Optimization of Pedicle Screw Parameters for Enhancing Implant Stability Based on Finite Element Analysis.

OBJECTIVE: To improve implant stability parameters, including pedicle screw (PS) outer diameter, thread depth, and pitch, by finite element analysis. METHODS: Insertion and pullout of the PS were simulated by finite element analysis, and the precision of simulation was evaluated by comparison with mechanical tests. Influences of the parameters on the maximum insertion torque and maximum pullout force were analyzed by computational simulations, including single-factor analysis and orthogonal experiments. RESULTS: The simulation results agreed with the mechanical test results. The order of parameters influencing insertion torque and pullout force was outer diameter > pitch > thread depth. When the pilot hole diameter is 0.1 mm larger than the inner diameter of the PS, the calculated Pearson correlation coefficient between the maximum insertion torque and maximum pullout force was r = 0.99. The optimized PS had a maximum insertion torque of 485.16 N·mm and a maximum pullout force of 1726.33 N, 23.9% and 9.1% higher, respectively, than the values of standard screws. CONCLUSIONS: The presently used models are feasible for evaluating the implant stability of PSs. The maximum insertion torque and maximum pullout force of PSs are highly correlated and can be improved by increasing the outer diameter and decreasing pitch. Although with the parameters of the PS, pedicle size and bone mineral density are 2 additional factors to consider for better implant stability.

FET-LM: Flow-Enhanced Variational Autoencoder for Topic-Guided Language Modeling.

Variational autoencoder (VAE) is widely used in tasks of unsupervised text generation due to its potential of deriving meaningful latent spaces, which, however, often assumes that the distribution of texts follows a common yet poor-expressed isotropic Gaussian. In real-life scenarios, sentences with different semantics may not follow simple isotropic Gaussian. Instead, they are very likely to follow a more intricate and diverse distribution due to the inconformity of different topics in texts. Considering this, we propose a flow-enhanced VAE for topic-guided language modeling (FET-LM). The proposed FET-LM models topic and sequence latent separately, and it adopts a normalized flow composed of householder transformations for sequence posterior modeling, which can better approximate complex text distributions. FET-LM further leverages a neural latent topic component by considering learned sequence knowledge, which not only eases the burden of learning topic without supervision but also guides the sequence component to coalesce topic information during training. To make the generated texts more correlative to topics, we additionally assign the topic encoder to play the role of a discriminator. Encouraging results on abundant automatic metrics and three generation tasks demonstrate that the FET-LM not only learns interpretable sequence and topic representations but also is fully capable of generating high-quality paragraphs that are semantically consistent.

Cyclic alternating pattern in non-rapid eye movement sleep in patients with vestibular migraine.

OBJECTIVE: This study aimed to analyze the microstructural features of sleep in patients with vestibular migraine and migraine, and to hypothesize the pathophysiological mechanism between vestibular migraine and sleep disorders. METHODS: From March 2021 to June 2022, 35 vestibular migraine patients, 35 migraine patients, and 30 controls were collected from the Vertigo Center & Sleep Center of the Second Affiliated Hospital of Zhengzhou University. The anxiety and depression status, sleep quality, and cyclic alternating pattern (CAP) of the three groups were analyzed and compared using the Pittsburgh Sleep Quality Index, Hamilton Anxiety and Depression Scale, and polysomnography (PSG). RESULTS: The vestibular migraine group had a higher CAP time (mean 173.64 vs. 122.11, P < 0.001), CAP index (mean 54.25 vs. 37.50, P < 0.001), CAP rate (mean 48.41 vs. 32.31, P < 0.001), CAP sequences (mean 42.60 vs. 29.83, P < 0.001), A3% (mean 45.58 vs. 17.50, P < 0.001) and A2%+A3% (mean 68.87 vs. 38.83, P < 0.001) compared to the control group, with a lower A1 index (mean 16.68 vs. 23.87, P < 0.001) and A1% (mean 31.13% vs. 61.17, P < 0.001). CONCLUSION: Patients with vestibular migraine have poor sleep quality, thalamic-cortical hyperfunction and active arousal system. In addition, high CAP rate and high A2 to A3 ratio make the sleep structure more fragmented.