methods A total of 504 Tibetan students were selected by cluster sampling from 2 primary schools in Chengguan District of Lhasa.All the participants were required to take oral health examination and complete a questionnaire about oral health awareness and behavior. Results The caries prevalence rate and mean decayed-missing-filled tooth(DMFT)of permanent teeth were 75.00% and 2.18±1.91,respectively.The rates of pit and fissure sealant and filling of permanent teeth were 3.77% and 6.81%,respectively.The caries prevalence rate of first permanent molars was 47.62%.The mean DMFT of permanent teeth and caries prevalence rate of first permanent molar were significantly higher in female group(P=0.001 and P=0.007,respectively).The prevalence rate of dental fluorosis was 61.51%,and the detection rate of dental calculus was 71.83%.Multivariate logistic regression analysis showed that prevalence of caries was influenced by many independent factors including gender,oral health awareness,intention of dental intervention,and dental experience. Conclusion High caries prevalence rate,low filling rate,and poor oral hygiene and health awareness were found among the primary school students in Lhasa,which require continuous dentistry investment and oral health education for the local students and their parents.

[Advances in the application of machine learning in maxillofacial cysts and tumors].

The application of artificial intelligence in medicine has gradually received attention along with its development. Many studies have shown that machine learning has a wide range of applications in stomatology, especially in the clinical diagnosis and treatment of maxillofacial cysts and tumors. This article reviews the application of machine learning in maxillofacial cyst and tumor to provide a new method for the diagnosis of oral and maxillofacial diseases.

The Optimal Outcome of Suppressing Ewing Sarcoma Growth in vivo With Biocompatible Bioengineered miR-34a-5p Prodrug.

Being the second most common type of primary bone malignancy in children and adolescents, Ewing Sarcoma (ES) encounters the dilemma of low survival rate with a lack of effective treatments. As an emerging approach to combat cancer, RNA therapeutics may expand the range of druggable targets. Since the genome-derived oncolytic microRNA-34a (miR-34a) is down-regulated in ES, restoration of miR-34a-5p expression or function represents a new therapeutic strategy which is, however, limited to the use of chemically-engineered miRNA mimics. Very recently we have developed a novel bioengineering technology using a stable non-coding RNA carrier (nCAR) to achieve high-yield production of biocompatible miRNA prodrugs, which is a great addition to current tools for the assessment of RNA therapeutics. Herein, for the first time, we investigated the biochemical pharmacology of bioengineered miR-34a-5p prodrug (nCAR/miR-34a-5p) in the control of ES using human ES cells and xenograft mouse models. The bioengineered nCAR/miR-34a-5p was precisely processed to mature miR-34a-5p in ES cells and subsequently suppressed cell proliferation, attributable to the enhancement of apoptosis and induction of G2 cell cycle arrest through downregulation of SIRT-1, BCL-2 and CDK6 protein levels. Furthermore, systemic administration of nCAR/miR-34a-5p dramatically suppressed the ES xenograft tumor growth in vivo while showing biocompatibility. In addition, the antitumor effect of bioengineered nCAR/miR-34a-5p was associated with a lower degree of tumoral cell proliferation and greater extent of apoptosis. These findings demonstrate the efficacy of bioengineered miR-34a-5p prodrug for the treatment of ES and support the development of miRNA therapeutics using biocompatible bioengineered miRNA prodrugs.

A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information.

BACKGROUND: The three-dimensional (3D) structure of chromatins plays significant roles during cell differentiation and development. Hi-C and other 3C-based technologies allow us to look deep into the chromatin architectures. Many studies have suggested that topologically associating domains (TAD), as the structure and functional unit, are conserved across different organs. However, our understanding about the underlying mechanism of the TAD boundary formation is still limited. RESULTS: We developed a computational method, TAD-Lactuca, to infer this structure by taking the contextual information of the epigenetic modification signals and the primary DNA sequence information on the genome. TAD-Lactuca is found stable in the case of multi-resolutions and different datasets. It could achieve high accuracy and even outperforms the state-of-art methods when the sequence patterns were incorporated. Moreover, several transcript factor binding motifs, besides the well-known CCCTC-binding factor (CTCF) motif, were found significantly enriched on the boundaries. CONCLUSIONS: We provided a low cost, effective method to predict TAD boundaries. Above results suggested the incorporation of sequence features could significantly improve the performance. The sequence motif enrichment analysis indicates several gene regulation motifs around the boundaries, which is consistent with TADs may serve as the functional units of gene regulation and implies the sequence patterns would be important in chromatin folding.

A novel method to predict protein-protein interactions based on the information of protein-protein interaction networks and protein sequence.

Protein-protein interactions (PPIs) are crucial to most biochemical processes in human beings. Although many human PPIs have been identified by experiments, the number is still limited compared to the available protein sequences of human organisms. Recently, many computational methods have been proposed to facilitate the recognition of novel human PPIs. However the existing methods only concentrated on the information of individual PPI, while the systematic characteristic of protein-protein interaction networks (PINs) was ignored. In this study, a new method was proposed by combining the global information of PINs and protein sequence information. Random forest (RF) algorithm was implemented to develop the prediction model, and a high accuracy of 91.88% was obtained. Furthermore, the RF model was tested using three independent datasets with good performances, suggesting that our method is a useful tool for identification of PPIs and investigation into PINs as well.

On the relation between residue flexibility and residue interactions in proteins.

B-factor from X-ray crystal structure can well measure protein structural flexibility, which plays an important role in different biological processes, such as catalysis, binding and molecular recognition. Understanding the essence of flexibility can be helpful for the further study of the protein function. In this study, we attempted to correlate the flexibility of a residue to its interactions with other residues by representing the protein structure as a residue contact network. Here, several well established network topological parameters were employed to feature such interactions. A prediction model was constructed for B-factor of a residue by using support vector regression (SVR). Pearson correlation coefficient (CC) was used as the performance measure. CC values were 0.63 and 0.62 for single amino acid and for the whole sequence, respectively. Our results revealed well correlations between B-factors and network topological parameters. This suggests that the protein structural flexibility could be well characterized by the inter-amino acid interactions in a protein.

Cross dehydrogenative arylation (CDA) of a benzylic C-H bond with arenes by iron catalysis.

Hooking up: FeCl(2) catalyzes the efficient cross dehydrogenative arylation of substrates having benzylic C-H bonds (see scheme). High regioselectivity was observed during the cross-coupling between compounds containing aromatic C(sp(2))-H bonds and benzylic C(sp(3))-H bonds. This process is proposed to proceed by single-electron-transfer oxidation and Friedel-Crafts alkylation.

Two multi-classification strategies used on SVM to predict protein structural classes by using auto covariance.

Machine learning methods play the very important role in protein secondary structure prediction and other related works. On condition of a certain approach, the prediction qualities mostly depend on the ways of representing protein sequences into numeric features. In this paper, two Support Vector Machine (SVM) multi-classification strategies, "one-against-one" (1-a-1) and "one-against-all" (1-a-a), were used in protein structural classes identification. Auto covariance (AC), which transforms the physicochemical properties of the amino acids of the proteins into a data matrix, focuses on the neighboring effects and the interactions between residues in protein sequences. "1-a-1" approach was used on SVM to predict protein structural classes and obtained very promising overall accuracy 90.69% by Jackknife test. It was more than 10% higher than the accuracy obtained by using "1-a-a". Experimental results led to the finding that the SVM predictor constructed by "1-a-1" can avoid the appearance of biased prediction accuracy. This current method, using the protein primary sequence information described by auto covariance (AC) and "1-a-1" approach on SVM, should play an important complementary role in other related applications.