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Introduction: The cerebellopontine angle (CPA) is a subarachnoid space in the lateral aspect of the posterior fossa. In this study, we propose a complementary analysis of the CPA from the cerebellopontine fissure.
Methods: We studied 50 hemi-cerebelli in the laboratory of neuroanatomy and included a description of the CPA anatomy from the cerebellopontine fissure and its relationship with the flocculus and the 5th, 6th, 7th, and 8th cranial nerves (CN) origins.
Results: The average distance from the 5th CN to the mid-line (ML) was 19.2 mm, 6th CN to ML was 4.4 mm, 7-8 complex to ML was 15.8 mm, flocculus to ML was 20.5 mm, and flocculus to 5th CN was 11.5 mm, additionally, and the diameter of the flocculus was 9.0 mm. The angle between the vertex in the flocculus and the V CN and the medullary-pontine line was 64.8 degrees.
Discussion: The most common access to the CPA is through the retrosigmoid-suboccipital region and this approach can be done with the help of an endoscope. The anatomy of origins of neural structures tends to be preserved in cases of CPA lesions.
Conclusion: Knowledge of the average distances between the neural structures in the cerebellar-pontine fissure and the angular relationships between these structures facilitates the use of surgical approaches such as microsurgery and endoscopy.
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http://dx.doi.org/10.1080/02688697.2018.1426722 | DOI Listing |
PLoS One
September 2025
School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China.
Accurate prediction of time-varying dynamic parameters during the milling process is a prerequisite for chatter-free cutting of thin-walled parts. In this paper, a matrix iterative prediction method based on weighted parameters is proposed for the time-varying structural modes during the milling of thin-walled blade structures. The thin-walled blade finite element model is established based on the 4-node plate element, and the time-varying dynamic parameters of the workpiece during the cutting process can be obtained by modifying the thickness of the nodes through the constructed mesh element finite element model It is not necessary to re-divide the mesh elements of the thin-walled parts at each cutting position, thus improving the calculation efficiency of the dynamic parameters of the workpiece.
View Article and Find Full Text PDFSci Prog
September 2025
School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China.
At present, significant progress has been made in the research of image encryption, but there are still some issues that need to be explored in key space, password generation and security verification, encryption schemes, and other aspects. Aiming at this, a digital image encryption algorithm was developed in this paper. This algorithm integrates six-dimensional cellular neural network with generalized chaos to generate pseudo-random numbers to generate the plaintext-related ciphers.
View Article and Find Full Text PDFJ Phys Chem Lett
September 2025
Tianjin Key Laboratory of Film Electronic and Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
Achieving UVA/B-selective, skin-inspired nociceptors with perception and blockade functions at the single-unit device level remains challenging. This is because the device necessitates distinct components for every performance metric, thereby leading to complex preparation processes and restricted performance, as well as the absence of deep UV (UVB and below)-selective semiconductors. Here, to address this, we develop a structure-simplification skin-inspired nociceptor using a reverse type-II CuAgSbI/MoS heterostructure.
View Article and Find Full Text PDFJ Chem Phys
September 2025
National Synchrotron Radiation Laboratory, State Key Laboratory of Advanced Glass Materials, Anhui Provincial Engineering Research Center for Advanced Functional Polymer Films, University of Science and Technology of China, Hefei, Anhui 230029, China.
Polymer density is a critical factor influencing material performance and industrial applications, and it can be tailored by modifying the chemical structure of repeating units. Traditional polymer density characterization methods rely heavily on domain expertise; however, the vast chemical space comprising over one million potential polymer structures makes conventional experimental screening inefficient and costly. In this study, we proposed a machine learning framework for polymer density prediction, rigorously evaluating four models: neural networks (NNs), random forest (RF), XGBoost, and graph convolutional neural networks (GCNNs).
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287, Darmstadt, Germany.
Chromatin dynamics play a crucial role in cellular differentiation, yet tools for studying global chromatin mobility in living cells remain limited. Here, a novel probe is developeded for the metabolic labeling of chromatin and tracking its mobility during neural differentiation. The labeling system utilizes a newly developed silicon rhodamine-conjugated deoxycytidine triphosphate (dCTP).
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