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

Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:Predictors of patient prognosis

Patients with mild traumatic brain injury have a diverse clinical presentation, and the underlying pathophysiology remains poorly understood. Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neurobiological markers after mild traumatic brain injury. This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury. Graph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function. However, most previous mild traumatic brain injury studies using graph theory have focused on specific populations, with limited exploration of simultaneous abnormalities in structural and functional connectivity. Given that mild traumatic brain injury is the most common type of traumatic brain injury encountered in clinical practice, further investigation of the patient characteristics and evolution of structural and functional connectivity is critical. In the present study, we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury. In this longitudinal study, we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 weeks of injury, as well as 36 healthy controls. Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis. In the acute phase, patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network. More than 3 months of followup data revealed signs of recovery in structural and functional connectivity, as well as cognitive function, in 22 out of the 46 patients. Furthermore, better cognitive function was associated with more efficient networks. Finally, our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury. These findings highlight the importance of integrating structural and functional connectivity in understanding the occurrence and evolution of mild traumatic brain injury. Additionally, exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.</p

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 &lt; 0.05), and pain sensation was significantly inhibited in acetic acid-induced writhing test (p &lt; 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

Primjena Monte Carlo metode s algoritmom simuliranog opuštanja u analizi Mossbauerovih spektara

A convenient and robust procedure for Mössbauer analysis based on Monte Carlo method is described. The method uses simulated annealing approach to find the optimum Mössbauer parameters in the Lorentzian profile as initial values for the Monte Carlo search program. A succession of solutions to the function describing the spectrum is then randomly generated until the solution with the minimum chi-square with respect to the experimental data is reached. The result having the reduced chi-square close to 1 shows the validity of the method.Opisujemo pogodan i snažan postupak za analizu Mössbauerovih spektara zasnovan na Monte Carlo metodi. Primjenjuje se pristup simuliranog opuštanja za nalaženje najpovoljnijih parametara Lorentzovih profila Mossbauerovih spektara koji su početne vrijednosti za Monte Carlo program traženja. Zatim se nasumice stvara niz rješenja za funkciju koja opisuje spektar dok se ne postigne rješenje koje je u najboljem skladu s eksperimentalnim podacima. Postignuti ishod je u dobrom skladu s mjerenim spektrom, što pokazuje vrijednost metode