An Injury Risk Function for the Leg, Foot, and Ankle Exposed to Axial Impact Loading Using Force and Impulse.

Most injury risk functions (IRFs) for dynamic axial loading of the leg have been targeted toward automotive applications such as predicting injury caused by intrusion into the occupant compartment from frontal collisions. Recent focus on leg injuries in the military has led to questions about the applicability of these IRFs shorter duration, higher amplitude loading associated with underbody blast (UBB). To investigate these questions, data were collected from seven separate test series that subjected post-mortem human legs to axial impact. A force and impulse-based Weibull survival model was developed from these studies to estimate fracture risk. Specimen age was included as a covariate to reduce variance and improve survival model fit. The injury criterion estimated 50% risk of injury for a leg exposed to 13 N s of impulse at peak force and 8.07 kN of force for force durations less than and greater than half the natural period of the leg, respectively. A supplemental statistical analysis estimated that the proposed IRF improves injury prediction accuracy by more than 9% compared to the predictions from automobile-based risk functions developed for automotive intrusion. The proposed leg IRF not only improves injury prediction for higher rate conditions but also provides a single injury prediction tool for an expanded range of load durations ranging from 5 to 90 ms, which spans both automotive and military loading environments.

Physician interpretation of genomic test results and treatment selection.

BACKGROUND: Genomic testing is increasingly performed in oncology, but concerns remain regarding the clinician's ability to interpret results. In the current study, the authors sought to determine the agreement between physicians and genomic annotators from the Precision Oncology Decision Support (PODS) team at The University of Texas MD Anderson Cancer Center in Houston regarding actionability and the clinical use of test results. METHODS: On a prospective protocol, patients underwent clinical genomic testing for hotspot mutations in 46 or 50 genes. Six months after sequencing, physicians received questionnaires for patients who demonstrated a variant in an actionable gene, investigating their perceptions regarding the actionability of alterations and clinical use of these findings. Genomic annotators independently classified these variants as actionable, potentially actionable, unknown, or not actionable. RESULTS: Physicians completed 250 of 288 questionnaires (87% response rate). Physicians considered 168 of 250 patients (67%) as having an actionable alteration; of these, 165 patients (98%) were considered to have an actionable alteration by the PODS team and 3 were of unknown significance. Physicians were aware of genotype-matched therapy available for 119 patients (71%) and 48 of these 119 patients (40%) received matched therapy. Approximately 46% of patients in whom physicians regarded alterations as not actionable (36 of 79 patients) were classified as having an actionable/potentially actionable mutation by the PODS team. However, many of these were only theoretically actionable due to limited trials and/or therapies (eg, KRAS). CONCLUSIONS: Physicians are aware of recurrent mutations in actionable genes on "hotspot" panels. As larger genomic panels are used, there may be a growing need for annotation of actionability. Decision support to increase awareness of genomically relevant trials and novel treatment options for recurrent mutations (eg, KRAS) also are needed. Cancer 2018;124:966-72. © 2017 American Cancer Society.

FXR silencing in human colon cancer by DNA methylation and KRAS signaling.

Farnesoid X receptor (FXR) is a bile acid nuclear receptor described through mouse knockout studies as a tumor suppressor for the development of colon adenocarcinomas. This study investigates the regulation of FXR in the development of human colon cancer. We used immunohistochemistry of FXR in normal tissue (n = 238), polyps (n = 32), and adenocarcinomas, staged I-IV (n = 43, 39, 68, and 9), of the colon; RT-quantitative PCR, reverse-phase protein array, and Western blot analysis in 15 colon cancer cell lines; NR1H4 promoter methylation and mRNA expression in colon cancer samples from The Cancer Genome Atlas; DNA methyltransferase inhibition; methyl-DNA immunoprecipitation (MeDIP); bisulfite sequencing; and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) knockdown assessment to investigate FXR regulation in colon cancer development. Immunohistochemistry and quantitative RT-PCR revealed that expression and function of FXR was reduced in precancerous lesions and silenced in a majority of stage I-IV tumors. FXR expression negatively correlated with phosphatidylinositol-4, 5-bisphosphate 3 kinase signaling and the epithelial-to-mesenchymal transition. The NR1H4 promoter is methylated in ~12% colon cancer The Cancer Genome Atlas samples, and methylation patterns segregate with tumor subtypes. Inhibition of DNA methylation and KRAS silencing both increased FXR expression. FXR expression is decreased early in human colon cancer progression, and both DNA methylation and KRAS signaling may be contributing factors to FXR silencing. FXR potentially suppresses epithelial-to-mesenchymal transition and other oncogenic signaling cascades, and restoration of FXR activity, by blocking silencing mechanisms or increasing residual FXR activity, represents promising therapeutic options for the treatment of colon cancer.

Laboratory Evaluation of Shell Add-On Products for American Football Helmets for Professional Linemen.

The Guardian Cap NXT (GC NXT) and the ProTech Helmet Cap (ProTech) are commercially available aftermarket products designed to augment the energy attenuation characteristics of American football helmets. The ability of these helmet shell add-on products to mitigate the severity of impacts typically experienced by professional offensive and defensive linemen was evaluated for seven helmet models using two test series. In linear impactor tests, the GC NXT reduced head impact severity as measured by the head acceleration response metric (HARM) by 9% relative to the helmets only, while the ProTech reduced HARM by 5%. While both products significantly improved the performance of the football helmets tested overall, effects varied by impact condition and helmet model with the add-ons worsening helmet performance in some conditions. The GC NXT had a strong effect size (Cohen's d = 0.8) whereas the ProTech had a medium effect (Cohen's d = 0.5). A second study investigated add-on performance for helmet-to-helmet impacts with eccentric impact vectors and resulted in a mixture of increased and decreased HARM when either add-on was placed on one or both helmets. Estimated risk for serious neck injury with add-ons and without differed by less than 4% for these eccentric impacts.

Characterization of Concussive Events in Professional American Football Using Videogrammetry.

Sports concussions offer a unique opportunity to study head kinematics associated with mild traumatic brain injury. In this study, a model-based image matching (MBIM) approach was employed to analyze video footage of 57 concussions which occurred in National Football League (NFL) games. By utilizing at least two camera views, higher frame rate footage (> 60 images s-1), and laser scans of the field and helmets involved in each case, it was possible to calculate the change in velocity of the helmet during impact in six degrees of freedom. The average impact velocity for these concussive events was 8.9 ± 2.0 m s-1. The average changes in translational and rotational velocity for the concussed players' helmets were 6.6 ± 2.1 m s-1 and 29 ± 13 rad s-1, respectively. The average change in translational velocity was higher for helmet-to-ground (n = 16) impacts compared to helmet-to-helmet (n = 30) or helmet-to-shoulder (n = 11) events (p < 0.001), while helmet-to-shoulder impacts had a smaller change in rotational velocity compared to the other impact sources (p < 0.001). By quantifying the impact velocities and locations associated with concussive impacts in professional American football, this study provides information that may be used to improve upon current helmet testing methodologies.

The biomechanics of concussive helmet-to-ground impacts in the National Football league.

This paper presents a detailed characterization of helmet-to-ground impacts in the National Football League. Video analysis was performed for 16 head-to-ground impacts that caused concussions. Average resultant closing velocity was 8.3 m/s at an angle nearly 45° to the surface. Preimpact rotational velocity of the helmet ranged from negligible to as high as 54.1 rad/s. Helmet impacts were concentrated on the posterior and lateral aspects. To study the interaction in greater detail, a helmeted anthropomorphic test device (ATD) was launched over a football field and fell to the ground in various impact conditions. Substantial decoupling between the helmet and the head was observed, such that the head rebounded within the helmet and underwent changes in linear and rotational motion greater than those of the helmet. Vertical helmet rebound was also observed; the helmet underwent a change in vertical velocity on average 24% greater than the vertical component of its closing velocity. Frictional interaction between the helmet and the ground surface caused the helmet to undergo an average horizontal change in velocity of 57% of the horizontal component of its closing velocity. Finally, the duration of a helmet-to-ground impact was generally in the range of 15 - 30 ms, suggesting that the impact surface provides little ride-down. Lengthening this duration could be beneficial both by reducing the peak linear and rotational acceleration and by shifting the impact toward a time regime where brain strain is related to rotational acceleration rather than rotational velocity.

Comparison of Laboratory and On-Field Performance of American Football Helmets.

The relationship between laboratory and on-field performance of football helmets was assessed for 31 football helmet models selected from those worn by players in the 2015-2019 National Football League (NFL) seasons. Linear impactor tests were conducted with helmets placed on an instrumented Hybrid III head and neck assembly mounted on a sliding table. Based on impacts to each helmet at six impact locations and three velocities, a helmet performance score (HPS) was calculated using a linear combination of the head injury criterion (HIC) and the diffuse axonal multi-axis general evaluation (DAMAGE). To determine the on-field performance of helmets, helmet model usage, player participation, and incident concussion data were collected from the five NFL seasons and used to calculate helmet model-specific concussion rates. Comparison of laboratory HPS to the helmet model-specific concussion rates on a per play basis showed a positive correlation (r2 = 0.61, p < 0.001) between laboratory and on-field performance of helmet models, indicating that helmets which exhibited reduced impact severity in the laboratory tests were also generally associated with lower concussion rates on-field. Further analysis showed that NFL-prohibited helmet models exhibited a significantly higher odds of concussion (OR 1.24; 95% CI 1.04-1.47; p = 0.017) relative to other helmet models.

Development and Evaluation of a Test Method for Assessing the Performance of American Football Helmets.

As more is learned about injury mechanisms of concussion and scenarios under which injuries are sustained in football games, methods used to evaluate protective equipment must adapt. A combination of video review, videogrammetry, and laboratory reconstructions was used to characterize concussive impacts from National Football League games during the 2015-2017 seasons. Test conditions were generated based upon impact locations and speeds from this data set, and a method for scoring overall helmet performance was created. Head kinematics generated using a linear impactor and sliding table fixture were comparable to those from laboratory reconstructions of concussive impacts at similar impact conditions. Impact tests were performed on 36 football helmet models at two laboratories to evaluate the reproducibility of results from the resulting test protocol. Head acceleration response metric, a head impact severity metric, varied 2.9-5.6% for helmet impacts in the same lab, and 3.8-6.0% for tests performed in a separate lab when averaged by location for the models tested. Overall inter-lab helmet performance varied by 1.1 ± 0.9%, while the standard deviation in helmet performance score was 7.0%. The worst helmet performance score was 33% greater than the score of the best-performing helmet evaluated by this study.

Precision Oncology Decision Support: Current Approaches and Strategies for the Future.

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.

Molecular Landscape of ERBB2/ERBB3 Mutated Colorectal Cancer.

Background: Despite growing therapeutic relevance of ERBB2 amplifications in colorectal cancer (CRC), little is known about ERBB2/ERBB3 mutations. We aimed to characterize these subsets of CRC. Methods: We performed a retrospective analysis of 419 CRC patients from MD Anderson (MDACC) and 619 patients from the Nurses' Health Study (NHS)/Health Professionals Follow-Up Study (HPFS) with tissue sequencing, clinicopathologic, mutational, and consensus molecular subtype (CMS) profiles of ERBB2/ERBB3 mutant patients. A third cohort of 1623 CRC patients with ctDNA assays characterized the ctDNA profile of ERBB2 mutants. All statistical tests were two-sided. Results: ERBB2 mutations occurred in 4.1% (95% confidence interval [CI] = 2.4% to 6.4%), 5.8% (95% CI = 4.1% to 8.0%), and 5.1% (95% CI = 4.0% to 6.2%) of MDACC, NHS/HPFS, and ctDNA patients, respectively. ERBB3 mutations occurred in 5.7% (95% CI = 3.7% to 8.4%, 95% CI = 4.0% to 7.8%) of patients in both tissue cohorts. Age, stage, and tumor location were not associated with either mutation. Microsatellite instability (MSI) was associated with ERBB2 (odds ratio [OR] = 5.98, 95% CI = 2.47 to 14.49, P < .001; OR = 5.13, 95% CI = 2.38 to 11.05, P < .001) and ERBB3 mutations (OR = 3.48, 95% CI = 1.51 to 8.02, P = .002; OR = 3.40, 95% CI = 1.05 to 10.96, P = .03) in both tissue cohorts. Neither gene was associated with TP53, APC, KRAS, NRAS, or BRAF mutations in tissue. However, PIK3CA mutations were strongly associated with ERBB2 mutations in all three cohorts (OR = 3.68, 95% CI = 1.83 to 7.41, P = .001; OR = 2.25, 95% CI = 1.11 to 4.58, P = .02; OR = 2.11, 95% CI = 1.25 to 3.58, P = .004) and ERBB3 mutations in the MDACC cohort (OR = 13.26, 95% CI = 5.27 to 33.33, P < .001). ERBB2 (P = 0.08) and ERBB3 (P = .008) mutations were associated with CMS1 subtype. ERBB2 (hazard ratio [HR] = 1.82, 95% CI = 1.23 to 4.03, P = .009), but not ERBB3 (HR = 0.88, 95% CI = 0.45 to 1.73, P = .73), mutations were associated with worse overall survival. Conclusions: MSI and PIK3CA mutations are associated with ERBB2/ERBB3 mutations. Co-occurring PIK3CA mutations may represent a second hit to oncogenic signaling that needs consideration when targeting ERBB2/ERBB3.

"Personalized Cancer Therapy": A Publicly Available Precision Oncology Resource.

High-throughput genomic and molecular profiling of tumors is emerging as an important clinical approach. Molecular profiling is increasingly being used to guide cancer patient care, especially in advanced and incurable cancers. However, navigating the scientific literature to make evidence-based clinical decisions based on molecular profiling results is overwhelming for many oncology clinicians and researchers. The Personalized Cancer Therapy website (www.personalizedcancertherapy.org) was created to provide an online resource for clinicians and researchers to facilitate navigation of available data. Specifically, this resource can be used to help identify potential therapy options for patients harboring oncogenic genomic alterations. Herein, we describe how content on www.personalizedcancertherapy.org is generated and maintained. We end with case scenarios to illustrate the clinical utility of the website. The goal of this publicly available resource is to provide easily accessible information to a broad oncology audience, as this may help ease the information retrieval burden facing participants in the precision oncology field. Cancer Res; 77(21); e123-6. ©2017 AACR.

Clinical Use of Precision Oncology Decision Support.

PURPOSE: Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced. METHODS: Genomic alterations were annotated to determine actionability based on a variant's known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued. RESULTS: PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials. CONCLUSION: Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

OBJECTIVE: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. METHODS: We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. RESULTS AND DISCUSSION: The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy.

Automated identification of molecular effects of drugs (AIMED).

INTRODUCTION: Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support. OBJECTIVES: To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains. METHODS: We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts. RESULTS: Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts. CONCLUSIONS: Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development.

Post Mortem Human Surrogate Injury Response of the Pelvis and Lower Extremities to Simulated Underbody Blast.

Military vehicle underbody blast (UBB) is the cause of many serious injuries in theatre today; however, the effects of these chaotic events on the human body are not well understood. The purpose of this research was to replicate both UBB loading conditions and investigate occupant response in a controlled laboratory setting. In addition to better understanding the response of the human to high rate vertical loading, this test series also aimed to identify high rate injury thresholds. Ten whole body post mortem human surrogate (PMHS) tests were completed using the University of Virginia's ODYSSEY simulated blast rig under a range of loading conditions. Seat pan accelerations ranged from 291 to 738 g's over 3 ms of positive phase duration, and foot pan accelerations from 234 to 858 g's over 3 ms of positive phase duration. Post-test computed tomography (CT) scans and necropsies were performed to determine injuries, and revealed a combination of pelvic, lumbar, thoracic, and lower extremity injuries. The research in this paper discusses pelvis and lower extremity injuries under high rate vertical loads.

Survival Model for Foot and Leg High Rate Axial Impact Injury Data.

OBJECTIVES: Understanding how lower extremity injuries from automotive intrusion and underbody blast (UBB) differ is of key importance when determining whether automotive injury criteria can be applied to blast rate scenarios. This article provides a review of existing injury risk analyses and outlines an approach to improve injury prediction for an expanded range of loading rates. This analysis will address issues with existing injury risk functions including inaccuracies due to inertial and potential viscous resistance at higher loading rates. METHODS: This survival analysis attempts to minimize these errors by considering injury location statistics and a predictor variable selection process dependent upon failure mechanisms of bone. Distribution of foot/ankle/leg injuries induced by axial impact loading at rates characteristic of UBB as well as automotive intrusion was studied and calcaneus injuries were found to be the most common injury; thus, footplate force was chosen as the main predictor variable because of its proximity to injury location to prevent inaccuracies associated with inertial differences due to loading rate. A survival analysis was then performed with age, sex, dorsiflexion angle, and mass as covariates. This statistical analysis uses data from previous axial postmortem human surrogate (PMHS) component leg tests to provide perspectives on how proximal boundary conditions and loading rate affect injury probability in the foot/ankle/leg (n = 82). RESULTS: Tibia force-at-fracture proved to be up to 20% inaccurate in previous analyses because of viscous resistance and inertial effects within the data set used, suggesting that previous injury criteria are accurate only for specific rates of loading and boundary conditions. The statistical model presented in this article predicts 50% probability of injury for a plantar force of 10.2 kN for a 50th percentile male with a neutral ankle position. Force rate was found to be an insignificant covariate because of the limited range of loading rate differences within the data set; however, compensation for inertial effects caused by measuring the force-at-fracture in a location closer to expected injury location improved the model's predictive capabilities for the entire data set. CONCLUSIONS: This study provides better injury prediction capabilities for both automotive and blast rates because of reduced sensitivity to inertial effects and tibia-fibula load sharing. Further, a framework is provided for future injury criteria generation for high rate loading scenarios. This analysis also suggests key improvements to be made to existing anthropomorphic test device (ATD) lower extremities to provide accurate injury prediction for high rate applications such as UBB.

The right drugs at the right time for the right patient: the MD Anderson precision oncology decision support platform.

The development of resources for clinical interpretation of cancer-associated genetic alterations has significantly lagged behind the technical developments enabling their detection in a time- and cost-efficient manner. The lack of scientific and informatics decision support for oncologists can lead to no action being taken or suboptimal therapeutic choices being made, which could affect the clinical outcome of a patient as well as convoluting research findings from clinical trials. In this article, we describe the precision oncology decision support (PODS) platform developed within The Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy (IPCT) at MD Anderson Cancer Center; the platform aims to bridge the gap between molecular alteration detection and identification of appropriate treatments.

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature.

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org

Implementation of biomarker-driven cancer therapy: existing tools and remaining gaps.

There has been growing interest in biomarker-driven personalized cancer therapy, also known as precision medicine. Recently, dozens of molecular tests, including next generation sequencing, have been developed to detect biomarkers that have the potential to predict response of cancers to particular targeted therapies. However, detection of cancer-related biomarkers is only the first step in the battle. Deciding what therapy options to pursue can also be daunting, especially when tumors harbor more than one potentially actionable aberration. Further, different mutations/variants in a single gene may have different functional consequences, and response to targeted agents may be context dependent. However, early clinical trials with new molecular entities are increasingly conducted in a biomarker-selected fashion, and even when trials are not biomarker-selected, much effort is placed on enrolling patients onto clinical trials where they have the highest probability of response. We review available molecular tests and therapy discerning tools, including tools available for assessing functional consequences of molecular alterations and tools for finding applicable clinical trials, which exist to help bridge the gap between detection of cancer-related biomarker to the initiation of biomarker-matched targeted therapies.

Injuries caused by brake pedal loading of the midfoot.

In a frontal car crash, the driver’s foot and ankle may be injured due to loading by the brake pedal. The driver of a vehicle often has time to initiate emergency braking before an impending collision, which places the forefoot or midfoot over the brake pedal. During the crash, the pedal may induce dorsiflexion and axial loading of the ankle due to forward motion of the occupant and rearward intrusion of the pedal relative to the vehicle. In order to investigate the injuries caused by pedal loading, impact tests were conducted on three cadaveric lower limbs. The limbs were braced at the knee, and a pedal positioned beneath the midfoot was driven towards the knee, inducing dorsiflexion and axial loading of the cadaveric limb. Ankle injury was generated in two specimens. Both injured limbs sustained a medial malleolar fracture, and one limb also suffered a talar neck fracture. These results suggest that pedal loading may be an important injury mechanism for fractures of the medial malleolus and talar neck in drivers involved in frontal crashes.