High-Performance Bidirectional Microelectrode Array for Assessing Sevoflurane Anesthesia Effects and In Situ Electrical Stimulation in Deep Brain Regions.

Precise assessment of wakefulness states during sevoflurane anesthesia and timely arousal are of paramount importance to refine the control of anesthesia. To tackle this issue, a bidirectional implantable microelectrode array (MEA) is designed with the capability to detect electrophysiological signal and perform in situ deep brain stimulation (DBS) within the dorsomedial hypothalamus (DMH) of mice. The MEA, modified with platinum nanoparticles/IrOx nanocomposites, exhibits exceptional characteristics, featuring low impedance, minimal phase delay, substantial charge storage capacity, high double-layer capacitance, and longer in vivo lifetime, thereby enhancing the sensitivity of spike firing detection and electrical stimulation (ES) effectiveness. Using this MEA, sevoflurane-inhibited neurons and sevoflurane-excited neurons, together with changes in the oscillation characteristics of the local field potential within the DMH, are revealed as indicative markers of arousal states. During the arousal period, varying-frequency ESs are applied to the DMH, eliciting distinct arousal effects. Through in situ detection and stimulation, the disparity between these outcomes can be attributed to the influence of DBS on different neurons. These advancements may further our understanding of neural circuits and their potential applications in clinical contexts.

Utilizing GO/PEDOT:PSS/PtNPs-enhanced high-stability microelectrode arrays for investigating epilepsy-induced striatal electrophysiology alterations.

The striatum plays a crucial role in studying epilepsy, as it is involved in seizure generation and modulation of brain activity. To explore the complex interplay between the striatum and epilepsy, we engineered advanced microelectrode arrays (MEAs) specifically designed for precise monitoring of striatal electrophysiological activities in rats. These observations were made during and following seizure induction, particularly three and 7 days post-initial modeling. The modification of graphene oxide (GO)/poly (3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS)/platinu-m nanoparticles (PtNPs) demonstrated a marked reduction in impedance (10.5 ± 1.1 kΩ), and maintained exceptional stability, with impedance levels remaining consistently low (23 kΩ) even 14 days post-implantation. As seizure intensity escalated, we observed a corresponding increase in neuronal firing rates and local field potential power, with a notable shift towards higher frequency peaks and augmented inter-channel correlation. Significantly, during the grand mal seizures, theta and alpha bands became the dominant frequencies in the local field potential. Compared to the normal group, the spike firing rates on day 3 and 7 post-modeling were significantly higher, accompanied by a decreased firing interval. Power in both delta and theta bands exhibited an increasing trend, correlating with the duration of epilepsy. These findings offer valuable insights into the dynamic processes of striatal neural activity during the initial and latent phases of temporal lobe epilepsy and contribute to our understanding of the neural mechanisms underpinning epilepsy.

SWCNTs/PEDOT:PSS nanocomposites-modified microelectrode arrays for revealing locking relations between burst and local field potential in cultured cortical networks.

Burst and local field potential (LFP) are fundamental components of brain activity, representing fast and slow rhythms, respectively. Understanding the intricate relationship between burst and LFP is crucial for deciphering the underlying mechanisms of brain dynamics. In this study, we fabricated high-performance microelectrode arrays (MEAs) using the SWCNTs/PEDOT:PSS nanocomposites, which exhibited favorable electrical properties (low impedance: 12.8 ± 2.44 kΩ) and minimal phase delay (-11.96 ± 1.64°). These MEAs enabled precise exploration of the burst-LFP interaction in cultured cortical networks. After a 14-day period of culture, we used the MEAs to monitor electrophysiological activities and revealed a time-locking relationship between burst and LFP, indicating the maturation of the neural network. To further investigate this relationship, we modulated burst firing patterns by treating the neural culture with increasing concentrations of glycine. The results indicated that glycine effectively altered burst firing patterns, with both duration and spike count increasing as the concentration rose. This was accompanied by an enhanced level of time-locking between burst and LFP but a decrease in synchrony among neurons. This study not only highlighted the pivotal role of SWCNTs/PEDOT:PSS-modified MEAs in elucidating the interaction between burst and LFP, bridging the gap between slow and fast brain rhythms in vitro but also provides valuable insights into the potential therapeutic strategies targeting neurological disorders associated with abnormal rhythm generation.

Wireless closed-loop deep brain stimulation using microelectrode array probes. / åŸºäºŽå¾®ç”µæžé˜µåˆ—æŽ¢é’ˆçš„æ— çº¿é—­çŽ¯è„‘æ·±éƒ¨åˆºæ¿€æŠ€æœ¯.

Deep brain stimulation (DBS), including optical stimulation and electrical stimulation, has been demonstrated considerable value in exploring pathological brain activity and developing treatments for neural disorders. Advances in DBS microsystems based on implantable microelectrode array (MEA) probes have opened up new opportunities for closed-loop DBS (CL-DBS) in situ. This technology can be used to detect damaged brain circuits and test the therapeutic potential for modulating the output of these circuits in a variety of diseases simultaneously. Despite the success and rapid utilization of MEA probe-based CL-DBS microsystems, key challenges, including excessive wired communication, need to be urgently resolved. In this review, we considered recent advances in MEA probe-based wireless CL-DBS microsystems and outlined the major issues and promising prospects in this field. This technology has the potential to offer novel therapeutic options for psychiatric disorders in the future.

17ß-estradiol biosensors based on different bioreceptors and their applications.

17ß-Estradiol (E2) is a critical sex steroid hormone, which has significant effects on the endocrine systems of both humans and animals. E2 is also believed to play neurotrophic and neuroprotective roles in the brain. Biosensors present a powerful tool to detect E2 because of their small, efficient, and flexible design. Furthermore, Biosensors can quickly and accurately obtain detection results with only a small sampling amount, which greatly meets the detection of the environment, food safety, medicine safety, and human body. This review focuses on previous studies of biosensors for detecting E2 and divides them into non-biometric sensors, enzyme biosensors, antibody biosensors, and aptamer biosensors according to different bioreceptors. The advantages, disadvantages, and design points of various bioreceptors for E2 detection are analyzed and summarized. Additionally, applications of different bioreceptors of E2 detection are presented and highlight the field of environmental monitoring, food and medicine safety, and disease detection in recent years. Finally, the development of E2 detection by biosensor is prospected.

[Progress of Immunotherapy in EGFR-mutated Advanced Non-small Cell Lung Cancer].

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are currently the first-line standard of care for patients with non-small cell lung cancer (NSCLC) that harbor EGFR mutations. Nevertheless, resistance to EGFR-TKIs is inevitable. In recent years, although immune checkpoint inhibitors (ICIs) have significantly shifted the treatment paradigm in advanced NSCLC without driver mutation, clinical benefits of these agents are limited in patients with EGFR-mutated NSCLC. Compared with wild-type tumors, tumors with EGFR mutations show more heterogeneity in the expression level of programmed cell death ligand 1 (PD-L1), tumor mutational burden (TMB), and other tumor microenvironment (TME) characteristics. Whether ICIs are suitable for NSCLC patients with EGFR mutations is still worth exploring. In this review, we summarized the clinical data with regard to the efficacy of ICIs in patients with EGFR-mutated NSCLC and deciphered the unique TME in EGFR-mutated NSCLC.
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Effect of taping on posture of thoracic region in patients with thoracic kyphosis using acceleration.

BACKGROUND: In the working environment of modern society, a poor sitting posture for a prolonged time may lead to abnormal spinal alignment such as thoracic kyphosis (TK). OBJECTIVE: This study aimed to evaluate the efficacy of taping for posture correction of patients with TK, providing theoretical and empirical guidance for clinicians attempting to rectify TK posture. METHODS: The study included 15 subjects aged 30-60 years, all with a TK angle of ⩾ 40∘. Subjects were required to ascend and descend a set of three steps (a low step, high step, and second low step) under three different conditions: without tape assistance, with taping assistance using 20% elongation, and with taping assistance using 40% elongation. A triaxial accelerometer was employed to measure and compare the anterior-posterior (AP), vertical (VT), and medial-lateral (MIL) movements of the thoracic vertebrae in the different conditions. RESULTS: There were no significant differences in the MIL (P= 0.903) or AP (P= 0.114) movements between the no tape assistance and 20% elongation taping conditions. However, a significant difference was found in the VT movement (P= 0.017). Comparing the no assistance condition to the 40% elongation taping condition, no significant changes were noted in the MIL movement (P= 0.650), but significant differences were detected in both the VT (P= 0.003) and AP movements (P= 0.016). No significant differences were found in any of the three measurements between 20% and 40% elongation taping. CONCLUSION: Taping serves as an effective method for immediately improving kyphotic posture. It corrects the position of the scapula and cervicothoracic line and exerts passive retraction on the relevant muscles, thus mitigating trunk imbalance.

Metabolic reprogramming involves in transition of activated/resting CD4+ memory T cells and prognosis of gastric cancer.

Background: Little is known on how metabolic reprogramming potentially prompts transition of activated and resting CD4+ memory T cells infiltration in tumor microenvironment of gastric cancer (GC). The study aimed to evaluate their interactions and develop a risk model for predicting prognosis in GC. Methods: Expression profiles were obtained from TCGA and GEO databases. An immunotherapeutic IMvigor210 cohort was also enrolled. CIBERSORT algorithm was used to evaluate the infiltration of immune cells. The ssGSEA method was performed to assess levels of 114 metabolism pathways. Prognosis and correlation analysis were conducted to identify metabolism pathways and genes correlated with activated CD4+ memory T cells ratio (AR) and prognosis. An AR-related metabolism gene (ARMG) risk model was constructed and validated in different cohorts. Flow cytometry was applied to validate the effect of all-trans retinoic acid (ATRA) on CD4+ memory T cells. Results: Since significantly inverse prognostic value and negative correlation of resting and activated CD4+ memory T cells, high AR level was associated with favorable overall survival (OS) in GC. Meanwhile, 15 metabolism pathways including retinoic acid metabolism pathway were significantly correlated with AR and prognosis. The ARMG risk model could classify GC patients with different outcomes, treatment responses, genomic and immune landscape. The prognostic value of the model was also confirmed in the additional validation, immunotherapy and pan-cancer cohorts. Functional analyses revealed that the ARMG model was positively correlated with pro-tumorigenic pathways. In vitro experiments showed that ATRA could inhibit levels of activated CD4+ memory T cells and AR. Conclusion: Our study showed that metabolic reprogramming including retinoic acid metabolism could contribute to transition of activated and resting CD4+ memory T cells, and affect prognosis of GC patients. The ARMG risk model could serve as a new tool for GC patients by accurately predicting prognosis and response to treatment.

Integrated Three-Electrode Dual-Mode Detection Chip for Place Cell Analysis: Dopamine Facilitates the Role of Place Cells in Encoding Spatial Locations of Novel Environments and Rewards.

The functioning of place cells requires the involvement of multiple neurotransmitters, with dopamine playing a critical role in hippocampal place cell activity. However, the exact mechanisms through which dopamine influences place cell activity remain largely unknown. Herein, we present the development of the integrated three-electrode dual-mode detection chip (ITDDC), which enables simultaneous recording of the place cell activity and dopamine concentration fluctuation. The working electrode, reference electrode, and counter electrode are all integrated within the ITDDC in electrochemical detection, enabling the real-time in situ monitoring of dopamine concentrations in animals in motion. The reference, working, and counter electrodes are surface-modified using PtNPs and polypyrrole, PtNPs and PEDOT:PSS, and PtNPs, respectively. This modification allows for the detection of dopamine concentrations as low as 20 nM. We conducted dual-mode testing on mice in a novel environment and an environment with food rewards. We found distinct dopamine concentration variations along different paths within a novel environment, implying that different dopamine levels may contribute to spatial memory. Moreover, environmental food rewards elevate dopamine significantly, followed by the intense firing of reward place cells, suggesting a crucial role of dopamine in facilitating the encoding of reward-associated locations in animals. The real-time and in situ recording capabilities of ITDDC offer new opportunities to investigate the interplay between electrophysiology and dopamine during animal exploration and reward-based memory and provide a novel glimpse into the correlation between dopamine levels and place cell activity.

Effects of Cinnamon Powder on Glucose Metabolism in Diabetic Mice and the Molecular Mechanisms.

The liver is the primary organ regulating glucose metabolism. In our recent study, cinnamon improved liver function in diabetic mice. However, it is not clear whether cinnamon can reduce the glycemia of diabetic animals by regulating liver glucose metabolism. The purpose of this study was to investigate the hypoglycemic mechanism of cinnamon powder (CP) from the perspective of regulating liver glucose metabolism. To achieve this, different doses of CP (200, 400, or 800 mg/kg body weight) were given to diabetic mice by gavage once per day for 8 weeks. These mice were compared with healthy controls, untreated diabetic mice, and diabetic mice treated with metformin (the main first-line drug for type 2 diabetes). CP treatment effectively reduced fasting blood glucose levels and food intake, improved glucose tolerance and fasting serum insulin levels, and decreased glycated serum protein levels in diabetic mice. Furthermore, treatment with CP increased liver glycogen content and reduced the level of the gluconeogenesis precursor pyruvate in the liver. Data obtained by qPCR and western blotting suggested that CP improved glucose metabolism disorders by regulating AMPKα/PGC1α-mediated hepatic gluconeogenesis and PI3K/AKT-mediated hepatic glycogen synthesis. CP exhibits good hypoglycemic effects by improving hepatic glycogen synthesis and controlling hepatic gluconeogenesis. Therefore, CP may be applied as a functional food to decrease blood glucose.

Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review.

In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA's role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.

Prognostic utility of TME-associated genes in pancreatic cancer.

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Disulfidptosis-associated LncRNAs index predicts prognosis and chemotherapy drugs sensitivity in cervical cancer.

Disulfidptosis is a newly discovered form of cell death. Not yet clearly classified as programmed cell death or accidental cell death. This study aimed to create a novel disulfidptosis-related lncRNA index (DLI) that can be used to predict survival and chemotherapy drugs sensitivity in patients with cervical cancer. First of all, we found lncRNAs associated with disulfidptosis between cervical cancer tissues and normal tissues. By LASSO-Cox analysis, overlapping lncRNAs were then used to construct lncRNA index associated with disulfidptosis, which can be served to predict the prognosis of patients with CC, especially the chemotherapy drugs sensitivity. ROC curves and PCA based on DLI and clinical signatures were developed and demonstrated to have good predictive potential. In addition, differences in immune cell subset infiltration and differences in immune checkpoint expression between high-DLI and low-DLI groups were analyzed, and we investigated the relationship between the DLI and tumor mutation burden (TMB). In summary, we constructed a lncRNA prediction index associated with disulfidptosis. This has important clinical implications, including improving the predictive value of cervical cancer patients and providing a biomarker for cervical cancer guiding individualized treatment.

Exploring retinal ganglion cells encoding to multi-modal stimulation using 3D microelectrodes arrays.

Microelectrode arrays (MEA) are extensively utilized in encoding studies of retinal ganglion cells (RGCs) due to their capacity for simultaneous recording of neural activity across multiple channels. However, conventional planar MEAs face limitations in studying RGCs due to poor coupling between electrodes and RGCs, resulting in low signal-to-noise ratio (SNR) and limited recording sensitivity. To overcome these challenges, we employed photolithography, electroplating, and other processes to fabricate a 3D MEA based on the planar MEA platform. The 3D MEA exhibited several improvements compared to planar MEA, including lower impedance (8.73 ± 1.66 kΩ) and phase delay (-15.11° ± 1.27°), as well as higher charge storage capacity (CSC = 10.16 ± 0.81 mC/cm2), cathodic charge storage capacity (CSCc = 7.10 ± 0.55 mC/cm2), and SNR (SNR = 8.91 ± 0.57). Leveraging the advanced 3D MEA, we investigated the encoding characteristics of RGCs under multi-modal stimulation. Optical, electrical, and chemical stimulation were applied as sensory inputs, and distinct response patterns and response times of RGCs were detected, as well as variations in rate encoding and temporal encoding. Specifically, electrical stimulation elicited more effective RGC firing, while optical stimulation enhanced RGC synchrony. These findings hold promise for advancing the field of neural encoding.

Comprehensive analysis for the immune related biomarkers of platinum-based chemotherapy in ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is one of the most lethal gynecological malignancies. This study aimed to identify biomarkers that were sensitive to platinum-based chemotherapeutic agents and can be used in immunotherapy and explore the importance of their mechanisms of action. METHODS: RNA-seq profiles and clinicopathological data for OC samples were obtained from The Cancer Genome Atlas (TCGA) and cBioPortal platform, respectively. Platinum-sensitive and platinum-resistant OC samples in the TCGA cohort were selected based on the clinical information. RNA-seq data for 70 OC samples withSingle-sample gene set enrichment analysis (ssGSEA) and unsupervised clustering were used to classify OC patients from the TCGA cohort into clusters with different proportions of infiltrating immune cells. ESTIMATE analysis was used to assess the immune landscape among clusters. Differential expression, univariate Cox regression, and LASSO regression analyses were performed to construct prognostic model. Spearman correlation analysis was conducted to investigate the correlations among immune checkpoint inhibitors (ICIs) and risk score, half-maximal drug inhibitory concentration (IC50) and risk score. RESULTS: Using ssGSEA and unsupervised clustering, OC samples were divided into two clusters with different immune cell infiltration. Then, 1715 differentially expressed immune-related genes (DEIRGs) were identified between two clusters, 984 differentially expressed platinum-sensitive related genes (DEPSRGs) between 149 platinum-sensitive and 63 platinum-resistant OC samples were identified, and 5384 differentially expressed genes (DEGs) between 380 OC and 194 normal samples were detected from the TCGA cohort. Six biomarkers (GMPPB, SRPK1, STC1, PRSS16, HPDL, and SPTSSB) were detected to establish a prognostic model. The OC patients in the TCGA cohort were classified into high- and low-risk groups. The receive operating characteristic (ROC) curve was plotted and demonstrated that the prognostic model performed well with the area under ROC curve (AUC) greater than 0.6. The expressions of 5 ICIs, including CD200, TNFRSF18, CD160, CD200R1, and CD274 (PD-L1), were significantly different between two risk groups, and the risk score was significant negative associated with CTLA4, TNFRSF4, TNFRSF18, and CD274. Moreover, there were significant differences in IC50 of 10 chemo drugs between two risk groups, patients in the high-risk group could be more resistant to po0tinib, dasatinib, and neratinib. CONCLUSION: In summary, this study constructed a novel prognostic model based on six prognostic biomarkers, including GMPPB, SRPK1, STC1, PRSS16, HPDL, and SPTSSB, which can be utilized for predicting the prognosis of OC patients. These biomarkers were the potential therapeutic targets.

Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays.

Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.

Genetically predicted ankylosing spondylitis is causally associated with psoriasis.

Background: Previous observational studies have reported the striking association between ankylosing spondylitis (AS) and psoriasis, but the causal relationship between the two diseases remains unclear. Methods: Two-sample Mendelian randomization (MR) analysis with methods of inverse-variance weighted, MR-Egger regression, weighted median, and weighted mode was conducted to evaluate the bidirectional causal associations between AS and psoriasis. Effective single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) were selected as instrumental variables (IVs). Sensitivity analyses were also applied to verify whether heterogeneity and pleiotropy can bias the results. Result: We found positive causal effects of genetically increased AS risk on psoriasis (IVW: OR = 1.009, 95% CI = 1.005-1.012, p = 8.07E-07). Comparable outcomes were acquired by MR-Egger regression, weighted median, and weighted mode approaches. Nevertheless, we did not find significant causal effects of psoriasis on AS (IVW: OR = 1.183, 95% CI = 0.137-10.199, p = 0.879). The sensitivity analyses showed that the horizontal pleiotropy was unlikely to skew the causality. The leave-one-out analysis demonstrated that no single SNP can drive the MR estimates. No evidence of heterogeneity was found between the selected IVs. Conclusion: Our findings provide evidence that AS has positive causal effects on the risk of psoriasis in the European population.

Risk factor analysis of bone cement leakage for polymethylmethacrylate-augmented cannulated pedicle screw fixation in spinal disorders.

Objective: To investigate the risk factors of cement leakage (CL) for polymethylmethacrylate-augmented cannulated pedicle screw (CPS) in spinal degenerative diseases and provided technical guidance for clinical surgery. Methods: This study enrolled 276 patients with spinal degenerative disease and osteoporosis who were augmented using CPSs (835 screws in total) from May 2011 to June 2018 in our hospital. The patients' age, sex, bone mineral density (BMD), diagnosis, augmented positions, number of CPS implanted, and CL during surgery were recorded. CL was observed by postoperative computed tomography (CT) and was classified by Yeom typing. Results: A total of 74 (74/835, 8.9%) CPSs in 64 patients leaked (64/276, 23.2%). CL was significantly correlated with the number and position of screws (P < 0.05), but not with sex, age, and BMD (P > 0.05). The position, number of CPSs, fracture, degenerative scoliosis, ankylosing spondylitis, and revision surgery were risk factors for CL (P < 0.05). Augmentation of the thoracic vertebral body, fracture, and ankylosing spondylitis were independent risk factors for Type S. Augmentation of the lumbar vertebral body, lumbar disc herniation, and lumbar spondylolisthesis were independent risk factors for Type B (P < 0.05). Conclusions: CL has a high incidence in clinical practice. High-risk factors for leakage should be addressed to avoid serious complications. Particularly, it is necessary to develop alternative solutions once CPSs can't be used in surgery caused by CL.

PPy/SWCNTs-Modified Microelectrode Array for Learning and Memory Model Construction through Electrical Stimulation and Detection of In Vitro Hippocampal Neuronal Network.

The learning and memory functions of the brain remain unclear, which are in urgent need for the detection of both a single cell signal with high spatiotemporal resolution and network activities with high throughput. Here, an in vitro microelectrode array (MEA) was fabricated and further modified with polypyrrole/carboxylated single-walled carbon nanotubes (PPy/SWCNTs) nanocomposites as the interface between biological and electronic systems. The deposition of the nanocomposites significantly improved the performance of microelectrodes including low impedance (60.3 ± 28.8 k Ω), small phase delay (-32.8 ± 4.4°), and good biocompatibility. Then the modified MEA was used to apply learning training and test on hippocampal neuronal network cultured for 21 days through electrical stimulation, and multichannel electrophysiological signals were recorded simultaneously. During the process of learning training, the stimulus/response ratio of the hippocampal learning population gradually increased and the response time gradually decreased. After training, the mean spikes in burst, number of bursts, and mean burst duration increased by 53%, 191%, and 52%, respectively, and the correlation of neurons in the network was significantly enhanced from 0.45 ± 0.002 to 0.78 ± 0.002. In addition, the neuronal network basically retained these characteristics for at least 5 h. These results indicated that we have successfully constructed a learning and memory model of hippocampal neurons on the in vitro MEA, contributing to understanding learning and memory based on synaptic plasticity. The proposed PPy/SWCNTs-modified in vitro MEA will provide a promising platform for the exploration of learning and memory mechanism and their applications in vitro.

An efficient 3D reconstruction method based on WT-TV denoising for low-dose CT images.

BACKGROUND: In order to reduce the impact of CT radiation, low-dose CT is often used, but low-dose CT will bring more noise, affecting image quality and subsequent 3D reconstruction results. OBJECTIVE: The study presents a reconstruction method based on wavelet transform-total variation (WT-TV) for low-dose CT. METHODS: First, the low-dose CT images were denoised using WT and TV denoising methods. The WT method could preserve the features, and the TV method could preserve the edges and structures. Second, the two sets of denoised images were fused so that the features, edges, and structures could be preserved at the same time. Finally, FBP reconstruction was performed to obtain the final 3D reconstruction result. RESULTS: The results show that The WT-TV method can effectively denoise low-dose CT and improve the clarity and accuracy of 3D reconstruction models. CONCLUSION: Compared with other reconstruction methods, the proposed reconstruction method successfully addressed the issue of low-dose CT noising by further denoising the CT images before reconstruction. The denoising effect of low-dose CT images and the 3D reconstruction model were compared via experiments.