Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.

Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems mostly rely on static visual representations for patients to perform motor imagination (MI) tasks, resulting in lower BCI performance. Therefore, this study innovatively used MI and high-frequency steady-state visual evoked potential (SSVEP) to construct a friendly and natural hybrid BCI paradigm. Specifically, the stimulation interface sequentially presented decomposed action pictures of the left and right hands gripping a ball, with the pictures flashing at specific stimulation frequencies (left: 34 Hz, right: 35 Hz). Integrating soft robotic glove as feedback, we established a comprehensive "peripheral - central - peripheral" hand rehabilitation system to facilitate the hand rehabilitation of patients. Filter bank common spatial pattern (FBCSP) and filter bank canonical correlation analysis (FBCCA) algorithms were used to identify MI and SSVEP signals, respectively. Additionally, to fuse the features of these two signals, we proposed a novel fusion algorithm for improving the recognition accuracy of the system. The feasibility of the proposed system was validated through online experiments involving 12 healthy subjects and 9 stroke patients, achieving accuracy rates of 95.83 ± 6.83% and 63.33 ± 10.38%, respectively. The accuracy of MI and SSVEP in 12 healthy subjects reached 81.67 ± 15.63% and 95.14 ± 7.47%, both lower than the accuracy after fusion, these results confirmed the effectiveness of the proposed algorithm. The accuracy rate was more than 50% in both healthy subjects and patients, confirming the effectiveness of the proposed system.

Improving SSVEP-BCI Performance Through Repetitive Anodal tDCS-Based Neuromodulation: Insights From Fractal EEG and Brain Functional Connectivity.

This study embarks on a comprehensive investigation of the effectiveness of repetitive transcranial direct current stimulation (tDCS)-based neuromodulation in augmenting steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs), alongside exploring pertinent electroencephalography (EEG) biomarkers for assessing brain states and evaluating tDCS efficacy. EEG data were garnered across three distinct task modes (eyes open, eyes closed, and SSVEP stimulation) and two neuromodulation patterns (sham-tDCS and anodal-tDCS). Brain arousal and brain functional connectivity were measured by extracting features of fractal EEG and information flow gain, respectively. Anodal-tDCS led to diminished offsets and enhanced information flow gains, indicating improvements in both brain arousal and brain information transmission capacity. Additionally, anodal-tDCS markedly enhanced SSVEP-BCIs performance as evidenced by increased amplitudes and accuracies, whereas sham-tDCS exhibited lesser efficacy. This study proffers invaluable insights into the application of neuromodulation methods for bolstering BCI performance, and concurrently authenticates two potent electrophysiological markers for multifaceted characterization of brain states.

A comprehensive study on the risk factors and pathogen analysis of postoperative wound infections following caesarean section procedures.

Postoperative wound infections (PWIs), a subtype of surgical site infections, are a significant concern for patients undergoing caesarean sections (C-sections). Understanding risk factors and pathogen profiles can greatly assist in early diagnosis and effective treatment. This study aimed to identify risk factors and analyse the pathogenic landscape contributing to PWIs in C-sections. A nested case-control study was carried out, utilising stringent criteria for case selection and control matching. Diagnostic criteria for surgical site infections included both clinical and microbiological parameters. Risk variables examined included patient age, Body Mass Index, duration of surgery and several other clinical indicators. Microbiological analysis was performed using the BD Phoenix-100 Automated Bacterial Identification System. Statistical analyses were conducted using SPSS version 26.0, and risk factors were evaluated through both univariate and multivariate analyses. A total of 50 patients, aged between 20 and 45 years (mean age 26.3 ± 5.6), developed PWIs following C-sections. The study revealed a temporal distribution and various clinical indicators of PWIs, including elevated white blood cell count and C-reactive protein levels. Gram-negative bacteria were found to be more prevalent at 57.4%. Notable pathogens included Pseudomonas aeruginosa and Acinetobacter baumannii. Antimicrobial resistance patterns were also identified, highlighting the need for a targeted antibiotic approach. Increased infection risks were linked to lack of prophylactic antibiotics, absence of preoperative povidone-iodine antisepsis, operations over an hour, anaemia, amniotic fluid contamination, diabetes, GTI, premature rupture of membranes and white blood cells counts above 10 × 109 /L. The study provides critical insights into the risk factors and microbial agents contributing to PWIs following C-sections. Our findings emphasise the importance of early diagnosis through clinical and laboratory parameters, as well as the need for constant surveillance and reassessment of antibiotic stewardship programs.

Regulated secretion of mutant p53 negatively affects T lymphocytes in the tumor microenvironment.

Several studies have demonstrated the role of the oncogenic mutant p53 in promoting tumor progression; however, there is limited information on the effects of secreted oncogenic mutant p53 on the tumor microenvironment and tumor immune escape. In this study, we found that secretion of mutant p53, determined by exosome content, is dependent on its N-terminal dileucine motif via its binding to ß-adaptin, and inhibited by the CHK2-mediated-Ser 20 phosphorylation. Moreover, we observed that the mutant p53 caused downregulation and dysfunction of CD4+ T lymphocytes in vivo and downregulated the levels and activities of rate-limiting glycolytic enzymes in vitro. Furthermore, inhibition of mutant p53 secretion by knocking down AP1B1 or mutation of dileucine motif could reverse the quantity and function of CD4+ T lymphocytes and restrain the tumor growth. Our study demonstrates that the tumor-derived exosome-mediated secretion of oncogenic mutant p53 inhibits glycolysis to alter the immune microenvironment via functional suppression of CD4+ T cells, which may be the underlying mechanism for tumor immune escape. Therefore, targeting TDE-mediated p53 secretion may serve as a potential therapeutic target for cancer treatment.

A High-Rate Hybrid BCI System Based on High-Frequency SSVEP and sEMG.

Recently, various biosignals have been combined with electroencephalography (EEG) to build hybrid brain-computer interface (BCI) systems to improve system performance. Since steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) are easy-to-use, non-invasive techniques, and have high signal-to-noise ratio (SNR), hybrid BCI systems combining SSVEP and sEMG have received much attention in the BCI literature. However, most existing studies regarding hybrid BCIs based on SSVEP and sEMG adopt low-frequency visual stimuli to induce SSVEPs. The comfort of these systems needs further improvement to meet the practical application requirements. The present study realized a novel hybrid BCI combining high-frequency SSVEP and sEMG signals for spelling applications. EEG and sEMG were obtained simultaneously from the scalp and skin surface of subjects, respectively. These two types of signals were analyzed independently and then combined to determine the target stimulus. Our online results demonstrated that the developed hybrid BCI yielded a mean accuracy of 88.07 ± 1.43% and ITR of 159.12 ± 4.31 bits/min. These results exhibited the feasibility and effectiveness of fusing high-frequency SSVEP and sEMG towards improving the total BCI system performance.

A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG.

Hybrid brain-computer interface (hBCI) systems that combine steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) signals have attracted attention of researchers due to the advantage of exhibiting significantly improved system performance. However, almost all existing studies adopt low-frequency SSVEP to build hBCI. It produces much more visual fatigue than high-frequency SSVEP. Therefore, the current study attempts to build a hBCI based on high-frequency SSVEP and sEMG. With these two signals, this study designed and realized a 32-target hBCI speller system. Thirty-two targets were separated from the middle into two groups. Each side contained 16 sets of targets with different high-frequency visual stimuli (i.e., 31-34.75 Hz with an interval of 0.25 Hz). sEMG was utilized to choose the group and SSVEP was adopted to identify intra-group targets. The filter bank canonical correlation analysis (FBCCA) and the root mean square value (RMS) methods were used to identify signals. Therefore, the proposed system allowed users to operate it without system calibration. A total of 12 healthy subjects participated in online experiment, with an average accuracy of 93.52 ± 1.66% and the average information transfer rate (ITR) reached 93.50 ± 3.10 bits/min. Furthermore, 12 participants perfectly completed the free-spelling tasks. These results of the experiments indicated feasibility and practicality of the proposed hybrid BCI speller system.

Downregulation of TCL6 protected human trophoblast cells from LPS-induced inflammation and ferroptosis.

Dysregulation of noncoding RNAs has been reported to have a close correlation with preeclampsia(PE)development. TCL6 was upregulated in patients with PE. In this study, we examined the impacts of TCL6 on modulating HTR-8/SVneo cells induced by LPS. LPS (100 and 200 ng/ml) was applied to induce inflammation in trophoblast cells HTR-8/SVneo. Cell viability, apoptosis, and transwell experiments were conducted. The ELISA methods were used for pro-inflammatory cytokines IL-1ß, IL-6, and TNF-α. MDA, GSH, and GPX kits were employed. Transfection was performed for expression regulation of TCL6, miR-485-5p, and TFRC in cells. Bioinformatic online tools were used to predict the targeting sites. Luciferase and RNA immunoprecipitation-qPCR were done to verify the interactions of TCL6, miR-485-5p, and TFRC. RNA expression levels were measured using RT-qPCR, and protein expression of TFRC and GPX4 was detected using a western blot. The free Fe (II) contents were measured. LPS decreased viability, invasion, and migration but enhanced apoptosis, ferroptosis, and inflammation. TCL6 expression was enhanced by LPS induction. The knockdown of TCL6 increased HTR-8/SVneo cell viability and invasion but inhibited cell apoptosis, inflammation, and ferroptosis while inhibition of miR-485-5p could reverse this through TFRC regulation. Moreover, miR-485-5p was sponged by TCL6 and bound to TFRC. TCL6 protected trophoblast cells from LPS-induced injury through the TFRC pathway.

Identifying Intraoperative Spinal Cord Injury Location from Somatosensory Evoked Potentials' Time-Frequency Components.

Excessive distraction in corrective spine surgery can lead to iatrogenic distraction spinal cord injury. Diagnosis of the location of the spinal cord injury helps in early removal of the injury source. The time-frequency components of the somatosensory evoked potential have been reported to provide information on the location of spinal cord injury, but most studies have focused on contusion injuries of the cervical spine. In this study, we established 19 rat models of distraction spinal cord injury at different levels and collected the somatosensory evoked potentials of the hindlimb and extracted their time-frequency components. Subsequently, we used k-medoid clustering and naive Bayes to classify spinal cord injury at the C5 and C6 level, as well as spinal cord injury at the cervical, thoracic, and lumbar spine, respectively. The results showed that there was a significant delay in the latency of the time-frequency components distributed between 15 and 30 ms and 50 and 150 Hz in all spinal cord injury groups. The overall classification accuracy was 88.28% and 84.87%. The results demonstrate that the k-medoid clustering and naive Bayes methods are capable of extracting the time-frequency component information depending on the spinal cord injury location and suggest that the somatosensory evoked potential has the potential to diagnose the location of a spinal cord injury.

A High-Frequency SSVEP-BCI System Based on Simultaneous Modulation of Luminance and Motion Using Intermodulation Frequencies.

The low-frequency steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) tend to induce visual fatigue in the subjects. In order to enhance the comfort of SSVEP-BCIs, a novel SSVEP-BCI encoding method based on simultaneous modulation of luminance and motion is proposed. In this work, sixteen stimulus targets are simultaneously flickered and radially zoomed using a sampled sinusoidal stimulation method. The flicker frequency is set to a 30 Hz for all the targets, while assigning different radial zoom frequencies (ranging from 0.4 Hz to 3.4 Hz, with an interval of 0.2 Hz) are assigned to each target separately. Accordingly, an extended vision of the filter bank canonical correlation analysis (eFBCCA) is proposed to detect the intermodulation (IM) frequencies and classify the targets. In addition, we adopt the comfort level scale to evaluate the subjective comfort experience. By optimizing the combination of IM frequencies for the classification algorithm, the average recognition accuracy of the offline and online experiments reaches 92.74 ± 1.53% and 93.33 ± 0.01%, respectively. Most importantly, the average comfort scores are above 5. These results demonstrate the feasibility and comfort of the proposed system using IM frequencies, which provides new ideas for the further development of highly comfortable SSVEP-BCIs.

Construction of tea tree oil/salicylic acid/palygorskite hybrids for advanced antibacterial and anti-inflammatory performance.

This study describes the construction of a tailor-made clay-based hybrid with advanced dermocompatibility, antibacterial and anti-inflammatory performance by incorporating tunable ratios of tea tree oil (TTO) and salicylic acid (SA) into the naturally occurring porous structure of palygorskite (Pal). Among the three TTO/SA/Pal (TSP) systems constructed, TSP-1 with a TTO : SA ratio of 1 : 3 demonstrated the lowest 3T3 NRU predicted acute oral toxicity and dermal HaCaT cytotoxicity as well as the most pronounced antibacterial activity with a selective inhibitory action against the pathogens (E. coli, P. acnes and S. aureus) over the beneficial (S. epdermidis) species inhabiting on the human skin. Also noticeable is that exposure of these skin commensal bacteria to TSP-1 prevented the antimicrobial resistance evolution compared to the conventional antibiotic ciprofloxacin. Mechanistic investigation of its antibacterial modes of action revealed a synergy between the TTO and SA loadings on the Pal supports in reactive oxygen production, causing oxidative damage to bacterial cell membranes and increased leakage of intracellular compounds. Additionally, TSP-1 significantly decreased the proinflammatory cytokines of IL-1ß, IL-6, IL-8, and TNF-α in a bacterial lipopolysaccharide-stimulated differentiated THP-1 macrophage model, showing the potential to inhibit inflammatory responses in bacterial infections. Overall, this is the first report exploring the potential of constructing clay-based organic-inorganic hybrids as alternatives to antibiotics to combat bacterial resistance with advanced compatibility and anti-inflammatory benefits that are desired for the development of topically applied biopharmaceuticals.

Activation of pyroptosis by specific organelle-targeting photodynamic therapy to amplify immunogenic cell death for anti-tumor immunotherapy.

Pyroptosis, a unique lytic programmed cell death, inspired tempting implications as potent anti-tumor strategy in pertinent to its potentials in stimulating anti-tumor immunity for eradication of primary tumors and metastasis. Nonetheless, rare therapeutics have been reported to successfully stimulate pyroptosis. In view of the intimate participation of reactive oxygen species (ROS) in stimulating pyroptosis, we attempted to devise a spectrum of well-defined subcellular organelle (including mitochondria, lysosomes and endoplasmic reticulum)-targeting photosensitizers with the aim of precisely localizing ROS (produced from photosensitizers) at the subcellular compartments and explore their potentials in urging pyroptosis and immunogenic cell death (ICD). The subsequent investigations revealed varied degrees of pyroptosis upon photodynamic therapy (PDT) towards cancerous cells, as supported by not only observation of the distinctive morphological and mechanistic characteristics of pyroptosis, but for the first-time explicit validation from comprehensive RNA-Seq analysis. Furthermore, in vivo anti-tumor PDT could exert eradication of the primary tumors, more importantly suppressed the distant tumor and metastatic tumor growth through an abscopal effect, approving the acquirement of specific anti-tumor immunity as a consequence of pyroptosis. Hence, pyroptosis was concluded unprecedently by our proposed organelles-targeting PDT strategy and explicitly delineated with molecular insights into its occurrence and the consequent ICD.

A Novel SSVEP Brain-Computer Interface System Based on Simultaneous Modulation of Luminance and Motion.

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have received significant attention owing to their high information transfer rate (ITR) and low training requirements. Previous SSVEP-based BCIs mostly adopt the stationary visual flickers where only a few studies have explored the effect of moving visual flickers on the SSVEP-BCI. In this study, a novel stimulus encoding method based on the simultaneous modulation of luminance and motion was proposed. We adopted the sampled sinusoidal stimulation method to encode the frequencies and phases of stimulus targets. In addition to luminance modulation, at the same time, visual flickers also moved horizontally towards right and left at different frequencies (i.e., 0, 0.2, 0.4, and 0.6 Hz) following a sinusoidal function. Accordingly, a nine-target SSVEP-BCI was built to evaluate the influence of motion modulation on the BCI performance. Filter bank canonical correlation analysis (FBCCA) approach was adopted to identify the stimulus targets. Offline experimental results of 17 subjects revealed that the system performance decreased with the increase of superimposed horizontal periodic motion frequency. Our online experimental results showed that the subjects achieved 85.00 ± 6.77 % and 83.15 ± 9.88 % accuracy for the superimposed horizontal periodic motion frequencies of 0 and 0.2 Hz, respectively. These results verified the feasibility of the proposed systems. In addition, the system with 0.2 Hz horizontal motion frequency provided the best visual experience for subjects. These results indicated that moving visual stimulus can provide an alternative option for SSVEP-BCIs. Furthermore, the proposed paradigm is expected to develop a more comfortable BCI system.

Transcranial Direct Current Stimulation-based Neuromodulation Improves the Performance of Brain-Computer Interfaces Based on Steady-State Visual Evoked Potential.

The study of brain state estimation and intervention methods is of great significance for the utility of brain-computer interfaces (BCIs). In this paper, a neuromodulation technology using transcranial direct current stimulation (tDCS) is explored to improve the performance of steady-state visual evoked potential (SSVEP)-based BCIs. The effects of pre-stimulation, sham-tDCS and anodal-tDCS are analyzed through a comparison of the EEG oscillations and fractal component characteristics. In addition, in this study, a novel brain state estimation method is introduced to assess neuromodulation-induced changes in brain arousal for SSVEP-BCIs. The results suggest that tDCS, and anodal-tDCS in particular, can be used to increase SSVEP amplitude and further improve the performance of SSVEP-BCIs. Furthermore, evidence from fractal features further validates that tDCS-based neuromodulation induces an increased level of brain state arousal. The findings of this study provide insights into the improvement of BCI performance based on personal state interventions and provide an objective method for quantitative brain state monitoring that may be used for EEG modeling of SSVEP-BCIs.

Optimizing Stimulus Frequency Ranges for Building a High-Rate High Frequency SSVEP-BCI.

The brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) have been extensively explored due to their advantages in terms of high communication speed and smaller calibration time. The visual stimuli in the low- and medium-frequency ranges are adopted in most of the existing studies for eliciting SSVEPs. However, there is a need to further improve the comfort of these systems. The high-frequency visual stimuli have been used to build BCI systems and are generally considered to significantly improve the visual comfort, but their performance is relatively low. The distinguishability of 16-class SSVEPs encoded by the three frequency ranges, i.e., 31-34.75 Hz with an interval of 0.25 Hz, 31-38.5 Hz with an interval of 0.5 Hz, 31-46 Hz with an interval of 1 Hz, is explored in this study. We compare classification accuracy and information transfer rate (ITR) of the corresponding BCI system. According to the optimized frequency range, this study builds an online 16-target high frequency SSVEP-BCI and verifies the feasibility of the proposed system based on 21 healthy subjects. The BCI based on visual stimuli with the narrowest frequency range, i.e., 31-34.5 Hz, have the highest ITR. Therefore, the narrowest frequency range is adopted to build an online BCI system. An averaged ITR obtained from the online experiment is 153.79 ± 6.39 bits/min. These findings contribute to the development of more efficient and comfortable SSVEP-based BCIs.

A complete hydatidiform mole and coexisting viable fetus in a twin pregnancy: a case report with literature review.

INTRODUCTION: A twin pregnancy involving a hydatidiform mole (HM) coexisting with a developing fetus is an extremely rare obstetric complication, which typically presents as a complete hydatidiform mole with a coexisting fetus (CHMCF) or a partial hydatidiform mole with a coexisting fetus (PHMCF). CASE PRESENTATION: A 26-year-old woman was admitted to our hospital due to a small volume of vaginal bleeding during the 31st week of pregnancy. The patient was previously healthy, and an intrauterine singleton pregnancy was detected by ultrasound on day 46 of gestation; however, bunch-of-grapes sign was observed in the uterine cavity at 24 weeks. The patient was subsequently diagnosed with CHMCF. As the patient insisted on continuing her pregnancy, she underwent hospital monitoring. Vaginal bleeding occurred in the 33rd week again and received a course of betamethasone, then continued pregnancy after bleeding stopped spontaneously. In the 37th week, a male infant weighing 3090 g was delivered by cesarean section, with an Apgar score of 10 at 1 min and a karyotype of 46XY. Placental pathology confirmed the diagnosis of a complete hydatid tumor. CONCLUSION: In this report, a case of CHMCF was maintained by monitoring of blood pressure, thyroid function, human chorionic gonadotrophin, and fetal condition during pregnancy. A live newborn was delivered by cesarean section. CHMCF is a clinically rare disease with high risks; thus, it should be diagnosed carefully using several tools, including ultrasound, magnetic resonance imaging, and karyotype analysis and dynamically monitored if the patient decides to continue the pregnancy.

Simultaneous Knockdown of Immune Suppressive Markers by Tumor Microenvironment-Responsive Multifaceted Prodrug Nanomedicine.

Tumors managing to exempt from immune clearance are attributable to their overexpressed immune suppressive molecules (CD47, PD-L1, etc.). Leadingly, the checkpoint blockade-based chemoimmunotherapy by means of knockdown of these immunosuppressive checkpoints, together with immunogenetic chemotherapeutics, is perceived to be a valid therapeutic strategy for improving anti-tumor outcomes. Herein, chemotherapeutic camptothecin was covalently introduced into an intriguing multifaceted nanomedicine. Note that the elaborated nanomedicine was chemically engineered to enable targeted transportation to the tumors via systemic administration, possessing intelligent responsiveness to sequential extracellular and intracellular microenvironments in the targeted tumors for prompted transcellular endocytosis owing to enzymolysis by the tumor-enriched matrix metalloproteinases and the selective liberation of cytocidal camptothecin in the cell interiors owing to thiolysis by glutathione. In addition, this chemotherapeutic nanomedicine allowed facile encapsulation of the negatively charged RNA interference payloads. Consequently, aiming for treatment of intractable triple-negative breast tumors, we attempted the small interfering RNA (siRNA) payloads aiming for CD47 and PD-L1 into the aforementioned nanomedicine. The subsequent investigations demonstrated drastic knockdown of these vital immune suppressive checkpoints by this siRNA-encapsulating chemotherapeutic nanomedicine, conducing to the reversal of the immune checkpoint suppressive microenvironment of triple-negative 4T1 tumors. Namely, the inhibited proceedings of the innate and adaptive anti-tumor immunities were revived, as supported by observation of the activated infiltration and retention of CD68+ macrophages and CD4+ and CD8+ lymphocytes into the tumors. Eventually, most potent anti-tumor efficacies were accomplished by systemic administration of this chemoimmunotherapeutic nanomedicine, which verified the amplified contribution from anti-tumor immunities by means of knockdown of the immune suppressive molecules to the ultimate anti-tumor efficacies. Note that the upregulation of the immune suppressive molecules was constantly reported in a variety of clinical therapies; hence, our facile chemoimmunotherapeutic platform should be emphasized in clinical translation for seeking improved therapeutic outcomes.

pH-responsive organic/inorganic hybrid nanocolloids for transcellular delivery of ribonucleolytic payloads toward targeted anti-glioma therapy.

Proteins have been appreciated to be a superlative modality of therapeutics in view of their direct roles in regulating diverse sets of biological events, nonetheless, the clinical applications of the proteinic therapeutics have been strictly limited to act on the cell surface receptors owing to their inherent cell-impermeable character of the proteins. To this obstacle, we contrived carboxylation reaction upon the proteins (RNase A) into the overall negatively charged pro-RNase, followed by elaboration of intelligent pH-responsive pro-RNase delivery nanocolloids based on co-precipitation of pro-RNase and Arg-Gly-Asp (RGD)-functionalized poly(ethylene glycol) (PEG)-block-polyanion with aids of inorganic calcium phosphate (CaP). The resulting nanocolloids appeared to actively accumulate into glioma due to the specific binding affinities of RGD and glioma-enriched αVß3 and αVß5 integrins. Furthermore, the pH responsiveness to the acidic endolysosomal microenvironment of all compositions of nanocolloids (including: decarboxylation of pro-RNase composition to restore the native RNase A, ionization of CaP composition to elicit osmotic pressure, and charge reversal of PEG-block-polyanion into membrane-disruptive polycation) could stimulate not only efficient endolysosomal escape for translocation into the cytosol but also structural disassembly for ready liberation of the RNase A payloads, eventually exerting non-specific RNA degradation for apoptosis of the affected cells. Systemic dosage of the proposed nanocolloids demonstrated potent anti-tumor efficacies towards xenograft glioma due to massive RNA degradation. Therefore, our proposed RNase A prodrug nanocolloids could represent as a versatile platform for engineering transcellular protein delivery systems, which are expected to spur thriving emergence of a spectrum of proteins in precision intervention of intractable diseases.

A Prediction Model for Normal Variation of Somatosensory Evoked Potential During Scoliosis Surgery.

Somatosensory evoked potential (SEP) has been commonly used as intraoperative monitoring to detect the presence of neurological deficits during scoliosis surgery. However, SEP usually presents an enormous variation in response to patient-specific factors such as physiological parameters leading to the false warning. This study proposes a prediction model to quantify SEP amplitude variation due to noninjury-related physiological changes of the patient undergoing scoliosis surgery. Based on a hybrid network of attention-based long-short-term memory (LSTM) and convolutional neural networks (CNNs), we develop a deep learning-based framework for predicting the SEP value in response to variation of physiological variables. The training and selection of model parameters were based on a 5-fold cross-validation scheme using mean square error (MSE) as evaluation metrics. The proposed model obtained MSE of 0.027[Formula: see text][Formula: see text] on left cortical SEP, MSE of 0.024[Formula: see text][Formula: see text] on left subcortical SEP, MSE of 0.031[Formula: see text][Formula: see text] on right cortical SEP, and MSE of 0.025[Formula: see text][Formula: see text] on right subcortical SEP based on the test set. The proposed model could quantify the affection from physiological parameters to the SEP amplitude in response to normal variation of physiology during scoliosis surgery. The prediction of SEP amplitude provides a potential varying reference for intraoperative SEP monitoring.

Identification of injury type using somatosensory and motor evoked potentials in a rat spinal cord injury model.

The spinal cord is at risk of injury during spinal surgery. If intraoperative spinal cord injury is identified early, irreversible impairment or loss of neurological function can be prevented. Different types of spinal cord injury result in damage to different spinal cord regions, which may cause different somatosensory and motor evoked potential signal responses. In this study, we examined electrophysiological and histopathological changes between contusion, distraction, and dislocation spinal cord injuries in a rat model. We found that contusion led to the most severe dorsal white matter injury and caused considerable attenuation of both somatosensory and motor evoked potentials. Dislocation resulted in loss of myelinated axons in the lateral region of the injured spinal cord along the rostrocaudal axis. The amplitude of attenuation in motor evoked potential responses caused by dislocation was greater than that caused by contusion. After distraction injury, extracellular spaces were slightly but not significantly enlarged; somatosensory evoked potential responses slightly decreased and motor evoked potential responses were lost. Correlation analysis showed that histological and electrophysiological findings were significantly correlated and related to injury type. Intraoperative monitoring of both somatosensory and motor evoked potentials has the potential to identify iatrogenic spinal cord injury type during surgery.