The impact of hand movement velocity on cognitive conflict processing in a 3D object selection task in virtual reality.

Detecting and correcting incorrect body movements is an essential part of everyday interaction with one's environment. The human brain provides a monitoring system that constantly controls and adjusts our actions according to our surroundings. However, when our brain's predictions about a planned action do not match the sensory inputs resulting from that action, cognitive conflict occurs. Much is known about cognitive conflict in 1D/2D environments; however, less is known about the role of movement characteristics associated with cognitive conflict in 3D environment. Hence, we devised an object selection task in a virtual reality (VR) environment to test how the velocity of hand movements impacts human brain responses. From a series of analyses of EEG recordings synchronized with motion capture, we found that the velocity of the participants' hand movements modulated the brain's response to proprioceptive feedback during the task and induced a prediction error negativity (PEN). Additionally, the PEN originates in the anterior cingulate cortex and is itself modulated by the ballistic phase of the hand's movement. These findings suggest that velocity is an essential component of integrating hand movements with visual and proprioceptive information during interactions with real and virtual objects.

Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation.

Driver mental fatigue leads to thousands of traffic accidents. The increasing quality and availability of low-cost electroencephalogram (EEG) systems offer possibilities for practical fatigue monitoring. However, non-data-driven methods, designed for practical, complex situations, usually rely on handcrafted data statistics of EEG signals. To reduce human involvement, we introduce a data-driven methodology for online mental fatigue detection: self-weight ordinal regression (SWORE). Reaction time (RT), referring to the length of time people take to react to an emergency, is widely considered an objective behavioral measure for mental fatigue state. Since regression methods are sensitive to extreme RTs, we propose an indirect RT estimation based on preferences to explore the relationship between EEG and RT, which generalizes to any scenario when an objective fatigue indicator is available. In particular, SWORE evaluates the noisy EEG signals from multiple channels in terms of two states: shaking state and steady state. Modeling the shaking state can discriminate the reliable channels from the uninformative ones, while modeling the steady state can suppress the task-nonrelevant fluctuation within each channel. In addition, an online generalized Bayesian moment matching (online GBMM) algorithm is proposed to online-calibrate SWORE efficiently per participant. Experimental results with 40 participants show that SWORE can maximally achieve consistent with RT, demonstrating the feasibility and adaptability of our proposed framework in practical mental fatigue estimation.

Stochastic Multichannel Ranking with Brain Dynamics Preferences.

A driver's cognitive state of mental fatigue significantly affects his or her driving performance and more important, public safety. Previous studies have leveraged reaction time (RT) as the metric for mental fatigue and aim at estimating the exact value of RT using electroencephalogram (EEG) signals within a regression model. However, due to the easily corrupted and also nonsmooth properties of RTs during data collection, methods focusing on predicting the exact value of a noisy measurement, RT generally suffer from poor generalization performance. Considering that human RT is the reflection of brain dynamics preference (BDP) rather than a single regression output of EEG signals, we propose a novel channel-reliability-aware ranking (CArank) model for the multichannel ranking problem. CArank learns from BDPs using EEG data robustly and aims at preserving the ordering corresponding to RTs. In particular, we introduce a transition matrix to characterize the reliability of each channel used in the EEG data, which helps in learning with BDPs only from informative EEG channels. To handle large-scale EEG signals, we propose a stochastic-generalized expectation maximum (SGEM) algorithm to update CArank in an online fashion. Comprehensive empirical analysis on EEG signals from 40 participants shows that our CArank achieves substantial improvements in reliability while simultaneously detecting noisy or less informative EEG channels.

Spectral Narrowing Accompanies Enhanced Spatial Resolution in Saturated Coherent Anti-Stokes Raman Scattering (CARS): Comparisons of Experiment and Theory.

We demonstrate theoretically and confirm experimentally the mechanism by which spectral narrowing accompanies enhanced spatial resolution in a saturated coherent anti-Stokes Raman scattering (CARS) signal that is demodulated at the third harmonic (3f) of the pump modulation frequency (f). Under these modulation conditions, theory predicts a narrowing of the full width at half-maximum (FWHM) of the CARS spectrum by a factor of 2.0 with respect to that of the spectrum obtained by demodulation at the fundamental frequency. Theory also predicts an improvement of spatial resolution by a factor of 1.7. Experimentally, narrowing of the FWHM of the CARS spectrum of 1,4-bis((E)-2-methylstyryl) benzene (MSB) crystals by a factor of 2.5 is observed upon saturation. Further experimental confirmation is provided from investigating diamond particles, for which spectral narrowing was enhanced by a factor of 2.8 and spatial resolution was enhanced by a factor of 2. Details of the mechanism and execution of the saturated CARS experiment are elucidated and limits to its applicability are suggested, one of which is the conclusion that the saturation approach is not suitable for extraction of harmonics beyond 3f. In this work, we have developed a more comprehensive understanding of the correlation between the observed experimental results and experimental factors than has been previously reported.

Femtosecond Hydration Map of Intrinsically Disordered α-Synuclein.

Protein hydration water plays a fundamentally important role in protein folding, binding, assembly, and function. Little is known about the hydration water in intrinsically disordered proteins that challenge the conventional sequence-structure-function paradigm. Here, by combining experiments and simulations, we show the existence of dynamical heterogeneity of hydration water in an intrinsically disordered presynaptic protein, namely α-synuclein, implicated in Parkinson's disease. We took advantage of nonoccurrence of cysteine in the sequence and incorporated a number of cysteine residues at the N-terminal segment, the central amyloidogenic nonamyloid-ß component (NAC) domain, and the C-terminal end of α-synuclein. We then labeled these cysteine variants using environment-sensitive thiol-active fluorophore and monitored the solvation dynamics using femtosecond time-resolved fluorescence. The site-specific femtosecond time-resolved experiments allowed us to construct the hydration map of α-synuclein. Our results show the presence of three dynamically distinct types of water: bulk, hydration, and confined water. The amyloidogenic NAC domain contains dynamically restrained water molecules that are strikingly different from the water molecules present in the other two domains. Atomistic molecular dynamics simulations revealed longer residence times for water molecules near the NAC domain and supported our experimental observations. Additionally, our simulations allowed us to decipher the molecular origin of the dynamical heterogeneity of water in α-synuclein. These simulations captured the quasi-bound water molecules within the NAC domain originating from a complex interplay between the local chain compaction and the sequence composition. Our findings from this synergistic experimental simulation approach suggest longer trapping of interfacial water molecules near the amyloidogenic hotspot that triggers the pathological conversion into amyloids via chain sequestration, chain desolvation, and entropic liberation of ordered water molecules.

Prediction of cognitive conflict during unexpected robot behavior under different mental workload conditions in a physical human-robot collaboration.

Objective. Brain-computer interface (BCI) technology is poised to play a prominent role in modern work environments, especially a collaborative environment where humans and machines work in close proximity, often with physical contact. In a physical human robot collaboration (pHRC), the robot performs complex motion sequences. Any unexpected robot behavior or faulty interaction might raise safety concerns. Error-related potentials, naturally generated by the brain when a human partner perceives an error, have been extensively employed in BCI as implicit human feedback to adapt robot behavior to facilitate a safe and intuitive interaction. However, the integration of BCI technology with error-related potential for robot control demands failure-free integration of highly uncertain electroencephalography (EEG) signals, particularly influenced by the physical and cognitive state of the user. As a higher workload on the user compromises their access to cognitive resources needed for error awareness, it is crucial to study how mental workload variations impact the error awareness as it might raise safety concerns in pHRC. In this study, we aim to study how cognitive workload affects the error awareness of a human user engaged in a pHRC.Approach. We designed a blasting task with an abrasive industrial robot and manipulated the mental workload with a secondary arithmetic task of varying difficulty. EEG data, perceived workload, task and physical performance were recorded from 24 participants moving the robot arm. The error condition was achieved by the unexpected stopping of the robot in 33% of trials.Main results. We observed a diminished amplitude for the prediction error negativity (PEN) and error positivity (Pe), indicating reduced error awareness with increasing mental workload. We further observed an increased frontal theta power and increasing trend in the central alpha and central beta power after the unexpected robot stopping compared to when the robot stopped correctly at the target. We also demonstrate that a popular convolution neural network model, EEGNet, could predict the amplitudes of PEN and Pe from the EEG data prior to the error.Significance. This prediction model could be instrumental in developing an online prediction model that could forewarn the system and operators of the diminished error awareness of the user, alluding to a potential safety breach in error-related potential-based BCI system for pHRC. Therefore, our work paves the way for embracing BCI technology in pHRC to optimally adapt the robot behavior for personalized user experience using real-time brain activity, enriching the quality of the interaction.

An investigation into the effectiveness of using acoustic touch to assist people who are blind.

Wearable smart glasses are an emerging technology gaining popularity in the assistive technologies industry. Smart glasses aids typically leverage computer vision and other sensory information to translate the wearer's surrounding into computer-synthesized speech. In this work, we explored the potential of a new technique known as "acoustic touch" to provide a wearable spatial audio solution for assisting people who are blind in finding objects. In contrast to traditional systems, this technique uses smart glasses to sonify objects into distinct sound auditory icons when the object enters the device's field of view. We developed a wearable Foveated Audio Device to study the efficacy and usability of using acoustic touch to search, memorize, and reach items. Our evaluation study involved 14 participants, 7 blind or low-visioned and 7 blindfolded sighted (as a control group) participants. We compared the wearable device to two idealized conditions, a verbal clock face description and a sequential audio presentation through external speakers. We found that the wearable device can effectively aid the recognition and reaching of an object. We also observed that the device does not significantly increase the user's cognitive workload. These promising results suggest that acoustic touch can provide a wearable and effective method of sensory augmentation.

Efficacy of miltefosine in the treatment of visceral leishmaniasis in India after a decade of use.

BACKGROUND: Miltefosine is the only oral drug available for treatment of Indian visceral leishmaniasis (VL), which was shown to have an efficacy of 94% in a phase III trial in the Indian subcontinent. Its unrestricted use has raised concern about its continued effectiveness. This study evaluates the efficacy and safety of miltefosine for the treatment of VL after a decade of use in India. METHODS: An open-label, noncomparative study was performed in which 567 patients received oral miltefosine (50 mg for patients weighing <25 kg, 100 mg in divided doses for those weighing ≥25 kg, and 2.5 mg per kg for those aged <12 years, daily for 28 days) in a directly observed manner. Patients were followed up for 6 months to see the response to therapy. RESULTS: At the end of treatment the initial cure rate was 97.5% (intention to treat), and 6 months after the end of treatment the final cure rate was 90.3%. The overall death rate was 0.9% (5 of 567), and 2 deaths were related to drug toxicity. Gastrointestinal intolerance was frequent (64.5%). The drug was interrupted in 9 patients (1.5%) because of drug-associated adverse events. CONCLUSIONS: As compared to the phase III trial that led to registration of the drug a decade ago, there is a substantial increase in the failure rate of oral miltefosine for treatment of VL in India.

One-Step Sortase-Mediated Chemoenzymatic Semisynthesis of Deubiquitinase-Resistant Ub-Peptide Conjugates.

Post-translational modifications (PTMs) of proteins increase the functional diversity of the proteome and play crucial regulatory roles in cellular processes. Ubiquitination is a highly regulated and reversible PTM accomplished by a complex multistep process with the sequential action of several specific ubiquitinating (E1-E3) and deubiquitinating enzymes. The different types of ubiquitination (mono-, poly-mono-, and poly-) and the presence of several target sites in a single substrate add to its complexity, which makes the in vitro reconstitution of this ubiquitin (Ub) machinery a quite cumbersome process. Defects in components of the ubiquitination process also contribute to disease pathogenesis, especially cancer and neurodegeneration. This makes them of interest as potential therapeutic targets. Therefore, the development of efficient and reliable methods that will generate a highly homogeneous ubiquitinated peptide and protein conjugate is a topical subject area of research. In this report, we describe the development of a simple and efficient in vitro sortase-mediated chemoenzymatic strategy for semisynthesis of defined and homogeneous ubiquitin conjugates with more than 90% yield. This was achieved by engineering a sortase recognition motif in the dynamic C-terminus of ubiquitin and its conjugation to an isopeptide-linked di-Gly appended peptide LMFK(ε-GG)TEG corresponding to the ubiquitination site residues 383LMFKTEG389 of p53. The defined and homogeneous ubiquitin conjugates were also weighed for their recognition propensity by deubiquitinating enzymes. This facile semisynthesis of ubiquitin conjugates establishes a simple one-step sortase-mediated chemoenzymatic route for the synthesis of homogeneous and defined isopeptide-linked polypeptides and will help in understanding the complexity of the ubiquitination machinery as well as designing isopeptide drugs and therapeutics.

Conformational and Solvation Dynamics of an Amyloidogenic Intrinsically Disordered Domain of a Melanosomal Protein.

The conformational plasticity of intrinsically disordered proteins (IDPs) allows them to adopt a range of conformational states that can be important for their biological functions. The driving force for the conformational preference of an IDP emanates from an intricate interplay between chain-chain and chain-solvent interactions. Using ultrafast femtosecond and picosecond time-resolved fluorescence measurements, we characterized the conformational and solvation dynamics around the N- and C-terminal segments of a disordered repeat domain of a melanosomal protein Pmel17 that forms functional amyloid responsible for melanin biosynthesis. Our time-resolved fluorescence anisotropy results revealed slight compaction and slower rotational dynamics around the amyloidogenic C-terminal segment when compared to the proline-rich N-terminal segment of the repeat domain. The compaction of the C-terminal region was also associated with the restrained mobility of hydration water as indicated by our solvation dynamics measurements. Our findings indicate that sequence-dependent chain-solvent interactions govern both the conformational and solvation dynamics that are crucial in directing the conversion of a highly dynamic IDP into an ordered amyloid assembly. Such an interplay of amino acid composition-dependent conformational and solvation dynamics might have important physicochemical consequences in specific water-protein, ion-protein, and protein-protein interactions involved in amyloid formation and phase transitions.

Unraveling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks.

Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators' performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just "when" but also "what" to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments.

A Functional Model for Unifying Brain Computer Interface Terminology.

Brain Computer Interface (BCI) technology is a critical area both for researchers and clinical practitioners. The IEEE P2731 working group is developing a comprehensive BCI lexicography and a functional model of BCI. The glossary and the functional model are inextricably intertwined. The functional model guides the development of the glossary. Terminology is developed from the basis of a BCI functional model. This paper provides the current status of the P2731 working group's progress towards developing a BCI terminology standard and functional model for the IEEE.

One-Step Synthesized ZnO np-Based Optical Sensors for Detection of Aldicarb via a Photoinduced Electron Transfer Route.

Pesticides are used in agriculture for crop production enhancement by controlling pests, but they have acute toxicological effects on other life forms. Thus, it becomes imperative to detect their concentration in food products in a fast and accurate manner. In this study, ZnO nanoparticles (ZnO nps) have been used as optical sensors for the detection of pesticide Aldicarb via a photoinduced electron transfer (PET) route. ZnO nps were synthesized directly by calcining zinc acetate at 450, 500, and 550 °C for 2 h. ZnO nps were characterized by X-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and UV-vis absorption and photoluminescence (PL) spectroscopies to study the phase, crystallinity, shape, morphology, absorbance, and fluorescence of the prepared ZnO nps. XRD and Raman studies confirmed the crystalline nature of ZnO nps. The average crystallite size obtained was 13-20 nm from the XRD study. The SEM study confirmed spherical-shaped ZnO nps with average sizes in the range of 70-150 nm. The maximum absorbance was obtained in the 200-500 nm regions with a prominent peak absorbance at 372 nm from UV-vis spectra. The corresponding band gap for ZnO nps was calculated using Tauc's plots and was found to be 3.8, 3.67, and 3.45 eV for the 450, 500, and 550 °C calcined samples, respectively. The fluorescence spectra showed an increase in the intensity along with the increase in the size of ZnO nps. The ZnO nps (samples calcined at 500 and 550 °C) exhibited a response toward Aldicarb, owing to their pure phase and higher PL intensity. Both the samples showed systematic detection of Aldicarb in the range of 250 pM to 2 nM (500 °C) and 250 pM to 5 nM (550 °C). Among the various quenching mechanisms, PET was found to be the dominant process for the detection of Aldicarb. This method can be used for the detection of Aldicarb in real (food) samples using a portable fluorimeter.

Evaluation of the Effectiveness of a Novel Brain-Computer Interface Neuromodulative Intervention to Relieve Neuropathic Pain Following Spinal Cord Injury: Protocol for a Single-Case Experimental Design With Multiple Baselines.

BACKGROUND: Neuropathic pain is a debilitating secondary condition for many individuals with spinal cord injury. Spinal cord injury neuropathic pain often is poorly responsive to existing pharmacological and nonpharmacological treatments. A growing body of evidence supports the potential for brain-computer interface systems to reduce spinal cord injury neuropathic pain via electroencephalographic neurofeedback. However, further studies are needed to provide more definitive evidence regarding the effectiveness of this intervention. OBJECTIVE: The primary objective of this study is to evaluate the effectiveness of a multiday course of a brain-computer interface neuromodulative intervention in a gaming environment to provide pain relief for individuals with neuropathic pain following spinal cord injury. METHODS: We have developed a novel brain-computer interface-based neuromodulative intervention for spinal cord injury neuropathic pain. Our brain-computer interface neuromodulative treatment includes an interactive gaming interface, and a neuromodulation protocol targeted to suppress theta (4-8 Hz) and high beta (20-30 Hz) frequency powers, and enhance alpha (9-12 Hz) power. We will use a single-case experimental design with multiple baselines to examine the effectiveness of our self-developed brain-computer interface neuromodulative intervention for the treatment of spinal cord injury neuropathic pain. We will recruit 3 participants with spinal cord injury neuropathic pain. Each participant will be randomly allocated to a different baseline phase (ie, 7, 10, or 14 days), which will then be followed by 20 sessions of a 30-minute brain-computer interface neuromodulative intervention over a 4-week period. The visual analog scale assessing average pain intensity will serve as the primary outcome measure. We will also assess pain interference as a secondary outcome domain. Generalization measures will assess quality of life, sleep quality, and anxiety and depressive symptoms, as well as resting-state electroencephalography and thalamic γ-aminobutyric acid concentration. RESULTS: This study was approved by the Human Research Committees of the University of New South Wales in July 2019 and the University of Technology Sydney in January 2020. We plan to begin the trial in October 2020 and expect to publish the results by the end of 2021. CONCLUSIONS: This clinical trial using single-case experimental design methodology has been designed to evaluate the effectiveness of a novel brain-computer interface neuromodulative treatment for people with neuropathic pain after spinal cord injury. Single-case experimental designs are considered a viable alternative approach to randomized clinical trials to identify evidence-based practices in the field of technology-based health interventions when recruitment of large samples is not feasible. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000556943; https://bit.ly/2RY1jRx. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/20979.

Use of reteplase for thrombolysis in patients with massive pulmonary embolism diagnosed by bedside transthoracic echocardiography: A retrospective study of safety and efficacy.

BACKGROUND: Pulmonary embolism (PE) is a lethal clinical condition requiring immediate systemic thrombolysis to decrease mortality. Reteplase has been extensively used in acute myocardial infarction but studies in massive PE are rare. We have presented here efficacy and safety of reteplase in patients with high risk PE diagnosed on basis of bedside transthoracic echocardiography. METHODS: This was retrospective study including 20 patients of massive PE undergoing thrombolysis with reteplase. Bedside TTE was used to evaluate presence of RV dysfunction and thrombi in these patients with hemodynamic compromise. Safety and efficacy outcomes were analysed till three months of follow up. RESULTS: 12 patients (60%) included in the study were males and mean age was 41 ± 19 years. The dyspnoea, chest pain and haemoptysis improved in all patients after thrombolysis. At discharge, RV dilatation normalised, systolic pulmonary artery pressure decreased, systolic blood pressure significantly increased and hypoxemia had completely corrected. Two patients had minor self-limiting bleeding episodes in form of mild haematuria and oral bleeding. During the follow up period of 3 months all patients were clinically stable and there were no bleeding episodes or death. Moreover, there was no recurrence of PE and/or DVT. CONCLUSION: Reteplase is highly efficacious in massive pulmonary embolism and results in rapid clinical improvement. Moreover, it can be safely used without increased risk of significant bleeding or mortality. Although limited by retrospective nature, reteplase appears to be an attractive option for massive PE but large prospective studies are further required.

Water Rearrangements upon Disorder-to-Order Amyloid Transition.

Water plays a critical role in governing the intricate balance between chain-chain and chain-solvent interactions during protein folding, misfolding, and aggregation. Previous studies have indicated the presence of different types of water in folded (globular) proteins. In this work, using femtosecond and picosecond time-resolved fluorescence measurements, we have characterized the solvation dynamics from ultrafast to ultraslow time scale both in the monomeric state and in the amyloid state of an intrinsically disordered protein, namely κ-casein. Monomeric κ-casein adopts a compact disordered state under physiological conditions and is capable of spontaneously aggregating into highly ordered ß-rich amyloid fibrils. Our results indicate that the mobility of "biological water" (type I) gets restrained as a result of conformational sequestration during amyloid formation. Additionally, a significant decrease in the bulk water component with a concomitant increase in the ultraslow component revealed the ordering of trapped interstitial water (type II) upon disorder-to-order amyloid transition. Our results provide an experimental underpinning of significant water rearrangements associated with both chain desolvation and water confinement upon amyloid formation.

Emergence of multidrug resistant acinetobacter blood stream infections in febrile neutropenia patients with haematological cancers and bone marrow failure syndromes.

Acinetobacter infections are fast emerging as a major nosocomial threat across the globe. With a predilection for blood stream infections in critically ill, immunocompromised patients, their presence is now being felt in febrile neutropenics with underlying malignancies and marrow failure. We aimed through this study to ascertain the current circulating pathogens and levels of antimicrobial resistance in blood stream infections in febrile neutropenia patients, with specific emphasis on elucidating acinetobacter and pseudomonas infections. Clinical and laboratory records of all consecutive neutropenic patients with underlying haematological malignancies and marrow failure, admitted to our AIIMS, New Delhi from April 2009 to March 2010 were analysed for blood stream infections, pathogen profiles and antimicrobial resistance. All clinical and microbiological variables were statistically analysed to elucidate potential risk factors, infection patterns and drug resistance trends. Of the 1,165 blood cultures investigated, 105 episodes of blood stream infections were microbiologically confirmed in febrile neutropenia patients. Gram-negative infections (n = 78, 72.9%) dominated with acinetobacter spp (n = 20, 18.7%) emerging as the most common pathogen. Acinetobacter and pseudomonas together were responsible for 42.9% of all blood stream infections. Both acinetobacter and pseudomonas displayed very high resistance to all five major classes of antibiotics, including multidrug resistance (90.0% and 76.9%) and ESBL production (90.0% and 84.6%), respectively. Comparison of infection patterns and resistance levels with reports over the past decade from this centre and other centres across the globe, revealed a striking increase in multidrug resistant acinetobacter blood stream infections in these patients. Multidrug resistant acinetobacter Infections are a fast emerging threat in febrile neutropenia patients and at this centre in general. Similar early trends from some Indian centres and neighbouring developing countries suggest grave concern. These emerging circulating pathogens and drug resistance patterns demand to systematically evaluate antibiotic and hospital infection policies and to sensitise all clinicians to curb this pathogen capable of rapid nosocomial spread.