Identification of ACAA1 and HADHB as potential prognostic biomarkers based on a novel fatty acid oxidation-related gene model in head and neck squamous cell carcinoma: A retrospective study.

OBJECTIVES: To investigate the importance of fatty acid oxidation (FAO)-related genes in predicting the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). METHODS: The FAO-related gene prognostic model was established employing Cox regression analyses, during which accuracy and sensitivity of the gene model were evaluated in The Cancer Genome Atlas (TCGA) internal testing and Gene Expression Omnibus (GEO) external validation cohorts. Ultimately, hub genes were identified among 13 model genes using STRING and Cytoscape, with preliminary validation carried out through immunohistochemistry. RESULTS: The model, which comprised 13 genes (ABCD2, ACAA1, ACACB, AKT1, CNR1, CPT1C, CROT, ECHDC2, ETFA, HADHB, IRS2, LONP2, and SLC25A17), was established. On the basis of the median risk score, the two cohorts were grouped into low-and high-risk groups in the subsequent test and validation, and the former exhibited significantly higher survival rates than the latter. Nomograms were established based on prognostic factors, including stage and risk score, and individualized for the prediction of HNSCC patients. Ultimately, immunohistochemical staining showed that ACAA1 and HADHB were significantly under-expressed in HNSCC, with a favorable prognosis associated with low HADHB and high ACAA1. CONCLUSIONS: The gene prognostic model has illustrated promising capability in predicting the prognosis, and ACAA1 and HADHB might serve as potential therapeutic biomarkers for HNSCC patients.

Speech decoding using cortical and subcortical electrophysiological signals.

Introduction: Language impairments often result from severe neurological disorders, driving the development of neural prosthetics utilizing electrophysiological signals to restore comprehensible language. Previous decoding efforts primarily focused on signals from the cerebral cortex, neglecting subcortical brain structures' potential contributions to speech decoding in brain-computer interfaces. Methods: In this study, stereotactic electroencephalography (sEEG) was employed to investigate subcortical structures' role in speech decoding. Two native Mandarin Chinese speakers, undergoing sEEG implantation for epilepsy treatment, participated. Participants read Chinese text, with 1-30, 30-70, and 70-150 Hz frequency band powers of sEEG signals extracted as key features. A deep learning model based on long short-term memory assessed the contribution of different brain structures to speech decoding, predicting consonant articulatory place, manner, and tone within single syllable. Results: Cortical signals excelled in articulatory place prediction (86.5% accuracy), while cortical and subcortical signals performed similarly for articulatory manner (51.5% vs. 51.7% accuracy). Subcortical signals provided superior tone prediction (58.3% accuracy). The superior temporal gyrus was consistently relevant in speech decoding for consonants and tone. Combining cortical and subcortical inputs yielded the highest prediction accuracy, especially for tone. Discussion: This study underscores the essential roles of both cortical and subcortical structures in different aspects of speech decoding.

Correction: Stretchable and durable HD-sEMG electrodes for accurate recognition of swallowing activities on complex epidermal surfaces.

[This corrects the article DOI: 10.1038/s41378-023-00591-3.].

GAD1-mediated GABA elicits aggressive characteristics of human oral cancer cells.

Studies suggest that the expression of glutamate decarboxylase 1 (GAD1), γ-aminobutyric acid (GABA), and GABA receptors are involved in tumor progression. However, the underlying mechanisms of high expression and potential functions of GAD1 and GABA in oral squamous cell carcinoma (OSCC) are not known. In this study, we found that the expressions of GAD1 and GABA were considerably increased in OSCC samples, which were closely associated with clinical stage and lymph node metastasis. The knockdown of GAD1 expression significantly inhibited the proliferation, migration and invasion abilities of OSCC cells by reducing the expression of GABA-mediated GABAB receptors, which could be reversed by exogenous GABA, but did not cause excessive OSCC cell proliferation. And GABA secreted by OSCC cells promoted M2 macrophage polarization for inhibiting anti-tumor immunity by activating GABBR1/ERK/Ca2+. In addition, GABA/GABABR promoted the proliferation and progression of OSCC xenograft tumor. Altogether, our results showed that GAD1 synthetized GABA to promote the malignant progression of OSCC and limits the anti-tumor immunity of macrophages, thereby targeting GABA can be a novel strategy for treating OSCC.

Stretchable and durable HD-sEMG electrodes for accurate recognition of swallowing activities on complex epidermal surfaces.

Surface electromyography (sEMG) is widely used in monitoring human health. Nonetheless, it is challenging to capture high-fidelity sEMG recordings in regions with intricate curved surfaces such as the larynx, because regular sEMG electrodes have stiff structures. In this study, we developed a stretchable, high-density sEMG electrode array via layer-by-layer printing and lamination. The electrode offered a series of excellent human‒machine interface features, including conformal adhesion to the skin, high electron-to-ion conductivity (and thus lower contact impedance), prolonged environmental adaptability to resist water evaporation, and epidermal biocompatibility. This made the electrode more appropriate than commercial electrodes for long-term wearable, high-fidelity sEMG recording devices at complicated skin interfaces. Systematic in vivo studies were used to investigate its ability to classify swallowing activities, which was accomplished with high accuracy by decoding the sEMG signals from the chin via integration with an ear-mounted wearable system and machine learning algorithms. The results demonstrated the clinical feasibility of the system for noninvasive and comfortable recognition of swallowing motions for comfortable dysphagia rehabilitation.

Clinicopathological and immunohistochemical analysis of maxillofacial granular cell tumor.

OBJECTIVES: To analyze the clinicopathological features of maxillofacial granular cell tumors (GCT) with the aid of immunohistochemical staining. METHODS: Seven cases of maxillofacial GCT were retrospectively collated, and the microscopic morphology of maxillofacial GCT was analyzed. The expression of S-100, neuron-specific enolase (NSE), SOX-10, CD68, actin, desmin, and Ki-67 in GCT was detected by immunohistochemical staining. The cases were observed in the follow-ups after clinical treatment. RESULTS: All seven GCT tumors lacked envelopes and were poorly defined. Microscopically, the sizes of the tumor cells were large and appeared with inconspicuous cell membranes, forming a syncytium-like appearance. The cytoplasm was filled with characteristic eosinophilic granules. The immunohistochemical results showed that six cases were NSE-positive, five cases were S-100-positive, seven cases were CD68-positive, five cases were SOX-10-positive, one case was actin-positive, and seven cases were desmin-negative. The Ki-67 index did not exceed 5% in all cases. In the follow-up sessions, none of the six cases presented a recurrence. CONCLUSIONS: Maxillofacial GCT has a characteristic histological structure. Immunohistochemical S-100, CD68, and other indicators can assist in diagnosis, and the prognosis is good after clinical resection.

Individualized targeting is warranted in subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression: A tractography analysis.

Subcallosal cingulate gyrus (SCG) is a target of deep brain stimulation (DBS) for treatment-resistant depression. However, previous randomized controlled trials report that approximately 42% of patients are responders to this therapy of last resort, and suboptimal targeting of SCG is a potential underlying factor to this unsatisfactory efficacy. Tractography has been proposed as a supplementary method to enhance targeting strategy. We performed a connectivity-based segmentation in the SCG region via probabilistic tractography in 100 healthy volunteers from the Human Connectome Project. The SCG voxels with maximum connectivity to brain regions implicated in depression, including Brodmann Area 10 (BA10), cingulate cortex, thalamus, and nucleus accumbens were identified, and the conjunctions were deemed as tractography-based targets. We then performed deterministic tractography using these targets in additional 100 volunteers to calculate streamline counts compassing to relevant brain regions and fibers. We also evaluated the intra- and inter-subject variance using test-retest dataset. Two tractography-based targets were identified. Tractography-based target-1 had the highest streamline counts to right BA10 and bilateral cingulate cortex, while tractography-based target-2 had the highest streamline counts to bilateral nucleus accumbens and uncinate fasciculus. The mean linear distance from individual tractography-based target to anatomy-based target was 3.2 ± 1.8 mm and 2.5 ± 1.4 mm in left and right hemispheres. The mean ± SD of targets between intra- and inter-subjects were 2.2 ± 1.2 and 2.9 ± 1.4 in left hemisphere, and 2.3 ± 1.4 and 3.1 ± 1.7 in right hemisphere, respectively. Individual heterogeneity as well as inherent variability from diffusion imaging should be taken into account during SCG-DBS target planning procedure.

Carcinoma within a lymphoepithelial cyst: a case report.

Malignant transformation arising in benign lymphoepithelial cysts is a complex and rare occurrence, and related research is limited. This study presents a case of the malignant degeneration of lymphoepithelial cyst in parapharyngeal space. Clinicopathological features and differential diagnosis are discussed with literature review to provide reference for clinical diagnosis and treatment management.

miR-183-5p overexpression orchestrates collective invasion in salivary adenoid cystic carcinoma through the FAT1/YAP1 signaling pathway.

The invasion of cancer cells into interstitial tissues in a cohesive unit is termed collective invasion, and it is important for the invasion and metastasis of salivary adenoid cystic carcinoma (SACC). However, the underlying mechanisms regulating SACC collective invasion are still poorly understood. Here, we found that SACC tissues exhibited remarkable FAT1 downregulation and YAP1 upregulation at the invasive front, which was closely associated with collective invasion and distant metastasis. Decreasing FAT1 expression significantly activated the YAP1 signaling pathway and promoted collective invasion. Moreover, miR-183-5p was identified as the candidate regulator of FAT1 by bioinformatic analysis and an online database algorithm. A dual luciferase reporter experiment further confirmed that miR-183-5p directly targeted the FAT1 3'-UTR to reduce FAT1 expression. Increasing or decreasing miR-183-5p expression promoted or attenuated collective invasion, which was reversed by YAP1 siRNA or FAT1 siRNA, respectively. In addition, knocking down miR-183-5p reduced tumor burden and attenuated collective invasion in vivo. Together, these results suggest that the miR-183-5p/FAT1/YAP1 signaling pathway is a critical driver of SACC collective invasion, revealing a novel therapeutic target.

Deep Brain Stimulation for Advanced Parkinson Disease in Developing Countries: A Cost-Effectiveness Study From China.

BACKGROUND: The cost-effectiveness of deep brain stimulation (DBS) is more favorable than best medical treatment (BMT) for advanced Parkinson disease (PD) in developed countries. However, it remains unclear in developing countries, where the cost of DBS may not be reimbursed by health care system. OBJECTIVE: To model and evaluate the long-term cost-effectiveness of DBS for advanced PD in China from a patient payer perspective. METHODS: We developed a Markov model representing the clinical progress of PD to predict the disease progression and related medical costs in a 15-year time horizon. The incremental cost-effectiveness ratio (ICER) and net benefit were used to evaluate the cost-effectiveness of DBS vs BMT. RESULTS: DBS treatment led to discounted total costs of ¥370 768 ($56 515.20) (95% CI, ¥369 621.53-371 914.88), compared with ¥48 808 ($7439.68) (95% CI, ¥48 502.63-49 114.21) for BMT, with an additional 1.51 quality-adjusted life years gained, resulting in an ICER of ¥213 544 ($32 549.96)/quality-adjusted life years (95% CI, ¥208 177.35-218 910.10). Sensitivity analysis showed that DBS-related cost has the most substantial impact on ICER. Nation-wide net benefit of BMT and DBS were ¥33 819 ($5154.94) (95% CI, ¥30 211.24-37 426) and ¥30 361 ($4627.85) (95% CI, ¥25 587.03-39 433.66), respectively. Patient demographic analysis showed that more favorable DBS cost-effectiveness was associated with younger age and less severe disease stage. CONCLUSION: DBS is cost-effective for patients with advanced PD over a 15-year time horizon in China. However, compared with developed countries, DBS remains a substantial economic burden for patients when no reimbursement is provided. Our findings may help inform cost-effectiveness-based decision making for clinical care of PD in developing countries.

A Graph-Attention-Based Method for Single-Resident Daily Activity Recognition in Smart Homes.

In ambient-assisted living facilitated by smart home systems, the recognition of daily human activities is of great importance. It aims to infer the household's daily activities from the triggered sensor observation sequences with varying time intervals among successive readouts. This paper introduces a novel deep learning framework based on embedding technology and graph attention networks, namely the time-oriented and location-oriented graph attention (TLGAT) networks. The embedding technology converts sensor observations into corresponding feature vectors. Afterward, TLGAT provides a sensor observation sequence as a fully connected graph to the model's temporal correlation as well as the sensor's location correlation among sensor observations and facilitates the feature representation of each sensor observation through receiving other sensor observations and weighting operations. The experiments were conducted on two public datasets, based on the diverse setups of sensor event sequence length. The experimental results revealed that the proposed method achieved favorable performance under diverse setups.

USc2C2 and USc2NC Clusters with U-C Triple Bond Character Stabilized Inside Fullerene Cages.

The chemistry of f-block metal-carbon multiple bonds is underdeveloped compared to well-established carbene complexes of the d-block transition metals. Herein, we report two new actinide-rare earth mixed metal carbides and nitrogen carbide cluster fullerenes, USc2C2@D5h(6)-C80 and USc2NC@D5h(6)-C80, which contain U-C bonds with triple bond character and were successfully synthesized and characterized by mass spectrometry, UV-vis-NIR spectroscopy, Fourier transform infrared spectroscopy, single crystal X-ray diffraction, and DFT calculations. Crystallographic studies show that the two previously unreported clusters, USc2C2 and USc2NC, are stabilized in the D5h(6)-C80 carbon cage and adopt unique trifoliate configurations, in which C2/NC units are almost vertically inserted into the plane defined by the U and two Sc atoms. Combined experimental and theoretical studies further reveal the bonding structure of USc2C2 and USc2NC, which contain C═U(VI)═C and C═U(V)═N bonding motifs. The electronic structures of the two compounds are determined as U6+(Sc2)6+(C4-)2@D5h(6)-C804- and U5+(Sc2)6+(N)3-(C)4-@D5h(6)-C804-, respectively. Quantum-chemical studies confirm that the U-C bonds in both molecules show unprecedented multicenter triple-bond character. The discovery of this unique U-C multiple bond offers a deeper understanding of the fundamentals of uranium chemistry.

Ictal EEG desynchronization during low-voltage fast activity for prediction of surgical outcomes in focal epilepsy.

OBJECTIVE: The authors investigated alterations in functional connectivity (FC) and EEG power during ictal onset patterns of low-voltage fast activity (LVFA) in drug-resistant focal epilepsy. They hypothesized that such changes would be useful to classify epilepsy surgical outcomes. METHODS: In a cohort of 79 patients with drug-resistant focal epilepsy who underwent stereoelectroencephalography (SEEG) evaluation as well as resective surgery, FC changes during the peri-LVFA period were measured using nonlinear regression (h2) and power spectral properties within/between three regions: the seizure onset zone (SOZ), early propagation zone (PZ), and noninvolved zone (NIZ). Desynchronization and power desynchronization h2 indices were calculated to assess the degree of EEG desynchronization during LVFA. Multivariate logistic regression was employed to control for confounding factors. Finally, receiver operating characteristic curves were generated to evaluate the performance of desynchronization indices in predicting surgical outcome. RESULTS: Fifty-three patients showed ictal LVFA and distinct zones of the SOZ, PZ, and NIZ. Among them, 39 patients (73.6%) achieved seizure freedom by the final follow-up. EEG desynchronization, measured by h2 analysis, was found in the seizure-free group during LVFA: FC decreased within the SOZ and between regions compared with the pre-LVFA and post-LVFA periods. In contrast, the non-seizure-free group showed no prominent EEG desynchronization. The h2 desynchronization index, but not the power desynchronization index, enabled classification of seizure-free versus non-seizure-free patients after resective surgery. CONCLUSIONS: EEG desynchronization during the peri-LVFA period, measured by within-zone and between-zone h2 analysis, may be helpful for identifying patients with favorable postsurgical outcomes and also may potentially improve epileptogenic zone identification in the future.

In Vivo Measurements of Transcranial Electrical Stimulation in Lesioned Human Brain: A Case Report.

Transcranial electrical stimulation (tES) has been utilized widely in populations with brain lesions, such as stroke patients. The tES-generated electric field (EF) within the brain is considered as one of the most important factors for physiological effects. However, it is still unclear how brain lesions may influence EF distribution induced by tES. In this case study, we reported in vivo measurements of EF in one epilepsy participant with brain lesions during different tES montages. With the in vivo EF data measured by implanted stereo-electroencephalography (sEEG) electrodes, the simulation model was investigated and validated. Our results demonstrate that the prediction ability of the current simulation model may be degraded in the lesioned human brain.

Dynamic Ensemble Bayesian Filter for Robust Control of a Human Brain-Machine Interface.

OBJECTIVE: Brain-machine interfaces (BMIs) aim to provide direct brain control of devices such as prostheses and computer cursors, which have demonstrated great potential for motor restoration. One major limitation of current BMIs lies in the unstable performance due to the variability of neural signals, especially in online control, which seriously hinders the clinical availability of BMIs. METHOD: We propose a dynamic ensemble Bayesian filter (DyEnsemble) to deal with the neural variability in online BMI control. Unlike most existing approaches using fixed models, DyEnsemble learns a pool of models that contains diverse abilities in describing the neural functions. In each time slot, it dynamically weights and assembles the models according to the neural signals in a Bayesian framework. In this way, DyEnsemble copes with variability in signals and improves the robustness of online control. RESULTS: Online BMI experiments with a human participant demonstrate that, compared with the velocity Kalman filter, DyEnsemble significantly improves the control accuracy (increases the success rate by 13.9% in the random target pursuit task) and robustness (performs more stably over different experiment days). CONCLUSION: Experimental results demonstrate the superiority of DyEnsemble in online BMI control. SIGNIFICANCE: DyEnsemble frames a novel and flexible dynamic decoding framework for robust BMIs, beneficial to various neural decoding applications.

White Matter Tracts Associated With Deep Brain Stimulation Targets in Major Depressive Disorder: A Systematic Review.

Background: Deep brain stimulation (DBS) has been proposed as a last-resort treatment for major depressive disorder (MDD) and has shown potential antidepressant effects in multiple clinical trials. However, the clinical effects of DBS for MDD are inconsistent and suboptimal, with 30-70% responder rates. The currently used DBS targets for MDD are not individualized, which may account for suboptimal effect. Objective: We aim to review and summarize currently used DBS targets for MDD and relevant diffusion tensor imaging (DTI) studies. Methods: A literature search of the currently used DBS targets for MDD, including clinical trials, case reports and anatomy, was performed. We also performed a literature search on DTI studies in MDD. Results: A total of 95 studies are eligible for our review, including 51 DBS studies, and 44 DTI studies. There are 7 brain structures targeted for MDD DBS, and 9 white matter tracts with microstructural abnormalities reported in MDD. These DBS targets modulate different brain regions implicated in distinguished dysfunctional brain circuits, consistent with DTI findings in MDD. Conclusions: In this review, we propose a taxonomy of DBS targets for MDD. These results imply that clinical characteristics and white matter tracts abnormalities may serve as valuable supplements in future personalized DBS for MDD.

Short report: surgery for implantable brain-computer interface assisted by robotic navigation system.

We present an implantable brain-computer interface surgical case assisted by robotic navigation system in an elderly patient with tetraplegia caused by cervical spinal cord injury. Left primary motor cortex was selected for implantation of microelectrode arrays based on fMRI location of motor imagery. Robotic navigation system was used during this procedure for precise and stable manipulation. A design of bipartite incision was made to reduce the risk of surgery-related infection and facilitate BCI training. At 1-year follow-up, the neural signals were robust, and this patient was able to control three-dimensional movement of a prosthetic limb without any complications.

In vivo Measurements of Electric Fields During Cranial Electrical Stimulation in the Human Brain.

Cranial electrical stimulation (CES) has been applied at various current levels in both adults and children with neurological conditions with seemingly promising but somewhat inconsistent results. Stimulation-induced spatial electric fields (EFs) within a specific brain region are likely a significant contributing factor for the biological effects. Although several simulation models have been used to predict EF distributions in the brain, these models actually have not been validated by in vivo CES-induced EF measurements in the live human brain. This study directly measured the CES-induced voltage changes with implanted stereotactic-electroencephalographic (sEEG) electrodes in twenty-one epilepsy participants (16 adults and 5 children) and then compared these measured values with the simulated ones obtained from the personalized models. In addition, we further investigated the influence of stimulation frequency, intensity, electrode montage and age on EFs in parts of participants. We found both measured voltages and EFs obtained in vivo are highly correlated with the predicted ones in our cohort (Voltages: r = 0.93, p < 0.001; EFs: r = 0.73, p < 0.001). In white matter and gray matter, the measured voltages linearly increased when the stimulation intensity increased from 5 to 500 µA but showed no significant changes (averaged coefficient of variation <4.10%) with changing stimulation frequency from 0.5 to 200 Hz. Electrode montage, but not age, significantly affects the distribution of the EFs (n = 5, p < 0.01). Our in vivo measurements demonstrate that the individualized simulation model can reliably predict the CES-induced EFs in both adults and children. It also confirms that the CES-induced EFs highly depend on the electrode montages and individual anatomical features.