Characterizing the Microparticles Deposition Structure and its Photonic Nature in Surfactant-Laden Evaporating Colloidal Sessile Droplets.

This work presents a simple method to create photonic microstructures via the natural evaporation of surfactant-laden colloidal sessile droplets on a flat substrate. In the absence of dissolved surfactant, the evaporating colloidal droplet forms a well-known coffee ring deposition. In contrast, the presence of surfactant leads to the formation of multiple ring structures due to the repetitive pinning-depinning behavior of the droplet contact line (CL). It is found that the multiring structure shows vibrant iridescent structural colors while the coffee ring lacks a photonic nature. This difference in the structural color for the presence and absence of the surfactant is found to be dependent on the arrangement of the particles in the deposition structure. The particle arrangement in the multirings is monolayered and well-ordered. The ordering of the particles is strongly influenced by the particle dynamics, contact angle (CA), and CL dynamics of the evaporating colloidal solution droplet. Furthermore, the iridescent nature of the multiring deposition is demonstrated and explained. The dependence of the multiring deposition structure on the concentration of the dissolved surfactant and the suspended particles is also studied. The findings demonstrate that an intermediate surfactant concentration is desirable for the formation of a multiring structure. Further, the pinning-depinning CL dynamics that causes the formation of the multiring deposition structure is discussed. Finally, we demonstrate the applicability of the approach to smaller droplet volumes.

Integrated Machine Learning Approach for the Early Prediction of Pressure Ulcers in Spinal Cord Injury Patients.

(1) Background: Pressure ulcers (PUs) substantially impact the quality of life of spinal cord injury (SCI) patients and require prompt intervention. This study used machine learning (ML) techniques to develop advanced predictive models for the occurrence of PUs in patients with SCI. (2) Methods: By analyzing the medical records of 539 patients with SCI, we observed a 35% incidence of PUs during hospitalization. Our analysis included 139 variables, including baseline characteristics, neurological status (International Standards for Neurological Classification of Spinal Cord Injury [ISNCSCI]), functional ability (Korean version of the Modified Barthel Index [K-MBI] and Functional Independence Measure [FIM]), and laboratory data. We used a variety of ML methods-a graph neural network (GNN), a deep neural network (DNN), a linear support vector machine (SVM_linear), a support vector machine with radial basis function kernel (SVM_RBF), K-nearest neighbors (KNN), a random forest (RF), and logistic regression (LR)-focusing on an integrative analysis of laboratory, neurological, and functional data. (3) Results: The SVM_linear algorithm using these composite data showed superior predictive ability (area under the receiver operating characteristic curve (AUC) = 0.904, accuracy = 0.944), as demonstrated by a 5-fold cross-validation. The critical discriminators of PU development were identified based on limb functional status and laboratory markers of inflammation. External validation highlighted the challenges of model generalization and provided a direction for future research. (4) Conclusions: Our study highlights the importance of a comprehensive, multidimensional data approach for the effective prediction of PUs in patients with SCI, especially in the acute and subacute phases. The proposed ML models show potential for the early detection and prevention of PUs, thus contributing substantially to improving patient care in clinical settings.

Correction to "Electrical and Thermal Properties of Surface-Modified Copper Nanowire/Polystyrene Nanocomposites through Latex Blending".

[This corrects the article DOI: 10.1021/acsomega.3c06775.].

Immobilized Candida antarctica lipase B as an sn-1,3 regiospecific biocatalyst for the interesterification of triacylglycerols with fatty acid ethyl esters.

Candida antarctica lipase B (CALB) is regarded as non-regiospecific. This study aimed to investigate the regiospecificity of CALB in the solvent-free interesterification of high-oleic sunflower oil with stearic acid ethyl ester for 1,3-distearoyl-2-oleoylglycerol (SOS)-rich fat preparation using a packed bed reactor. The content ratio of 1,2-distearoyl-3-oleoylglycerol (SSO) to SOS (denoted by SSO/SOS content) obtained using Lipozyme 435 (a commercially immobilized CALB; 0-4.1%), at residence times (1-32 min) was similar to that obtained using Lipozyme RM IM (0-3.0%), but lower than that obtained using Lipozyme TL IM (6.0-39.4%). When immobilized on Lewatit VP OC 1600, Lipozyme CALB had an SSO/SOS content of 0-10.4%, which was greater than that of Palatase 20,000 L (0-1.1%) but was lower than that of Lipozyme TL 100 L (8.8-97.7%). Our findings suggest that immobilized CALB shows distinct sn-1,3 regiospecificity in the interesterification of triacylglycerol with fatty acid ethyl esters.

Acoustofluidic separation of prolate and spherical micro-objects.

Most microfluidic separation techniques rely largely on object size as a separation marker. The ability to separate micro-objects based on their shape is crucial in various biomedical and chemical assays. Here, we develop an on-demand, label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and torque. The freely rotating non-spherical micro-objects were aligned under the progressive acoustic field by the counterrotating radiation torque, and the major axis of the prolate ellipsoids was parallel to the progressive wave propagation. The specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave propagation. As a consequence, the acoustic backscattering decreased, resulting in a decreased magnitude of the radiation force. Through the variation in radiation force, which depended on the micro-object morphology enabled the acoustofluidic shape-based separation. We conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method. A series of experiments with polystyrene microspheres, prolate ellipsoids, and peanut-shaped microparticles were performed for validation. Through quantitative analysis of the separation efficiency, we confirmed the high purity and high recovery rate of the proposed acoustofluidic shape-based separation of micro-objects. As a bioparticle, we utilize Thalassiosira eccentrica to perform shape-based separation, as the species has a variety of potential applications in drug delivery, biosensing, nanofabrication, bioencapsulation and immunoisolation.

Electrical and Thermal Properties of Surface-Modified Copper Nanowire/Polystyrene Nanocomposites through Latex Blending.

The incorporation of conductive nanofillers into an insulating polymer matrix commonly leads to nanocomposites with good electrical, thermal, and mechanical properties. In this study, copper nanowires (CuNWs) and polystyrene (PS) microspheres were synthesized along with the fabrication of CuNW/PS polymer nanocomposites. The electrical, thermal, mechanical, rheological, and morphological properties of the CuNW/PS nanocomposites were examined. The CuNWs were homogeneously dispersed in the PS matrix through latex blending. For the CuNW/PS nanocomposites, the storage modulus was higher than the loss modulus at all frequencies, indicating their elastic-dominant behavior. The electrical and thermal conductivities of the nanocomposites increased with an increasing CuNW content. Using a mixed dispersion of two monodisperse PS particles of 500 nm and 5 µm in diameter resulted in the highest electrical conductivity (ca. 10° S/m for 30 wt % nanofillers) among the nanocomposites. In addition, the introduction of silica- and polydopamine-coated CuNWs as nanofillers imparted insulation properties to the nanocomposites, with electrical conductivities to 10-10-10-8 S/m. When using 500 nm PS particles, the thermal conductivity of the surface-modified CuNW/PS nanocomposite at 30 wt % of CuNW was enhanced to 0.22 W/m·K compared to 0.17 W/m·K for its unmodified counterpart. We have achieved multiple innovative approaches, including the use of mixed particle sizes, surface modification of CuNW, and the exploration of elastic-dominant behavior. This enhanced thermal conductivity, coupled with the attainment of insulation properties, presents a distinct advantage for thermal interface material (TIM) applications.

Light-Scattering Analysis of Drying Behavior in Suspension Droplets with Silica and Polystyrene Particles and a Hydrosoluble Polymer.

The coffee-ring structure, which is the final drying pattern of a sessile suspension droplet, is a key factor in controlling the uniformity of the particulate deposits in various coatings. Two light-scattering methods, diffusing wave spectroscopy (DWS) and multispeckle DWS (MSDWS), were used to quantitatively distinguish temporal changes in particle mobility in evaporating suspension droplets containing micrometer-sized silica and polystyrene (PS) particles. The characteristic particle mobility was measured in terms of the mean square displacement in the early stage of drying, and the local particle dynamics around the edge and center regimes of the droplets during drying were analyzed using MSDWS. Hydroxyethyl cellulose (HEC), a hydrosoluble polymer, was added to the silica and PS suspensions to further investigate its role in suppressing or enhancing coffee-ring patterns based on particle-polymer interactions. Consequently, dried microstructures can be directly correlated with real-time drying dynamics, as well as the interactions between solutes by comprehensive light-scattering methods.

Clinical Practice Guideline for Stroke Rehabilitation in Korea-Part 1: Rehabilitation for Motor Function (2022).

This clinical practice guideline (CPG) is the fourth edition of the Korean guideline for stroke rehabilitation, which was last updated in 2016. The development approach has been changed from a consensus-based approach to an evidence-based approach using the Grading of Recommendations Assessment Development and Evaluation (GRADE) method. This change ensures that the guidelines are based on the latest and strongest evidence available. The aim is to provide the most accurate and effective guidance to stroke rehabilitation teams, and to improve the outcomes for stroke patients in Korea. Fifty-five specialists in stroke rehabilitation and one CPG development methodology expert participated in this development. The scope of the previous clinical guidelines was very extensive, making it difficult to revise at once. Therefore, it was decided that the scope of this revised CPG would be limited to Part 1: Rehabilitation for Motor Function. The key questions were selected by considering the preferences of the target population and referring to foreign guidelines for stroke rehabilitation, and the recommendations were completed through systematic literature review and the GRADE method. The draft recommendations, which were agreed upon through an official consensus process, were refined after evaluation by a public hearing and external expert evaluation.

Retardation of Capillary Force between Janus Particles at the Oil-Water Interface.

Interactions among colloidal particles govern the hierarchical microstructure and its physical properties. Here, optical laser tweezers and Monte Carlo simulations are used to evaluate the effects of azimuthal rotation of Janus particles at the oil-water interface on interparticle interactions. We find that the capillary-induced attractive force between two Janus particles at the interface can be relaxed by azimuthal rotation around the critical separation region, at which the capillary force is ∼0.053 pN. Force relaxation leads to a decrease in capillary force around the critical separation region, resulting in a slight increase in the scaling exponent, compared to the theoretical prediction.

Quantitative Analysis in Cervical Spinal Cord Injury Patients Using Diffusion Tensor Imaging and Tractography.

OBJECTIVE: To investigate the clinical usefulness of diffusion tensor imaging (DTI) and tractography in the prediction of outcomes after traumatic cervical spinal cord injury (SCI) and to assess whether the predictability is different between DTI and tractography administered before and after surgery. METHODS: Sixty-one subjects with traumatic cervical SCI were randomly assigned to preop or postop groups and received DTI accordingly. Among the patients who had DTI before surgery, we assigned 10 patients who had received repeated DTI examinations at 8 weeks after injury to the follow-up group. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained from DTI, and imaginary fiber and crossing fiber numbers were calculated from the tractography. Neurological status and functional status were assessed at 4 and 8 weeks after SCI. RESULTS: The neurologic and functional statuses of both groups improved after 4 weeks. Out of the initial 61 patients who were enrolled in the study, the failure rate of DTI image analysis was significantly higher in the postop group (n=17, 41.5%) than in the preop group (n=6, 20%). The FA values and fiber numbers in the preop group tended to be higher than those in the postop group, whereas ADC values were lower in the preop group. When comparing the tractographic findings in the follow-up group, imaginary fiber numbers at the C6 and C7 levels and crossing fiber numbers from the C3 to C6 levels were significantly decreased after surgery. Several DTI and tractographic parameters (especially the ADC value at the C4 level and imaginary fiber numbers at the C6 level) showed significant correlations with neurologic and functional statuses in both the preop and postop groups. These findings were most prominent when DTI and physical examination were simultaneously performed. CONCLUSION: Preoperative DTI and tractography demonstrated better FA and ADC values with lower interpretation failure rates than those obtained after surgery, whereas postoperative data significantly reflected the patient's clinical state at the time of evaluation. Therefore, DTI and tractography could be useful in predicting clinical outcomes after traumatic cervical SCI and should be interpreted separately before and after spine surgery.

Prediction of Poststroke Depression Based on the Outcomes of Machine Learning Algorithms.

Poststroke depression (PSD) is a major psychiatric disorder that develops after stroke; however, whether PSD treatment improves cognitive and functional impairments is not clearly understood. We reviewed data from 31 subjects with PSD and 34 age-matched controls without PSD; all subjects underwent neurological, cognitive, and functional assessments, including the National Institutes of Health Stroke Scale (NIHSS), the Korean version of the Mini-Mental Status Examination (K-MMSE), computerized neurocognitive test (CNT), the Korean version of the Modified Barthel Index (K-MBI), and functional independence measure (FIM) at admission to the rehabilitation unit in the subacute stage following stroke and 4 weeks after initial assessments. Machine learning methods, such as support vector machine, k-nearest neighbors, random forest, voting ensemble models, and statistical analysis using logistic regression were performed. PSD was successfully predicted using a support vector machine with a radial basis function kernel function (area under curve (AUC) = 0.711, accuracy = 0.700). PSD prognoses could be predicted using a support vector machine linear algorithm (AUC = 0.830, accuracy = 0.771). The statistical method did not have a better AUC than that of machine learning algorithms. We concluded that the occurrence and prognosis of PSD in stroke patients can be predicted effectively based on patients' cognitive and functional statuses using machine learning algorithms.

Electrically Conductive Silicone-Based Nanocomposites Incorporated with Carbon Nanotubes and Silver Nanowires for Stretchable Electrodes.

Stretchable electrode materials have attracted great attention as next-generation electronic materials because of their ability to maintain intrinsic properties with rare damage when undergoing repetitive deformations, such as folding, twisting, and stretching. In this study, an electrically conductive PDMS nanocomposite was manufactured by combining the hybrid nanofillers of carbon nanotubes (CNTs) and silver nanowires (AgNWs). The amphiphilic isopropyl alcohol molecules temporarily adhered simultaneously to the hydrophobic CNT and hydrophilic AgNW surfaces, thereby improving the dispersity. As the CNT/AgNW ratio (wt %/wt %) decreased under the constant nanofiller content, the tensile modulus decreased and the elongation at break increased owing to the poor interaction between the AgNWs and matrix. The shear storage moduli of all nanocomposites were higher than the loss moduli, indicating the elastic behavior with a cross-linked network. The electrical conductivities of the nanocomposite containing the hybrid nanofillers were superior to those of the nanocomposite containing either CNT or AgNW at the same filler content (4 wt %). The hybrid nanofillers were rearranged and deformed by 5000 cyclic strain tests, relaxing the PDMS matrix chain and weakening the interfacial bonding. However, the elastic behavior was maintained. The dynamic electrical conductivities gradually increased under the cyclic strain tests due to the rearrangement and tunneling effect of the nanofillers. The highest dynamic electrical conductivity (10 S/m) was obtained for the nanocomposite consisting of 2 wt % of CNTs and 2 wt % of AgNWs.

Reliability of Machine and Human Examiners for Detection of Laryngeal Penetration or Aspiration in Videofluoroscopic Swallowing Studies.

Computer-assisted analysis is expected to improve the reliability of videofluoroscopic swallowing studies (VFSSs), but its usefulness is limited. Previously, we proposed a deep learning model that can detect laryngeal penetration or aspiration fully automatically in VFSS video images, but the evidence for its reliability was insufficient. This study aims to compare the intra- and inter-rater reliability of the computer model and human raters. The test dataset consisted of 173 video files from which the existence of laryngeal penetration or aspiration was judged by the computer and three physicians in two sessions separated by a one-month interval. Intra- and inter-rater reliability were calculated using Cohen's kappa coefficient, the positive reliability ratio (PRR) and the negative reliability ratio (NRR). Intrarater reliability was almost perfect for the computer and two experienced physicians. Interrater reliability was moderate to substantial between the model and each human rater and between the human raters. The average PRR and NRR between the model and the human raters were similar to those between the human raters. The results demonstrate that the deep learning model can detect laryngeal penetration or aspiration from VFSS video as reliably as human examiners.

Hyoid Bone Tracking in a Videofluoroscopic Swallowing Study Using a Deep-Learning-Based Segmentation Network.

Kinematic analysis of the hyoid bone in a videofluorosopic swallowing study (VFSS) is important for assessing dysphagia. However, calibrating the hyoid bone movement is time-consuming, and its reliability shows wide variation. Computer-assisted analysis has been studied to improve the efficiency and accuracy of hyoid bone identification and tracking, but its performance is limited. In this study, we aimed to design a robust network that can track hyoid bone movement automatically without human intervention. Using 69,389 frames from 197 VFSS files as the data set, a deep learning model for detection and trajectory prediction was constructed and trained by the BiFPN-U-Net(T) network. The present model showed improved performance when compared with the previous models: an area under the curve (AUC) of 0.998 for pixelwise accuracy, an accuracy of object detection of 99.5%, and a Dice similarity of 90.9%. The bounding box detection performance for the hyoid bone and reference objects was superior to that of other models, with a mean average precision of 95.9%. The estimation of the distance of hyoid bone movement also showed higher accuracy. The deep learning model proposed in this study could be used to detect and track the hyoid bone more efficiently and accurately in VFSS analysis.

Identification of Nucleolin as a Novel AEG-1-Interacting Protein in Breast Cancer via Interactome Profiling.

Breast cancer is one of the most common malignant diseases worldwide. Astrocyte elevated gene-1 (AEG-1) is upregulated in breast cancer and regulates breast cancer cell proliferation and invasion. However, the molecular mechanisms by which AEG-1 promotes breast cancer have yet to be fully elucidated. In order to delineate the function of AEG-1 in breast cancer development, we mapped the AEG-1 interactome via affinity purification followed by LC-MS/MS. We identified nucleolin (NCL) as a novel AEG-1 interacting protein, and co-immunoprecipitation experiments validated the interaction between AEG-1 and NCL in breast cancer cells. The silencing of NCL markedly reduced not only migration/invasion, but also the proliferation induced by the ectopic expression of AEG-1. Further, we found that the ectopic expression of AEG-1 induced the tyrosine phosphorylation of c-Met, and NCL knockdown markedly reduced this AEG-1 mediated phosphorylation. Taken together, our report identifies NCL as a novel mediator of the oncogenic function of AEG-1, and suggests that c-Met could be associated with the oncogenic function of the AEG-1-NCL complex in the context of breast cancer.

Preparation of Low-Diacylglycerol Cocoa Butter Equivalents by Hexane Fractionation of Palm Stearin and Shea Butter.

Herein, we prepared 1,3-dipalmitoyl-2-oleoyl glycerol (POP)-rich fats with reduced levels of diacylglycerols (DAGs), adversely affecting the tempering of chocolate, via two-step hexane fractionation of palm stearin. DAG content in the as-prepared fats was lower than that in POP-rich fats obtained by previously reported conventional two-step acetone fractionation. Cocoa butter equivalents (CBEs) were fabricated by blending the as-prepared fats with 1,3-distearoyl-2-oleoyl glycerol (SOS)-rich fats obtained by hexane fractionation of degummed shea butter. POP-rich fats achieved under the best conditions for the fractionation of palm stearin had a significantly lower DAG content (1.6 w/w%) than that in the counterpart (4.6 w/w%) prepared by the previously reported method. The CBEs fabricated by blending the POP- and SOS-rich fats in a weight ratio of 40:60 contained 63.7 w/w% total symmetric monounsaturated triacylglycerols, including 22.0 w/w% POP, 8.6 w/w% palmitoyl-2-oleoyl-3-stearoyl-rac-glycerol, 33.1 w/w% SOS, and 1.3 w/w% DAGs, which was not substantially different from the DAG content in cocoa butter (1.1 w/w%). Based on the solid-fat content results, it was concluded that, when these CBEs were used for chocolate manufacture, they blended with cocoa butter at levels up to 40 w/w%, without distinctively altering the hardness and melting behavior of cocoa butter.

Latex-Based Polystyrene Nanocomposites with Non-Covalently Modified Carbon Nanotubes.

We prepared electrically conductive polystyrene (PS) nanocomposites by incorporating non-covalently surface-modified carbon nanotubes (CNTs) with hydrophilic polymers such as polydopamine (PDA) and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). Further, ethylene glycol (EG) was introduced as a second dopant to improve the electrical properties of the nanocomposites prepared with PEDOT:PSS-wrapped CNTs. All conductive PS nanocomposites were prepared through latex-based process, and the morphology and properties of the nanocomposites were investigated. The electrical properties of the nanocomposites with PEDOT:PSS-wrapped CNTs were better than those of the nanocomposites with PDA-coated CNTs owing to the conducting nature of PEDOT:PSS, although the dispersions of both types of modified CNTs in the PS matrix were excellent, as evidenced by morphology and rheology. In the case of PEDOT:PSS modification, the electrical properties of the nanocomposites with EG-doped PEDOT:PSS-wrapped CNTs were superior to those of the nanocomposites without EG treatment.

Predictors of Aspiration Pneumonia in the Elderly With Swallowing Dysfunction: Videofluoroscopic Swallowing Study.

OBJECTIVE: To identify the variables of videofluoroscopic swallowing study (VFSS) that are useful for predicting the risk of aspiration pneumonia in elderly patients with dysphagia. METHODS: A total of 251 patients (aged 65 years or more) were included and divided into a pneumonia group (n=133) and a non-pneumonia group (n=118). The pneumonia group included patients who had been diagnosed with aspiration pneumonia, and individuals in the non-pneumonia group did not have pneumonia but were referred for VFSS. The medical records and results of VFSS were reviewed and compared between the groups retrospectively. RESULTS: The pneumonia group exhibited a male preponderance and a higher 8-point Penetration-Aspiration Scale (8PPAS) score. The mean values of 8PPAS score for swallowing thick liquid and rice porridge was significantly higher in the pneumonia group. The pharyngeal delay time (PDT) and pharyngeal transit time (PTT) were significantly longer in the pneumonia group. The amounts of vallecular and pyriform sinus residue were increased in the pneumonia group. The delay in swallowing reflex and the decrease in laryngeal elevation were more frequently observed in the pneumonia group. Among those variables, PDT and PTT were identified as significant predictors of aspiration pneumonia based on logistic regression analysis. CONCLUSION: The present study delineated the findings of VFSS, suggesting an increased risk of aspiration pneumonia in elderly patients with dysphagia. The results demonstrate that prolonged PDT and PTT are significant predictors of aspiration pneumonia.

Effectiveness of Chin Tuck on Laryngeal Penetration: Quantitative Assessment.

The effectiveness of the chin tuck maneuver is still controversial, despite being widely used in clinical practice. The chin tuck maneuver has been shown to be able to reduce or eliminate aspiration in a group of patients with a number of favorable conditions, but its effectiveness in preventing or managing penetration remains unclear. This study was designed to investigate whether the chin tuck maneuver is effective in reducing penetration. Images from a videofluoroscopic swallowing study (VFSS) taken from 76 patients with penetration were collected and reviewed retrospectively. The severity of penetration was assessed by the penetration ratio (ratio of the penetration depth to the length of the epiglottis) measured and calculated from the images in which the deepest penetration was observed. The penetration ratio was significantly decreased in the chin tuck posture compared with the ratio in the neutral position (p = 0.001). Significant reducing effect was observed in 26 (34.2%) out of 76 patients. When comparing other parameters of VFSS, residues in the vallecular and pyriformis sinuses were less severe in the effective group. Chin tuck significantly decreased residues in both effective and ineffective group. The results demonstrate that the chin tuck maneuver can reduce penetration, but its effectiveness is limited.

Exercise Ameliorates Spinal Cord Injury by Changing DNA Methylation.

Exercise training is a traditional method to maximize remaining function in patients with spinal cord injury (SCI), but the exact mechanism by which exercise promotes recovery after SCI has not been identified; whether exercise truly has a beneficial effect on SCI also remains unclear. Previously, we showed that epigenetic changes in the brain motor cortex occur after SCI and that a treatment leading to epigenetic modulation effectively promotes functional recovery after SCI. We aimed to determine how exercise induces functional improvement in rats subjected to SCI and whether epigenetic changes are engaged in the effects of exercise. A spinal cord contusion model was established in rats, which were then subjected to treadmill exercise for 12 weeks. We found that the size of the lesion cavity and the number of macrophages were decreased more in the exercise group than in the control group after 12 weeks of injury. Immunofluorescence and DNA dot blot analysis revealed that levels of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in the brain motor cortex were increased after exercise. Accordingly, the expression of ten-eleven translocation (Tet) family members (Tet1, Tet2, and Tet3) in the brain motor cortex also elevated. However, no macrophage polarization was induced by exercise. Locomotor function, including Basso, Beattie, and Bresnahan (BBB) and ladder scores, also improved in the exercise group compared to the control group. We concluded that treadmill exercise facilitates functional recovery in rats with SCI, and mechanistically epigenetic changes in the brain motor cortex may contribute to exercise-induced improvements.