Nasal Airflow Dynamics following LeFort I Advancement in Cleft Nasal Deformities: A Retrospective Preliminary Study.

Unilateral cleft lip and palate (UCLP) nasal deformity impacts airflow patterns and pressure distribution, leading to nasal breathing difficulties. This study aims to create an integrated approach using computer-aided design (CAD) and computational fluid dynamics (CFD) to simulate airway function and assess outcomes in nasal deformities associated with unilateral cleft lip and palate (UCLP) after LeFort I osteotomy advancement. Significant alterations were observed in nasal geometry, airflow velocity, pressure dynamics, volumetric flow rate, and nasal resistance postoperatively, indicating improved nasal airflow. The cross-sectional area increased by 26.6%, airflow rate by 6.53%, and nasal resistance decreased by 6.23%. The study offers quantitative insights into the functional impacts of such surgical interventions, contributing to a deeper understanding of UCLP nasal deformity treatment and providing objective metrics for assessing surgical outcome.

Machine learning-based approaches for identifying human blood cells harboring CRISPR-mediated fetal chromatin domain ablations.

Two common hemoglobinopathies, sickle cell disease (SCD) and ß-thalassemia, arise from genetic mutations within the ß-globin gene. In this work, we identified a 500-bp motif (Fetal Chromatin Domain, FCD) upstream of human ϒ-globin locus and showed that the removal of this motif using CRISPR technology reactivates the expression of ϒ-globin. Next, we present two different cell morphology-based machine learning approaches that can be used identify human blood cells (KU-812) that harbor CRISPR-mediated FCD genetic modifications. Three candidate models from the first approach, which uses multilayer perceptron algorithm (MLP 20-26, MLP26-18, and MLP 30-26) and flow cytometry-derived cellular data, yielded 0.83 precision, 0.80 recall, 0.82 accuracy, and 0.90 area under the ROC (receiver operating characteristic) curve when predicting the edited cells. In comparison, the candidate model from the second approach, which uses deep learning (T2D5) and DIC microscopy-derived imaging data, performed with less accuracy (0.80) and ROC AUC (0.87). We envision that equivalent machine learning-based models can complement currently available genotyping protocols for specific genetic modifications which result in morphological changes in human cells.

In Vitro Flow Visualization in a Lactating Human Breast Model.

Human milk extraction from the breast is affected by the infant's oral activities. Natural suckling by the infant includes both intraoral vacuum and peripheral oral compression during breastfeeding. However, the contribution of each of these motions to milk extraction at the outlet and at the duct bifurcations is unclear. In this work, we investigated the flow field in a lactating breast model considering bifurcated milk ducts and multiphase breast-infant interactions. A bio-inspired breastfeeding simulator device was utilized to mimic an infant's oral feeding mechanism during breastfeeding and extract the human milk-mimicking Fluid from the transparent and elastic lactating breast phantom during experiments. Using a particle image velocimetry system, we found that the oscillatory flow under vacuum pressure provides a higher velocity field at the outlet compared to that when an infant applies both vacuum and oral compression pressures. Additionally, the intraoral vacuum coordinated with the oral peripheral compression causes stronger vorticities and secondary flows at the adjunction of the bifurcated ducts than the vacuum-only case. Vacuum-only extraction yields an increase in flow velocity at the outlet and could be one of the reasons for nipple pain, whereas infant's oral activities on the breast generated more vortices in the milk duct adjunctions and might cause milk duct clogs. This phenomenon is rationalized based on the validation of a previous in vivo clinical study of milk production compared between commercial pumps and infant suckling. The fact that milk consumption of vacuum-only extraction is less than that of vacuum plus oral compression further explains the effectiveness of applying a natural suckling pattern in human lactation.

Pilot Clinical Study Investigating the Thermal Physiology of Breast Cancer via High-Resolution Infrared Imaging.

This descriptive study investigates breast thermal characteristics in females histologically diagnosed with unilateral breast cancer and in their contralateral normal breasts. The multi-institutional clinical pilot study was reviewed and approved by the Institutional Review Boards (IRBs) at participating institutions. Eleven female subjects with radiologic breast abnormalities were enrolled in the study between June 2019 and September 2019 after informed consent was obtained. Static infrared images were recorded for each subject. The Wilcoxon signed rank test was used to conduct paired comparisons in temperature data between breasts among the eight histologically diagnosed breast cancer subjects (n = 8). Localized temperatures of cancerous breast lesions were significantly warmer than corresponding regions in contralateral breasts (34.0 ± 0.9 °C vs. 33.2 ± 0.5 °C, p = 0.0142, 95% CI 0.25-1.5 °C). Generalized temperatures over cancerous breasts, in contrast, were not significantly warmer than corresponding regions in contralateral breasts (33.9 ± 0.8 °C vs. 33.4 ± 0.4 °C, p = 0.0625, 95% CI -0.05-1.45 °C). Among the breast cancers enrolled, breast cancers elevated temperatures locally at the site of the lesion (localized hyperthermia), but not over the entire breast (generalized hyperthermia).

Fluid-structure interaction modeling of lactating breast: Newtonian vs. non-Newtonian milk.

Breastfeeding is a highly dynamic and complex mechanism. The suckling process by the infant involves compression and intra-oral vacuum pressure, leading to milk expression from breast. The accumulated milk from the nipple varies depending on the milk properties and transient flow rate during the suckling cycle. Rheological studies on raw human milk indicate that milk has a non-Newtonian shear-thinning flow behavior. This study aims to investigate the effect of non-Newtonian milk on flow behavior through the breast ductal system using fluid-structure interaction (FSI) simulation. The results of the non-Newtonian effects on flow velocity and the volumetric flow rate of expressed milk are presented. The results show that non-Newtonian Carreau model is promising for the simulation of human milk flow through the breast ductal systems. Also, the results show that the non-Newtonian effects on the milk flow behavior appear for 30-35% of the suckling cycle. Therefore, the Newtonian model is acceptable for the purpose of numerical simulation.

Three-Dimensional Printing of Ceramics through "Carving" a Gel and "Filling in" the Precursor Polymer.

Achieving a viable process for three-dimensional (3D) printing of ceramics is a sought-after goal in a wide range of fields including electronics and sensors for harsh environments, microelectromechanical devices, energy storage materials, and structural materials, among others. Low laser absorption of ceramic powders renders available additive manufacturing (AM) technologies for metals not suitable for ceramics. Polymer solutions that can be converted to ceramics (preceramic polymers) offer a unique opportunity to 3D-print ceramics; however, due to the low viscosity of these polymers, so far, their 3D printing has only been possible by combining them with specialized light-sensitive agents and subsequently cross-linking them layer by layer by rastering an optical beam. The slow rate, lack of scalability to large specimens, and specialized chemistry requirements of this optical process are fundamental limitations. Here, we demonstrate 3D printing of ceramics enabled by dispensing the preceramic polymer at the tip of a moving nozzle into a gel that can reversibly switch between fluid and solid states, and subsequently thermally cross-linking the entire printed part "at-once" while still inside the same gel. The solid gel, which is composed of mineral oil and silica nanoparticles, converts to fluid at the tip of the moving nozzle, allows the polymer solution to be dispensed, and quickly returns to a solid state to maintain the geometry of the printed polymer both during printing and the subsequent high-temperature (160 °C) cross-linking. We retrieve the cross-linked part from the gel and convert it to ceramic by high-temperature pyrolysis. This scalable process opens up new opportunities for low-cost and high-speed production of complex three-dimensional ceramic parts and will be widely used for high temperature and corrosive environment applications, including electronics and sensors, microelectromechanical systems, energy and structural applications.

Determining the thermal characteristics of breast cancer based on high-resolution infrared imaging, 3D breast scans, and magnetic resonance imaging.

For over the three decades, various researchers have aimed to construct a thermal (or bioheat) model of breast cancer, but these models have mostly lacked clinical data. The present study developed a computational thermal model of breast cancer based on high-resolution infrared (IR) images, real three-dimensional (3D) breast surface geometries, and internal tumor definition of a female subject histologically diagnosed with breast cancer. A state-of-the-art IR camera recorded IR images of the subject's breasts, a 3D scanner recorded surface geometries, and standard diagnostic imaging procedures provided tumor sizes and spatial locations within the breast. The study estimated the thermal characteristics of the subject's triple negative breast cancer by calibrating the model to the subject's clinical data. Constrained by empirical blood perfusion rates, metabolic heat generation rates reached as high as 2.0E04 W/m3 for normal breast tissue and ranged between 1.0E05-1.2E06 W/m3 for cancerous breast tissue. Results were specific to the subject's unique breast cancer molecular subtype, stage, and lesion size and may be applicable to similar aggressive cases. Prior modeling efforts are briefly surveyed, clinical data collected are presented, and finally thermal modeling results are presented and discussed.

Bio-Inspired Breastfeeding Simulator (BIBS): A Tool for Studying the Infant Feeding Mechanism.

OBJECTIVE: This work introduces a bio-inspired breastfeeding simulator (BIBS), an experimental apparatus that mimics infant oral behavior and milk extraction, with the application of studying the breastfeeding mechanism in vitro. METHODS: The construction of the apparatus follows a clinical study by the authors that collects measurements of natural intra-oral vacuum, the pressure from infant's jaw, tongue and upper palate, as well as nipple deformation on the breast areola area. The infant feeding mechanism simulator consists of a self-programmed vacuum pump assembly simulating the infant's oral vacuum, two linear actuators mimicking the oral compressive forces, and a motor-driven gear representing the tongue motion. A flexible, transparent and tissue-like breast phantom with bifurcated milk duct structure is designed and developed to work as the lactating human breast model. Bifurcated ducts are connected with a four-outlet manifold under a reservoir filled with milk-mimicking liquid. Piezoelectric sensors and a CCD (charge-coupled device) camera are used to record and measure the in vitro dynamics of the apparatus. RESULTS: All mechanisms are successfully coordinated to mimic the infant's feeding mechanism. Suckling frequency and pressure values on the breast phantom from the experimental apparatus are in good agreement with the clinical data. Also, the change in nipple deformation captured by BIBS matches with those from in vivo clinical ultrasound images. SIGNIFICANCE: The fully-developed breastfeeding simulator provides a powerful tool for understanding the bio-mechanics of breastfeeding and formulates a foundation for future breastfeeding device development.

Fluid-structure interaction modeling of lactating breast.

There are two theories for the dynamics of milk expression by the infant. One hypothesis is that milk expression is due to the negative pressure applied by the infant sucking; the alternative hypothesis is that the tongue movement and squeezing of nipple/areola due to mouthing is responsible for the extraction of milk from the nipple. In this study, 3-D two-way Fluid-Structure Interaction (FSI) simulations are conducted to investigate the factors that play the primary role in expressing milk from the nipple. The models include the solid deformation and periodic motion of the tongue and jaw movement. To obtain the boundary conditions, ultrasound images of the oral cavity and motion of the tongue movement during breastfeeding are extracted in parallel to the intra-oral vacuum pressure. The numerical results are cross-validated with clinical data. The results show that, while vacuum pressure plays an important role in the amount of milk removal, the tongue/jaw movement is essential for facilitating this procedure by decreasing the shear stress within the main duct in the nipple. The developed model can contribute to a better understanding of breastfeeding complications due to infant or breast abnormalities and for the design of medical devices such as breast pumps and artificial teats.

Nipple Deformation and Peripheral Pressure on the Areola During Breastfeeding.

Breastfeeding is a complex process where the infant utilizes two forms of pressure during suckling, vacuum and compression. Infant applied compression, or positive oral pressure, to the breast has not been previously studied in vivo. The goal of this study is to use a methodology to capture the positive oral pressure values exerted by infants' maxilla (upper jaw) and mandible (lower jaw) on the breast areola during breastfeeding. In this study, the positive and negative (vacuum) pressure values are obtained simultaneously on six lactating mothers. Parallel to the pressure data measurements, ultrasound images are captured and processed to reveal the nipple deformations and the displacements of infants' tongues and jaw movements during breastfeeding. Motivated by the significant differences in composition between the tissue of the breast and the nipple-areola complex, the strain ratio values of the lactating nipples are obtained using these deformation measurements along with pre- and postfeed three-dimensional (3D) scans of the breast. The findings show an oscillatory positive pressure profile on the breast under both maxilla and mandible, which differs from clinical indications that only the mandible of an infant moves during breastfeeding. The strain ratio varies between mothers, which indicates volume changes in the nipple during feeding and suggests that previous assumptions regarding strain ratio for nonlactating breasts will not accurately apply to breast tissue during lactation.

Lactation in the Human Breast From a Fluid Dynamics Point of View.

This study is a collaborative effort among lactation specialists and fluid dynamic engineers. The paper presents clinical results for suckling pressure pattern in lactating human breast as well as a 3D computational fluid dynamics (CFD) modeling of milk flow using these clinical inputs. The investigation starts with a careful, statistically representative measurement of suckling vacuum pressure, milk flow rate, and milk intake in a group of infants. The results from clinical data show that suckling action does not occur with constant suckling rate but changes in a rhythmic manner for infants. These pressure profiles are then used as the boundary condition for the CFD study using commercial ansys fluent software. For the geometric model of the ductal system of the human breast, this work takes advantage of a recent advance in the development of a validated phantom that has been produced as a ground truth for the imaging applications for the breast. The geometric model is introduced into CFD simulations with the aforementioned boundary conditions. The results for milk intake from the CFD simulation and clinical data were compared and cross validated. Also, the variation of milk intake versus suckling pressure are presented and analyzed. Both the clinical and CFD simulation show that the maximum milk flow rate is not related to the largest vacuum pressure or longest feeding duration indicating other factors influence the milk intake by infants.

Mathematical modeling of mammary ducts in lactating human females.

This work studies a model for milk transport through lactating human breast ducts and describes mathematically the mass transfer from alveolar sacs through the mammary ducts to the nipple. In this model, both the phenomena of diffusion in the sacs and conventional flow in ducts have been considered. The ensuing analysis reveals that there is an optimal range of bifurcation numbers leading to the easiest milk flow based on the minimum flow resistance. This model formulates certain difficult-to-measure values like diameter of the alveolar sacs and the total length of the milk path as a function of easy-to-measure properties such as milk fluid properties and macroscopic measurements of the breast. Alveolar dimensions from breast tissues of six lactating women are measured and reported in this paper. The theoretically calculated alveoli diameters for optimum milk flow (as a function of bifurcation numbers) show excellent match with our biological data on alveolar dimensions. Also, the mathematical model indicates that for minimum milk flow resistance the glandular tissue must be within a short distance from the base of the nipple, an observation that matches well with the latest anatomical and physiological research.

Modeling of milk flow in mammary ducts in lactating human female breast.

A transient laminar Newtonian three-dimensional CFD simulation has been studied for milk flow in a phantom model of the 6-generations human lactating breast branching system. Milk is extracted by the cyclic pattern of suction from the alveoli through the duct and to the nipple. The real negative (suction) pressure data are applied as an outlet boundary condition in nipple. In this study, the commercial CFD code (Fluent Inc., 2004) is employed for the numerical solution of the milk flow. The milk intake flow rate from simulation is compared to the real clinical data from published paper. The results are in good agreement. It is believed that the methodology of the lactating human breast branching modeling proposed here can provide potential guidelines for further clinical and research application.

Mathematical analysis of mammary ducts in lactating human breast.

This work studies a simple model for milk transport through lactating human breast ducts, and describes mathematically the mass transfer from alveolar sacs through the mammary ducts to the nipple. In this model both the phenomena of diffusion in the sacs and conventional flow in ducts have been considered. The ensuing analysis reveals that there is an optimal range of bifurcation numbers leading to the easiest milk flow based on the minimum flow resistance. This model formulates certain difficult-to-measure values like diameter of the alveolar sacs, and the total length of the milk path as a function of easy-to-measure properties such as milk fluid properties and macroscopic measurements of the breast. Alveolar dimensions from breast tissues of six lactating women are measured and reported in this paper. The theoretically calculated alveoli diameters for optimum milk flow (as a function of bifurcation numbers) show excellent match with our biological data on alveolar dimensions. Also, the mathematical model indicates that for minimum milk flow resistance the glandular tissue must be within a short distance from the base of the nipple, an observation that matches well with the latest anatomical and physiological research.