Mathematical evaluation of the influence of multiple factors on implant stability quotient values in clinical practice: a retrospective study

Objectives: The objective of this study is to mathematically evaluate the influence of multiple factors on implant stability quotient values in clinical practice. Patients and methods: Resonance frequency analysis was performed at T1 (measured immediately at the time of implant placement) and at T2 (measured before dental restoration) in 177 patients (329 implants). Using a multivariate linear regression model, we analyzed the influence of the following eleven candidate factors: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting (presence or absence), insertion torque, I-/II-stage healing pattern, implant diameter, implant length, and T1-T2 time interval. Results: The following factors were identified to significantly influence the implant stability quotient (ISQ) values at T1: insertion torque, bone grafting, I-/II-stage healing pattern, immediate/delayed implantation, maxillary/mandibular location, implant diameter, and sex. In contrast, the ISQ values at T2 were significantly influenced only by three factors: implant diameter, T1-T2 time interval, and insertion torque. Conclusion: Among the eleven candidate factors, seven key factors were found to influence the T1-ISQ values, while only three key factors influenced the T2-ISQ values. Both T1 and T2-ISQ values were found to be influenced by implant diameter and insertion torque. T1 was influenced specifically by the sex of the patient, the location (maxillary or mandibular), the implantation mode (immediate/delayed implantation), the healing stage, and the absence or presence of bone graft materials

Human Bone Typing Using Quantitative Cone-Beam Computed Tomography.

INTRODUCTION Bone typing is crucial to enable the choice of a suitable implant, the surgical technique, and the evaluation of the clinical outcome. Currently, bone typing is assessed subjectively by the surgeon. OBJECTIVE The aim of this study is to establish an automatic quantification method to determine local bone types by the use of cone-beam computed tomography (CBCT) for an observer-independent approach. METHODS Six adult human cadaver skulls were used. The 4 generally used bone types in dental implantology and orthodontics were identified, and specific Hounsfield unit (HU) ranges (grey-scale values) were assigned to each bone type for identification by quantitative CBCT (qCBCT). The selected scanned planes were labelled by nonradiolucent markers for reidentification in the backup/cross-check evaluation methods. The selected planes were then physically removed as thick bone tissue sections for in vitro correlation measurements by qCBCT, quantitative micro-computed tomography (micro-CT), and quantitative histomorphometry. RESULTS Correlation analyses between the different bone tissue quantification methods to identify bone types based on numerical ranges of HU values revealed that the Pearson correlation coefficient of qCBCT with micro-CT and quantitative histomorphometry was R = 0.9 (P = .001) for all 4 bone types . CONCLUSIONS We found that  qCBCT can reproducibly and objectively assess human bone types at implant sites

Comparative studies on the toxicological, antiinflammatory and analgesic properties of three sources of Xuedan in mice and their rapid identification by electronic tongue

Purpose: To compare the toxicological, anti-inflammatory and analgesic properties of three sources of Xuedan, viz, Hemsleya omeiensis (HO), Hemsleya giganth (HG) and Hemsleya dolichocarpa (HD) in mice, and to study their rapid identification based on electronic tongue (E-tongue).Methods: After 7 days of administration, the median lethal doses (LD50) of the three xuedan decoctions in mice were determined. In addition, the anti-inflammatory and analgesic effects of the three xuedans were evaluated in mice using xylene-induced ear edema and acetic acid-induced pain. Furthermore, Etongue technology was used to identify HO, HG and HD. Principal component analysis (PCA) and discriminant factor analysis (DFA) were used to analyze the data acquired by E-tongue.Results: The median lethal dose (LD50) values of H. omeiensis, H. gigantha and H. dolichocarpa were 32.3, 17.4 and 13.7g/kg, respectively. Compared with normal control group, the anti-inflammatory effects of Xuedan were obvious in xylene-induced ear edema (p < 0.05), and pain sensation was significantly inhibited in acetic acid-induced writhing test (p < 0.05). Furthermore, E-tongue technology effectively identified HO, HG and HD.Conclusion: H. omeiensis exhibits the highest LD50 value and best analgesic effect among the three sources of xuedan. E-tongue technology is effective and rapid in identifying HO, HG and HD.Keywords: Xuedan, Hemsleya omeiensis, Hemsleya gigantha, Hemsleya dolichocarpa, Antiinflammation, Analgesia, Electronic tongu

Composition Spectrum of Oral Microbiota Diversity in Patients with Pancreatic Cancer: A Systematic Review

Objective To systematically evaluate the diversity of oral flora in patients with pancreatic cancer. Methods A cross-sectional study was conducted, focusing on the oral flora diversity profiles of patients with pancreatic cancer. The studies were retrieved from PubMed, Web of science, EMbase, The Cochrane Library, CBM, CNKI, Wanfang, and VIP databases, and the search period was from the establishment of the database to July 15, 2023. According to the inclusion and exclusion criteria, two researchers screened intensive review literature, extracted data and information, and carried out Meta-analysis using qualitative systematic review and Review Manager 5.4. Results Seven cross-sectional studies were reviewed, including 187 patients with pancreatic cancer and 440 healthy controls. The results of meta-analysis showed that the oral microbiota diversity Simpson index of patients with pancreatic cancer was reduced compared with that of healthy controls. Qualitative analysis showed that the relative abundance of Firmicute, Prevotella, Roseburia, and Streptococcus in patients with pancreatic cancer was higher than that in healthy people. The relative abundance of Proteobacteria, Neisseria, Haemophilus, porphyromonas, and Haemophilus parainfluenza in patients with pancreatic cancer was lower than that in healthy people. Conclusion Patients with pancreatic cancer have distinct oral flora, which has high relative abundance of Firmicutes, Prevotella etc. and low relative abundance of Proteobacteria, Neisseria, etc