The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images.

OBJECTIVE: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. METHODS: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net's segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. RESULTS: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. CONCLUSION: Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Cigarette smoke-induced dysbiosis: comparative analysis of lung and intestinal microbiomes in COPD mice and patients.

BACKGROUND: The impact of cigarette smoke (CS) on lung diseases and the role of microbiome dysbiosis in chronic obstructive pulmonary disease (COPD) have been previously reported; however, the relationships remain unclear. METHODS: Our research examined the effects of 20-week cigarette smoke (CS) exposure on the lung and intestinal microbiomes in C57BL/6JNarl mice, alongside a comparison with COPD patients' intestinal microbiome data from a public dataset. RESULTS: The study found that CS exposure significantly decreased forced vital capacity (FVC), thickened airway walls, and induced emphysema. Increased lung damage was observed along with higher lung keratinocyte chemoattractant (KC) levels by CS exposure. Lung microbiome analysis revealed a rise in Actinobacteriota, while intestinal microbiome showed significant diversity changes, indicating dysbiosis. Principal coordinate analysis highlighted distinct intestinal microbiome compositions between control and CS-exposed groups. In the intestinal microbiome, notable decreases in Patescibacteria, Campilobacterota, Defferibacterota, Actinobacteriota, and Desulfobacterota were observed. We also identified correlations between lung function and dysbiosis in both lung and intestinal microbiomes. Lung interleukins, interferon-É£, KC, and 8-isoprostane levels were linked to lung microbiome dysbiosis. Notably, dysbiosis patterns in CS-exposed mice were similar to those in COPD patients, particularly of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 4 patients. This suggests a systemic impact of CS exposure. CONCLUSION: In summary, CS exposure induces significant dysbiosis in lung and intestinal microbiomes, correlating with lung function decline and injury. These results align with changes in COPD patients, underscoring the important role of microbiome in smoke-related lung diseases.

Correlation of Disease Severity, Proinflammatory Cytokines, and Reduced Brain Gray Matter Volumes in Patients with Atopic Dermatitis.

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease. However, few studies have investigated brain changes associated with chronic inflammation. We hypothesized that chronic inflammation might be related to brain structural alterations in patients with AD. Objectives: To investigate the association between disease severity (Eczema Area and Severity Index [EASI]), proinflammatory cytokines, and differences in brain gray matter (GM) volume in patients with AD. Methods: Nineteen patients with AD and 19 age- and sex-matched healthy subjects were enrolled. All participants underwent clinical assessment and brain magnetic resonance imaging. Voxel-based morphometry was performed to analyze GM volume differences. Results: Patients with AD exhibited significantly decreased GM volume in many brain regions, such as bilateral precentral gyrus, right frontal pole, and right middle temporal gyrus (P < 0.001), compared with healthy subjects. Notably, in patients with AD, the GM volume in right middle temporal gyrus was negatively associated with both EASI score and proinflammatory cytokines (sIL-2R [soluble interleukin 2 receptor] and TNF-α receptor-1), whereas the GM volume in left precentral gyrus was negatively associated with both EASI score and proinflammatory cytokines (sIL-2R and CRP). Conclusion: Patients with AD demonstrated significant brain GM volume reduction in many brain regions, which is related to disease severity and proinflammatory cytokines.

Amelioration of the brain structural connectivity is accompanied with changes of gut microbiota in a tuberous sclerosis complex mouse model.

Tuberous sclerosis complex (TSC) is a genetic disease that causes benign tumors and dysfunctions in many organs, including the brain. Aside from the brain malformations, many individuals with TSC exhibit neuropsychiatric symptoms. Among these symptoms, autism spectrum disorder (ASD) is one of the most common co-morbidities, affecting up to 60% of the population. Past neuroimaging studies strongly suggested that the impairments in brain connectivity contribute to ASD, whether or not TSC-related. Specifically, the tract-based diffusion tensor imaging (DTI) analysis provides information on the fiber integrity and has been used to study the neuropathological changes in the white matter of TSC patients with ASD symptoms. In our previous study, curcumin, a diet-derived mTOR inhibitor has been shown to effectively mitigate learning and memory deficits and anxiety-like behavior in Tsc2+/- mice via inhibiting astroglial proliferation. Recently, gut microbiota, which is greatly influenced by the diet, has been considered to play an important role in regulating several components of the central nervous system, including glial functions. In this study, we showed that the abnormal social behavior in the Tsc2+/- mice can be ameliorated by the dietary curcumin treatment. Second, using tract-based DTI analysis, we found that the Tsc2+/- mice exhibited altered fractional anisotropy, axial and radial diffusivities of axonal bundles connecting the prefrontal cortex, nucleus accumbens, hypothalamus, and amygdala, indicating a decreased brain network. Third, the dietary curcumin treatment improved the DTI metrics, in accordance with changes in the gut microbiota composition. At the bacterial phylum level, we showed that the abundances of Actinobacteria, Verrucomicrobia, and Tenericutes were significantly correlated with the DTI metrics FA, AD, and RD, respectively. Finally, we revealed that the expression of myelin-associated proteins, myelin bassic protein (MBP) and proteolipid protein (PLP) was increased after the treatment. Overall, we showed a strong correlation between structural connectivity alterations and social behavioral deficits, as well as the diet-dependent changes in gut microbiota composition.

Nucleus accumbens deep brain stimulation improves depressive-like behaviors through BDNF-mediated alterations in brain functional connectivity of dopaminergic pathway.

Major depressive disorder (MDD), a common psychiatric condition, adversely affects patients' moods and quality of life. Despite the development of various treatments, many patients with MDD remain vulnerable and inadequately controlled. Since anhedonia is a feature of depression and there is evidence of leading to metabolic disorder, deep brain stimulation (DBS) to the nucleus accumbens (NAc) might be promising in modulating the dopaminergic pathway. To determine whether NAc-DBS alters glucose metabolism via mitochondrial alteration and neurogenesis and whether these changes increase neural plasticity that improves behavioral functions in a chronic social defeat stress (CSDS) mouse model. The Lab-designed MR-compatible neural probes were implanted in the bilateral NAc of C57BL/6 mice with and without CSDS, followed by DBS or sham stimulation. All animals underwent open-field and sucrose preference testing, and brain resting-state functional MRI analysis. Meanwhile, we checked the placement of neural probes in each mouse by T2 images. By confirming the placement location, mice with incorrect probe placement (the negative control group) showed no significant therapeutic effects in behavioral performance and functional connectivity (FC) after receiving electrical stimulation and were excluded from further analysis. Western blotting, seahorse metabolic analysis, and electron microscopy were further applied for the investigation of NAc-DBS. We found NAc-DBS restored emotional deficits in CSDS-subjected mice. Concurrent with behavioral amelioration, the CSDS DBS-on group exhibited enhanced FC in the dopaminergic pathway with increased expression of BDNF- and NeuN-positive cells increased dopamine D1 receptor, dopamine D2 receptors, and TH in the medial prefrontal cortex, NAc, ventral hippocampus, ventral tegmental area, and amygdala. Increased pAMPK/total AMPK and PGC-1α levels, functions of oxidative phosphorylation, and mitochondrial biogenesis were also observed after NAc-DBS treatment. Our findings demonstrate that NAc-DBS can promote BDNF expression, which alters FC and metabolic profile in the dopaminergic pathway, suggesting a potential strategy for ameliorating emotional processes in individuals with MDD.

Assessing traffic-related air pollution-induced fiber-specific white matter degradation associated with motor performance declines in aged rats.

Fine particulate matter (PM2.5) is thought to exacerbate Parkinson's disease (PD) in the elderly, and early detection of PD progression may prevent further irreversible damage. Therefore, we used diffusion tensor imaging (DTI) for probing microstructural changes after late-life chronic traffic-related PM2.5 exposure. Herein, 1.5-year-old Fischer 344 rats were exposed to clean air (control), high-efficiency particulate air (HEPA)-filtered ambient air (HEPA group), and ambient traffic-related PM2.5 (PM2.5 group, 9.933 ± 1.021 µg/m3) for 3 months. Rotarod test, DTI tractographic analysis, and immunohistochemistry were performed in the end of study period. Aged rats exposed to PM2.5 exhibited motor impairment with decreased fractional anisotropy and tyrosine hydroxylase expression in olfactory and nigrostriatal circuits, indicating disrupted white matter integrity and dopaminergic (DA) neuronal loss. Additionally, increased radial diffusivity and lower expression of myelin basic protein in PM2.5 group suggested ageing progression of demyelination exacerbated by PM2.5 exposure. Significant production of tumor necrosis factor-α was also observed after PM2.5 exposure, revealing potential inflammation of injury to multiple fiber tracts of DA pathways. Microstructural changes demonstrated potential links between PM2.5-induced inflammatory white matter demyelination and behavioral performance, with indication of pre-manifestation of DTI-based biomarkers for early detection of PD progression in the elderly.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task.

Complete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided forelimb reaching movements, we propose a parallel computing neural network using both M1 and medial agranular cortex (AGm) neural activities of rats to predict forelimb-reaching movements. The proposed network decodes M1 neural activities into the primary components of the forelimb movement and decodes AGm neural activities into internal feedforward information to calibrate the forelimb movement in a goal-reaching movement. We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration. We also show that the M1 and AGm neural activities contribute to controlling forelimb movement during goal-reaching movements, and we report an increase in the power of the local field potential (LFP) in beta and gamma bands over AGm in response to a change in the target distance, which may involve sensorimotor transformation and communication between the visual cortex and AGm when preparing for an upcoming reaching movement. The proposed parallel computing neural network with the internal feedback model improves prediction accuracy for goal-reaching movements.

The Critical Role of Equilibrative Nucleoside Transporter-2 in Modulating Cerebral Damage and Vascular Dysfunction in Mice with Brain Ischemia-Reperfusion.

BACKGROUND: Cerebral vascular protection is critical for stroke treatment. Adenosine modulates vascular flow and exhibits neuroprotective effects, in which brain extracellular concentration of adenosine is dramatically increased during ischemic events and ischemia-reperfusion. Since the equilibrative nucleoside transporter-2 (Ent2) is important in regulating brain adenosine homeostasis, the present study aimed to investigate the role of Ent2 in mice with cerebral ischemia-reperfusion. METHODS: Cerebral ischemia-reperfusion injury was examined in mice with transient middle cerebral artery occlusion (tMCAO) for 90 minutes, followed by 24-hour reperfusion. Infarct volume, brain edema, neuroinflammation, microvascular structure, regional cerebral blood flow (rCBF), cerebral metabolic rate of oxygen (CMRO2), and the production of reactive oxygen species (ROS) were examined following the reperfusion. RESULTS: Ent2 deletion reduced the infarct volume, brain edema, and neuroinflammation in mice with cerebral ischemia-reperfusion. tMCAO-induced disruption of brain microvessels was ameliorated in Ent2-/- mice, with a reduced expression of matrix metalloproteinases-9 and aquaporin-4 proteins. Following the reperfusion, the rCBF of the wild-type (WT) mice was quickly restored to the baseline, whereas, in Ent2-/- mice, rCBF was slowly recovered initially, but was then higher than that in the WT mice at the later phase of reperfusion. The improved CMRO2 and reduced ROS level support the beneficial effects caused by the changes in the rCBF of Ent2-/- mice. Further studies showed that the protective effects of Ent2 deletion in mice with tMCAO involve adenosine receptor A2AR. CONCLUSIONS: Ent2 plays a critical role in modulating cerebral collateral circulation and ameliorating pathological events of brain ischemia and reperfusion injury.

Data on lung and intestinal microbiome after air pollution exposure in ageing rats.

Air pollution has been linked to respiratory diseases, and urban air pollution can be attributed to a number of emission sources. The emitted particles and gases are the primary components of air pollution that enter the lungs during respiration. Particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5) can deposit deep into the respiratory tract via inhalation and has been proposed as a causative agent for adverse respiratory health. In addition, the lung contains a diverse microbial community (microbiome) that maintains normal homeostasis and is significantly altered in a variety of pulmonary disorders. Air pollution, specifically PM2.5, has previously been shown to significantly alter the composition of the lower airway microbiome, which has been linked to decreased lung function in chronic obstructive pulmonary disease (COPD) patients. Surprisingly, the intestinal microbiome has also been implicated in the modulation of pulmonary inflammatory diseases. Therefore, dysbiosis of the lung and intestinal microbiomes pose significant negative effects on human health. This dataset describes the microbial community profiles of the lungs and intestines of ageing rats exposed to ambient unconcentrated traffic-related air pollution for three months. The whole-body exposure system was equipped with and without high efficiency particulate air (HEPA) filtration (gaseous vs. PM2.5 pollution). The data can provide valuable information on lung and intestinal microbiome changes, including that which was only found after traffic-related air pollution exposure.

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring.

Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were -1.36 ± 7.24 and -2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time.

Experimental Verification for Numerical Simulation of Thalamic Stimulation-Evoked Calcium-Sensitive Fluorescence and Electrophysiology with Self-Assembled Multifunctional Optrode.

Owing to its capacity to eliminate a long-standing methodological limitation, fiber photometry can assist research gaining novel insight into neural systems. Fiber photometry can reveal artifact-free neural activity under deep brain stimulation (DBS). Although evoking neural potential with DBS is an effective method for mediating neural activity and neural function, the relationship between DBS-evoked neural Ca2+ change and DBS-evoked neural electrophysiology remains unknown. Therefore, in this study, a self-assembled optrode was demonstrated as a DBS stimulator and an optical biosensor capable of concurrently recording Ca2+ fluorescence and electrophysiological signals. Before the in vivo experiment, the volume of tissue activated (VTA) was estimated, and the simulated Ca2+ signals were presented using Monte Carlo (MC) simulation to approach the realistic in vivo environment. When VTA and the simulated Ca2+ signals were combined, the distribution of simulated Ca2+ fluorescence signals matched the VTA region. In addition, the in vivo experiment revealed a correlation between the local field potential (LFP) and the Ca2+ fluorescence signal in the evoked region, revealing the relationship between electrophysiology and the performance of neural Ca2+ concentration behavior. Concurrent with the VTA volume, simulated Ca2+ intensity, and the in vivo experiment, these data suggested that the behavior of neural electrophysiology was consistent with the phenomenon of Ca2+ influx to neurons.

Proof of Concept for Sustainable Manufacturing of Neural Electrode Array for In Vivo Recording.

Increasing requirements for neural implantation are helping to expand our understanding of nervous systems and generate new developmental approaches. It is thanks to advanced semiconductor technologies that we can achieve the high-density complementary metal-oxide-semiconductor electrode array for the improvement of the quantity and quality of neural recordings. Although the microfabricated neural implantable device holds much promise in the biosensing field, there are some significant technological challenges. The most advanced neural implantable device relies on complex semiconductor manufacturing processes, which are required for the use of expensive masks and specific clean room facilities. In addition, these processes based on a conventional photolithography technique are suitable for mass production, which is not applicable for custom-made manufacturing in response to individual experimental requirements. The microfabricated complexity of the implantable neural device is increasing, as is the associated energy consumption, and corresponding emissions of carbon dioxide and other greenhouse gases, resulting in environmental deterioration. Herein, we developed a fabless fabricated process for a neural electrode array that was simple, fast, sustainable, and customizable. An effective strategy to produce conductive patterns as the redistribution layers (RDLs) includes implementing microelectrodes, traces, and bonding pads onto the polyimide (PI) substrate by laser micromachining techniques combined with the drop coating of the silver glue to stack the laser grooving lines. The process of electroplating platinum on the RDLs was performed to increase corresponding conductivity. Sequentially, Parylene C was deposited onto the PI substrate to form the insulation layer for the protection of inner RDLs. Following the deposition of Parylene C, the via holes over microelectrodes and the corresponding probe shape of the neural electrode array was also etched by laser micromachining. To increase the neural recording capability, three-dimensional microelectrodes with a high surface area were formed by electroplating gold. Our eco-electrode array showed reliable electrical characteristics of impedance under harsh cyclic bending conditions of over 90 degrees. For in vivo application, our flexible neural electrode array demonstrated more stable and higher neural recording quality and better biocompatibility as well during the 2-week implantation compared with those of the silicon-based neural electrode array. In this study, our proposed eco-manufacturing process for fabricating the neural electrode array reduced 63 times of carbon emissions compared to the traditional semiconductor manufacturing process and provided freedom in the customized design of the implantable electronic devices as well.

YAP-regulated type II alveolar epithelial cell differentiation mediated by human umbilical cord-derived mesenchymal stem cells in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) contributes to higher mortality worldwide. Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) have immunomodulatory and regenerative potential. However, the effects of hUC-MSCs as an ARDS treatment remain unclear. We investigated the role of hUC-MSCs in the differentiation of type II alveolar epithelial cells (AECII) by regulating Yes-associated protein (YAP) in ARDS. Male C57BL/6JNarl mice were intratracheally (i.t.) administered lipopolysaccharide (LPS) to induce an ARDS model, followed by a single intravenous (i.v.) dose of hUC-MSCs. hUC-MSCs improved pulmonary function, decreased inflammation on day 3, and mitigated lung injury by reducing the lung injury score and increasing lung aeration (%) in mice on day 7 (p < 0.05). hUC-MSCs inactivated YAP on AECII and facilitated cell differentiation by decreasing Pro-surfactant protein C (Pro-SPC) and galectin 3 (LGALS3) while increasing podoplanin (T1α) in lungs of mice (p < 0.05). In AECII MLE-12 cells, both coculture with hUC-MSCs after LPS exposure and the YAP inhibitor, verteporfin, reduced Pro-SPC and LGALS3, whereas the YAP inhibitor increased T1α expression (p < 0.05). In conclusion, hUC-MSCs ameliorated lung injury of ARDS and regulated YAP to facilitate AECII differentiation.

Effects of antibiotics and metals on lung and intestinal microbiome dysbiosis after sub-chronic lower-level exposure of air pollution in ageing rats.

We investigated the effects of antibiotics, drugs, and metals on lung and intestinal microbiomes after sub-chronic exposure of low-level air pollution in ageing rats. Male 1.5-year-old Fischer 344 ageing rats were exposed to low-level traffic-related air pollution via whole-body exposure system for 3 months with/without high-efficiency particulate air (HEPA) filtration (gaseous vs. particulate matter with aerodynamic diameter of ≤2.5 µm (PM2.5) pollution). Lung functions, antibiotics, drugs, and metals in lungs were examined and linked to lung and fecal microbiome analyses by high-throughput sequencing analysis of 16 s ribosomal (r)DNA. Rats were exposed to 8.7 µg/m3 PM2.5, 10.1 ppb NO2, 1.6 ppb SO2, and 23.9 ppb O3 in average during the study period. Air pollution exposure decreased forced vital capacity (FVC), peak expiratory flow (PEF), forced expiratory volume in 20 ms (FEV20), and FEF at 25∼75% of FVC (FEF25-75). Air pollution exposure increased antibiotics and drugs (benzotriazole, methamphetamine, methyl-1 H-benzotriazole, ketamine, ampicillin, ciprofloxacin, pentoxifylline, erythromycin, clarithromycin, ceftriaxone, penicillin G, and penicillin V) and altered metals (V, Cr, Cu, Zn, and Ba) levels in lungs. Fusobacteria and Verrucomicrobia at phylum level were increased in lung microbiome by air pollution, whereas increased alpha diversity, Bacteroidetes and Proteobacteria and decreased Firmicutes at phylum level were occurred in intestinal microbiome. Lung function decline was correlated with increasing antibiotics, drugs, and metals in lungs as well as lung and intestinal microbiome dysbiosis. The antibiotics, drugs, and Cr, Co, Ca, and Cu levels in lung were correlated with lung and intestinal microbiome dysbiosis. The lung microbiome was correlated with intestinal microbiome at several phylum and family levels after air pollution exposure. Our results revealed that antibiotics, drugs, and metals in the lung caused lung and intestinal microbiome dysbiosis in ageing rats exposed to air pollution, which may lead to lung function decline.

Wireless charging-mediated angiogenesis and nerve repair by adaptable microporous hydrogels from conductive building blocks.

Traumatic brain injury causes inflammation and glial scarring that impede brain tissue repair, so stimulating angiogenesis and recovery of brain function remain challenging. Here we present an adaptable conductive microporous hydrogel consisting of gold nanoyarn balls-coated injectable building blocks possessing interconnected pores to improve angiogenesis and recovery of brain function in traumatic brain injury. We show that following minimally invasive implantation, the adaptable hydrogel is able to fill defects with complex shapes and regulate the traumatic brain injury environment in a mouse model. We find that placement of this injectable hydrogel at peri-trauma regions enhances mature brain-derived neurotrophic factor by 180% and improves angiogenesis by 250% in vivo within 2 weeks after electromagnetized stimulation, and that these effects facilitate neuron survival and motor function recovery by 50%. We use blood oxygenation level-dependent functional neuroimaging to reveal the successful restoration of functional brain connectivity in the corticostriatal and corticolimbic circuits.

Neuro-Inspired Reinforcement Learning to Improve Trajectory Prediction in Reward-Guided Behavior.

Hippocampal pyramidal cells and interneurons play a key role in spatial navigation. In goal-directed behavior associated with rewards, the spatial firing pattern of pyramidal cells is modulated by the animal's moving direction toward a reward, with a dependence on auditory, olfactory, and somatosensory stimuli for head orientation. Additionally, interneurons in the CA1 region of the hippocampus monosynaptically connected to CA1 pyramidal cells are modulated by a complex set of interacting brain regions related to reward and recall. The computational method of reinforcement learning (RL) has been widely used to investigate spatial navigation, which in turn has been increasingly used to study rodent learning associated with the reward. The rewards in RL are used for discovering a desired behavior through the integration of two streams of neural activity: trial-and-error interactions with the external environment to achieve a goal, and the intrinsic motivation primarily driven by brain reward system to accelerate learning. Recognizing the potential benefit of the neural representation of this reward design for novel RL architectures, we propose a RL algorithm based on [Formula: see text]-learning with a perspective on biomimetics (neuro-inspired RL) to decode rodent movement trajectories. The reward function, inspired by the neuronal information processing uncovered in the hippocampus, combines the preferred direction of pyramidal cell firing as the extrinsic reward signal with the coupling between pyramidal cell-interneuron pairs as the intrinsic reward signal. Our experimental results demonstrate that the neuro-inspired RL, with a combined use of extrinsic and intrinsic rewards, outperforms other spatial decoding algorithms, including RL methods that use a single reward function. The new RL algorithm could help accelerate learning convergence rates and improve the prediction accuracy for moving trajectories.

Reduction of Emphysema Severity by Human Umbilical Cord-Derived Mesenchymal Stem Cells in Mice.

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality in chronic lung disease patients throughout the world. Mesenchymal stem cells (MSCs) have been shown to regulate immunomodulatory, anti-inflammatory, and regenerative responses. However, the effects of human-umbilical-cord-derived mesenchymal stem cells (hUC-MSCs) on the lung pathophysiology of COPD remain unclear. We aimed to investigate the role of hUC-MSCs in emphysema severity and Yes-associated protein (Yap) phosphorylation (p-Yap) in a porcine-pancreatic-elastase (PPE)-induced emphysema model. We observed that the emphysema percentages (normalized to the total lung volume) measured by chest computed tomography (CT) and exercise oxygen desaturation were significantly reduced by hUC-MSCs at 107 cells/kg body weight (BW) via intravenous administration in emphysematous mice (p < 0.05). Consistently, the emphysema index, as assessed by the mean linear intercept (MLI), significantly decreased with hUC-MSC administration at 3 × 106 and 107 cells/kg BW (p < 0.05). Changes in the lymphocytes, monocytes, and splenic cluster of differentiation 4-positive (CD4+) lymphocytes by PPE were significantly reversed by hUC-MSC administration in emphysematous mice (p < 0.05). An increasing neutrophil/lymphocyte ratio was reduced by hUC-MSCs at 3 × 106 and 107 cells/kg BW (p < 0.05). The higher levels of tumor necrosis factor (TNF)-α, keratinocyte chemoattractant (KC), and lactate dehydrogenase (LDH) in bronchoalveolar lavage fluid (BALF) were significantly decreased by hUC-MSC administration (p < 0.05). A decreasing p-Yap/Yap ratio in type II alveolar epithelial cells (AECII) of mice with PPE-induced emphysema was significantly increased by hUC-MSCs (p < 0.05). In conclusion, the administration of hUC-MSCs improved multiple pathophysiological features of mice with PPE-induced emphysema. The effectiveness of the treatment of pulmonary emphysema with hUC-MSCs provides an essential and significant foundation for future clinical studies of MSCs in COPD patients.

A Potent Histone Deacetylase Inhibitor MPT0E028 Mitigates Emphysema Severity via Components of the Hippo Signaling Pathway in an Emphysematous Mouse Model.

Background: Chronic obstructive pulmonary disease (COPD) is a major cause of chronic mortality. The objective of this study was to investigate the therapeutic potential of a novel potent histone deacetylase (HDAC) inhibitor MPT0E028 on emphysema. Materials and Methods: A mouse model of porcine pancreatic elastase (PPE)-induced emphysema was orally administered 0, 25, or 50 mg/kg body weight (BW) of the MPT0E028 five times/week for 3 weeks. Pulmonary function, mean linear intercept (MLI), chest CT, inflammation, yes-associated protein (YAP), transcriptional coactivator with PDZ-binding motif (TAZ), surfactant protein C (SPC), T1-α, p53, and sirtuin 1 (SIRT1) levels were examined. Results: 50 mg/kg BW of the MPT0E028 significantly decreased the tidal volume in emphysematous mice (p < 0.05). Emphysema severity was significantly reduced from 26.65% (PPE only) to 13.83% (50 mg/kg BW of the MPT0E028). Total cell counts, neutrophils, lymphocytes, and eosinophils significantly decreased with both 25 and 50 mg/kg BW of the MPT0E028 (p < 0.05). Also, 50 mg/kg BW of the MPT0E028 significantly decreased the levels of KC, TNF-α, and IL-6 in lung tissues and serum (p < 0.05). Expressions of p-TAZ/TAZ in lung tissues significantly decreased with 50 mg/kg BW of the MPT0E028 (p < 0.05). Expressions of p53 significantly decreased in alveolar regions with 50 mg/kg BW of the MPT0E028 (p < 0.05), and the expression of SPC increased in alveolar regions with 50 mg/kg BW of the MPT0E028 (p < 0.05). Conclusions: Our study showed that the potent HDAC inhibitor MPT0E028 reduced the severity and inflammation of emphysema with improvement in lung function, which could be regulated by Hippo signaling pathway. The MPT0E028 may have therapeutic potential for emphysema.

A Differentiable Dynamic Model for Musculoskeletal Simulation and Exoskeleton Control.

An exoskeleton, a wearable device, was designed based on the user's physical and cognitive interactions. The control of the exoskeleton uses biomedical signals reflecting the user intention as input, and its algorithm is calculated as an output to make the movement smooth. However, the process of transforming the input of biomedical signals, such as electromyography (EMG), into the output of adjusting the torque and angle of the exoskeleton is limited by a finite time lag and precision of trajectory prediction, which result in a mismatch between the subject and exoskeleton. Here, we propose an EMG-based single-joint exoskeleton system by merging a differentiable continuous system with a dynamic musculoskeletal model. The parameters of each muscle contraction were calculated and applied to the rigid exoskeleton system to predict the precise trajectory. The results revealed accurate torque and angle prediction for the knee exoskeleton and good performance of assistance during movement. Our method outperformed other models regarding the rate of convergence and execution time. In conclusion, a differentiable continuous system merged with a dynamic musculoskeletal model supported the effective and accurate performance of an exoskeleton controlled by EMG signals.