Effective Local and Secondary Protein Structure Prediction by Combining a Neural Network-Based Approach with Extensive Feature Design and Selection without Reliance on Evolutionary Information.

Protein structure prediction continues to pose multiple challenges despite outstanding progress that is largely attributable to the use of novel machine learning techniques. One of the widely used representations of local 3D structure-protein blocks (PBs)-can be treated in a similar way to secondary structure classes. Here, we present a new approach for predicting local conformation in terms of PB classes solely from amino acid sequences. We apply the RMSD metric to ensure unambiguous future 3D protein structure recovery. The selection of statistically assessed features is a key component of the proposed method. We suggest that ML input features should be created from the statistically significant predictors that are derived from the amino acids' physicochemical properties and the resolved structures' statistics. The statistical significance of the suggested features was assessed using a stepwise regression analysis that permitted the evaluation of the contribution and statistical significance of each predictor. We used the set of 380 statistically significant predictors as a learning model for the regression neural network that was trained using the PISCES30 dataset. When using the same dataset and metrics for benchmarking, our method outperformed all other methods reported in the literature for the CB513 nonredundant dataset (for the PBs, Q16 = 81.01%, and for the DSSP, Q3 = 85.99% and Q8 = 79.35%).

A Perspective on the (Rise and Fall of) Protein ß-Turns.

The ß-turn is the third defined secondary structure after the α-helix and the ß-sheet. The ß-turns were described more than 50 years ago and account for more than 20% of protein residues. Nonetheless, they are often overlooked or even misunderstood. This poor knowledge of these local protein conformations is due to various factors, causes that I discuss here. For example, confusion still exists about the assignment of these local protein structures, their overlaps with other structures, the potential absence of a stabilizing hydrogen bond, the numerous types of ß-turns and the software's difficulty in assigning or visualizing them. I also propose some ideas to potentially/partially remedy this and present why ß-turns can still be helpful, even in the AlphaFold 2 era.

Quantitative [18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy.

OBJECTIVE: Fluorodeoxyglucose-positron emission tomography (FDG-PET) is an established, independent, strong predictor of surgical outcome in refractory epilepsy. In this study, we explored the added value of quantitative [18F]FDG-PET features combined with clinical variables, including electroencephalography (EEG), [18F]FDG-PET, and magnetic resonance imaging (MRI) qualitative interpretations, to predict long-term seizure recurrence (mean post-op follow-up of 5.85 ±â€¯3.77 years). METHODS: Machine learning predictive models of surgical outcome were created using a random forest classifier trained on quantitative features in 89 patients with drug-refractory temporal lobe epilepsy evaluated at the Hospital of the University of Pennsylvania epilepsy surgery program (2003-2016). Quantitative features were calculated from asymmetry features derived from image processing using Advanced Normalization Tools (ANTs). RESULTS: The best-performing model used quantification and had an out-of-bag accuracy of 0.71 in identifying patients with seizure recurrence (Engel IB or worse) which outperformed that using qualitative clinical data by 10%. This model is shared through open-source software for research use. In addition, several asymmetry features in temporal and extratemporal regions that were significantly associated with seizure freedom are identified for future study. SIGNIFICANCE: Complex quantitative [18F]FDG-PET imaging features can predict seizure recurrence in patients with refractory temporal lobe epilepsy. These initial retrospective results in a cohort with long-term follow-up suggest that using quantitative imaging features from regions in the epileptogenic network can inform the clinical decision-making process.

α-Helices in the Type III Secretion Effectors: A Prevalent Feature with Versatile Roles.

Type III Secretion Systems (T3SSs) are multicomponent nanomachines located at the cell envelope of Gram-negative bacteria. Their main function is to transport bacterial proteins either extracellularly or directly into the eukaryotic host cell cytoplasm. Type III Secretion effectors (T3SEs), latest to be secreted T3S substrates, are destined to act at the eukaryotic host cell cytoplasm and occasionally at the nucleus, hijacking cellular processes through mimicking eukaryotic proteins. A broad range of functions is attributed to T3SEs, ranging from the manipulation of the host cell's metabolism for the benefit of the bacterium to bypassing the host's defense mechanisms. To perform this broad range of manipulations, T3SEs have evolved numerous novel folds that are compatible with some basic requirements: they should be able to easily unfold, pass through the narrow T3SS channel, and refold to an active form when on the other side. In this review, the various folds of T3SEs are presented with the emphasis placed on the functional and structural importance of α-helices and helical domains.

Evaluation of a dual signal subspace projection algorithm in magnetoencephalographic recordings from patients with intractable epilepsy and vagus nerve stimulators.

Magnetoencephalography (MEG) data is subject to many sources of environmental noise, and interference rejection is a necessary step in the processing of MEG data. Large amplitude interference caused by sources near the brain have been common in clinical settings and are difficult to reject. Artifact from vagal nerve stimulators (VNS) is a prototypical example. In this study, we describe a novel MEG interference rejection algorithm called dual signal subspace projection (DSSP), and evaluate its performance in clinical MEG data from people with epilepsy and implanted VNS. The performance of DSSP was evaluated in a retrospective cohort study of patients with epilepsy and VNS who had MEG scans for source localization of interictal epileptiform discharges. DSSP was applied to the MEG data and compared with benchmark for performance. We evaluated the clinical impact of interference rejection based on human expert detection and estimation of the location and time-course of interictal spikes, using an empirical Bayesian source reconstruction algorithm (Champagne). Clinical recordings, after DSSP processing, became more readable and a greater number of interictal epileptic spikes could be clearly identified. Source localization results of interictal spikes also significantly improved from those achieved before DSSP processing, including meaningful estimates of activity time courses. Therefore, DSSP is a valuable novel interference rejection algorithm that can be successfully deployed for the removal of strong artifacts and interferences in MEG.

PCASSO: a fast and efficient Cα-based method for accurately assigning protein secondary structure elements.

Proteins are often characterized in terms of their primary, secondary, tertiary, and quaternary structure. Algorithms such as define secondary structure of proteins (DSSP) can automatically assign protein secondary structure based on the backbone hydrogen-bonding pattern. However, the assignment of secondary structure elements (SSEs) becomes a challenge when only the Cα coordinates are available. In this work, we present protein C-alpha secondary structure output (PCASSO), a fast and accurate program for assigning protein SSEs using only the Cα positions. PCASSO achieves ∼95% accuracy with respect to DSSP and takes ∼0.1 s using a single processor to analyze a 1000 residue system with multiple chains. Our approach was compared with current state-of-the-art Cα-based methods and was found to outperform all of them in both speed and accuracy. A practical application is also presented and discussed.

Facilities that make the PDB data collection more powerful.

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF-formatted files with a computer-readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB-REDO collection of reanalyzed and re-refined protein structures that were solved by X-ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.

Evaluation of binding and antagonism/downregulation of brilanestrant molecule in estrogen receptor-α via quantum mechanics/molecular mechanics, molecular dynamics and binding free energy calculations.

The resistance to the endocrine therapy of breast cancer leads to the emergence of new class of drugs that downregulates the estrogen receptor action known as selective estrogen receptor downregulators (SERDs). The first approved SERD is fluvestrant; after this, there are several downregulators evolved and are in clinical trials, in which the brilanestrant (BRI) molecule shows nM range of binding affinity and efficacy. In the present study, to understand the binding nature of BRI molecule in the active site of ERα, the molecular docking analysis has been performed. Further, the QM/MM calculations were performed for the BRI-ERα complex to analyze the charge density distribution of intermolecular interactions. The molecular dynamics (MD) simulation was employed to understand the stability and binding mechanism of BRI molecule through root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF) and binding free energy calculations. From the MD simulation trajectory analysis, the alterations of Helix12 conformation and the key residue (Lys529), which is responsible for the ERα downregulation, have been identified. Further, the interaction between the H3 and H12 regions was identified for the antagonism of BRI molecule. The current study led us to understand the binding mechanism, antagonism and downregulation of BRI molecule, and this knowledge is essential to design novel SERDs for the treatment of endocrine-resistant positive breast cancer.Communicated by Ramaswamy H. Sarma.

Differences in cerebellar perfusion between Parkinson's disease and multiple system atrophy.

INTRODUCTION: Objective biomarkers are required for differential diagnosis of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). OBJECTIVE: We aimed to determine if cerebellar blood flow, measured using N-isopropyl-[123I] p-iodoamphetamine single photon emission computed tomography (123I -IMP-SPECT), was useful for differentiating between PD, MSA and PSP. METHODS: Twenty-four patients with PD, seventeen patients with MSA with predominant parkinsonian features (MSA-P), sixteenth patients with MSA with predominant cerebellar ataxia (MSA-C) and eight patients with PSP were enrolled. Twenty-seven normal controls' data were used for the calculation of z score. All patients underwent 123I -IMP-SPECT, and data were analyzed using a three-dimensional-stereotactic surface projection program. RESULTS: Cerebellar perfusion in MSA-P (MSA-P vs PD, P = .002; MSA-P vs PSP, P < .001) and MSA-C (MSA-C vs PD, P < .001; MSA-C vs PSP, P < .001) were significantly decreased compared with PD or PSP. There was no significant difference in perfusion between PD and PSP groups (P = .061). The area under the receiver operating characteristic curve for cerebellar perfusion between MSA-P and PD was 0.858. CONCLUSION: Our findings revealed that cerebellar perfusion by 123I-IMP-SPECT was useful for differentiating between PD and MSA-P.

Impact of protein dynamics on secondary structure prediction.

Protein 3D structures support their biological functions. As the number of protein structures is negligible in regards to the number of available protein sequences, prediction methodologies relying only on protein sequences are essential tools. In this field, protein secondary structure prediction (PSSPs) is a mature area, and is considered to have reached a plateau. Nonetheless, proteins are highly dynamical macromolecules, a property that could impact the PSSP methods. Indeed, in a previous study, the stability of local protein conformations was evaluated demonstrating that some regions easily changed to another type of secondary structure. The protein sequences of this dataset were used by PSSPs and their results compared to molecular dynamics to investigate their potential impact on the quality of the secondary structure prediction. Interestingly, a direct link is observed between the quality of the prediction and the stability of the assignment to the secondary structure state. The more stable a local protein conformation is, the better the prediction will be. The secondary structure assignment not taken from the crystallized structures but from the conformations observed during the dynamics slightly increase the quality of the secondary structure prediction. These results show that evaluation of PSSPs can be done differently, but also that the notion of dynamics can be included in development of PSSPs and other approaches such as de novo approaches.

Homology Searches Using Supersecondary Structure Code.

Supersecondary structure code (SSSC), which is represented as the combination of α-helix-type (SSSC: H), ß-sheet-type (SSSC: S), the other (SSSC: T), and disorder residue or C-terminal (SSSC: D) patterns, has been produced by the developed concept of Ramachandran plot, in addition, with the ω angle and with the specification of positions of torsion angles in a protein by the registration of codes for torsion angles of each amino acid peptide unit, derived from the fuzzy search of structural code homology using the template patterns 3a5c4a (SSSC: H) and 6c4a4a (SSSC: S) with conformational codes. The DSSP (Dictionary of Secondary Structure in Proteins) method assigns the secondary structure including hydrogen bond well. In contrast, supersecondary structure code is very sensitive to the supersecondary structures of proteins. In this chapter, the protocol of homology search methods, the sequence alignment using supersecondary structure code, the assignment of supersecondary structure code T, the fuzzy search using supersecondary structure code, and the exact search using supersecondary structure code are described. Supersecondary structure code is variable with the conformational change. If possible, many Protein Data Bank (PDB) data of similar main chains of proteins should be used for the homology searches. The thorough check of SSSC sequences is also useful to reveal the role of target pattern.

Identification of the hot spot residues for pyridine derivative inhibitor CCT251455 and ATP substrate binding on monopolar spindle 1 (MPS1) kinase by molecular dynamic simulation.

Protein kinase monopolar spindle 1 plays an important role in spindle assembly checkpoint at the onset of mitosis. Over expression of MPS1 correlated with a wide range of human tumors makes it an attractive target for finding an effective and specific inhibitor. In this work, we performed molecular dynamics simulations of protein MPS1 itself as well as protein bound systems with the inhibitor and natural substrate based on crystal structures. The reported orally bioavailable 1 h-pyrrolo [3,2-c] pyridine inhibitors of MPS1 maintained stable binding in the catalytic site, while natural substrate ATP could not stay. Comparative study of stability and flexibility of three systems reveals position shifting of ß-sheet region within the catalytic site, which indicates inhibition mechanism was through stabilizing the ß-sheet region. Binding free energies calculated with MM-GB/PBSA method shows different binding affinity for inhibitor and ATP. Finally, interactions between protein and inhibitor during molecular dynamic simulations were measured and counted. Residue Gly605 and Leu654 were suggested as important hot spots for stable binding of inhibitor by molecular dynamic simulation. Our results reveal an important position shifting within catalytic site for non-inhibited proteins. Together with hot spots found by molecular dynamic simulation, the results provide important information of inhibition mechanism and will be referenced for designing novel inhibitors.

Introducing a simple model system for binding studies of known and novel inhibitors of AMPK: a therapeutic target for prostate cancer.

Prostate cancer (PC) is one of the leading cancers in men, raising a serious health issue worldwide. Due to lack of suitable biomarker, their inhibitors and the platform for testing those inhibitors result in poor prognosis of PC. AMP-activated protein kinase (AMPK) is a highly conserved protein kinase found in eukaryotes that is involved in growth and development, and also acts as a therapeutic target for PC. The aim of the present study is to identify novel potent inhibitors of AMPK and propose a simple cellular model system for understanding its biology. Structural modelling and MD simulations were performed to construct and refine the 3D models of Dictyostelium and human AMPK. Binding mechanisms of different drug compounds were studied by performing molecular docking, molecular dynamics and MM-PBSA methods. Two novel drugs were isolated having higher binding affinity over the known drugs and hydrophobic forces that played a key role during protein-ligand interactions. The study also explored the simple cellular model system for drug screening and understanding the biology of a therapeutic target by performing in vitro experiments.

Does applying resolution recovery to normal databases confer an advantage over conventional 3D-stereotactic surface projection techniques?

We evaluated a novel normal database (NDB) generated using single photon emission computed tomography (SPECT) data obtained from healthy brains by using a SPECT/CT system, analyzed using a resolution recovery (RR) technique applied to the three-dimensional stereotactic surface projection (3D-SSP) technique. We used a three-dimensional ordered subset expectation maximization method (3D-OSEM) with applied scatter correction (SC), attenuation correction, and RR to reconstruct the data. We verified the accuracy of the novel NDB's values (Z, extent, and error scores), and compared the novel NDB to the 3D-SSP technique by using simulated misery perfusion-related patient data from a conventional NDB. In addition, Z, extent, and error scores at the precuneus, cuneus, and posterior cingulate were compared under different reconstruction conditions by using the patient data. In the simulation, Z scores decreased when using the novel NDB corrected using computed tomography-based attenuation correction (CTAC), SC, and RR. The extent scores of the posterior cingulate increased using the novel NDB, relative to the other NDBs. The error score with the novel NDB without RR decreased by 15% compared to that of the conventional NDB. Z scores generated from patient data decreased in the novel NDB with RR. The extent scores tended to decrease in the novel NDB with RR. The extent scores in the novel NDB with RR improved at the posterior cingulate, compared to the scores with the other NDBs. However, applying RR to the novel NDB conferred no advantage because the cut-off of the current Z score must be reconsidered when using the additive RR technique.

Evaluation of early-phase [18F]-florbetaben PET acquisition in clinical routine cases.

OBJECTIVES: In recent years several [18F]-labelled amyloid PET tracers have been developed and have obtained clinical approval. There is accumulating evidence that early (post injection) acquisitions with these tracers are equally informative as conventional blood flow and metabolism studies for diagnosis of Alzheimer's disease, but there have been few side-by-side studies. Therefore, we investigated the performance of early acquisitions of [18F]-florbetaben (FBB) PET compared to [18F]-fluorodeoxyglucose (FDG) PET in a clinical setting. METHODS: All subjects were recruited with clinical suspicion of dementia due to neurodegenerative disease. FDG PET was undertaken by conventional methods, and amyloid PET was performed with FBB, with early recordings for the initial 10 min (early-phase FBB), and late recordings at 90-110 min p.i. (late-phase FBB). Regional SUVR with cerebellar and global mean normalization were calculated for early-phase FBB and FDG PET. Pearson correlation coefficients between FDG and early-phase FBB were calculated for predefined cortical brain regions. Furthermore, a visual interpretation of disease pattern using 3-dimensional stereotactic surface projections (3D-SSP) was performed, with assessment of intra-reader agreement. RESULTS: Among a total of 33 patients (mean age 67.5 ± 11.0 years) included in the study, 18 were visually rated amyloid-positive, and 15 amyloid-negative based on late-phase FBB scans. Correlation coefficients for early-phase FBB vs. FDG scans displayed excellent agreement in all target brain regions for global mean normalization. Cerebellar normalization gave strong, but significantly lower correlations. 3D representations of early-phase FBB visually resembled the corresponding FDG PET images, irrespective of the amyloid-status of the late FBB scans. CONCLUSIONS: Early-phase FBB acquisitions correlate on a relative quantitative and visual level with FDG PET scans, irrespective of the amyloid plaque density assessed in late FBB imaging. Thus, early-phase FBB uptake depicts a metabolism-like image, suggesting it as a valid surrogate marker for synaptic dysfunction, which could ultimately circumvent the need for additional FDG PET investigation in diagnosis of dementia.

The predictive value of FDG-PET with 3D-SSP for surgical outcomes in patients with temporal lobe epilepsy.

PURPOSE: We retrospectively evaluated the diagnostic value of (18)F-2-fluorodeoxy-d-glucose positron emission tomography (FDG-PET) with statistical analysis for the foci detection and predictive utility for postsurgical seizure outcome of patients with mesial temporal lobe epilepsy (mTLE). METHOD: We evaluated 40 patients who were diagnosed mTLE and underwent selective amygdalohippocampectomy (SAH) or anterior temporal lobectomy (ATL) in our institute. Preoperative interictal FDG-PET with statistical analysis using three-dimensional stereotactic surface projection (3D-SSP) was detected with several clinical data including seizure semiology, MRI, scalp electroencephalography, surgical procedure with SAH or ATL and postsurgical outcome. The region of interest (ROI) was defined on 'Hippocampus & Amygdala', 'Parahippocampal gyrus & Uncus', 'T1 & T2', and 'T3 & Fusiform gyrus'. We obtained the ratio of hypometabolism difference (RHD) by 3D-SSP, and evaluated the relation among hypometabolic extent, surgical outcome and surgical procedure. RESULT: The RHD in each ROIs ipsilateral to operative side was significantly higher than that of contralateral side in good outcome group. Hypometabolism of 'Hippocampus & Amygdala' was most reliable prognostic factor. Patients of discordant with presurgical examinations hardly showed obvious lateralized hypometabolism. Nevertheless, when they have significantly high RHD in mesial temporal lobe, good surgical outcome was expected. There was not significant difference of RHD distribution between SAH and ATL in good outcome group. CONCLUSION: Significant hypometabolism in mesial temporal lobe on FDG-PET with 3D-SSP is useful to predict good surgical outcome for patients with mTLE, particularly in discordant patients with hypometabolism in mesial temporal structure. However, FDG-PET is not indicative of surgical procedure.

Computational Prediction of Protein Secondary Structure from Sequence.

Secondary structure of proteins refers to local and repetitive conformations, such as α-helices and ß-strands, which occur in protein structures. Computational prediction of secondary structure from protein sequences has a long history with three generations of predictive methods. This unit summarizes several recent third-generation predictors. We discuss their inputs and outputs, availability, and predictive performance and explain how to perform and interpret their predictions. We cover methods for the prediction of the 3-class secondary structure states (helix, strand, and coil) as well as the 8-class secondary structure states. Recent empirical assessments and our small-scale analysis reveal that these predictions are characterized by high levels of accuracy, between 70% and 80%. We emphasize that modern predictors are available to end users in the form of convenient-to-use Web servers and stand-alone software. © 2016 by John Wiley & Sons, Inc.

Comparative Study of Voxel-Based Epileptic Foci Localization Accuracy between Statistical Parametric Mapping and Three-dimensional Stereotactic Surface Projection.

INTRODUCTION: Fluorine-18-fluorodeoxyglucose positron-emission tomography (18F-FDG-PET) is widely used to help localize the hypometabolic epileptogenic focus for presurgical evaluation of drug-refractory epilepsy patients. Two voxel-based brain mapping methods to interpret 18F-FDG-PET, statistical parametric mapping (SPM) and three-dimensional stereotactic surface projection (3D-SSP), improve the detection rate of seizure foci. This study aimed to compare the consistency of epileptic focus detection between SPM and 3D-SSP for 18F-FDG-PET brain mapping analysis. METHODS: We retrospectively reviewed the clinical, electroecephalographic, and brain imaging results of 35 patients with refractory epilepsy. 18F-FDG-PET studies were revaluated by SPM, 3D-SSP, and visual assessment, and the results were compared to the magnetic resonance imaging (MRI) lesion location and to the presumed epileptogenic zone (PEZ) defined by video-electroencephalogram and other clinical data. A second consistency study compared PET analyses to histopathology and surgical outcomes in the 19 patients who underwent lesion resection surgery. RESULTS: Of the 35 patients, consistency with the PEZ was 29/35 for SPM, 25/35 for 3D-SSP, 14/35 for visual assessment, and 10/35 for MRI. Concordance rates with the PEZ were significantly higher for SPM and 3D-SSP than for MRI (P < 0.05) and visual assessment (P < 0.05). Differences between SPM and 3D-SSP and between visual assessment and MRI were not significant. In the 19 surgical patients, concordance with histopathology/clinical outcome was 14/19 for SPM, 15/19 for 3D-SSP, 14/19 for visual assessment, and 9/19 for MRI (P > 0.05). A favorable Engel outcome (class I/II) was found in 16 of 19 cases (84%), and failure of seizure control was found in 3 of 19 patients (class III/IV). CONCLUSION: Voxel-based 18F-FDG-PET brain mapping analysis using SPM or 3D-SSP can improve the detection rate of the epileptic focus compared to visual assessment and MRI. Consistency with PEZ was similar between SPM and 3D-SSP; according to their own characteristics, 3D-SSP is recommended for primary evaluation due to greater efficiency and operability of the software, while SPM is recommended for high-accuracy localization of complex lesions. Therefore, joint application of both software packages may be the best solution for FDG-PET analysis of epileptic focus localization.

Intraoperative middle cerebral artery pressure measurements during superficial temporal artery to middle cerebral artery bypass procedures in patients with cerebral atherosclerotic disease.

OBJECTIVE No previous study has monitored middle cerebral artery (MCA) pressure during the superficial temporal artery (STA)-MCA bypass procedure for cerebral atherosclerotic disease. In this paper, the authors describe their method of monitoring MCA pressure and report their initial data on intraoperative MCA pressure and its relationship with hemodynamics prior to and after the bypass procedures. METHODS The results from a total of 39 revascularization procedures performed between 2004 and 2014 were analyzed. The patient group included 27 men and 12 women, and their mean age at surgery was 67.6 years (range 39-83 years). The authors investigated the MCA pressure via the STA during STA-MCA bypass procedures. After one branch of the STA was anastomosed to the MCA, the other branch was connected to an arterial line, and a clip was placed temporally on the main STA trunk to monitor the pre-anastomosis MCA pressure. Simultaneously, the radial artery (RA) pressure was determined before removing the temporal clip to measure the post-anastomosis MCA pressure. The relationship between MCA pressures and single photon emission computed tomography findings and the risk factors for hyperperfusion after STA-MCA bypass were analyzed. RESULTS The MCA/RA (%) pressure was significantly correlated with that of the resting stenotic/normal side cerebral blood flow (CBF) ratio (%) in the linear regression analysis (slope 1.200, r2 = 0.3564, F = 20.49, p < 0.0001). The intraoperative MCA pressure was 39.3% of RA pressure in patients with Powers' Stage 2 cerebral atherosclerotic disease. After 1 branch of the STA was anastomosed, the intraoperative MCA pressure increased to 75.3% of the RA pressure. The rate of increase in pressure was significantly correlated with the increase in the STA diameter in the linear regression analysis (slope 2.59, r2 = 0.205, F = 9.549, p = 0.0038). Hyperperfusion occurred in 2 cases. When mean values for these 2 patients were compared with those for the 37 patients without hyperperfusion, significant differences were found in the stenotic/normal side CBF ratio (p = 0.0001), pre-anastomosis MCA pressure (p = 0.02), rate of increase in pressure (p = 0.02), pre-anastomotic MCA/RA pressure ratio (p = 0.01), vascular reserve (p = 0.0489), and STA diameter (p = 0.0002). CONCLUSIONS The measurement of intraoperative MCA pressure may be a useful technique to assess cerebral perfusion and for predicting the risk of hyperperfusion. Monitoring MCA pressure is recommended during STA-MCA bypass procedures for atherosclerotic disease.

Differential sequential septal pacing: a simple maneuver to differentiate nodal versus extranodal ventriculoatrial conduction.

BACKGROUND: Distinguishing retrograde nodal conduction from extranodal conduction using an accessory pathway (AP) can sometimes be challenging. OBJECTIVE: To distinguish nodal from extranodal ventriculoatrial (VA) conduction regardless of AP location by proposing a simple method. This method is based on the principle that moving the pacing site progressively from the basal region toward the entrance of the His-Purkinje system should shorten VA time for nodal but not for AP conduction. METHODS: Sixty-seven patients with supraventricular tachycardia were prospectively recruited. Quadripolar catheters were placed at the right ventricular (RV) apex, right atrium, and His and coronary sinus. The RV septum was sequentially paced at 4 sites: (1) basal, (2) high midventricle, (3) low midventricle, and (4) apex at a cycle length 100 ms shorter than the resting cycle length. The stimulus-to-atrial (SA) interval was measured by using the proximal coronary sinus atrial electrogram. RESULTS: Group 1 (n = 33) had nodal VA conduction; all patients had typical atrioventricular nodal reentrant tachycardia. Group 2 (n = 34) had extranodal VA conduction via an AP: 19 left-sided, 6 right-sided, and 9 posteroseptal. In group 1, the SA interval decreased significantly as pacing site moved closer toward the apex (site 1: 166 ± 35 ms, site 2: 153 ± 32 ms, site 3: 149 ± 32 ms, site 4: 154 ± 33 ms, P < .001, respectively, at sites 2-4 compared with site 1). In contrast, in group 2, the SA interval increased significantly toward the apex (site 1: 149 ± 45 ms, site 2: 158 ± 43 ms, site 3: 161 ± 43 ms, and site 4: 163 ± 40 ms, P < .001, respectively, at sites 2-4 compared with site 1). The SA interval at the high midventricular site (site 2) - SA interval at the base (site 1) ≤ 0 ms for nodal and > 0 ms for extranodal conduction had optimal sensitivity and specificity (nodal: selectivity = 97.0% and specificity = 85.3%; extranodal: selectivity = 85.3% and specificity = 97.0%). CONCLUSIONS: Differential sequential pacing of the RV septum reliably distinguishes retrograde atrioventricular nodal conduction from AP conduction.