AB073. Electrocorticography high-gamma dynamics during intraoperative hand movement mapping.

BACKGROUND: Intraoperative functional mapping for glioma resection often necessitates awake craniotomies, requiring active patient participation. This procedure presents challenges for both the surgical team and the patient. Thus, minimizing mapping time becomes crucial. Passive mapping utilizing electrocorticography (ECoG) presents a promising approach to reduce intraoperative mapping efforts via direct electrical stimulation. This study aims to identify an efficient mapping protocol for hand movement by optimizing mapping duration and localization accuracy. METHODS: Three glioma patients (two males, one female) underwent awake craniotomy for tumor resection at Asahikawa Medical University Hospital and Kindai University in Osaka. Patients were maintained at a bispectral index (BIS) level above 90 to ensure wakefulness during mapping. Data were collected using a DC-coupled g.HIamp biosignal amplifier, digitized with 24-bit resolution at a minimum sampling rate of 1,200 Hz. Each session comprised ten runs, each lasting 250 seconds, consisting of a 12-second rest phase (baseline) followed by a 12-second grasping period containing ten grasping movements. High-gamma activity (HGA, 60-170 Hz) was recorded from ECoG locations on the pre- and postcentral gyrus. Locations exhibiting significant grasping-related HGA, with stronger responses during early trials within a run, were classified as "attenuated". RESULTS: Among 37 electrodes on the sensorimotor cortex, 16 exhibited significant HGA during grasping. Three locations demonstrated significant attenuation after three runs, with one location showing attenuation after the first three trials within a run. CONCLUSIONS: The observed attenuation effect of short-term repeated movements during intraoperative monitoring is relatively modest initially. However, as the number of repeated grasping blocks increases, the number of attenuated locations also rises. Consequently, minimizing overall mapping time, rather than reducing the number of tasks per block, is paramount. For statistical analysis, a minimum of 20 grasping trials (two runs of ten movements) or 48 seconds of motor mapping is recommended. Alternatively, a mapping protocol involving a third run or 30 grasping trials (72 seconds) may enhance data robustness. These preliminary findings, though based on a limited patient cohort, warrant confirmation and further investigation, particularly in epilepsy patients.

Normative atlases of high-frequency oscillation and spike rates under Sevoflurane anesthesia.

OBJECTIVE: We analyzed the dose-dependent effects of Sevoflurane anesthesia on high-frequency oscillations (HFOs) and spike discharges at non-epileptic sites and evaluated their effectiveness in identifying the epileptogenic zone. METHODS: We studied 21 children with drug-resistant focal epilepsy who achieved seizure control after focal resective surgery. Open-source detectors quantified HFO and spike rates during extraoperative and intraoperative intracranial EEG recordings performed before resection. We determined under which anesthetic conditions HFO and spike rates differentiated the seizure onset zone (SOZ) within the resected area from non-epileptic sites. RESULTS: We analyzed 925 artifact-free electrodes, including 867 at non-epileptic sites and 58 at SOZ sites. Higher Sevoflurane doses significantly increased HFO and spike rates at non-epileptic sites, exhibiting spatial variability among different detectors. These biomarkers were elevated in the SOZ more than in non-epileptic sites under 2-4 vol% Sevoflurane anesthesia, with Cohen's d effect sizes above 3.0 and Mann-Whitney U-Test r effect sizes above 0.5. CONCLUSIONS: We provided normative atlases of HFO and spike rates under different Sevoflurane anesthesia conditions. Sevoflurane elevates HFO and spike rates preferentially in the epileptogenic zone. SIGNIFICANCE: Assessing the relative severity of biomarker levels across sites may be relevant for localizing the epileptogenic zone under Sevoflurane anesthesia.

Seizure outcome in surgically treated pediatric gangliogliomas and dysembryoplastic neuroepitheliomas according to imaging and resection strategies.

PURPOSE: Imaging and resection strategies for pediatric gangliogliomas (GG) and dysembryoplastic neuroepitheliomas (DNET) presenting with epilepsy were retrospectively analyzed in a consecutive institutional series of surgically treated patients. METHODS: Twenty-two children (median 8 years, 3-18 years) presented with seizures for 30 months median (14-55.2 months) due to a histologically verified GG/DNET. RESULTS: There were 20 GG and 2 DNT, 68 % located temporal, 32 % extra-temporal. Seizure history was significantly longer in temporal cases (38 versus 14 months median, p < 0.01). MRI contrast enhancement was present in 50 % and methionine (MET) positron emission tomography (PET) uptake in 70 % (standard uptake values (SUVs) 2.92 mean, from 1.6 to 6.4). 27 % had glucose PET hypometabolism. Primarily, in temporal GG, ECoG (electrocorticography) -guided lesionectomies were performed in 87 % and antero-mesial temporal lobe resections (AMTLR) in 13 %, whereas in extra-temporal GG/DNETs, lesionectomies were performed in 100 %. ILAE Class 1 seizure outcome was primarily achieved in 73 % of the temporal cases, and was increased to 93 % by performing six repeat surgeries using AMTLR. Extratemporal patients experienced ILAE Class 1 seizure outcomes in 86 % without additional surgeries, although harboring significantly more residual tumor (p < 0.005, mean follow-up 28 months). CONCLUSION: In children, MET PET imaging for suspected GG is proposed preoperatively showing a high diagnostic sensitivity and an option to delineate the lesions for navigated resection, whereas MRI contrast behavior was of no differential diagnostic use. As a surgical strategy we propose primarily lesionectomies for extratemporal but AMTLR for temporal GG respecting eloquent brain areas.

Adjuvant (chemo)radiotherapy for patients with head and neck cancer: can comorbidity risk scores predict outcome?

PURPOSE: This study compares the objective American Society of Anesthesiologists (ASA) and Adult Comorbidity Evaluation-27 (ACE-27) scores with the subjective Eastern Cooperative Oncology Group performance status (ECOG PS) for patient outcome prediction. METHODS: We retrospectively analyzed head and neck squamous cell carcinoma patients treated with adjuvant (chemo)radiotherapy at the LMU Munich from June 2008 to June 2015. The study focused on associations between patient outcomes; treatment failures; known risk factors (including human papillomavirus [HPV] status and tumor stage); and the comorbidity indices ECOG-PS, ASA score, and ACE-27. The Kaplan-Meier method and Cox proportional hazards model were used for survival analysis and identifying independent risk factors. RESULTS: A total of 302 patients were analyzed, 175 received concurrent chemotherapy. Median follow-up was 61.8 months, and median age at diagnosis was 61 years. The 3­ and 5­year overall survival (OS) and disease-free survival (DFS) rates were 70.5%/60.2% and 64.7%/57.6%, respectively. Both ACE-27 and ASA showed significant correlations with OS in univariate and multivariate analyses, while ECOG-PS was significant only in univariate analysis. ASA and ACE-27 scores were also significantly correlated with local and locoregional recurrence, but only HPV status and tumor stage were significant in multivariate models. CONCLUSION: ACE-27 and ASA score effectively categorize patients' risks in adjuvant radiotherapy for head and neck cancer, proving more predictive of overall survival than ECOG-PS. These results underscore the importance of objective comorbidity assessment and suggest further prospective studies.

Novel cyclic homogeneous oscillation detection method for high accuracy and specific characterization of neural dynamics.

Determining the presence and frequency of neural oscillations is essential to understanding dynamic brain function. Traditional methods that detect peaks over 1/f noise within the power spectrum fail to distinguish between the fundamental frequency and harmonics of often highly non-sinusoidal neural oscillations. To overcome this limitation, we define fundamental criteria that characterize neural oscillations and introduce the cyclic homogeneous oscillation (CHO) detection method. We implemented these criteria based on an autocorrelation approach to determine an oscillation's fundamental frequency. We evaluated CHO by verifying its performance on simulated non-sinusoidal oscillatory bursts and validated its ability to determine the fundamental frequency of neural oscillations in electrocorticographic (ECoG), electroencephalographic (EEG), and stereoelectroencephalographic (SEEG) signals recorded from 27 human subjects. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method's specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.

Auditory cortex encodes lipreading information through spatially distributed activity.

Watching a speaker's face improves speech perception accuracy. This benefit is enabled, in part, by implicit lipreading abilities present in the general population. While it is established that lipreading can alter the perception of a heard word, it is unknown how these visual signals are represented in the auditory system or how they interact with auditory speech representations. One influential, but untested, hypothesis is that visual speech modulates the population-coded representations of phonetic and phonemic features in the auditory system. This model is largely supported by data showing that silent lipreading evokes activity in the auditory cortex, but these activations could alternatively reflect general effects of arousal or attention or the encoding of non-linguistic features such as visual timing information. This gap limits our understanding of how vision supports speech perception. To test the hypothesis that the auditory system encodes visual speech information, we acquired functional magnetic resonance imaging (fMRI) data from healthy adults and intracranial recordings from electrodes implanted in patients with epilepsy during auditory and visual speech perception tasks. Across both datasets, linear classifiers successfully decoded the identity of silently lipread words using the spatial pattern of auditory cortex responses. Examining the time course of classification using intracranial recordings, lipread words were classified at earlier time points relative to heard words, suggesting a predictive mechanism for facilitating speech. These results support a model in which the auditory system combines the joint neural distributions evoked by heard and lipread words to generate a more precise estimate of what was said.

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations.

Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.

Short- and Long-Term Prognosis in Hemodynamically Stable Pulmonary Embolism With Unresectable or Metastatic Malignancies: The Role of Performance Status.

BACKGROUND: The simplified Pulmonary Embolism Severity Index (sPESI) has limitations when evaluating acute pulmonary embolism (PE) in patients with concurrent malignancy. Despite its utility in predicting outcomes among cancer patients, the role of the Eastern Cooperative Oncology Group Performance Status (ECOG PS) in acute PE remains underexplored. This study aims to assess the prognostic significance of ECOG PS ≥ 3 on short- and long-term mortality in acute PE with malignancy, correlating it with the sPESI. METHODS AND RESULTS: We retrospectively analyzed 44 hemodynamically stable acute PE patients with unresectable or metastatic malignancies ineligible for curative treatment at Kameda Medical Center, a tertiary medical facility in Japan, from April 1, 2019, to March 2, 2023. Of these patients, 16 (36.4%) had ECOG PS ≥ 3. No 30-day mortality occurred in patients with ECOG PS ≤ 2, compared to 18.8% in those with ECOG PS ≥ 3 (p = 0.04). Groups were similar in the sPESI scores, hospital-onset PE proportion, and initial treatments. Post PE diagnosis, 92.9% of ECOG PS ≤ 2 patients and 50% of ECOG PS ≥ 3 patients received chemotherapy (p = 0.002). Cox regression analysis revealed ECOG PS ≥ 3 was independently associated with increased overall survival hazard (adjusted HR = 4.0; P = 0.002). CONCLUSIONS: ECOG PS ≥ 3 suggests a poorer short-term prognosis and independently predicts a worse long-term prognosis in hemodynamically stable acute PE patients with advanced malignancies.

Induction chemotherapy backbone in frail patients with advanced NSCLC treated with chemotherapy plus pembrolizumab: a single institution retrospective audit of dose intensities from modified regimens.

Guidelines historically recommended mono-chemotherapy for the 1st line treatment of elderly patients with non-small cell lung cancer (NSCLC) and poor performance status (PS). Nowadays, there is no clear indication whether chemo-immunotherapy (chemo-IO) combinations can be effectively delivered in this population. We collected induction chemotherapy data in consecutive patients with advanced NSCLC treated with carboplatin-based chemotherapy regimens plus pembrolizumab, to compute the received dose intensity (RDI) from standard regimens or patient-tailored regimens modified due to age, comorbidities and PS. Comorbidities were stratified according to the comorbidity-polypharmacy score (CPS). The established cut-off of ≥85% for RDI was used to define adequate delivery. 116 pts were treated from Feb-20 to July-23, of whom 96 and 20 with non-squamous and squamous NSCLC, treated with carboplatin-pemetrexed or carboplatin-paclitaxel doublets plus pembrolizumab, respectively. The majority of patients were aged ≥ 70 years (52.6%), the median CPS was 5, with 58.6% having a CPS ≥5, whilst 47.4%, 44.8% and 7.8% had an Eastern Cooperative Oncology Group (ECOG) - PS of 0, 1 and 2, respectively. PD-L1 TPS were <1% in 31.9% and 1-49% in 65.4%. Overall, 47.4% received a priori modified regimens due to poor PS, age, or comorbidities. Among patients with non-squamous NSCLC, median received doses of carboplatin and pemetrexed were 1.37 AUC/week and 138.8 mg/m2/week, with RDIs of 86% and 75% (p < 0.01) for patients treated with standard or modified regimens, respectively. Of note, the RDI was 57.9% among patients with ECOG-PS 2. However, patients treated with modified regimens experienced similar toxicities as those treated with standard regimens, despite being older (p < 0.01), with higher PS (p < 0.01) and more comorbid (p = 0.03). Patients treated with modified regimens achieved a shorter survival (7.1 vs 13.9 months), which is comparable to IO-free historical controls. Among patients with squamous NSCLC, 90% received modified regimens upfront, with median received doses of carboplatin and paclitaxel of 1.19 AUC/week and 40 mg/m2/week, and an overall RDI of 73.5%. Although regimen modifications ensure a safe administration of chemotherapy plus pembrolizumab in frail patients, the RDI seems to be subtherapeutic, especially in those with squamous histology. Dedicated trials are needed to implement combination strategies in this population.

Prospects of Electrocorticography in Neuropharmacological Studies in Small Laboratory Animals.

Electrophysiological methods of research are widely used in neurobiology. To assess the bioelectrical activity of the brain in small laboratory animals, electrocorticography (ECoG) is most often used, which allows the recording of signals directly from the cerebral cortex. To date, a number of methodological approaches to the manufacture and implantation of ECoG electrodes have been proposed, the complexity of which is determined by experimental tasks and logistical capabilities. Existing methods for analyzing bioelectrical signals are used to assess the functional state of the nervous system in test animals, as well as to identify correlates of pathological changes or pharmacological effects. The review presents current areas of applications of ECoG in neuropharmacological studies in small laboratory animals. Traditionally, this method is actively used to study the antiepileptic activity of new molecules. However, the possibility of using ECoG to assess the neuroprotective activity of drugs in models of traumatic, vascular, metabolic, or neurodegenerative CNS damage remains clearly underestimated. Despite the fact that ECoG has a number of disadvantages and methodological difficulties, the recorded data can be a useful addition to traditional molecular and behavioral research methods. An analysis of the works in recent years indicates a growing interest in the method as a tool for assessing the pharmacological activity of psychoactive drugs, especially in combination with classification and prediction algorithms.

A Polymer Thick Film on an Organic Substrate Grid Electrode and an Open-Source Recording System for UHF MRI: An Imaging Study.

Electrocorticography (ECoG) is a critical tool in preclinical neuroscience research for studying global network activity. However, integrating ECoG with functional magnetic resonance imaging (fMRI) has posed challenges, due to metal electrode interference with imaging quality and heating around the metallic electrodes. Here, we introduce recent advancements in ECoG grid development that utilize a polymer-thick film on an organic substrate (PTFOS). PTFOS offers notable advantages over traditional ECoG grids. Firstly, it significantly reduces imaging artifacts, ensuring minimal interference with MR image quality when overlaying brain tissue with PTFOS grids. Secondly, during a 30-min fMRI acquisition, the temperature increase associated with PTFOS grids is remarkably low, measuring only 0.4 °C. These findings suggest that utilizing ECoG with PTFOS grids has the potential to enhance the safety and efficacy of neurosurgical procedures. By providing clearer imaging results and mitigating risk factors such as excessive heating during MRI scans, PTFOS-based ECoG grids represent a promising advancement in neurosurgical technology. Furthermore, we describe a cutting-edge open-source system designed for simultaneous electrophysiology and fMRI. This system stands out due to its exceptionally low input noise levels (<0.6 V peak-to-peak), robust electromagnetic compatibility (it is suitable for use in MRI environments up to 9.4 teslas), and the inclusion of user-programmable real-time signal-processing capabilities. The open-platform software is a key feature, enabling researchers to swiftly implement and customize real-time signal-processing algorithms to meet specific experimental needs. This innovative system has been successfully utilized in several rodent EEG/fMRI studies, particularly at magnetic field strengths of 4.7 and 9.4 teslas, focusing on the somatosensory system. These studies have allowed for detailed observation of neural activity and responses within this sensory system, providing insights that are critical for advancing our understanding of neurophysiological processes. The versatility and high performance of our system make it an invaluable tool for researchers aiming to integrate and analyze complex datasets from advanced imaging and electrophysiological recordings, ultimately enhancing the depth and scope of neuroscience research.

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction. NEW METHOD: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories. RESULTS: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control. COMPARISON WITH EXISTING METHODS: The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models. CONCLUSIONS: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control.

A low-activity cortical network selectively encodes syntax.

Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

Evoking artificial speech perception through invasive brain stimulation for brain-computer interfaces: current challenges and future perspectives.

Encoding artificial perceptions through brain stimulation, especially that of higher cognitive functions such as speech perception, is one of the most formidable challenges in brain-computer interfaces (BCI). Brain stimulation has been used for functional mapping in clinical practices for the last 70 years to treat various disorders affecting the nervous system, including epilepsy, Parkinson's disease, essential tremors, and dystonia. Recently, direct electrical stimulation has been used to evoke various forms of perception in humans, ranging from sensorimotor, auditory, and visual to speech cognition. Successfully evoking and fine-tuning artificial perceptions could revolutionize communication for individuals with speech disorders and significantly enhance the capabilities of brain-computer interface technologies. However, despite the extensive literature on encoding various perceptions and the rising popularity of speech BCIs, inducing artificial speech perception is still largely unexplored, and its potential has yet to be determined. In this paper, we examine the various stimulation techniques used to evoke complex percepts and the target brain areas for the input of speech-like information. Finally, we discuss strategies to address the challenges of speech encoding and discuss the prospects of these approaches.

Consistent spectro-spatial features of human ECoG successfully decode naturalistic behavioral states.

Objective: Understanding the neural correlates of naturalistic behavior is critical for extending and confirming the results obtained from trial-based experiments and designing generalizable brain-computer interfaces that can operate outside laboratory environments. In this study, we aimed to pinpoint consistent spectro-spatial features of neural activity in humans that can discriminate between naturalistic behavioral states. Approach: We analyzed data from five participants using electrocorticography (ECoG) with broad spatial coverage. Spontaneous and naturalistic behaviors such as "Talking" and "Watching TV" were labeled from manually annotated videos. Linear discriminant analysis (LDA) was used to classify the two behavioral states. The parameters learned from the LDA were then used to determine whether the neural signatures driving classification performance are consistent across the participants. Main results: Spectro-spatial feature values were consistently discriminative between the two labeled behavioral states across participants. Mainly, θ, α, and low and high γ in the postcentral gyrus, precentral gyrus, and temporal lobe showed significant classification performance and feature consistency across participants. Subject-specific performance exceeded 70%. Combining neural activity from multiple cortical regions generally does not improve decoding performance, suggesting that information regarding the behavioral state is non-additive as a function of the cortical region. Significance: To the best of our knowledge, this is the first attempt to identify specific spectro-spatial neural correlates that consistently decode naturalistic and active behavioral states. The aim of this work is to serve as an initial starting point for developing brain-computer interfaces that can be generalized in a realistic setting and to further our understanding of the neural correlates of naturalistic behavior in humans.

Increasing serum complement component 1q is associated with worse prognosis in advanced non-small cell lung cancer treated with immune checkpoint inhibitors: a single-center, retrospective study.

Background: There is a lack of readily available clinical markers of non-small cell lung cancer (NSCLC) immunotherapy efficacy. Previous studies have found that overexpressed complement component 1q (C1q) promotes macrophage M2 polarization and an immunosuppressive tumor microenvironment. This study aimed to evaluate the association between serum C1q and the efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced NSCLC. Methods: A total of 168 patients with advanced NSCLC who received ICIs in the Renmin Hospital of Wuhan University were included in this study. Serum C1q levels were collected before and 3 weeks after immunotherapy treatment, together with other data on clinical and demographic characteristics. The primary outcome was overall survival (OS) (months from first dose of ICIs to death, censored at date of last follow-up). Secondary outcome was progression-free survival (PFS) [defined as months from first dose of ICIs to clinical or radiographic progression by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) or death, censored at date of last follow-up] and objective response rate (ORR) which was defined as rate of complete response (CR) or partial response (PR) at best response by RECIST 1.1. Results: A total of 168 patients were included in this study, including 127 males (75.60%) and 41 females (24.40%). Thirty-nine patients achieved objective response (2 CR, 37 PR), and 111 patients (66.07%) had stable disease (SD) as best response. The ORR was 23.21% and the disease control rate was 89.28%. The upward trends of serum C1q levels between baseline and post-treatment were strongly associated with the shorter PFS [hazard ratio (HR) =1.554, 95% confidence interval (CI): 1.07-2.10, P=0.01] and OS (HR =1.444, 95% CI: 1.01-1.98, P=0.03). Moreover, taking the median OS 18.9 months as the cut-off of prognosis, receiver operating characteristic (ROC) analysis showed that serum baseline C1q yielded an area under the ROC curve of 0.785 (95% CI: 0.711-0.869). The optimal serum baseline C1q cut-off point to predict immunotherapy prognosis was 216.2 mg/L. Conclusions: These findings suggested that elevated serum C1q after ICIs treatment was related to a worse prognosis in NSCLC. Monitoring the baseline and dynamic data of C1q during hospitalization showed the potential to predict the prognosis of NSCLC patients.

Dependence of rhythmic activity and oddball effects in the rat cortex on the depth of sedation during dissociative anesthesia.

The reactions to novelty manifesting in mismatch negativity in the rat brain were studied. During dissociative anesthesia, mismatch negativity-like waves were recorded from the somatosensory cortex using an epidural 32-electrode array. Experimental animals: 7 wild-type Wistar rats and 3 transgenic rats. During high-dose anesthesia, deviant 1,500 Hz tones were presented randomly among many standard 1,000 Hz tones in the oddball paradigm. "Deviant minus standard_before_deviant" difference waves were calculated using both the classical method of Naatanen and method of cross-correlation of sub-averages. Both methods gave consistent results: an early phasic component of the N40 and later N100 to 200 (mismatch negativity itself) tonic component. The gamma and delta rhythms power and the frequency of down-states (suppressed activity periods) were assessed. In all rats, the amplitude of tonic component grew with increasing sedation depth. At the same time, a decrease in gamma power with a simultaneous increase in delta power and the frequency of down-states. The earlier phasic frontocentral component is associated with deviance detection, while the later tonic one over the auditory cortex reflects the orienting reaction. Under anesthesia, this slow mismatch negativity-like wave most likely reflects the tendency of the system to respond to any influences with delta waves, K-complexes and down-states, or produce them spontaneously.

Stability of ECoG high gamma signals during speech and implications for a speech BCI system in an individual with ALS: a year-long longitudinal study.

Objective.Speech brain-computer interfaces (BCIs) have the potential to augment communication in individuals with impaired speech due to muscle weakness, for example in amyotrophic lateral sclerosis (ALS) and other neurological disorders. However, to achieve long-term, reliable use of a speech BCI, it is essential for speech-related neural signal changes to be stable over long periods of time. Here we study, for the first time, the stability of speech-related electrocorticographic (ECoG) signals recorded from a chronically implanted ECoG BCI over a 12 month period.Approach.ECoG signals were recorded by an ECoG array implanted over the ventral sensorimotor cortex in a clinical trial participant with ALS. Because ECoG-based speech decoding has most often relied on broadband high gamma (HG) signal changes relative to baseline (non-speech) conditions, we studied longitudinal changes of HG band power at baseline and during speech, and we compared these with residual high frequency noise levels at baseline. Stability was further assessed by longitudinal measurements of signal-to-noise ratio, activation ratio, and peak speech-related HG response magnitude (HG response peaks). Lastly, we analyzed the stability of the event-related HG power changes (HG responses) for individual syllables at each electrode.Main Results.We found that speech-related ECoG signal responses were stable over a range of syllables activating different articulators for the first year after implantation.Significance.Together, our results indicate that ECoG can be a stable recording modality for long-term speech BCI systems for those living with severe paralysis.Clinical Trial Information.ClinicalTrials.gov, registration number NCT03567213.

Bellmunt risk score as a survival predictor in patients with metastatic castration-resistant prostate cancer.

BACKGROUND: The prognosis of metastatic castration-resistant prostate cancer (mCRPC) is influenced by numerous individual factors. Despite various proposed prognostic models, the clinical application of these remains limited, probably due to complexity. Our study aimed to evaluate the predictive value of the Bellmunt risk score, which is well-known for urothelial carcinoma and easily assessed, in mCRPC patients. METHODS: The Bellmunt risk score was calculated from three risk factors (Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥1, serum hemoglobin <10 g/dL, presence of liver metastases) in 125 patients who received first-line mCRPC treatment between 2005 and 2023. In addition, a modified score was established (one point each for hemoglobin <10 g/dL and the presence of liver metastases added to the ECOG PS). Associations with overall survival (OS) under first- and second-line therapy were tested using Cox regression analyzes, log-rank tests, concordance index (C-index) and time-dependent receiver operating characteristic. RESULTS: There is a significant correlation between the level of the Bellmunt risk score and shorter OS (hazard ratio: 3.23, 95% confidence interval: 2.06-5.05; log-rank p < 0.001; C-index: 0.724). The semi-quantitative modified risk score showed even better prognostic discrimination (log-rank p < 0.001, C-index: 0.764). The score and its dynamics were also predictive in the second-line setting (log-rank p < 0.001 and = 0.01; C-index: 0.742 and 0.595). CONCLUSIONS: The Bellmunt risk score is easy to assess and provides useful prognostic information in mCRPC, and can support physicians in their treatment decisions.