From Promise to Practice: Recent Growth in 30 Years of Tissue Engineering Commercialization.

This perspective, marking the 30th anniversary of the Tissue Engineering journal, discusses the exciting trends in the global commercialization of tissue engineering technology. Within a historical context, we present an evolution of challenges and a discussion of the last 5 years of global commercial successes and emerging market trends, highlighting the continued expansion of the field in the northeastern United States. This leads to an overview of the last 5 years' progress in clinical trials for tissue-engineered therapeutics, including an analysis of trends in success and failure. Finally, we provide a broad overview of preclinical research and a perspective on where the state-of-the-art lies on the horizon.

Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population.

Determination of prognosis in the triage process after traumatic brain injury (TBI) is difficult to achieve. Current severity measures like the Trauma and injury severity score (TRISS) and revised trauma score (RTS) rely on additional information from the Glasgow Coma Scale (GCS) and the Injury Severity Score (ISS) which may be inaccurate or delayed, limiting their usefulness in the rapid triage setting. We hypothesized that machine learning based estimations of GCS and ISS obtained through modeling of continuous vital sign features could be used to rapidly derive an automated RTS and TRISS. We derived variables from electrocardiograms (ECG), photoplethysmography (PPG), and blood pressure using continuous data obtained in the first 15 min of admission to build machine learning models of GCS and ISS (ML-GCS and ML-ISS). We compared the TRISS and RTS using ML-ISS and ML-GCS and its value using the actual ISS and GCS in predicting in-hospital mortality. Models were tested in TBI with systemic injury (head abbreviated injury scale (AIS) ≥ 1), and isolated TBI (head AIS ≥ 1 and other AIS ≤ 1). The area under the receiver operating characteristic curve (AUROC) was used to evaluate model performance. A total of 21,077 cases (2009-2015) were in the training set. 6057 cases from 2016 to 2017 were used for testing, with 472 (7.8%) severe TBI (GCS 3-8), 223 (3.7%) moderate TBI (GCS 9-12), and 5913 (88.5%) mild TBI (GCS 13-15). In the TBI with systemic injury group, ML-TRISS had similar AUROC (0.963) to TRISS (0.965) in predicting mortality. ML-RTS had AUROC (0.823) and RTS had AUROC 0.928. In the isolated TBI group, ML-TRISS had AUROC 0.977, and TRISS had AUROC 0.983. ML-RTS had AUROC 0.790 and RTS had AUROC 0.957. Estimation of ISS and GCS from machine learning based modeling of vital sign features can be utilized to provide accurate assessments of the RTS and TRISS in a population of TBI patients. Automation of these scores could be utilized to enhance triage and resource allocation during the ultra-early phase of resuscitation.

Adjunctive virtual reality pain relief after traumatic injury: a proof-of-concept within-person randomized trial.

ABSTRACT: In this study, we hypothesized that immersive virtual reality (VR) environments may reduce pain in patients with acute traumatic injuries, including traumatic brain injuries. We performed a randomized within-subject study in patients hospitalized with acute traumatic injuries, including traumatic brain injury with moderate pain (numeric pain score ≥3 of 10). We compared 3 conditions: (1) an immersive VR environment (VR Blu), (2) a content control with the identical environment delivered through nonimmersive tablet computer (Tablet Blu), and (3) a second control composed of donning VR headgear without content to control for placebo effects and sensory deprivation (VR Blank). We enrolled 60 patients, and 48 patients completed all 3 conditions. Objective and subjective data were analyzed using linear mixed-effects models. Controlling for demographics, baseline pain, and injury severity, we found differences by conditions in relieving pain (F 2,75.43 = 3.32, P = 0.042). VR Blu pain reduction was greater than Tablet Blu (-0.92 vs -0.16, P = 0.043), but VR Blu pain reduction was similar to VR Blank (-0.92 vs -1.24, P = 0.241). VR Blu was perceived as most effective by patients for pain reduction (F 2,66.84 = 16.28, P < 0.001), and changes in measures of parasympathetic activity including heart rate variability (F 2,55.511 = 7.87, P < 0.001) and pupillary maximum constriction velocity (F 2,61.41 = 3.50, 1-tailed P = 0.038) echoed these effects. There were no effects on opioid usage. These findings outlined a potential clinical benefit for mollifying pain related to traumatic injuries.

Rapid prediction of secondary neurologic decline after traumatic brain injury: a data analytic approach.

Secondary neurologic decline (ND) after traumatic brain injury (TBI) is independently associated with outcome, but robust predictors of ND are lacking. In this retrospective analysis of consecutive isolated TBI admissions to the R. Adams Cowley Shock Trauma Center between November 2015 and June 2018, we aimed to develop a triage decision support tool to quantify risk for early ND. Three machine learning models based on clinical, physiologic, or combined characteristics from the first hour of hospital resuscitation were created. Among 905 TBI cases, 165 (18%) experienced one or more ND events (130 clinical, 51 neurosurgical, and 54 radiographic) within 48 h of presentation. In the prediction of ND, the clinical plus physiologic data model performed similarly to the physiologic only model, with concordance indices of 0.85 (0.824-0.877) and 0.84 (0.812-0.868), respectively. Both outperformed the clinical only model, which had a concordance index of 0.72 (0.688-0.759). This preliminary work suggests that a data-driven approach utilizing physiologic and basic clinical data from the first hour of resuscitation after TBI has the potential to serve as a decision support tool for clinicians seeking to identify patients at high or low risk for ND.

Leveraging Continuous Vital Sign Measurements for Real-Time Assessment of Autonomic Nervous System Dysfunction After Brain Injury: A Narrative Review of Current and Future Applications.

Subtle and profound changes in autonomic nervous system (ANS) function affecting sympathetic and parasympathetic homeostasis occur as a result of critical illness. Changes in ANS function are particularly salient in neurocritical illness, when direct structural and functional perturbations to autonomic network pathways occur and may herald impending clinical deterioration or intervenable evolving mechanisms of secondary injury. Sympathetic and parasympathetic balance can be measured quantitatively at the bedside using multiple methods, most readily by extracting data from electrocardiographic or photoplethysmography waveforms. Work from our group and others has demonstrated that data-analytic techniques can identify quantitative physiologic changes that precede clinical detection of meaningful events, and therefore may provide an important window for time-sensitive therapies. Here, we review data-analytic approaches to measuring ANS dysfunction from routine bedside physiologic data streams and integrating this data into multimodal machine learning-based model development to better understand phenotypical expression of pathophysiologic mechanisms and perhaps even serve as early detection signals. Attention will be given to examples from our work in acute traumatic brain injury on detection and monitoring of paroxysmal sympathetic hyperactivity and prediction of neurologic deterioration, and in large hemispheric infarction on prediction of malignant cerebral edema. We also discuss future clinical applications and data-analytic challenges and future directions.

Adjunctive virtual reality pain relief following traumatic injury: protocol for a randomised within-subjects clinical trial.

INTRODUCTION: The annual mortality and national expense of the opioid crisis continue to rise in the USA (130 deaths/day, $50 billion/year). Opioid use disorder usually starts with the prescription of opioids for a medical condition. Its risk is associated with greater pain intensity and coping strategies characterised by pain catastrophising. Non-pharmacological analgesics in the hospital setting are critical to abate the opioid epidemic. One promising intervention is virtual reality (VR) therapy. It has performed well as a distraction tool and pain modifier during medical procedures; however, little is known about VR in the acute pain setting following traumatic injury. Furthermore, no studies have investigated VR in the setting of traumatic brain injury (TBI). This study aims to establish the safety and effect of VR therapy in the inpatient setting for acute traumatic injuries, including TBI. METHODS AND ANALYSIS: In this randomised within-subjects clinical study, immersive VR therapy will be compared with two controls in patients with traumatic injury, including TBI. Affective measures including pain catastrophising, trait anxiety and depression will be captured prior to beginning sessions. Before and after each session, we will capture pain intensity and unpleasantness, additional affective measures and physiological measures associated with pain response, such as heart rate and variability, pupillometry and respiratory rate. The primary outcome is the change in pain intensity of the VR session compared with controls. ETHICS AND DISSEMINATION: Dissemination of this protocol will allow researchers and funding bodies to stay abreast in their fields through exposure to research not otherwise widely publicised. Study protocols are compliant with federal regulation and University of Maryland Baltimore's Human Research Protections and Institutional Review Board (protocol number HP-00090603). Study results will be published on completion of enrolment and analysis, and deidentified data can be shared by request to the corresponding author. TRIAL REGISTRATION NUMBER: NCT04356963; Pre-results.

Gold-catalyzed diastereoselective cycloisomerization of alkylidene-cyclopropane-bearing 1,6-diynes.

An unprecedented gold-catalyzed diastereoselective cycloisomerization of 1,6-diynes bearing an alkylidene cyclopropane moiety has been developed. This methodology enables rapid access to a variety of 1,2-trimethylenenorbornanes, which are important building blocks in the preparations of abiotic and sesquiterpene core structures.

Electrophilic Pt(II) complexes: precision instruments for the initiation of transformations mediated by the cation-olefin reaction.

A discontinuity exists between the importance of the cation-olefin reaction as the principal C-C bond forming reaction in terpene biosynthesis and the synthetic tools for mimicking this reaction under catalyst control; that is, having the product identity, stereochemistry, and functionality under the control of a catalyst. The main reason for this deficiency is that the cation-olefin reaction starts with a reactive intermediate (a carbocation) that reacts exothermically with an alkene to reform the reactive intermediate; not to mention that reactive intermediates can also react in nonproductive fashions. In this Account, we detail our efforts to realize catalyst control over this most fundamental of reactions and thereby access steroid like compounds. Our story is organized around our progress in each component of the cascade reaction: the metal controlled electrophilic initiation, the propagation and termination of the cyclization (the cyclase phase), and the turnover deplatinating events. Electrophilic Pt(II) complexes efficiently initiate the cation-olefin reaction by first coordinating to the alkene with selection rules that favor less substituted alkenes over more substituted alkenes. In complex substrates with multiple alkenes, this preference ensures that the least substituted alkene is always the better ligand for the Pt(II) initiator, and consequently the site at which all electrophilic chemistry is initiated. This control element is invariant. With a suitably electron deficient ligand set, the catalyst then activates the coordinated alkene to intramolecular addition by a second alkene, which initiates the cation-olefin reaction cascade and generates an organometallic Pt(II)-alkyl. Deplatination by a range of mechanisms (ß-H elimination, single electron oxidation, two-electron oxidation, etc.) provides an additional level of control that ultimately enables A-ring functionalizations that are orthogonal to the cyclase cascade. We particularly focus on reactions that combine an initiated cyclization reaction with a turnover defining ß-hydride elimination, fluorination, and oxygenation. These latter demetalation schemes lead to new compounds functionalized at the C3 carbon of the A-ring (steroid numbering convention) and thus provide access to interesting potentially bioactive targets. Progress toward efficient and diverse polycyclization reactions has been achieved by investing in both synthetic challenges and fundamental organometallic reactivity. In addition to an interest in the entrance and exit of the metal catalyst from this reaction scheme, we have been intrigued by the role of neighboring group participation in the cyclase phase. Computational studies have served to provide nuance and clarity on several key aspects, including the role (and consequences) of neighboring group participation in cation generation and stabilization. For example, these calculations have demonstrated that traversing carbonium ion transition states significantly impacts the kinetics of competitive 6-endo and 5-exo A-ring forming reactions. The resulting nonclassical transition states then become subject to a portion of the strain energy inherent to bicyclic structures, with the net result being that the 6-endo pathway becomes kinetically favored for alkene nucleophiles, in contrast to heteroatom nucleophiles which progress through classical transition states and preferentially follow 5-exo pathways. These vignettes articulate our approach to achieving the desired catalyst control.

Gold-catalyzed enantioselective ring-expanding cycloisomerization of cyclopropylidene bearing 1,5-enynes.

An enantioselective ring-expanding cycloisomerization of 1,5-enynes bearing a cyclopropylidene moiety has been developed. This methodology provides a new approach to bicyclo[4.2.0]octanes, a structural motif present in many biologically active natural products.

Gold(I)-catalyzed formation of bicyclo[4.2.0]oct-1-enes.

Gold(I) catalysts effectively promote the Cope rearrangement of acyclic 1,5-dienes bearing a terminal cyclopropylidene. When this methodology is applied to cyclic substrates an unexpected transformation occurs, resulting in the formation of a tricyclic compound incorporating a bicyclo[4.2.0]oct-1-ene core, a portion of which is found in a number of natural products. Density functional theory calculations (M06 and M06-2X) reveal insight into the mechanism and thermodynamics of this unique transformation.

Carbonium vs. carbenium ion-like transition state geometries for carbocation cyclization - how strain associated with bridging affects 5-exo vs. 6-endo selectivity.

Quantum chemical calculations are used to explore the origins of regioselectivity for proton-, Pt(II)- and Pd(II)-promoted cyclizations of 1,5-hexadienes, 5-aminoalkenes, and allylic acetimidates. The strain associated with achieving carbonium ion-like transition state geometries is shown to be a key factor in controlling 5-exo vs. 6-endo selectivity.

A gold-catalysed enantioselective Cope rearrangement of achiral 1,5-dienes.

Since the discovery of the Cope rearrangement in the 1940s, no asymmetric variant of the rearrangement of achiral 1,5-dienes has emerged, despite the successes that have been achieved with its heteroatom variants (Claisen, aza-Cope, and so on). This article reports the first example of an enantioselective Cope reaction that starts from an achiral diene. The new gold(I) catalyst derived from double Cl(-)-abstraction of ((S)-3,5-xylyl-PHANEPHOS(AuCl)(2)), has been developed for the sigmatropic rearrangement of alkenyl-methylenecyclopropanes. The reaction proceeds at low temperature and the synthetically useful vinylcyclopropane products are obtained in high yield and enantioselectivity. Density functional theory calculations predict that: (1) the reaction proceeds via a cyclic carbenium ion intermediate, (2) the relief of strain in the methylenecyclopropane moiety provides the thermodynamic driving force for the rearrangement and (3) metal complexation of the transition-state structure lowers the rearrangement barriers.