Precise and Programmable Detection of Mutations Using Ultraspecific Riboregulators.

The ability to identify single-nucleotide mutations is critical for probing cell biology and for precise detection of disease. However, the small differences in hybridization energy provided by single-base changes makes identification of these mutations challenging in living cells and complex reaction environments. Here, we report a class of de novo-designed prokaryotic riboregulators that provide ultraspecific RNA detection capabilities in vivo and in cell-free transcription-translation reactions. These single-nucleotide-specific programmable riboregulators (SNIPRs) provide over 100-fold differences in gene expression in response to target RNAs differing by a single nucleotide in E. coli and resolve single epitranscriptomic marks in vitro. By exploiting the programmable SNIPR design, we implement an automated design algorithm to develop riboregulators for a range of mutations associated with cancer, drug resistance, and genetic disorders. Integrating SNIPRs with portable paper-based cell-free reactions enables convenient isothermal detection of cancer-associated mutations from clinical samples and identification of Zika strains through unambiguous colorimetric reactions.

Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP.

Toehold switches: de-novo-designed regulators of gene expression.

Efforts to construct synthetic networks in living cells have been hindered by the limited number of regulatory components that provide wide dynamic range and low crosstalk. Here, we report a class of de-novo-designed prokaryotic riboregulators called toehold switches that activate gene expression in response to cognate RNAs with arbitrary sequences. Toehold switches provide a high level of orthogonality and can be forward engineered to provide average dynamic range above 400. We show that switches can be integrated into the genome to regulate endogenous genes and use them as sensors that respond to endogenous RNAs. We exploit the orthogonality of toehold switches to regulate 12 genes independently and to construct a genetic circuit that evaluates 4-input AND logic. Toehold switches, with their wide dynamic range, orthogonality, and programmability, represent a versatile and powerful platform for regulation of translation, offering diverse applications in molecular biology, synthetic biology, and biotechnology.

Paper-based synthetic gene networks.

Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides an alternate, versatile venue for synthetic biologists to operate and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze dried onto paper, enabling the inexpensive, sterile, and abiotic distribution of synthetic-biology-based technologies for the clinic, global health, industry, research, and education. For field use, we create circuits with colorimetric outputs for detection by eye and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small-molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors.

A Randomized Crossover Trial Evaluating the Impact of Cultural Dexterity Training on Surgical Residents' Knowledge, Cross-Cultural Care, Skills, and Beliefs: The Provider Awareness and Cultural Dexterity Training for Surgeons (PACTS) Trial.

OBJECTIVES: This trial examines the impact of the Provider Awareness and Cultural dexterity Toolkit for Surgeons (PACTS) curriculum on surgical residents' knowledge, cross-cultural care, skills, and beliefs. BACKGROUND: Cross-cultural training of providers may reduce health care outcome disparities, but its effectiveness in surgical trainees is unknown. METHODS: PACTS focuses on developing skills needed for building trust, working with patients with limited English proficiency, optimizing informed consent, and managing pain. The PACTS trial was a randomized crossover trial of 8 academic general surgery programs in the United States: The Early group ("Early") received PACTS between periods 1 and 2, while the Delayed group ("Delayed") received PACTS between periods 2 and 3. Residents were assessed preintervention and postintervention on Knowledge, Cross-Cultural Care, Self-Assessed Skills, and Beliefs. χ 2 and Fisher exact tests were conducted to evaluate within-intervention and between-intervention group differences. RESULTS: Of 406 residents enrolled, 315 were exposed to the complete PACTS curriculum. Early residents' Cross-Cultural Care (79.6%-88.2%, P <0.0001), Self-Assessed Skills (74.5%--85.0%, P <0.0001), and Beliefs (89.6%-92.4%, P =0.0028) improved after PACTS; knowledge scores (71.3%-74.3%, P =0.0661) were unchanged. Delayed resident scores pre-PACTS to post-PACTS showed minimal improvements in all domains. When comparing the 2 groups in period 2, Early residents had modest improvement in all 4 assessment areas, with a statistically significant increase in Beliefs (92.4% vs 89.9%, P =0.0199). CONCLUSIONS: The PACTS curriculum is a comprehensive tool that improved surgical residents' knowledge, preparedness, skills, and beliefs, which will help with caring for diverse patient populations.

Spatiotemporal signal space separation for regions of interest: Application for extracting neuromagnetic responses evoked by deep brain stimulation.

Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources may spatially extend (known as source leakage) into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large-scale cortical networks. In this technical report, we develop a novel denoising approach for suppressing the leakage of interference source activity into the activity representing a brain region of interest. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We apply this denoising approach to reconstruct simulated evoked response topographies to deep brain stimulation (DBS) in a phantom recording. We highlight the advantages of our approach compared to the benchmark-spatiotemporal signal space separation-and show that it can more accurately reveal brain stimulation-evoked response topographies. Finally, we apply our method to MEG recordings from a single patient with Parkinson's disease, to reveal early cortical-evoked responses to DBS of the subthalamic nucleus.

Near-infrared spectroscopy as a novel method of ex vivo bladder cancer tissue characterisation.

OBJECTIVE: To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. PATIENTS AND METHODS: A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. RESULTS: A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. CONCLUSIONS: This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.

Safety of robotic cholecystectomy as index training procedure: the UK experience.

AIMS: To evaluate the safety profile of robotic cholecystectomy performed within the United Kingdom (UK) Robotic Hepatopancreatobiliary (HPB) training programme. METHODS: A retrospective evaluation of prospectively collected data from eleven centres participating in the UK Robotic HPB training programme was conducted. All adult patients undergoing robotic cholecystectomy for symptomatic gallstone disease or gallbladder polyp were considered. Bile duct injury, conversion to open procedure, conversion to subtotal cholecystectomy, length of hospital stay, 30-day re-admission, and post-operative complications were the evaluated outcome parameters. RESULTS: A total of 600 patients were included. The median age was 53 (IQR 65-41) years and the majority (72.7%; 436/600) were female. The main indications for robotic cholecystectomy were biliary colic (55.5%, 333/600), cholecystitis (18.8%, 113/600), gallbladder polyps (7.7%, 46/600), and pancreatitis (6.2%, 37/600). The median length of stay was 0 (IQR 0-1) days. Of the included patients, 88.5% (531/600) were discharged on the day of procedure with 30-day re-admission rate of 5.5% (33/600). There were no bile duct injuries and the rate of conversion to open was 0.8% (5/600) with subtotal cholecystectomy rate of 0.8% (5/600). CONCLUSION: The current study confirms that robotic cholecystectomy can be safely implemented to routine practice with a low risk of bile duct injury, low bile leak rate, low conversion to open surgery, and low need for subtotal cholecystectomy.

Evaluation of 3D C-Arm Fluoroscopy versus Diagnostic CT for Deep Brain Stimulation Stereotactic Registration and Post-Operative Lead Localization.

INTRODUCTION: DBS efficacy depends on accuracy. CT-MRI fusion is established for both stereotactic registration and electrode placement verification. The desire to streamline DBS workflows, reduce operative time, and minimize patient transfers has increased interest in portable imaging modalities such as the Medtronic O-arm® and mobile CT. However, these remain expensive and bulky. 3D C-arm fluoroscopy (3DXT) units are a smaller and less costly alternative, albeit incompatible with traditional frame-based localization and without useful soft tissue resolution. We aimed to compare fusion of 3DXT and CT with pre-operative MRI to evaluate if 3DXT-MRI fusion alone is sufficient for accurate registration and reliable targeting verification. We further assess DBS targeting accuracy using a 3DXT workflow and compare radiation dosimetry between modalities. METHODS: Patients underwent robot-assisted DBS implantation using a workflow incorporating 3DXT which we describe. Two intra-operative 3DXT spins were performed for registration and accuracy verification followed by conventional CT post-operatively. Post-operative 3DXT and CT images were independently fused to the same pre-operative MRI sequence and co-ordinates generated for comparison. Registration accuracy was compared to 15 consecutive controls who underwent CT-based registration. Radial targeting accuracy was calculated and radiation dosimetry recorded. RESULTS: Data were obtained from 29 leads in 15 consecutive patients. 3DXT registration accuracy was significantly superior to CT with mean error 0.22 ± 0.03 mm (p < 0.0001). Mean Euclidean electrode tip position variation for CT to MRI versus 3DXT to MRI fusion was 0.62 ± 0.40 mm (range 0.0 mm-1.7 mm). In comparison, direct CT to 3DXT fusion showed electrode tip Euclidean variance of 0.23 ± 0.09 mm. Mean radial targeting accuracy assessed on 3DXT was 0.97 ± 0.54 mm versus 1.15 ± 0.55 mm on CT with differences insignificant (p = 0.30). Mean patient radiation doses were around 80% lower with 3DXT versus CT (p < 0.0001). DISCUSSION: Mobile 3D C-arm fluoroscopy can be safely incorporated into DBS workflows for both registration and lead verification. For registration, the limited field of view requires the use of frameless transient fiducials and is highly accurate. For lead position verification based on MRI co-registration, we estimate there is around a 0.4 mm discrepancy between lead position seen on 3DXT versus CT when corrected for brain shift. This is similar to that described in O-arm® or mobile CT series. For units where logistical or financial considerations preclude the acquisition of a cone beam CT or mobile CT scanner, our data support portable 3D C-arm fluoroscopy as an acceptable alternative with significantly lower radiation exposure.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation.

BACKGROUND AND OBJECTIVES: Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers. MATERIALS AND METHODS: We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation. RESULTS: High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment. CONCLUSIONS: High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming.

Probabilistic Mapping Reveals Optimal Stimulation Site in Essential Tremor.

OBJECTIVE: The objective of this study was to obtain individual clinical and neuroimaging data of patients undergoing deep brain stimulation (DBS) for essential tremor (ET) from 5 different European centers to identify predictors of outcome and to identify an optimal stimulation site. METHODS: We analyzed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (for 12 months) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data were used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement. RESULTS: Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement >50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural connectivity-based cerebellothalamic tract (CTT). The combined features "distance between the stimulation volume and the significant cluster" and "CTT activation" were used as a predictor of tremor improvement. This correctly classified a >50% tremor improvement with a sensitivity of 89% and a specificity of 57%. INTERPRETATION: Our multicenter ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of DBS in the future. ANN NEUROL 2022;91:602-612.

Predictable control of RNA lifetime using engineered degradation-tuning RNAs.

The ability to tune RNA and gene expression dynamics is greatly needed for biotechnological applications. Native RNA stabilizers or engineered 5' stability hairpins have been used to regulate transcript half-life to control recombinant protein expression. However, these methods have been mostly ad hoc and hence lack predictability and modularity. Here, we report a library of RNA modules called degradation-tuning RNAs (dtRNAs) that can increase or decrease transcript stability in vivo and in vitro. dtRNAs enable modulation of transcript stability over a 40-fold dynamic range in Escherichia coli with minimal influence on translation initiation. We harness dtRNAs in messenger RNAs and noncoding RNAs to tune gene circuit dynamics and enhance CRISPR interference in vivo. Use of stabilizing dtRNAs in cell-free transcription-translation reactions also tunes gene and RNA aptamer production. Finally, we combine dtRNAs with toehold switch sensors to enhance the performance of paper-based norovirus diagnostics, illustrating the potential of dtRNAs for biotechnological applications.

Complex cellular logic computation using ribocomputing devices.

Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our 'ribocomputing' systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.

Towards a point-of-care multimodal spectroscopy instrument for the evaluation of human cardiac tissue.

To demonstrate that point-of-care multimodal spectroscopy using Near-Infrared (NIR) and Raman Spectroscopy (RS) can be used to diagnose human heart tissue. We generated 105 spectroscopic scans, which comprised 4 NIR and 3 RS scans per sample to generate a "multimodal spectroscopic scan" (MSS) for each heart, done across 15 patients, 5 each from the dilated cardiomyopathy (DCM), Ischaemic Heart Disease (IHD) and Normal pathologies. Each of the MSS scans was undertaken in 3 s. Data were entered into machine learning (ML) algorithms to assess accuracy of MSS in diagnosing tissue type. The median age was 50 years (IQR 49-52) for IHD, 47 (IQR 45-50) for DCM and 36 (IQR 33-52) for healthy patients (p = 0.35), 60% of which were male. MSS identified key differences in IHD, DCM and normal heart samples in regions typically associated with fibrosis and collagen (NIR wavenumbers: 1433, 1509, 1581, 1689 and 1725 nm; RS wavelengths: 1658, 1450 and 1330 cm-1). In principal component (PC) analyses, these differences explained 99.2% of the variation in 4 PCs for NIR, 81.6% in 10 PCs for Raman, and 99.0% in 26 PCs for multimodal spectroscopic signatures. Using a stack machine learning algorithm with combined NIR and Raman data, our model had a precision of 96.9%, recall of 96.6%, specificity of 98.2% and Area Under Curve (AUC) of 0.989 (Table 1). NIR and Raman modalities alone had similar levels of precision at 94.4% and 89.8% respectively (Table 1). MSS combined with ML showed accuracy of 90% for detecting dilated cardiomyopathy, 100% for ischaemic heart disease and 100% for diagnosing healthy tissue. Multimodal spectroscopic signatures, based on NIR and Raman spectroscopy, could provide cardiac tissue scans in 3-s to aid accurate diagnoses of fibrosis in IHD, DCM and normal hearts. Table 1 Machine learning performance metrics for validation data sets of (a) Near-Infrared (NIR), (b) Raman and (c and d) multimodal data using logistic regression (LR), stochastic gradient descent (SGD) and support vector machines (SVM), with combined "stack" (LR + SGD + SVM) AUC Precision Recall Specificity (a) NIR model  Logistic regression 0.980 0.944 0.933 0.967  SGD 0.550 0.281 0.400 0.700  SVM 0.840 0.806 0.800 0.900  Stack 0.933 0.794 0.800 0.900 (b) Raman model  Logistic regression 0.985 0.940 0.929 0.960  SGD 0.892 0.869 0.857 0.932  SVM 0.992 0.940 0.929 0.960  Stack 0.954 0.869 0.857 0.932 (c) MSS: multimodal (NIR + Raman) to detect DCM vs. IHD vs. normal patients  Logistic regression 0.975 0.841 0.828 0.917  SGD 0.847 0.803 0.793 0.899  SVM 0.971 0.853 0.828 0.917  Stack 0.961 0.853 0.828 0.917 (d) MSS: multimodal (NIR + Raman) to detect pathological vs. normal patients  Logistic regression 0.961 0.969 0.966 0.984  SGD 0.944 0.967 0.966 0.923  SVM 1.000 1.000 1.000 1.000  Stack 1.000 0.944 0.931 0.969 Bold values indicate values obtained from the stack algorithm and used for analyses.

Deep Brain Stimulation and Levodopa Affect Gait Variability in Parkinson Disease Differently.

BACKGROUND: Both dopaminergic medication and subthalamic nucleus (STN) deep brain stimulation (DBS) can improve the amplitude and speed of gait in Parkinson disease (PD), but relatively little is known about their comparative effects on gait variability. Gait irregularity has been linked to the degeneration of cholinergic neurons in the pedunculopontine nucleus (PPN). OBJECTIVES: The STN and PPN have reciprocal connections, and we hypothesized that STN DBS might improve gait variability by modulating PPN function. Dopaminergic medication should not do this, and we therefore sought to compare the effects of medication and STN DBS on gait variability. MATERIALS AND METHODS: We studied 11 patients with STN DBS systems on and off with no alteration to their medication, and 15 patients with PD without DBS systems on and off medication. Participants walked for two minutes in each state, wearing six inertial measurement units. Variability has previously often been expressed in terms of SD or coefficient of variation over a testing session, but these measures conflate long-term variability (eg, gradual slowing, which is not necessarily pathological) with short-term variability (true irregularity). We used Poincaré analysis to separate the short- and long-term variability. RESULTS: DBS decreased short-term variability in lower limb gait parameters, whereas medication did not have this effect. In contrast, STN DBS had no effect on arm swing and trunk motion variability, whereas medication increased them, without obvious dyskinesia. CONCLUSIONS: Our results suggest that STN DBS acts through a nondopaminergic mechanism to reduce gait variability. We believe that the most likely explanation is the retrograde activation of cholinergic PPN projection neurons.

Gait-Phase Modulates Alpha and Beta Oscillations in the Pedunculopontine Nucleus.

The pedunculopontine nucleus (PPN) is a reticular collection of neurons at the junction of the midbrain and pons, playing an important role in modulating posture and locomotion. Deep brain stimulation of the PPN has been proposed as an emerging treatment for patients with Parkinson's disease (PD) or multiple system atrophy (MSA) who have gait-related atypical parkinsonian syndromes. In this study, we investigated PPN activities during gait to better understand its functional role in locomotion. Specifically, we investigated whether PPN activity is rhythmically modulated by gait cycles during locomotion. PPN local field potential (LFP) activities were recorded from PD or MSA patients with gait difficulties during stepping in place or free walking. Simultaneous measurements from force plates or accelerometers were used to determine the phase within each gait cycle at each time point. Our results showed that activities in the alpha and beta frequency bands in the PPN LFPs were rhythmically modulated by the gait phase within gait cycles, with a higher modulation index when the stepping rhythm was more regular. Meanwhile, the PPN-cortical coherence was most prominent in the alpha band. Both gait phase-related modulation in the alpha/beta power and the PPN-cortical coherence in the alpha frequency band were spatially specific to the PPN and did not extend to surrounding regions. These results suggest that alternating PPN modulation may support gait control. Whether enhancing alternating PPN modulation by stimulating in an alternating fashion could positively affect gait control remains to be tested.SIGNIFICANCE STATEMENT The therapeutic efficacy of pedunculopontine nucleus (PPN) deep brain stimulation (DBS) and the extent to which it can improve quality of life are still inconclusive. Understanding how PPN activity is modulated by stepping or walking may offer insight into how to improve the efficacy of PPN DBS in ameliorating gait difficulties. Our study shows that PPN alpha and beta activity was modulated by the gait phase, and that this was most pronounced when the stepping rhythm was regular. It remains to be tested whether enhancing alternating PPN modulation by stimulating in an alternating fashion could positively affect gait control.

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

Cervical dystonia is a non-degenerative movement disorder characterized by dysfunction of both motor and sensory cortico-basal ganglia networks. Deep brain stimulation targeted to the internal pallidum is an established treatment, but its specific mechanisms remain elusive, and response to therapy is highly variable. Modulation of key dysfunctional networks via axonal connections is likely important. Fifteen patients underwent preoperative diffusion-MRI acquisitions and then progressed to bilateral deep brain stimulation targeting the posterior internal pallidum. Severity of disease was assessed preoperatively and later at follow-up. Scans were used to generate tractography-derived connectivity estimates between the bilateral regions of stimulation and relevant structures. Connectivity to the putamen correlated with clinical improvement, and a series of cortical connectivity-based putaminal parcellations identified the primary motor putamen as the key node (r = 0.70, P = 0.004). A regression model with this connectivity and electrode coordinates explained 68% of the variance in outcomes (r = 0.83, P = 0.001), with both as significant explanatory variables. We conclude that modulation of the primary motor putamen-posterior internal pallidum limb of the cortico-basal ganglia loop is characteristic of successful deep brain stimulation treatment of cervical dystonia. Preoperative diffusion imaging contains additional information that predicts outcomes, implying utility for patient selection and/or individualized targeting.

The Neurostimulation Appropriateness Consensus Committee (NACC): Recommendations for Surgical Technique for Spinal Cord Stimulation.

INTRODUCTION: The field of neurostimulation for the treatment of chronic pain is a rapidly developing area of medicine. Although neurostimulation therapies have advanced significantly as a result of technologic improvements, surgical planning, device placement, and postoperative care are of equal importance to optimize outcomes. This Neurostimulation Appropriateness Consensus Committee (NACC) project intends to provide evidence-based guidance for these often-overlooked areas of neurostimulation practice. MATERIALS AND METHODS: Authors were chosen based on their clinical expertise, familiarity with the peer-reviewed literature, research productivity, and contributions to the neuromodulation literature. Section leaders supervised literature searches of MEDLINE, BioMed Central, Current Contents Connect, Embase, International Pharmaceutical Abstracts, Web of Science, Google Scholar, and PubMed from the last NACC publication in 2017 to the present. Identified studies were graded using the United States Preventive Services Task Force criteria for evidence and certainty of net benefit. Recommendations are based on evidence strength and consensus when evidence was scant. RESULTS: This NACC project provides guidance on preoperative assessment, intraoperative techniques, and postoperative management in the form of consensus points with supportive evidence. These results are based on grade of evidence, strength of consensus, and expert opinion. CONCLUSIONS: The NACC has given guidance for a surgical plan that encompasses the patient journey from the planning stage through the surgical experience and postoperative care. The overall recommendations are designed to improve efficacy and the safety of patients undergoing these neuromodulation procedures and are intended to apply throughout the international community.

The Neurostimulation Appropriateness Consensus Committee (NACC): Recommendations on Best Practices for Cervical Neurostimulation.

INTRODUCTION: The International Neuromodulation Society convened a multispecialty group of physicians based on expertise with international representation to establish evidence-based guidance on the use of neurostimulation in the cervical region to improve outcomes. This Neurostimulation Appropriateness Consensus Committee (NACC) project intends to provide evidence-based guidance for an often-overlooked area of neurostimulation practice. MATERIALS AND METHODS: Authors were chosen based upon their clinical expertise, familiarity with the peer-reviewed literature, research productivity, and contributions to the neuromodulation literature. Section leaders supervised literature searches of MEDLINE, BioMed Central, Current Contents Connect, Embase, International Pharmaceutical Abstracts, Web of Science, Google Scholar, and PubMed from 2017 (when NACC last published guidelines) to the present. Identified studies were graded using the US Preventive Services Task Force criteria for evidence and certainty of net benefit. Recommendations are based on the strength of evidence or consensus when evidence was scant. RESULTS: The NACC examined the published literature and established evidence- and consensus-based recommendations to guide best practices. Additional guidance will occur as new evidence is developed in future iterations of this process. CONCLUSIONS: The NACC recommends best practices regarding the use of cervical neuromodulation to improve safety and efficacy. The evidence- and consensus-based recommendations should be utilized as a guide to assist decision making when clinically appropriate.