FLUXestimator: a webserver for predicting metabolic flux and variations using transcriptomics data.

Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, laboratory-based single cell fluxomics is currently impractical, and the current computational tools for flux estimation are not designed for single cell-level prediction. Given the well-established link between transcriptomic and metabolomic profiles, leveraging single cell transcriptomics data to predict single cell fluxome is not only feasible but also an urgent task. In this study, we present FLUXestimator, an online platform for predicting metabolic fluxome and variations using single cell or general transcriptomics data of large sample-size. The FLUXestimator webserver implements a recently developed unsupervised approach called single cell flux estimation analysis (scFEA), which uses a new neural network architecture to estimate reaction rates from transcriptomics data. To the best of our knowledge, FLUXestimator is the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data of human, mouse and 15 other common experimental organisms. The FLUXestimator webserver is available at http://scFLUX.org/, and stand-alone tools for local use are available at https://github.com/changwn/scFEA. Our tool provides a new avenue for studying metabolic heterogeneity in diseases and has the potential to facilitate the development of new therapeutic strategies.

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning.

A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features that mediate functions of these regions, such as short motifs, amino acid repeats and physicochemical properties. Here, we introduce a proteome-scale feature discovery approach for IDRs. Our approach, which we call "reverse homology", exploits the principle that important functional features are conserved over evolution. We use this as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a held-out homolog from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and standard interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, or bulk features like charge or amino acid propensities. We also show that our model can be used to produce visualizations of what residues and regions are most important to IDR function, generating hypotheses for uncharacterized IDRs. Our results suggest that feature discovery using unsupervised neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences.

C2 translaminar screw fixation in pediatric occipitocervical fusion.

PURPOSE: Rigid occipitocervical (O-C) instrumentation can reduce the anterior pathology and has a high fusion rate in children with craniovertebral instability. Typically, axis (C2) screw fixation utilizes C1-C2 transarticular screws or C2 pars screws. However, anatomic variation may preclude these screw types due to the size of fixation elements or by placing the vertebral artery at risk for injury. Pediatric C2 translaminar screw fixation has low risk of vertebral artery injury and may be used when the anatomy is otherwise unsuitable for C1-C2 transarticular screws or C2 pars screws. METHODS: We retrospectively reviewed a neurosurgical database at UCSF Benioff Children's Hospital Oakland for patients who had undergone a cervical spinal fusion that utilized translaminar screws for occipitocervical instrumentation between 2002 and 2020. We then reviewed the operative records to determine the parameters of C2 screw fixations performed. Demographic and all other relevant clinical data were then recorded. RESULTS: Twenty-five patients ranging from 2 to 18 years of age underwent O-C fusion, with a total of 43 translaminar screws at C2 placed. Twenty-three patients were fused (92%) after initial surgery with a mean follow-up of 43 months. Two patients, both with Down syndrome, had a nonunion. Another 2 patients had a superficial wound dehiscence that required wound revision. One patient died of unknown cause 7 months after surgery. One patient developed an adjacent-level kyphosis. CONCLUSION: When performing occipitocervical instrumentation in the pediatric population, C2 translaminar screw fixation is an effective option to other methods of C2 screw fixation dependent on anatomic feasibility.

Updated SARS-CoV-2 single nucleotide variants and mortality association.

By analyzing newly collected SARS-CoV-2 genomes and comparing them with our previous study about SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found that the SNV clustering had changed remarkably since June 2020. Apart from that the group of SNVs became dominant, which is represented by two nonsynonymous mutations A23403G (S:D614G) and C14408T (ORF1ab:P4715L), a few emerging groups of SNVs were recognized with sharply increased monthly incidence ratios of up to 70% in November 2020. Further investigation revealed sets of SNVs specific to patients' ages and/or gender, or strongly associated with mortality. Our logistic regression model explored features contributing to mortality status, including three critical SNVs, G25088T(S:V1176F), T27484C (ORF7a:L31L), and T25A (upstream of ORF1ab), ages above 40 years old, and the male gender. The protein structure analysis indicated that the emerging subgroups of nonsynonymous SNVs and the mortality-related ones were located on the protein surface area. The clashes in protein structure introduced by these mutations might in turn affect the viral pathogenesis through the alteration of protein conformation, leading to a difference in transmission and virulence. Particularly, we explored the fact that nonsynonymous SNVs tended to occur in intrinsic disordered regions of Spike and ORF1ab to significantly increase hydrophobicity, suggesting a potential role in the change of protein folding related to immune evasion.

Single versus dual operative spine fractures in ankylosing spondylitis.

OBJECTIVE: Ankylosing spondylitis, the most common spondyloarthritis, fuses individual spinal vertebrae into long segments. The unique biomechanics of the ankylosed spine places patients at unusually high risk for unstable fractures secondary to low-impact mechanisms. These injuries are unique within the spine trauma population and necessitate thoughtful management. Therefore, the authors aimed to present a richly annotated data set of operative AS spine fractures with a significant portion of patients with simultaneous dual noncontiguous fractures. METHODS: Patients with ankylosing spondylitis with acute fractures who received operative management between 2012 and 2020 were reviewed. Demographic, admission, surgical, and outcome parameters were retrospectively collected and reviewed. RESULTS: In total, 29 patients were identified across 30 different admissions. At admission, the mean age was 71.7 ± 11.8 years. The mechanism of injury in 77% of the admissions was a ground-level fall; 30% also presented with polytrauma. Of admissions, 50% were patient transfers from outside hospitals, whereas the other half presented primarily to our emergency departments. Fifty percent of patients sustained a spinal cord injury, and 35 operative fractures were identified and treated in 32 surgeries. The majority of fractures clustered around the cervicothoracic (C4-T1, 48.6%) and thoracolumbar (T8-L3, 37.11%) junctions. Five patients (17.2%) had simultaneous dual noncontiguous operative fractures; these patients were more likely to have presented with a higher-energy mechanism of injury such as a bicycle or motor vehicle accident compared with patients with a single operative fracture (60% vs 8%, p = 0.024). On preoperative MRI, 56.3% of the fractures had epidural hematomas (EDHs); 25% were compressive of the underlying neural elements, which dictated the number of laminectomy levels performed (no EDH, 2.1 ± 2.36; noncompressive EDH, 2.1 ± 1.85; and compressive EDH, 7.4 ± 4 [p = 0.003]). The mean difference in instrumented levels was 8.7 ± 2.6 with a mean estimated blood loss (EBL) of 1183 ± 1779.5 mL. Patients on a regimen of antiplatelet therapy had a significantly higher EBL (2635.7 mL vs 759.4 mL, p = 0.015). Overall, patients had a mean hospital length of stay of 15.2 ± 18.5 days; 5 patients died during the same admission or after transfer to an outside hospital. Nine of 29 patients (31%) had died by the last follow-up (the mean follow-up was 596.3 ± 878.9 days). CONCLUSIONS: Patients with AS who have been found to have unstable spine fractures warrant a thorough diagnostic evaluation to identify secondary fractures as well as compressive EDHs. These patients experienced prolonged inpatient hospitalizations with significant morbidity and mortality.

Multiple Tumor-Associated Intracranial Aneurysms Adjacent to a Suprasellar Germ Cell Tumor: Case Report and Review of Literature.

INTRODUCTION: Tumor-associated intracranial aneurysms are rare and not well understood. CASE PRESENTATION: We describe a 4-year-old female with multiple intracranial aneurysms intimately associated with a suprasellar germ cell tumor (GCT). We provide the clinical history, medical, and surgical treatment course, as well as a comprehensive and concise synthesis of the literature on tumor-associated aneurysms. DISCUSSION: We discuss mechanisms for aneurysm formation with relevance to the current case, including cellular and paracrine signaling pertinent to suprasellar GCTs and possible molecular pathways involved. We review the complex multidisciplinary treatment required for complex tumor and cerebrovascular interactions.

YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells.

SUMMARY: We introduce YeastSpotter, a web application for the segmentation of yeast microscopy images into single cells. YeastSpotter is user-friendly and generalizable, reducing the computational expertise required for this critical preprocessing step in many image analysis pipelines. AVAILABILITY AND IMPLEMENTATION: YeastSpotter is available at http://yeastspotter.csb.utoronto.ca/. Code is available at https://github.com/alexxijielu/yeast_segmentation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Application of droplet digital PCR for the detection of vector copy number in clinical CAR/TCR T cell products.

BACKGROUND: Genetically engineered T cells have become an important therapy for B-cell malignancies. Measuring the efficiency of vector integration into the T cell genome is important for assessing the potency and safety of these cancer immunotherapies. METHODS: A digital droplet polymerase chain reaction (ddPCR) assay was developed and evaluated for assessing the average number of lenti- and retroviral vectors integrated into Chimeric Antigen Receptor (CAR) and T Cell Receptor (TCR)-engineered T cells. RESULTS: The ddPCR assay consistently measured the concentration of an empty vector in solution and the average number of CAR and TCR vectors integrated into T cell populations. There was a linear relationship between the average vector copy number per cell measured by ddPCR and the proportion of cells transduced as measured by flow cytometry. Similar vector copy number measurements were obtained by different staff using the ddPCR assay, highlighting the assays reproducibility among technicians. Analysis of fresh and cryopreserved CAR T and TCR engineered T cells yielded similar results. CONCLUSIONS: ddPCR is a robust tool for accurate quantitation of average vector copy number in CAR and TCR engineered T cells. The assay is also applicable to other types of genetically engineered cells including Natural Killer cells and hematopoietic stem cells.

Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting.

Cellular microscopy images contain rich insights about biology. To extract this information, researchers use features, or measurements of the patterns of interest in the images. Here, we introduce a convolutional neural network (CNN) to automatically design features for fluorescence microscopy. We use a self-supervised method to learn feature representations of single cells in microscopy images without labelled training data. We train CNNs on a simple task that leverages the inherent structure of microscopy images and controls for variation in cell morphology and imaging: given one cell from an image, the CNN is asked to predict the fluorescence pattern in a second different cell from the same image. We show that our method learns high-quality features that describe protein expression patterns in single cells both yeast and human microscopy datasets. Moreover, we demonstrate that our features are useful for exploratory biological analysis, by capturing high-resolution cellular components in a proteome-wide cluster analysis of human proteins, and by quantifying multi-localized proteins and single-cell variability. We believe paired cell inpainting is a generalizable method to obtain feature representations of single cells in multichannel microscopy images.

Cost determinants in management of brain arteriovenous malformations.

INTRODUCTION: There is little data on the cost of treating brain arteriovenous malformations (AVMs). The goal of this study then is to identify cost determinants in multimodal management of brain AVMs. METHODS: One hundred forty patients with brain AVMs prospectively enrolled in the UCSF brain AVM registry and treated between 2012 and 2015 were included in the study. Patient and AVM characteristics, treatment type, and length of stay and radiographic evidence of obliteration were collected from the registry. We then calculated the cost of all inpatient and outpatient encounters, interventions, and imaging attributable to the AVM. We used generalized linear models to test whether there was an association between patient and AVM characteristics, treatment type, and cost and length of stay. We tested whether the proportion of patients with radiographic evidence of obliteration differed between treatment modalities using Fisher's exact test. RESULTS: The overall median cost of treatment and interquartile range was $77,865 (49,566-107,448). Surgery with preoperative embolization was the costliest treatment at $91,948 (79,914-140,600), while radiosurgery was the least at $20,917 (13,915-35,583). In multi-predictor analyses, hemorrhage, Spetzler-Martin grade, and treatment type were significant predictors of cost. Patients who had surgery had significantly higher rates of obliteration compared with radiosurgery patients. CONCLUSIONS: Hemorrhage, AVM grade, and treatment modality are significant cost determinants in AVM management. Surgery with preoperative embolization was the costliest treatment and radiosurgery the least; however, surgical cases had significantly higher rates of obliteration.

National trends in cerebral bypass surgery in the United States, 2002-2014.

OBJECTIVECerebral bypass procedures are microsurgical techniques to augment or restore cerebral blood flow when treating a number of brain vascular diseases including moyamoya disease, occlusive vascular disease, and cerebral aneurysms. With advances in endovascular therapy and evolving evidence-based guidelines, it has been suggested that cerebral bypass procedures are in a state of decline. Here, the authors characterize the national trends in cerebral bypass surgery in the United States from 2002 to 2014.METHODSUsing the National (Nationwide) Inpatient Sample, the authors extracted for analysis the data on all adult patients who had undergone cerebral bypass as indicated by ICD-9-CM procedure code 34.28. Indications for bypass procedures, patient demographics, healthcare costs, and regional variations are described. Results were stratified by indication for cerebral bypass including moyamoya disease, occlusive vascular disease, and cerebral aneurysms. Predictors of inpatient complications and death were evaluated using multivariable logistic regression analysis.RESULTSFrom 2002 to 2014, there was an increase in the annual number of cerebral bypass surgeries performed in the United States. This increase reflected a growth in the number of cerebral bypass procedures performed for adult moyamoya disease, whereas cases performed for occlusive vascular disease or cerebral aneurysms declined. Inpatient complication rates for cerebral bypass performed for moyamoya disease, vascular occlusive disease, and cerebral aneurysm were 13.2%, 25.1%, and 56.3%, respectively. Rates of iatrogenic stroke ranged from 3.8% to 20.4%, and mortality rates were 0.3%, 1.4%, and 7.8% for moyamoya disease, occlusive vascular disease, and cerebral aneurysms, respectively. Multivariate logistic regression confirmed that cerebral bypass for vascular occlusive disease or cerebral aneurysm is a statistically significant predictor of inpatient complications and death. Mean healthcare costs of cerebral bypass remained unchanged from 2002 to 20014 and varied with treatment indication: moyamoya disease $38,406 ± $483, vascular occlusive disease $46,618 ± $774, and aneurysm $111,753 ± $2381.CONCLUSIONSThe number of cerebral bypass surgeries performed for adult revascularization has increased in the United States from 2002 to 2014. Rising rates of surgical bypass reflect a greater proportion of surgeries performed for moyamoya disease, whereas bypasses performed for vascular occlusive disease and aneurysms are decreasing. Despite evolving indications, cerebral bypass remains an important surgical tool in the modern endovascular era and may be increasing in use. Stagnant complication rates highlight the need for continued interest in advancing available bypass techniques or technologies to improve patient outcomes.

Cerebrospinal fluid untargeted metabolomic profiling of aneurysmal subarachnoid hemorrhage: an exploratory study.

INTRODUCTION: Despite advancements in medical and surgical therapies, clinical outcomes of aneurysmal subarachnoid hemorrhage (aSAH) continue to be poor. Currently, aSAH pathophysiology remains poorly understood. No aSAH biomarkers are commonly used in the clinical setting. This exploratory study used metabolomics profiling to identify global metabolic changes and metabolite predictors of long-term outcome using cerebrospinal fluid (CSF) samples of aSAH patients. METHODS AND METHODS: Gas chromatography time-of-flight mass spectrometry was applied to CSF samples collected from 15 consecutive high-grade aSAH patients (modified Fisher grade 3 or 4). Collected CSF samples were analyzed at two time points (admission and the anticipated vasospasm timeframe). Metabolite levels at both time points were compared and correlated with vasospasm status and Glasgow Outcome Scale (GOS) of patients at 1 year post-aSAH. Significance level was defined as p < 0.05 with false discovery rate correction for multiple comparisons. RESULTS: Of 97 metabolites identified, 16 metabolites, primarily free amino acids, significantly changed between the two time points. These changes were magnified in modified Fisher grade 4 compared with grade 3. Six metabolites (2-hydroxyglutarate, tryptophan, glycine, proline, isoleucine, and alanine) correlated with GOS at 1 year post-aSAH independent of vasospasm status. When predicting patients who had low disability (GOS 5 vs. GOS ≤4), 2-hydroxyglutarate had a sensitivity and specificity of 0.89 and 0.83 respectively. CONCLUSIONS: Our preliminary study suggests that specific metabolite changes occur in the brain during the course of aSAH and that quantification of specific CSF metabolites may be used to predict long-term outcome in patients with aSAH. This is the first study to implicate 2-hydroxyglutarate, a known marker of tissue hypoxia, in aSAH pathogenesis.

Angiopoietin-like 4 promotes angiogenesis in the tendon and is increased in cyclically loaded tendon fibroblasts.

KEY POINTS: Angiopoietin-like 4 (ANGPTL4) modulates tendon neovascularization. Cyclic loading stimulates the activity of transforming growth factor-ß and hypoxia-inducible factor 1α and thereby increases the expression and release of ANGPTL4 from human tendon cells. Targeting ANGPTL4 and its regulatory pathways is a potential avenue for regulating tendon vascularization to improve tendon healing or adaptation. ABSTRACT: The mechanisms that regulate angiogenic activity in injured or mechanically loaded tendons are poorly understood. The present study examined the potential role of angiopoietin-like 4 (ANGPTL4) in the angiogenic response of tendons subjected to repetitive mechanical loading or injury. Cyclic stretching of human tendon fibroblasts stimulated the expression and release of ANGPTL4 protein via transforming growth factor-ß (TGF-ß) and hypoxia-inducible factor 1α (HIF-1α) signalling, and the released ANGPTL4 was pro-angiogenic. Angiogenic activity was increased following ANGPTL4 injection into mouse patellar tendons, whereas the patellar tendons of ANGPTL4 knockout mice displayed reduced angiogenesis following injury. In human rotator cuff tendons, the expression of ANGPTL4 was correlated with the density of tendon endothelial cells. To our knowledge, this is the first study characterizing a role of ANGPTL4 in the tendon. ANGPTL4 may assist in the regulation of vascularity in the injured or mechanically loaded tendon. TGF-ß and HIF-1α comprise two signalling pathways that modulate the expression of ANGPTL4 by mechanically stimulated tendon fibroblasts and, in the future, these could be manipulated to influence tendon healing or adaptation.

Enhanced collagen type I synthesis by human tenocytes subjected to periodic in vitro mechanical stimulation.

BACKGROUND: Mechanical stimulation (e.g. slow heavy loading) has proven beneficial in the rehabilitation of chronic tendinopathy, however the optimal parameters of stimulation have not been experimentally determined. In this study of mechanically stimulated human tenocytes, the influence of rest insertion and cycle number on (1) the protein and mRNA levels of type I and III collagen; (2) the mRNA levels of transforming growth factor beta (TGFB1) and scleraxis (SCXA); and (3) tenocyte morphology, were assessed. METHODS: Human hamstring tenocytes were mechanically stimulated using a Flexcell® system. The stimulation regimens were 1) continuous and 2) rest-inserted cyclic equiaxial strain at a frequency of 0.1 Hz for 100 or 1000 cycles. Data were normalized to unstimulated (non-stretched) control groups for every experimental condition. qPCR was performed to determine relative mRNA levels and quantitative immunocytochemistry image analysis was used to assess protein levels and cell morphology. RESULTS: Collagen type I mRNA level and pro-collagen protein levels were higher in tenocytes that were subjected to rest-inserted mechanical stimulation, compared to continuous stretching (p<0.05). Rest insertion and increased cycle number also had significant positive effects on the levels of mRNA for TGFB1 and SCXA (p<0.05). There was no direct relation between cell morphology and gene expression, however mechanical stimulation, overall, induced a metabolically active tenocyte phenotype as evidenced by cells that on average demonstrated a decreased major-minor axis ratio (p<0.05) with greater branching (p<0.01). CONCLUSIONS: The incorporation of rest periods in a mechanical stretching regimen results in greater collagen type I synthesis. This knowledge may be beneficial in refining rehabilitation protocols for tendon injury.

Hemifacial spasm and neurovascular compression.

Hemifacial spasm (HFS) is characterized by involuntary unilateral contractions of the muscles innervated by the ipsilateral facial nerve, usually starting around the eyes before progressing inferiorly to the cheek, mouth, and neck. Its prevalence is 9.8 per 100,000 persons with an average age of onset of 44 years. The accepted pathophysiology of HFS suggests that it is a disease process of the nerve root entry zone of the facial nerve. HFS can be divided into two types: primary and secondary. Primary HFS is triggered by vascular compression whereas secondary HFS comprises all other causes of facial nerve damage. Clinical examination and imaging modalities such as electromyography (EMG) and magnetic resonance imaging (MRI) are useful to differentiate HFS from other facial movement disorders and for intraoperative planning. The standard medical management for HFS is botulinum neurotoxin (BoNT) injections, which provides low-risk but limited symptomatic relief. The only curative treatment for HFS is microvascular decompression (MVD), a surgical intervention that provides lasting symptomatic relief by reducing compression of the facial nerve root. With a low rate of complications such as hearing loss, MVD remains the treatment of choice for HFS patients as intraoperative technique and monitoring continue to improve.

Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy.

High-throughput microscopy has enabled screening of cell phenotypes at unprecedented scale. Systematic identification of cell phenotype changes (such as cell morphology and protein localization changes) is a major analysis goal. Because cell phenotypes are high-dimensional, unbiased approaches to detect and visualize the changes in phenotypes are still needed. Here, we suggest that changes in cellular phenotype can be visualized in reduced dimensionality representations of the image feature space. We describe a freely available analysis pipeline to visualize changes in protein localization in feature spaces obtained from deep learning. As an example, we use the pipeline to identify changes in subcellular localization after the yeast GFP collection was treated with hydroxyurea.

Convolutions are competitive with transformers for protein sequence pretraining.

Pretrained protein sequence language models have been shown to improve the performance of many prediction tasks and are now routinely integrated into bioinformatics tools. However, these models largely rely on the transformer architecture, which scales quadratically with sequence length in both run-time and memory. Therefore, state-of-the-art models have limitations on sequence length. To address this limitation, we investigated whether convolutional neural network (CNN) architectures, which scale linearly with sequence length, could be as effective as transformers in protein language models. With masked language model pretraining, CNNs are competitive with, and occasionally superior to, transformers across downstream applications while maintaining strong performance on sequences longer than those allowed in the current state-of-the-art transformer models. Our work suggests that computational efficiency can be improved without sacrificing performance, simply by using a CNN architecture instead of a transformer, and emphasizes the importance of disentangling pretraining task and model architecture. A record of this paper's transparent peer review process is included in the supplemental information.

Protein structure generation via folding diffusion.

The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases. Despite recent advances in protein structure prediction, directly generating diverse, novel protein structures from neural networks remains difficult. In this work, we present a diffusion-based generative model that generates protein backbone structures via a procedure inspired by the natural folding process. We describe a protein backbone structure as a sequence of angles capturing the relative orientation of the constituent backbone atoms, and generate structures by denoising from a random, unfolded state towards a stable folded structure. Not only does this mirror how proteins natively twist into energetically favorable conformations, the inherent shift and rotational invariance of this representation crucially alleviates the need for more complex equivariant networks. We train a denoising diffusion probabilistic model with a simple transformer backbone and demonstrate that our resulting model unconditionally generates highly realistic protein structures with complexity and structural patterns akin to those of naturally-occurring proteins. As a useful resource, we release an open-source codebase and trained models for protein structure diffusion.

Intraoperative cortical stimulation mapping with laryngeal electromyography for the localization of human laryngeal motor cortex.

OBJECTIVE: The objectives of this study were to describe the authors' clinical methodology and outcomes for mapping the laryngeal motor cortex (LMC) and define localization of the LMC in a cohort of neurosurgical patients undergoing intraoperative brain mapping. Because of mapping variability across patients, the authors aimed to define the probabilistic distribution of cortical sites that evoke laryngeal movement, as well as adjacent cortical somatotopic representations for the face (mouth), tongue, and hand. METHODS: Thirty-six patients underwent left (n = 18) or right (n = 18) craniotomy with asleep motor mapping. For each patient, electromyography (EMG) electrodes were placed in the face, tongue, and hand; a nerve integrity monitor (NIM) endotracheal tube with surface electrodes detected EMG activity from the bilateral vocal folds. After dense cortical stimulation was delivered throughout the sensorimotor cortex, motor responses were then mapped onto a three-dimensional reconstruction of the patient's cortical surfaces for location characterization of the evoked responses. Finally, stimulation sites were transformed into a two-dimensional coordinate system for probabilistic mapping of the stimulation site relative to the central sulcus and sylvian fissure. RESULTS: The authors found that the LMC was predominantly localized to a mid precentral gyrus region, dorsal to face representation and surrounding a transverse sulcus ventral to the hand knob. In 14 of 36 patients, the authors identified additional laryngeal responses located ventral to all orofacial representations, providing evidence for dual LMC representations. CONCLUSIONS: The authors determined the probabilistic distribution of the LMC. Cortical stimulation mapping with an NIM endotracheal tube is an easy and effective method for mapping the LMC and is simply integrated into the current neuromonitoring methods for brain mapping.