Time analysis of alveolar ridge preservation using a combination of mineralized boneâ plug and denseâ polytetrafluoroethylene membrane: A histomorphometric study

BackgroundThe objective of this study was to histologically evaluate and compare vital bone formation, residual graft particles, and fraction of connective tissue (CT)/other tissues between three different time points at 2â month intervals after alveolar ridge preservation with a cancellous allograft and denseâ polytetrafluoroethylene (dâ PTFE) membrane.MethodsRidge preservation with a cancellous allograft and dâ PTFE membrane was performed at 49 extraction sockets (one per patient). Volunteers were assigned to implant placement at three different time points of 2, 4, and 6 months, at which time core biopsies were obtained. Histomorphometric analysis was performed to determine the percentages of vital bone, residual graft particles, and connective tissue/other nonâ bone components, and subjected to statistical analyses.ResultsThere was a statistically significant difference in the amount of vital bone at every time point from 28.31% to 40.87% to 64.11% (at 2â , 4â , and 6â month groups, respectively) (P < 0.05). The percentage of residual graft particles ranged from 44.57% to 36.16% to 14.86%, showing statistical significance from 4 to 6 months (21.29%, P < 0.001), and 2 to 6 months (29.71%, P < 0.001), while there were no significant differences for the amount of CT/other tissue among the different time points.ConclusionsThis study provided the first histologic comparison of alveolar ridge preservation using a cancellous allograft and dâ PTFE membrane at three different time points. Extraction sockets that healed for 6 months produced the highest amount of vital bone in combination with the least percentage of residual graft particles, while similar results were observed for the fraction of CT/other tissues between the three time points.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154387/1/jper10405.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154387/2/jper10405_am.pd

The Differential Role of Human Cationic Trypsinogen (PRSS1) p.R122H Mutation in Hereditary and Nonhereditary Chronic Pancreatitis: A Systematic Review and Meta-Analysis.

Background:Environmental factors and genetic mutations have been increasingly recognized as risk factors for chronic pancreatitis (CP). The PRSS1 p.R122H mutation was the first discovered to affect hereditary CP, with 80% penetrance. We performed here a systematic review and meta-analysis to evaluate the associations of PRSS1 p.R122H mutation with CP of diverse etiology. Methods:The PubMed, EMBASE, and MEDLINE database were reviewed. The pooled odds ratio (OR) with 95% confidence intervals was used to evaluate the association of p.R122H mutation with CP. Initial analysis was conducted with all etiologies of CP, followed by a subgroup analysis for hereditary and nonhereditary CP, including alcoholic or idiopathic CP. Results:A total of eight case-control studies (1733 cases and 2415 controls) were identified and included. Overall, PRSS1 p.R122H mutation was significantly associated with an increased risk of CP (OR = 4.78[1.13-20.20]). Further analysis showed p.R122H mutation strongly associated with the increased risk of hereditary CP (OR = 65.52[9.09-472.48]) but not with nonhereditary CP, both alcoholic and idiopathic CP. Conclusions:Our study showing the differential role of p.R122H mutation in various etiologies of CP indicates that this complex disorder is likely influenced by multiple genetic factors as well as environmental factors

Entanglement control in one-dimensional s=1/2s=1/2 random XY spin chain

The entanglement in one-dimensional random XY spin systems where the impurities of exchange couplings and the external magnetic fields are considered as random variables is investigated by solving the different spin-spin correlation functions and the average magnetization per spin. The entanglement dynamics near particular locations of the system is also studied when the exchange couplings (or the external magnetic fields) satisfy three different distributions(the Gaussian distribution, double-Gaussian distribution, and bimodal distribution). We find that the entanglement can be controlled by varying the strength of external magnetic field and the different distributions of impurities. Moreover, the entanglement of some nearest-neighboring qubits can be increased for certain parameter values of the three different distributions.Comment: 13 pages, 4 figure

Machine-learning-inspired quantum optimal control of nonadiabatic geometric quantum computation via reverse engineering

Quantum control plays an irreplaceable role in practical use of quantum computers. However, some challenges have to be overcome to find more suitable and diverse control parameters. We propose a promising and generalizable average-fidelity-based machine-learning-inspired method to optimize the control parameters, in which a neural network with periodic feature enhancement is used as an ansatz. In the implementation of a single-qubit gate by cat-state nonadiabatic geometric quantum computation via reverse engineering, compared with the control parameters in the simple form of a trigonometric function, our approach can yield significantly higher-fidelity ($>99.99\%$) phase gates, such as the $\pi / 8$ gate (T gate). Single-qubit gates are robust against systematic noise, additive white Gaussian noise and decoherence. We numerically demonstrate that the neural network possesses the ability to expand the model space. With the help of our optimization, we provide a feasible way to implement cascaded multi-qubit gates with high quality in a bosonic system. Therefore, the machine-learning-inspired method may be feasible in quantum optimal control of nonadiabatic geometric quantum computation.Comment: 12 pages, 8 figure