Volume Changes Research Articles

Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction.

Although high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, Representation Learning for Genetic Discovery on Low-Dimensional Embeddings (REGLE), for discovering associations between genetic variants and HDCD. REGLE leverages variational autoencoders to compute nonlinear disentangled embeddings of HDCD, which become the inputs to genome-wide association studies (GWAS). REGLE can uncover features not captured by existing expert-defined features and enables the creation of accurate disease-specific polygenic risk scores (PRSs) in datasets with very few labeled data. We apply REGLE to perform GWAS on respiratory and circulatory HDCD-spirograms measuring lung function and photoplethysmograms measuring blood volume changes. REGLE replicates known loci while identifying others not previously detected. REGLE are predictive of overall survival, and PRSs constructed from REGLE loci improve disease prediction across multiple biobanks. Overall, REGLE contain clinically relevant information beyond that captured by existing expert-defined features, leading to improved genetic discovery and disease prediction.

Strain-dependent work function of metal surfaces: Insights from first-principles investigation

Establishing a fundamental understanding of the relationship between electronic work function (WF) and applied strain is crucial for the development flexible electrodes of and enhancement of metal corrosion resistance. The underlying mechanisms of this relationship have remained unknown, largely due to inconsistencies from previous studies caused by different strain states and the complex impact of anisotropic surface effects. In this study, we employ first-principles methods to investigate the work functions of strained metal surfaces. Our research findings suggest that lateral strain states significantly affect the WF, while strain perpendicular to the surface has minimal influence. Through subjecting the metal surface to linear elastic deformation, we establish a canonical relationship between the work function and strain. Further comparison of work functions under biaxial strain indicates that surfaces with high atom packing density exhibit greater susceptibility to strain. The mechanism behind the strain-dependent WF is attributed to the interplay of bulk electronic structure and surface dipole effects, which. These effects are influenced by volume changes and the redistributedion of charge density. To this end, we propose an effective strain-induced approach for engineering the WF of metal electrode is proposeds, with potential applications in other various materials.

Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction.

Although high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, Representation Learning for Genetic Discovery on Low-Dimensional Embeddings (REGLE), for discovering associations between genetic variants and HDCD. REGLE leverages variational autoencoders to compute nonlinear disentangled embeddings of HDCD, which become the inputs to genome-wide association studies (GWAS). REGLE can uncover features not captured by existing expert-defined features and enables the creation of accurate disease-specific polygenic risk scores (PRSs) in datasets with very few labeled data. We apply REGLE to perform GWAS on respiratory and circulatory HDCD-spirograms measuring lung function and photoplethysmograms measuring blood volume changes. REGLE replicates known loci while identifying others not previously detected. REGLE are predictive of overall survival, and PRSs constructed from REGLE loci improve disease prediction across multiple biobanks. Overall, REGLE contain clinically relevant information beyond that captured by existing expert-defined features, leading to improved genetic discovery and disease prediction.

Enzyme replacement therapy for CLN2 disease: MRI volumetry shows significantly slower volume loss compared to a natural history cohort.

Neuronal ceroid lipofuscinoses (NCL) are a group of neurodegenerative disorders. Recently, enzyme replacement therapy (ERT) was approved for CLN2, a subtype of NCL. The aim of this study was to quantify brain volume loss in CLN2 disease of patients on ERT in comparison to a natural history cohort using magnetic resonance imaging (MRI). Nineteen (13 female, 6 male) patients with CLN2 disease at one UK center were studied using serial 3D T1-weighted MRI (follow-up time, 1 to 9 years). Brain segmentation was done using FreeSurfer. Volume measurements for supratentorial grey and white matter, deep grey matter (basal ganglia/thalami), lateral ventricles, and cerebellar grey and white matter were recorded. The volume change over time was analyzed using a linear mixed-effects model excluding scans before treatment start. Comparison was made to a published natural history cohort of 12 patients (8 female, 4 male) which was reanalyzed using the same method. Brain volume loss of all segmented brain regions was much slower in treated patients compared to the natural history cohort. For example, supratentorial grey matter volume in treated patients decreased by 3±0.74% (p<0.001) annually compared to an annual volume loss of 16.8±1.5% (p<0.001) in the natural history cohort. Our treatment cohort showed a significantly slower rate of brain parenchymal volume loss compared to a natural history cohort in several anatomical regions. Our results complement prior clinical data which found a positive response to ERT. We demonstrate that automated MRI volumetry is a sensitive tool to monitor treatment response in children with CLN2 disease. NCL = Neuronal Ceroid Lipofuscinosis, CLN2 = Neuronal Ceroid Lipofuscinosis type 2, TPP1 = tripeptidyl peptidase 1, ERT = enzyme replacement therapy, EMA = European Medicines Agency, ICV = intra-cerebro-ventricular reservoir.

The predictive role of lung clearance index on FEV&lt;sub&gt;1&lt;/sub&gt; decline in cystic fibrosis

Background. The lung clearance index (LCI) is a sensitive lung function index that is used to detect early lung disease changes in children with cystic fibrosis (CF). This study aimed to define the predictive role of baseline LCI, along with other potential factors on the change in forced expiratory volume in one second (FEV1) during one-year follow-up in CF patients who had a percent predicted (pp) FEV1≥80. Methods. LCI was concurrently performed on 57 CF patients who had ppFEV1 ≥80 at month zero. The ppFEV1 decline was evaluated prospectively during the one year follow up. The primary outcome of ppFEV1 decline in the study group in one year was dichotomized according to the median value for the decline in ppFEV1, which was 3.7. The LCI value predicting ppFEV1 decline at the end of one year was calculated with receiver operating characteristic curve analysis. Regression analysis was performed. Furthermore, a decision tree was constructed using classification and regression tree methods to better define the potential effect of confounders on the ppFEV1 decline. Results. The LCI value for predicting ppFEV1 decline &gt;3.7% at the end of one year was 8.2 (area under the curve: 0.80) Multivariable regression analysis showed that the absence of the F508del mutation in at least one allele, LCI &gt;8.2 and initial FEV1 z-score were predictors of a ppFEV1 decline &gt;3.7 (p&lt;0.001). Factors altering ppFEV1 decline&gt;3.7% at the end of one-year evaluated by decision trees were as follows: initial FEV1 z-score, type of CFTR mutation, LCI value and initial weight-for-age z-score. Conclusions. LCI is sensitive for predicting ppFEV1 decline in patients with ppFEV1 ≥80 along with the initial FEV1-z-score and type of CFTR mutation.

The predictive role of lung clearance index on FEV&lt;sub&gt;1&lt;/sub&gt; decline in cystic fibrosis

Background. The lung clearance index (LCI) is a sensitive lung function index that is used to detect early lung disease changes in children with cystic fibrosis (CF). This study aimed to define the predictive role of baseline LCI, along with other potential factors on the change in forced expiratory volume in one second (FEV1) during one-year follow-up in CF patients who had a percent predicted (pp) FEV1≥80. Methods. LCI was concurrently performed on 57 CF patients who had ppFEV1 ≥80 at month zero. The ppFEV1 decline was evaluated prospectively during the one year follow up. The primary outcome of ppFEV1 decline in the study group in one year was dichotomized according to the median value for the decline in ppFEV1, which was 3.7. The LCI value predicting ppFEV1 decline at the end of one year was calculated with receiver operating characteristic curve analysis. Regression analysis was performed. Furthermore, a decision tree was constructed using classification and regression tree methods to better define the potential effect of confounders on the ppFEV1 decline. Results. The LCI value for predicting ppFEV1 decline &gt;3.7% at the end of one year was 8.2 (area under the curve: 0.80) Multivariable regression analysis showed that the absence of the F508del mutation in at least one allele, LCI &gt;8.2 and initial FEV1 z-score were predictors of a ppFEV1 decline &gt;3.7 (p&lt;0.001). Factors altering ppFEV1 decline&gt;3.7% at the end of one-year evaluated by decision trees were as follows: initial FEV1 z-score, type of CFTR mutation, LCI value and initial weight-for-age z-score. Conclusions. LCI is sensitive for predicting ppFEV1 decline in patients with ppFEV1 ≥80 along with the initial FEV1-z-score and type of CFTR mutation.

Fabrication of NiO-CuO/RGO Composite for Lithium Storage Property

The lithium storage performance of binary transition metal oxide/graphene composites as anode materials has been attracting more interest from researchers, based on the fact that binary transition metal oxides and graphene are expected to create a synergistic effect and exhibit improved lithium storage characteristics. In this work, a NiO-CuO/reduced graphene oxide composite (NiO-CuO/RGO) was prepared by an ultrasonic agitation process. When the NiO-CuO/RGO is applied to the anode material for lithium-ion batteries (LIBs), the batteries display high discharge capacities (at 730 mA h/g after 100 cycles at 100 mA/g), high-rate performance (311 mA h/g with 5000 mA/g), and excellent stable cyclability (375 mA h/g within 2000 mA/g after 400 cycles). Such results indicate that the combination of NiO-CuO and RGO leads to enhanced lithium storage performance, for the RGO sheets inhibit the large volume change of binary NiO-CuO and enhance the fast transport of both lithium ions and electrons during the repeated lithium cycling processes.

Fabrication of NiO-CuO/RGO Composite for Lithium Storage Property

The lithium storage performance of binary transition metal oxide/graphene composites as anode materials has been attracting more interest from researchers, based on the fact that binary transition metal oxides and graphene are expected to create a synergistic effect and exhibit improved lithium storage characteristics. In this work, a NiO-CuO/reduced graphene oxide composite (NiO-CuO/RGO) was prepared by an ultrasonic agitation process. When the NiO-CuO/RGO is applied to the anode material for lithium-ion batteries (LIBs), the batteries display high discharge capacities (at 730 mA h/g after 100 cycles at 100 mA/g), high-rate performance (311 mA h/g with 5000 mA/g), and excellent stable cyclability (375 mA h/g within 2000 mA/g after 400 cycles). Such results indicate that the combination of NiO-CuO and RGO leads to enhanced lithium storage performance, for the RGO sheets inhibit the large volume change of binary NiO-CuO and enhance the fast transport of both lithium ions and electrons during the repeated lithium cycling processes.

High-Entropy Metal Nitride Embedded in Concave Porous Carbon Enabling Polysulfide Conversion in Lithium-Sulfur Batteries.

The practical implementation of lithium-sulfur batteries is severely hindered by the rapid capacity fading due to the solubility of the intermediate lithium polysulfides (LiPSs) and the sluggish redox kinetics. Herein, high-entropy metal nitride nanocrystals (HEMN) embedded within nitrogen-doped concave porous carbon (N-CPC) polyhedra are rationally designed as a sulfur host via a facile zeolitic imidazolate framework (ZIF)-driven adsorption-nitridation process toward this challenge. The configuration of high-entropy with incorporated metal manganese (Mn) and chromium (Cr)will optimize the d-band center of active sites with more electrons occupied in antibonding orbitals, thus promoting the adsorption and catalytic conversion of LiPSs. While the concave porous carbon not only accommodates the volume change upon the cycling processes but also physically confines and exposes active sites for accelerated sulfur redox reactions. As a result, the resultant HEMN/N-CPC composites-based sulfur cathode can deliver a high specific capacity of 1274 mAh g-1 at 0.2C and a low capacity decay rate of 0.044% after 1000 cycles at 1C. Moreover, upon sulfur loading of 5.0mg cm-2, the areal capacity of 5.0mAhcm-2 can still be achieved. The present work may provide a new avenue for the design of high-performance cathodes in Li-S batteries.

Enabling stable high lithium storage of Si anode via synergistic effects of nanosized Fe3C and partially graphitized porous carbon

Si is considered as a promising anode for high-energy lithium-ion batteries (LIBs) because of its ultrahigh theoretical specific capacity and desired working potential. However, the main problems of Si as an anode are still faced with low conductivity and inevitable structure damage caused by large volume change during cycle. Although design of Si/C composites effectively mitigates the above problems, their preparation usually involves complex methods. This work demonstrates a very simple ball milling and subsequent carbonization approach for the preparation of high-performance Si NPs@Fe3C@PC anode, which integrates partially hollow Fe3C nanoparticles (Fe3C) and partially graphitized porous carbon (PC) into Si nanoparticles (Si NPs)-based composite. It is found that Fe3C with catalysis is favorable not only to formation of a graphitized porous carbon during material preparation but also to formation of a stable solid electrolyte interfaces (SEI) on electrode surface during cycle. With Fe3C, the Si NPs@Fe3C@PC shows smaller Li+ adsorption energy, lower activation energy, higher electric conductivity, larger Li+ diffusion coefficient and a thinner SEI film than Si NPs and Si NPs@PC counterparts. The findings verify that the synergistic effects of the Fe3C and PC provide fast kinetics, high capacitive contribution, improved structure stability and a stable LiF-rich SEI film for Si NPs@Fe3C@PC during cycle. Therefore, Si NPs@Fe3C@PC shows excellent electrochemical performance, gaining 1786, 1211.4 and 411.5 mAh/g after 210, 650 and 840 cycles at 100, 1000 and 5000 mA g−1, respectively. Finally, this contribution proposes a simple and effective strategy for improving Si NPs performance and hence obtaining a high-performance of Si-based anode for LIBs.

A Gel Polymer Electrolyte with High Uniform Na+ Flux and its Constructed Hybrid Interface Synergistically to Facilitate High-Performance Sodium Batteries.

Sodium metal batteries (SMBs) can be developed on a large scale to achieve low-cost and high-capacity energy storage systems. Gel polymer electrolyte (GPE) can relieve volatilization of liquid electrolyte, adapt to volume changes in electrodes, and better satisfy the requirements of long-term SMBs. Herein, a dense polyurethane-based GPE modified with polyacrylonitrile is synthesized by rapidly swelling two-component polyurethane/polyacrylonitrile electrospun fiber film. Compared to traditional porous GPEs obtained by swelling porous matrixes, the fiber film provides uniform high Na+ flux inside GPE due to its partial solubility property and ability to dissociate salts. Therefore, it can reduce the polarization effect and induce uniform metal deposition under high current in conjunction with its constructed hybrid N/F-containing solid electrolyte interface (SEI) that possesses low ionic diffusion barrier. The study demonstrates that GPE has an ionic conductivity of 1.816 mS cm-1 at 20 °C and an ion transference number of 0.53. The full battery (NVP/GPE/Na) assembled with this GPE and Na3V2(PO4)3 (NVP) cathode shows 90.8% capacity retention rate after 1000 cycles at 10 C. Considering the convenient preparation and outstanding electrochemical performances of the obtained GPE, it can also be matched with other electrodes in the future to expand the application of sodium-based batteries.

Subsurface Profiling of Ion Migration and Swelling in Conducting Polymer Actuators with Modulated Electrochemical Atomic Force Microscopy.

Understanding the dynamics of ion migration and volume change is crucial to studying the functionality and long-term stability of soft polymeric materials operating at liquid interfaces, but the subsurface characterization of swelling processes in these systems remains elusive. In this work, we address the issue using modulated electrochemical atomic force microscopy as a depth-sensitive technique to study electroswelling effects in the high-performance actuator material polypyrrole doped with dodecylbenzenesulfonate (Ppy:DBS). We perform multidimensional measurements combining local electroswelling and electrochemical impedance spectroscopies on microstructured Ppy:DBS actuators. We interpret charge accumulation in the polymeric matrix with a quantitative model, giving access to both the spatiotemporal dynamics of ion migration and the distribution of electroswelling in the electroactive polymer layer. The findings demonstrate a nonuniform distribution of the effective ionic volume in the Ppy:DBS layer depending on the film morphology and redox state. Our findings indicate that the highly efficient actuation performance of Ppy:DBS is caused by rearrangements of the polymer microstructure induced by charge accumulation in the soft polymeric matrix, increasing the effective ionic volume in the bulk of the electroactive film for up to two times the value measured in free water.

The Preparation of N, P-Doped NiSe Nanorod Electrode Materials on Nickel Foam Using the Microwave Method for High-Performance Supercapacitors.

Transition metal selenides have the leading position in the field of energy storage and conversion due to their high theoretical capacity, good electrical conductivity, and cycling stability. Nickel is widely used for the construction of positive electrodes in devices due to its good conductivity, variable valence state, and ideal redox activity. NiSe materials have high internal resistance and are prone to volume change during charging and discharging, thus affecting the practical application of this electrode material, and the reported NiSe materials have not achieved a more desirable capacity value. Therefore, in this study, N, P-NiSe nanoelectrode materials were prepared using nickel foam as the nickel source and hexachlorocyclotriphonitrile as the nitrogen and phosphorus dopant using an efficient, energy-saving, and simple microwave method. It was also characterised by XRD and XPS to confirm the successful preparation of N, P-NiSe materials. In addition, the material yielded a high capacitance value (3184 F g-1) and good cycling stability (72% of the initial capacitance value was retained after 4000 cycles) in electrochemical tests. To demonstrate its excellent suitability for practical applications, an asymmetric supercapacitor was assembled using N, P-NiSe as the anode and activated carbon as the cathode. At an operating voltage of 1.6 V, the device achieved an energy density of 289.06 Wh kg-1 and a power density of 799.26 W kg-1 and retained 80% of its initial capacity after 20,000 cycles.

Interactions between Hydrodynamic Forcing, Suspended Sediment Transport, and Morphology in a Microtidal Intermediate-Dissipative Beach

This study aims to investigate the hydrodynamic-morphological interactions on a microtidal intermediate-dissipative beach under low to moderate wave energy conditions using field measurements during two climatic seasons. The separate contributions of currents, sea-swell waves, and infragravity waves to high- and low-frequency sediment fluxes were analyzed. The infragravity wave energy was more relevant near the swash zone than in other areas. Although the currents are the primary suspended sediment transport mechanism, the results suggest that the waves are an important driver of sediment suspension from the seabed. The results indicate that Sea-Swell (SS) waves and cross-shore currents are the prevailing hydrodynamic factors in nearshore sediment transport, and the cross-shore suspended sediment transport rates are higher than those in alongshore transport. The submerged bar intensified during the wet season (1–4 November 2018) when the wave height intensities were lower, contrary to the dry season (24–25 March 2018). Significant accretion nearshore was identified (in the subaerial beach) during the wet season when the suspended sediments were greater, the SS-wave heights nearshore were lower, and sediment flux was directed onshore. A notorious erosion was distinguished during the dry season. The most representative volume changes occurred during the dry season (with high erosion), which is attributed to the high SS-wave energy.

Interactions between Hydrodynamic Forcing, Suspended Sediment Transport, and Morphology in a Microtidal Intermediate-Dissipative Beach

This study aims to investigate the hydrodynamic-morphological interactions on a microtidal intermediate-dissipative beach under low to moderate wave energy conditions using field measurements during two climatic seasons. The separate contributions of currents, sea-swell waves, and infragravity waves to high- and low-frequency sediment fluxes were analyzed. The infragravity wave energy was more relevant near the swash zone than in other areas. Although the currents are the primary suspended sediment transport mechanism, the results suggest that the waves are an important driver of sediment suspension from the seabed. The results indicate that Sea-Swell (SS) waves and cross-shore currents are the prevailing hydrodynamic factors in nearshore sediment transport, and the cross-shore suspended sediment transport rates are higher than those in alongshore transport. The submerged bar intensified during the wet season (1–4 November 2018) when the wave height intensities were lower, contrary to the dry season (24–25 March 2018). Significant accretion nearshore was identified (in the subaerial beach) during the wet season when the suspended sediments were greater, the SS-wave heights nearshore were lower, and sediment flux was directed onshore. A notorious erosion was distinguished during the dry season. The most representative volume changes occurred during the dry season (with high erosion), which is attributed to the high SS-wave energy.

Ultralight, dual-conductive, all-fiber based 3D anode current collector for anode-free lithium metal battery

The anode-free Li metal batteries (AFLMBs), by pairing Li-containing cathode with bare anode current collector (CC), have the potential to enable the maximum improvement (>70 %) in energy density of lithium batteries. Here, we report an ultralight, dual-conductive all-fiber based Cu–CNF-CNT as anode CC, which takes advantage of the high electronic conductivity of carbon nanotube (CNT), good ionic conductivity of copper-coordinated cellulose nanofiber (Cu–CNF), and the three-dimensional porous structure by nanofibers. The interactions between CNTs and Cu-CNFs enables good mechanical strength (4.71 MPa), high electrical conductivity (31.7 S/cm), low density (1.1 g/cm3) and good wettability with electrolyte. The 3D microstructure effectively homogenizes the Li+ flux and buffers the volume changes during cycling, leading to stable Li plating/stripping. As a result, AFLMB using Cu–CNF-CNT exhibits improved capacity retention by 33 % compared to that using Cu CC. The significantly elevated energy-density shows great application potential of the Cu–CNF-CNT in AFLMBs.

The Lungs in Space: A Review of Current Knowledge and Methodologies

Space travel presents multiple risks to astronauts such as launch, radiation, spacewalks or extravehicular activities, and microgravity. The lungs are composed of a combination of air, blood, and tissue, making it a complex organ system with interactions between the external and internal environment. Gravity strongly influences the structure of the lung which results in heterogeneity of ventilation and perfusion that becomes uniform in microgravity as shown during parabolic flights, Spacelab, and Skylab experiments. While changes in lung volumes occur in microgravity, efficient gas exchange remains and the lungs perform as they would on Earth; however, little is known about the cellular response to microgravity. In addition to spaceflight and real microgravity, devices, such as clinostats and random positioning machines, are used to simulate microgravity to study cellular responses on the ground. Differential expression of cell adhesion and extracellular matrix molecules has been found in real and simulated microgravity. Immune dysregulation is a known consequence of space travel that includes changes in immune cell morphology, function, and number, which increases susceptibility to infections. However, the majority of in vitro studies do not have a specific respiratory focus. These studies are needed to fully understand the impact of microgravity on the function of the respiratory system in different conditions.

The Lungs in Space: A Review of Current Knowledge and Methodologies.

Space travel presents multiple risks to astronauts such as launch, radiation, spacewalks or extravehicular activities, and microgravity. The lungs are composed of a combination of air, blood, and tissue, making it a complex organ system with interactions between the external and internal environment. Gravity strongly influences the structure of the lung which results in heterogeneity of ventilation and perfusion that becomes uniform in microgravity as shown during parabolic flights, Spacelab, and Skylab experiments. While changes in lung volumes occur in microgravity, efficient gas exchange remains and the lungs perform as they would on Earth; however, little is known about the cellular response to microgravity. In addition to spaceflight and real microgravity, devices, such as clinostats and random positioning machines, are used to simulate microgravity to study cellular responses on the ground. Differential expression of cell adhesion and extracellular matrix molecules has been found in real and simulated microgravity. Immune dysregulation is a known consequence of space travel that includes changes in immune cell morphology, function, and number, which increases susceptibility to infections. However, the majority of in vitro studies do not have a specific respiratory focus. These studies are needed to fully understand the impact of microgravity on the function of the respiratory system in different conditions.

A like-bulletproof glass structure flexibility-rigidity coating layer strategy for high-performance Li ion batteries Si anodes

In order to overcome the problems about the volume expansion and poor electronic conductivity of Si, a flexibility and rigidity double coating layer CNTs-rGO- PAIN was constructed. The CNTs-rGO-PANI network with porous structure and high electronic conductivity provides sufficient space to accommodate the volume change of Si, and abundant transmission path for electron and Li ion. Moreover, the coating network with flexibility and rigidity characteristic could absorb the expansion stress of Si, maintain electrode structural integrity, promote the growth of stable SEI. The polymer-nanocarbon network dual coating layer effectively safeguards the electrochemical-mechanical interplay within the electrode. The 20Si-CNTs-rGO-PANI exhibits a reversible capacity as high as 1856 mAh g−1 after 400 cycles at 0.2 A g−1 and a remarkable rate capacity of 570 and 459 mAh g−1, at 5 and 10 A g−1, respectively. The outstanding Li ion storage performance of 20Si-CNTs-rGO-PANI anode, suggests the flexibility-rigidity dual coating layer strategy is a potential way to improve the performance of alloy type anode.

A three-dimensional quantitative assessment on bony growth and symmetrical recovery of mandible after decompression for unicystic ameloblastoma

Unicystic ameloblastoma (UAM) of the jaw can be effectively reduced in volume through decompression, which promotes bone regeneration and restores jaw symmetry. This study quantitatively evaluated changes in mandible volume and symmetry following decompression of mandibular UAM. This study included 17 patients who underwent surgical decompression followed by second-stage curettage for mandibular UAM. Preoperative and postoperative three-dimensional computed tomography (CT) images were collected. Bone volume and the area of cortical perforation were measured to assess bone growth during decompression. Mandibular volumetric symmetry was analyzed by calculating the volumetric ratio of the two sides of the mandible. Twelve pairs of landmarks were identified on the surface of the lesion regions, and their coordinates were used to calculate the mean asymmetry index (AI) of the mandible. Paired t-tests and the Mann–Whitney U test were used for statistical analysis, with p < 0.05 considered indicative of statistical significance. The mean duration of decompression was 9.41 ± 3.28 months. The mean bone volume increased by 8.07 ± 2.41%, and cortical perforation recovery was 71.97 ± 14.99%. The volumetric symmetry of the mandible improved significantly (p < 0.05), and a statistically significant decrease in AI was observed (p < 0.05). In conclusion, UAM decompression enhances bone growth and symmetry recovery of the mandible. The present evaluation technique is clinically useful for quantitatively assessing mandibular asymmetry.