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This paper presents a method for tessellating tissue boundaries and their interiors, given as input a tissue map consisting of relevant classes of the head, in order to produce anatomical models for finite element-based simulation of endoscopic pituitary surgery. Our surface meshing method is based on the simplex model, which is initialized by duality from the topologically accurate results of the Marching Cubes algorithm, and which features explicit control over mesh scale, while using tissue information to adhere to relevant boundaries. Our mesh scale strategy is spatially varying, based on the distance to a central point or linearized surgical path. The tetrahedralization stage also features a spatially varying mesh scale, consistent with that of the surface mesh. [ABSTRACT FROM AUTHOR]

Purpose: To test whether radiolysis-induced fragmentation in frozen aqueous protein solution is dependent on solvent access to the surface of the protein or to the molecular mass of the polypeptide chain. Materials and methods: [sup 60]Co gamma-irradiation of three proteins at -78°C: lysozyme, citrate synthase and alpha-lactalbumin in their native state, with or without bound substrate, or denatured (random coil in urea/acid-denatured state). Results: By SDS-polyacrylamide gel electrophoresis/analysis of the protein-fragmentation process, it was found that for a given protein D[sub 37] values (dose to decrease the measured amount of protein, with an unaltered polypeptidic chain, to 37% of the initial amount) varied according to the state of the protein. D[sub 37] for denatured proteins was always much smaller than for native states, indicating a greater susceptibility to fragmentation. In urea, contrary to the native state, no well-defined fragments were observed. Radiolysis decay constants (K = 1/D[sub 37]) increased with solvent-accessible surface area of these proteins estimated from their radii of gyration in the various states. This is shown also in previous data on native or SDS-denatured proteins. Denatured proteins which have a large surface area exposed to the solvent compared with native ones are more fragmented at equal doses. Conclusions: It is concluded that D[sub 37] is directly related to the exposed surface area and not to the molecular mass of the polypeptide chain. [ABSTRACT FROM AUTHOR]

We identified two different inherited mutations in KCNH2 gene, or human ether-a-go-go related gene (hERG), which are linked to Long QT Syndrome. The first mutation was in a 1-day-old infant, whereas the second was in a 14-year-old girl. The two KCNH2 mutations were transiently transfected into either human embryonic kidney (HEK) cells or human induced pluripotent stem-cell derived cardiomyocytes. We performed associated multiscale computer simulations to elucidate the arrhythmogenic potentials of the KCNH2 mutations. Genetic screening of the first and second index patients revealed a heterozygous missense mutation in KCNH2, resulting in an amino acid change (P632L) in the outer loop of the channel and substitution at position 428 from serine to proline (S428P), respectively. Heterologous expression of P632L and S428P into HEK cells produced no hERG current compared to the wild type (WT). Moreover, the co-transfection of WT and P632L yielded no hERG current; however, the co-transfection of WT and S428P yielded partial hERG current. Action potentials were prolonged in a complete or partial blockade of hERG current from computer simulations which was more severe in Purkinje than ventricular myocytes. Three dimensional simulations revealed a higher susceptibility to reentry in the presence of hERG current blockade. Our experimental findings suggest that both P632L and S428P mutations may impair the KCNH2 gene. The Purkinje cells exhibit a more severe phenotype than ventricular myocytes, and the hERG current blockade renders the ventricles an arrhythmogenic substrate from computer modeling., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Owusu-Mensah et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ligament properties in the literature are variable, yet scarce, but needed to calibrate computational models for spine clinical research applications. A comparison of ligament stiffness properties and their effect on the kinematic behavior of a thoracic functional spinal unit (FSU) is examined in this paper. Six unique ligament property sets were utilized within a volumetric T7-T8 finite element (FE) model developed using computer-aided design (CAD) spinal geometry. A 7.5 Nm moment was applied along three anatomical planes both with and without costovertebral (CV) joints present. Range of Motion (RoM) was assessed for each property set and compared to published experimental data. Intact and serial ligament removal procedures were implemented in accordance with experimental protocol. The variance in both kinematic behavior and comparability with experimental data among property sets emphasizes the role nonlinear characterization plays in determining proper kinematic behavior in spinal FE models. Additionally, a decrease in RoM variation among property sets was exhibited when the model setup incorporated the CV joint. With proper assessment of the source and size of each ligament, the material properties considered here could be expanded and justified for implementation into thoracic spine clinical studies.

Mutation in the hERG gene leading to partial or complete blockade of the rapid delayed rectifier current causes Long QT Type 2 (LQT2) phenotype, the second most common form of Long QT Syndrome. However, the exact involvement of the His-Purkinje System (HPS) remains elusive. We utilized a finite element model of the rabbit ventricles integrated with a HPS to elucidate the role of HPS during LQT2-mediated arrhythmia. Following the induction of persistent reentry from an ectopic stimulus, we isolated the HPS at different time points. Moreover, we varied the coupling resistance and the number of myocytes at the Purkinje-Myocardial Junctions (PMJs) to ascertain how the junctional parameters altered reentry dynamics. Reentry was terminated with the earliest termination time for reentry coinciding with the earliest time the HPS was isolated. This observation provides evidence of direct involvement of the HPS during LQT2-mediated ventricular arrhythmia. Increasing the coupling resistance or the number of myocytes at the PMJs reduced the percentage of successful retrograde propagation during reentry. Thus, the HPS alters reentry dynamics. Our multi-scale computer modeling outcomes offer important new understandings of probable arrhythmia mechanisms under LQT2 circumstances.

The statistical data from the National Council on Aging indicates that a senior adult dies in the US from a fall every 19 minutes. The care of elderly people can be improved by enabling the detection of falling events, especially if it triggers the pneumatic actuation of a protective airbag. This work focuses on detecting impending fall risk of senior subjects within the geriatric population, towards a planned approach to mitigating fall injuries through pneumatic airbag deployment. With the widespread adoption of wearable sensors, there is an increased emphasis on fall prediction models that effectively cope with accelerometry signal data. Fall detection and gait classification are challenging tasks, especially in differentiating falls from near falls. We propose to apply attention to the deep neural network (DNN) analysis of acceleration data where a fall is known to have occurred. We take the maximum value of the sensor signals to define the observation window of the detector. Powered by a transformer DNN with word embedding, attention networks have achieved a state-of-the-art in natural language processing (NLP) tasks. Besides the success of the transformer for efficiently processing long sequences, it supports parallel computing with fast computation. In this paper, we propose a novel transformer attention network for gait analysis of fall detection modeling with Time2Vec positional encoding- founded on a Masked Transformer Network. Using our dataset, we demonstrate that the proposed approach achieves better specificity and sensitivity than the present models.

This paper presents early work on a fall detection method using transfer learning method, in conjunction with a long-term effort to combine efficient machine learning and prior personalized musculoskeletal modeling to deploy fall injury mitigation in geriatric subjects. Inspired by the tremendous progress in image-based object recognition with deep convolutional neural networks (DCNNs), we opt for a pre-trained kinematics-based machine learning approach through existing large-scale annotated accelerometry datasets. The accelerometry datasets are converted to images using time-frequency analysis, based on scalograms, by computing the continuous wavelet transform filter bank. Subsequently, data augmentation is performed on these scalogram images to increase accuracy, thereby complementing limited labeled fall sensor data, enabling transfer learning from the existing pre-trained model. The experimental results on publicly available URFD datasets demonstrate that transfer learning leads to a better performance than the existing methods in the case of scarce labeled training data.

Pre-eclampsia, a hypertensive disorder of pregnancy, continues to be a significant cause of global maternal morbidity. Low-dose aspirin remains the only standard-of-care prophylactic therapy for preventing pre-eclampsia, but is limited in efficacy. Heparin and its derivatives may further enhance the efficacy of aspirin therapy to prevent pre-eclampsia, but the mechanisms mediating this augmentative effect are not known. Although heparin is an anticoagulant agent, it also possesses many anticoagulant-independent properties that may be relevant in the prevention of pre-eclampsia, including effects on placental, vascular and inflammatory function. This review summarizes the non-anticoagulant properties of heparin, and extrapolates how these actions may influence the trajectory of pre-eclampsia pathogenesis as a means of pathway-specific therapy., (© 2018 International Society on Thrombosis and Haemostasis.)

An error-controlled mesh refinement procedure for needle insertion simulations is presented. As an example, the procedure is applied for simulations of electrode implantation for deep brain stimulation. We take into account the brain shift phenomena occurring when a craniotomy is performed. We observe that the error in the computation of the displacement and stress fields is localised around the needle tip and the needle shaft during needle insertion simulation. By suitably and adaptively refining the mesh in this region, our approach enables to control, and thus to reduce, the error whilst maintaining a coarser mesh in other parts of the domain. Through academic and practical examples we demonstrate that our adaptive approach, as compared with a uniform coarse mesh, increases the accuracy of the displacement and stress fields around the needle shaft and, while for a given accuracy, saves computational time with respect to a uniform finer mesh. This facilitates real-time simulations. The proposed methodology has direct implications in increasing the accuracy, and controlling the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anaesthesia, or cryotherapy. Moreover, the proposed approach can be helpful in the development of robotic surgeries because the simulation taking place in the control loop of a robot needs to be accurate, and to occur in real time., (Copyright © 2018 John Wiley & Sons, Ltd.)

Introduction: The placenta contains efflux transporters, including P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), that limit the passage of xenobiotics, certain hormones and nutrients from the maternal to the fetal circulation. The expression of these transporters changes with gestational age, yet the mechanisms involved remain unknown. However, the changes in P-gp and BCRP transporter expression coincide with those of oxygen tension in the placenta, and oxygen tension has been shown to modulate P-gp and BCRP expression in other tissues. The objective of this study was to investigate the effects of oxygen tension on P-gp and BCRP expression in the term human placenta., Methods: Following equilibration in culture (96 h), term placental explants (n = 7) were cultured in 3% or 20% oxygen for 24 and 48 h. Culture medium was collected every 24 h to measure lactate dehydrogenase (LDH; explant viability) and human chorionic gonadotropin (hCG; syncytiotrophoblast function). P-gp (encoded by ABCB1) and BCRP (encoded by ABCG2) protein and mRNA, as well as VEGFA mRNA were measured using western blot and qRT-PCR. P-gp localization was determined using immunofluorescence., Results: Oxygen tension had a significant effect on P-gp expression, with ABCB1/P-gp mRNA and protein levels increased in the hypoxic condition (3% O2) after 48 h (p < 0.05). VEGFA mRNA was elevated by hypoxia at both 24 and 48 h (p < 0.05). In contrast, placental ABCG2/BCRP mRNA and protein expression were stable with changes in oxygen tension. We identified profound differences in the glycosylation of P-gp between cultured and non-cultured placental tissue, with cultured explants expressing deglycosylated P-gp., Conclusions: These findings demonstrate that, at term, the expression of placental P-gp, is regulated by oxygen tension. This suggests that changes in oxygenation of the placenta in the third trimester may alter levels of placental P-gp, and in doing so alter fetal exposure to P-gp substrates, including xenobiotics and certain hormones., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The human placenta has a number of protective mechanisms that help to prevent potentially harmful compounds from entering the fetal compartment. Two important transporter proteins are phospho-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) which are mainly expressed in the syncytiotrophoblast where they actively extrude a wide range of xenobiotics. The expression profile of these transporters varies with advancing gestation. P-gp has been shown to decline near term, leaving the fetus susceptible to potentially teratogenic drugs commonly administered to pregnant women (i.e., synthetic glucocorticoids, selective serotonin reuptake inhibitors, glyburide, antiretrovirals, etc.). Drug transporter expression is regulated by a number of transcription factors, and steroid hormones present during pregnancy, such as progesterone, estrogen and corticosteroids. Drug transporter levels have also been found to be altered in pathological pregnancies (preterm, pre-eclampsia, growth restriction and infection). Genetic variation in the genes that encode these drug transporters can significantly alter transporter function and may play a significant role in determining the susceptibility of a fetus to maternally-administered therapeutic drugs. Understanding the regulation of placental drug transporters in normal and pathological pregnancies is critical to further our knowledge of fetal development, and may lead to the development of more selectively-targeted maternal and fetal drug treatments., (Copyright © 2012 Elsevier Ltd. All rights reserved.)