We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

MUSCLE: multiple sequence alignment with high accuracy and high throughput

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromolecular systems. The program can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed a set of simple and physically motivated criteria for secondary structure, programmed as a pattern-recognition process of hydrogen-bonded and geometrical features extracted from x-ray coordinates. Cooperative secondary structure is recognized as repeats of the elementary hydrogen-bonding patterns “turn” and “bridge.” Repeating turns are “helices,” repeating bridges are “ladders,” connected ladders are “sheets.” Geometric structure is defined in terms of the concepts torsion and curvature of differential geometry. Local chain “chirality” is the torsional handedness of four consecutive Cα positions and is positive for right-handed helices and negative for ideal twisted β-sheets. Curved pieces are defined as “bends.” Solvent “exposure” is given as the number of water molecules in possible contact with a residue. The end result is a compilation of the primary structure, including SS bonds, secondary structure, and solvent exposure of 62 different globular proteins. The presentation is in linear form: strip graphs for an overall view and strip tables for the details of each of 10.925 residues. The dictionary is also available in computer-readable form for protein structure prediction work.

Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features

6.2.2. Definition of Effective Properties 3064 6.3. Response Properties to Magnetic Fields 3066 6.3.1. Nuclear Shielding 3066 6.3.2. Indirect Spin−Spin Coupling 3067 6.3.3. EPR Parameters 3068 6.4. Properties of Chiral Systems 3069 6.4.1. Electronic Circular Dichroism (ECD) 3069 6.4.2. Optical Rotation (OR) 3069 6.4.3. VCD and VROA 3070 7. Continuum and Discrete Models 3071 7.1. Continuum Methods within MD and MC Simulations 3072

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Quantum mechanical continuum solvation models.

This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and analysis programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.

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GROMACS: Fast, flexible, and free

Background Tools predicting intracranial dural arteriovenous fistulas (dAVFs) treatment outcomes remain scarce. This study aimed to use a multicenter database comprising more than 1000 dAVFs to develop a practical scoring system that predicts treatment outcomes. Methods Patients with angiographically confirmed dAVFs who underwent treatment within the Consortium for Dural Arteriovenous Fistula Outcomes Research-participating institutions were retrospectively reviewed. A subset comprising 80% of patients was randomly selected as training dataset, and the remaining 20% was used for validation. Univariable predictors of complete dAVF obliteration were entered into a stepwise multivariable regression model. The components of the proposed score (VEBAS) were weighted based on their ORs. Model performance was assessed using receiver operating curves (ROC) and areas under the ROC. Results A total of 880 dAVF patients were included. Venous stenosis (presence vs absence), elderly age (<75 vs ≥75 years), Borden classification (I vs II-III), arterial feeders (single vs multiple), and past cranial surgery (presence vs absence) were independent predictors of obliteration and used to derive the VEBAS score. A significant increase in the likelihood of complete obliteration (OR=1.37 (1.27–1.48)) with each additional point in the overall patient score (range 0–12) was demonstrated. Within the validation dataset, the predicted probability of complete dAVF obliteration increased from 0% with a 0–3 score to 72–89% for patients scoring ≥8. Conclusion The VEBAS score is a practical grading system that can guide patient counseling when considering dAVF intervention by predicting the likelihood of treatment success, with higher scores portending a greater likelihood of complete obliteration.

The VEBAS score: a practical scoring system for intracranial dural arteriovenous fistula obliteration

Part I – IntroductIon It has been two decades since the first ‘patientspecific’ 3D computational fluid dynamics (CFD) models of intracranial aneurysms were published in the American Journal of Neuroradiology (AJNR). 2 Thousands of cases have since been simulated, 4 primarily towards identifying hemodynamic factors associated with aneurysm wall degradation as proxies for rupture risk, and secondarily for planning treatments and/or predicting their outcomes. It has also been nearly a decade since the Food and Drug Administration's approval of the first clinical CFD application: calculating pressure drops and fractional flow reserve (FFR) noninvasively for coronary artery disease. Nevertheless, clinical utility of CFD for cerebral artery diseases still seems like fusion energy—always at least a couple of decades away. It is therefore understandable that journal readers may view with some skepticism recent work in the Journal of NeuroInterventional Surgery (JNIS) and other journals applying CFD to cerebral veins. As we outline here, CFD modeling in venous diseases, while not without its own challenges, might have a more straightforward path to the clinic. This is because, as for FFR, it is the pathophysiology of the blood flow itself, rather than the impact of disturbed flow on the pathobiology of the blood or wall, that is of central interest. It is perhaps fitting that the first computational models for cerebral venous diseases began to emerge during the heyday of promising but controversial neurointerventions for multiple sclerosis. These models were primarily onedimensional networks, aimed at understanding the upstream effects of chronic cerebrospinal venous insufficiency (CCSVI) on permeability of the blood–brain barrier. As the promise of the CCSVI hypothesis faded, so too did interest in CFD modeling of cerebral venous diseases. There is, however, now a growing recognition of the contribution of venous disease—and associated disturbed venous blood flow— to a subset of patients, notably those with idiopathic intracranial hypertension (IIH) or pulsatile tinnitus (PT). As extensively reported in the pages of this Journal, there has been an explosion of interest in cerebral venous sinus stenting as a primary treatment modality for IIH, due to the perceived benefits over traditional surgical methods, 15 and stenting or coiling has shown promise in patients with refractory PT.

You’re so vein, you probably think this model’s about you: opportunities and challenges for computational fluid dynamics in cerebral venous disease

Increased plasma concentrations of a variety of cellular enzymes (alanine transaminase, aspartate aminotransferase, alkaline phosphatase, amylase, etc.) are commonly used as routine screening tests for a range of conditions. An increased concentration usually is assumed to result from an increased rate of delivery to the plasma. Factors such as decreased metabolism or excretion or altered extravascular distribution usually are ignored. As a prelude to a detailed analysis of all the factors producing altered plasma enzyme levels, we have reviewed the relevant literature describing the pharmacokinetics (PK) of 13 of the commonly measured plasma proteins and developed a PK model that provides a simple physiological description of all the data. Our model starts with the general 3-compartment, 6-parameter system previously developed for albumin and interprets the fluxes in terms of unidirectional sieved protein convectional volume flows from the plasma to the two tissue compartments and equal lymph flows returning to the plasma. This greatly constrains the model such that each protein is characterized by only two adjustable parameters (plasma clearance and sieving factor). In addition to accurately fitting the plasma kinetics, the model can accurately describe the tissue and lymph protein PK. For example, it can describe the thoracic duct lymph protein concentration following an intravenous infusion or the plasma concentration following a subcutaneous tissue injection. This simple model provides a satisfactory framework for the PK of 12 of the 13 proteins investigated. The glycoprotein intestinal alkaline phosphatase is the exception, requiring the addition of a liver recycling compartment involving the asialoglycoprotein receptor.

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Development and application of a simple pharmacokinetic model that quantitatively describes the distribution and elimination of the commonly measured proteins

‘Failing to consider second and third order consequences is the cause of a lot of painfully bad decisions, and it is especially deadly when the first inferior option confirms your biases. Never seize on the first available option, no matter how good it seems, before you’ve asked questions and explored.’ In his 2017 book Principles: Life and Work, billionaire investor Ray Dalio urges readers to look past the results of an immediate decision (firstorder thinking). Secondorder thinking is the process of considering not just the immediate and direct consequences of a decision but also the potential secondorder effects (‘ripple’ effects), which may result from that decision. The merits of such thinking have been highlighted in fields such as behavioral economics as well as medicine. While this approach may be useful in a variety of situations, it can also lead to overestimating risks ultimately yielding poor firstorder decisions. These are the result of a variety of cognitive biases, including negativity bias, social influence, and complexity. Negativity bias is the tendency for negative information to weigh more heavily on one’s mind than positive or neutral information when making decisions. This skews the estimation of risk due to the outsized influence of potentially negative consequences or futility. While this can be a useful evolutionary tool in avoiding danger, when employing secondorder thinking it may dissuade clinicians from making obvious lowerrisk firstorder decisions for fear of rare but negative secondorder effects. In general, clinicians overestimate the burden of disease. For example, concern about rare complications (such as symptomatic intracranial hemorrhage) or futility from stroke thrombectomy may preclude neurointerventionalists from offering it to patients who would otherwise benefit. The benefits of thrombectomy are clear in many situations, while futility and complications are rarer. However, the Stroke treatment Assessments prior to thrombectomy in Neurointervention (SATIN) study demonstrated that neurointerventionalists overestimate the risk of futility in mechanical thrombectomy. It found that of those patients in whom thrombectomy was prospectively thought to be futile (ie, mRS 5–6), a good outcome (mRS 0–2) occurred in 10%. There are many drivers for this effect, although the authors found clinicians seemed to overestimate the effect of occlusion site (such as the basilar artery) and high National Institutes of Health Stroke Scale (NIHSS) score in their estimation of futility; such patients who underwent thrombectomy often had far better outcomes. The firstorder decision (thrombectomy or not) has high upside and low risk, but the secondorder decision (the outsized perception of futility or risk of complication) may have exerted substantial and undue influence on the decision to withhold thrombectomy. Not long ago ‘large core’ strokes fell into this trap and such patients were not offered thrombectomy due to concerns about futility and complication risk. Recent randomized trials have demonstrated that the firstorder effects (benefit from thrombectomy) clearly offset the secondorder effects (perceived risk of harm), changing the overall risk calculus. Social influence, also called ‘groupshift’ or ‘risk shift’ can also distort risk calculations. When surrounded by others who are also concerned about a particular risk, individuals tend to perceive that risk as being more significant than it actually is. Conversely, if the group is overall less concerned about risk, individuals’ risk assessments diminish. This can create a feedback loop where concerns feed off each other and grow more exaggerated over time. Previous studies have shown that interventionalists tend to accept more risks than noninterventionalists in hypothetical situations, and that groups that include more proceduralists are, perhaps not surprisingly, inclined to pursue interventions when compared with groups that include a balance of proceduralists and nonspecialists. Recent work surveying stroke clinicians (interventionalists and noninterventionalists) also demonstrate an increased appetite for risk in procedural specialties. This underscores the need for a multidisciplinary approach to neurointerventional decisionmaking, which will pull individuals toward a more reasoned approach rather than extremes of risk calculation. Finally, situational complexity can heavily influence decisions and risk perception. Risks tend to be overestimated when people are presented with complex and uncertain situations, as with many emergent situations regarding stroke treatment. As demonstrated in behavioral economics, when faced with a high degree of uncertainty, heuristics or mental shortcuts are often used to make decisions. Uncertainty increases in the face of increasing complexity, so more complicated patients may be considered higher risk without a thorough evaluation. As an example, patients with active cancer who presented with acute ischemic stroke were often considered more likely to have worse outcomes than those without, with implications for patient selection for mechanical thrombectomy such as exclusion from major stroke trials. 17 However, propensitymatched analysis of such patients demonstrates similar functional outcomes despite a higher risk of hemorrhagic transformation. Yet again, secondorder concerns for risk (in this case, influenced by patient complexity) should not overshadow the clear firstorder benefit of thrombectomy. Overall, secondorder thinking can be a valuable tool for decisionmaking, but the discussion above demonstrates situations in which decisionmaking can be affected by situational or implicit factors. By understanding how psychological and sociological factors can influence risk perceptions, we can work to make more informed and effective firstorder decisions. Clinicians should be considerate of these factors when making treatment decisions, and seek to not only ‘Do no harm’, but also ‘Keep it simple’.

Was it worth it?

Background: Penetrating crossbow head injuries are rare with no clear consensus regarding the optimal management paradigm for such injuries. We present three cases of crossbow injury to the head, with emphasis on the need for a comprehensive multidisciplinary management plan. Case Description: Three cases are presented of patients presenting with self-inflicted penetrating crossbow to head injuries. All three patients presented with intact neurological exam. A comprehensive multidisciplinary plan was created for all three cases with subsequent successful removal of the arrows. All three patients were discharged home with modified Rankin scale score of <2. Conclusion: Penetrating crossbow brain injuries are rare and require complex management. A comprehensive management strategy is necessary to manage these injuries. Moreover, careful consideration of factors such as the arrow trajectory, complexity of the injuries, and availability of the required expertise is important to increase the chances of success.

Michael Levitt

Papers

The VEBAS score: a practical scoring system for intracranial dural arteriovenous fistula obliteration

You’re so vein, you probably think this model’s about you: opportunities and challenges for computational fluid dynamics in cerebral venous disease

Development and application of a simple pharmacokinetic model that quantitatively describes the distribution and elimination of the commonly measured proteins

Was it worth it?

A case series of crossbow injury to the head highlighting the importance of an interdisciplinary management approach