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Ultrasonic pulse echo techniques have proven particularly valuable in locating discrete flaws, such as cracks or inclusions, in metal components. It has long been recognized that many factors influence the echo amplitude from a defect. Three factors of particular significance are the angle of incidence between pulse and defect, the shape and size of the defect, and the roughness of its surface. A diffraction model is developed which includes these parameters and successfully accounts for the experimentally observed reflections of ultrasonic pulses from a variety of surfaces. The equations describing reflection in the frequency domain essentially predict the complex frequency spectra of pulses reflected from surfaces of various geometries: by Fourier transforming them, expressions describing the actual pulse waveforms reflected from the surfaces have been obtained. The predicted effects of surface roughness, size, shape, and defect orientation on both the reflected pulse waveform and its frequency spectrum are confirmed by experiment. The converse problem of using the reflected pulse to infer information about the reflecting surface via a deconvolution technique is also demonstrated. [ABSTRACT FROM AUTHOR]

An investigation has been made of the frequency dependence of amplitude and phase information when broadband ultrasonic pulses, in the region 1-30 MHz, are reflected from layered targets. An on line computer performing Fourier analysis of sampled ultrasonic pulses allowed both amplitude and phase information to be studied. Layers of various acoustic impedances, velocities, and attenuation have been investigated, and in particular, layers of magnetite grown on mild steel. In all cases excellent agreement between experiment and theory has been achieved. The possible use of the techniques of deconvolution has also been considered for the measurement of the thickness of layers. The methods developed have found application in the problem of determining the thickness of a corrosion layer on the inside surface of a component where access can only be gained through the outer surface. [ABSTRACT FROM AUTHOR]

Background: The Food and Drug Administration (FDA) maintains the Manufacturer and User Facility Device Experience (MAUDE) database for reporting adverse events associated with medical devices, including emerging technologies, such as robotic-assisted total hip arthroplasty (THA). Aim of this study was to evaluate the variation of adverse events associated with robotics in THA., Methods: Medical device reports (MDRs) within the MAUDE database were identified between 2017 and 2021. For MDR identification the product class "orthopaedic stereotaxic equipment" and terms associated with THA were used. Individual adverse events were identified and organised by type and consequences, such as patient injury, surgical delay, or conversion to the manual technique., Results: 521 MDRs constituting 546 discrete events were found. The most common reported complication was intraoperative hardware failure (304/546, 55.7%), among which the most common failure was a broken impaction handle/platform (110, 20.1%). Inaccurate cup placement was the second most common reported complication (63, 11.5%). Abandoning the robot occurred in 13.0% (71/521) of reports. A surgical delay was noted in 28% (146/521) of reports, with an average delay of 17.9 (range 1-60) minutes., Conclusions: Identifying complications that may occur with robotics in THA is an important first step in preventing adverse events and surgical delays. Database analysis provide an overview of the range of complications., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The Iowa Gambling Task (IGT) is used to assess decision-making in clinical populations. The original IGT does not disambiguate reward and punishment learning; however, an adaptation of the task, the "play-or-pass" IGT, was developed to better distinguish between reward and punishment learning. We evaluated the test-retest reliability of measures of reward and punishment learning from the play-or-pass IGT and examined associations with self-reported measures of reward/punishment sensitivity and internalizing symptoms. Participants completed the task across two sessions, and we calculated mean-level differences and rank-order stability of behavioral measures across the two sessions using traditional scoring, involving session-wide choice proportions, and computational modeling, involving estimates of different aspects of trial-level learning. Measures using both approaches were reliable; however, computational modeling provided more insights regarding between-session changes in performance, and how performance related to self-reported measures of reward/punishment sensitivity and internalizing symptoms. Our results show promise in using the play-or-pass IGT to assess decision-making; however, further work is still necessary to validate the play-or-pass IGT., (© 2024. The Author(s).)

Advances in computational statistics and corresponding shifts in funding initiatives over the past few decades have led to a proliferation of neuroscientific measures being developed in the context of mental health research. Although such measures have undoubtedly deepened our understanding of neural mechanisms underlying cognitive, affective, and behavioral processes associated with various mental health conditions, the clinical utility of such measures remains underwhelming. Recent commentaries point toward the poor reliability of neuroscientific measures to partially explain this lack of clinical translation. Here, we provide a concise theoretical overview of how unreliability impedes clinical translation of neuroscientific measures; discuss how various modeling principles, including those from hierarchical and structural equation modeling frameworks, can help to improve reliability; and demonstrate how to combine principles of hierarchical and structural modeling within the generative modeling framework to achieve more reliable, generalizable measures of brain-behavior relationships for use in mental health research., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background Orthopedic surgery traditionally has been a male-dominant specialty with the lowest percentage of female residents and female faculty of all medical specialties. Prior studies demonstrate gender biases from both referring providers and patients. This study investigates surgeon, referring provider, and patient demographic differences in new patient orthopedic referrals. Methodology A retrospective chart review was performed to analyze the demographics of new patients referred to male and female orthopedic surgeons within adult reconstruction and shoulder/elbow specialties at a single academic institution. Patients and referring provider demographics were compared for male and female orthopedic surgeons. Statistical analysis utilized Student's t-test and chi-square analyses for quantitative and qualitative data, respectively. Results In total, 2,642 new patients were analyzed, with 2,084 patients being referred from a provider, and 306 patients requesting specific providers. When compared to male surgeons, female surgeons had fewer referrals from male providers (45.3% vs. 50.3%, p = 0.03) and no difference from female providers (30.6% vs, 29.9%, p = 0.72). The female adult reconstruction surgeon had fewer internal referrals compared to a male surgeon of similar experience and time at the institution (8.4% vs. 12.8%, p = 0.03). Female patients requested male surgeons more frequently than female surgeons (76.7% vs. 23.3%, p = 0.02). Conclusions New patient demographics differed between male and female orthopedic surgeons at a single academic institution with more male referring providers referring to male surgeons. Female patients requesting male orthopedic providers may reflect patient and specialty-driven biases. There remains a need for additional female representation in orthopedic surgery, and new patient referral patterns may be a marker to assess and monitor gender biases., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Bertha et al.)

When making decisions based on probabilistic outcomes, people guide their behavior using knowledge gathered through both indirect descriptions and direct experience. Paradoxically, how people obtain information significantly impacts apparent preferences. A ubiquitous example is the description-experience gap: individuals seemingly overweight low probability events when probabilities are described yet underweight them when probabilities must be experienced firsthand. A leading explanation for this fundamental gap in decision-making is that probabilities are weighted differently when learned through description relative to experience, yet a formal theoretical account of the mechanism responsible for such weighting differences remains elusive. We demonstrate how various learning and memory retention models incorporating neuroscientifically motivated learning mechanisms can explain why probability weighting and valuation parameters often are found to vary across description and experience. In a simulation study, we show how learning through experience can lead to systematically biased estimates of probability weighting when using a traditional cumulative prospect theory model. We then use hierarchical Bayesian modeling and Bayesian model comparison to show how various learning and memory retention models capture participants' behavior over and above changes in outcome valuation and probability weighting, accounting for description and experience-based decisions in a within-subject experiment. We conclude with a discussion of how substantive models of psychological processes can lead to insights that heuristic statistical models fail to capture., (© 2023. The Psychonomic Society, Inc.)

Objectives: To characterize the recruitment rates at a Level I trauma center enroling for multiple prospective orthopaedic trauma research studies and identify patient-related and study-related predictors of consent., Design: We conducted a case-control study to identify predictors of study consent. The authors categorized studies based on intensity of the study intervention (low, intermediate, or high). A 2-level generalized linear model with random intercept for study was used to predict study consent., Setting: This analysis includes data from 10 federally funded studies conducted as part of a large, national consortium that were enroling patients in 2013-2014., Patients/participants: Three hundred thirty-four patients were approached for at least 1 study and included in the analysis., Intervention: N/A., Main Outcome Measures: Consent to participate in the research study., Results: A total of 315 patients consented to be in a study (71% of approached patients). Consent rate varied by study (45%-95%). No patient characteristics (race, age, or sex) were associated with consent. Patients approached for studies of intermediate intensity were 83% less likely to consent (odds ratio = 0.17; 95% confidence interval: 0.04-0.67), and those approached for studies of high intensity were 91% less likely to consent (odds ratio = 0.09; 95% confidence interval: 0.03-0.32)., Conclusion: Patient factors were not associated with consent. Study intensity is a major driver of consent rates. Studies of higher intensity will require the study team to approach up to twice as many patients as the target enrolment. This study provides a framework that can be used in study planning and determination of feasibility., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Poor psychometrics, particularly low test-retest reliability, pose a major challenge for using behavioral tasks in individual differences research. Here, we demonstrate that full generative modeling of the Iowa Gambling Task (IGT) substantially improves test-retest reliability and may also enhance the IGT's validity for use in characterizing internalizing pathology, compared to the traditional analytic approach. IGT data ( n = 50 ) was collected across two sessions, one month apart. Our full generative model incorporated (1) the Outcome Representation Learning (ORL) computational model at the person-level and (2) a group-level model that explicitly modeled test-retest reliability, along with other group-level effects. Compared to the traditional ' summary score ' (proportion good decks selected), the ORL model provides a theoretically rich set of performance metrics ( Reward Learning Rate ( A + ) , Punishment Learning Rate ( A - ) , Win Frequency Sensitivity ( β f ) , Perseveration Tendency ( β p ) , Memory Decay ( K ) ), capturing distinct psychological processes. While test-retest reliability for the traditional summary score was only moderate ( r = . 37 , BCa 95% CI [.04, .63]), test-retest reliabilities for ORL performance metrics produced by the full generative model were substantially improved, with test-retest correlations ranging between r = . 64 - . 82 for the five ORL parameters. Further, while summary scores showed no substantial associations with internalizing symptoms, ORL parameters were significantly associated with internalizing symptoms. Specifically, Punishment Learning Rate was associated with higher self-reported depression and Perseveration Tendency was associated with lower self-reported anhedonia. Generative modeling offers promise for advancing individual differences research using the IGT, and behavioral tasks more generally, through enhancing task psychometrics.

Machine learning has the potential to facilitate the development of computational methods that improve the measurement of cognitive and mental functioning. In three populations (college students, patients with a substance use disorder, and Amazon Mechanical Turk workers), we evaluated one such method, Bayesian adaptive design optimization (ADO), in the area of delay discounting by comparing its test-retest reliability, precision, and efficiency with that of a conventional staircase method. In all three populations tested, the results showed that ADO led to 0.95 or higher test-retest reliability of the discounting rate within 10-20 trials (under 1-2 min of testing), captured approximately 10% more variance in test-retest reliability, was 3-5 times more precise, and was 3-8 times more efficient than the staircase method. The ADO methodology provides efficient and precise protocols for measuring individual differences in delay discounting.

Background: Impulsivity is central to all forms of externalizing psychopathology, including problematic substance use. The Cambridge Gambling task (CGT) is a popular neurocognitive task used to assess impulsivity in both clinical and healthy populations. However, the traditional methods of analysis in the CGT do not fully capture the multiple cognitive mechanisms that give rise to impulsive behavior, which can lead to underpowered and difficult-to-interpret behavioral measures., Objectives: The current study presents the cognitive modeling approach as an alternative to traditional methods and assesses predictive and convergent validity across and between approaches., Methods: We used hierarchical Bayesian modeling to fit a series of cognitive models to data from healthy controls (N = 124) and individuals with histories of substance use disorders (Heroin: N = 79; Amphetamine: N = 76; Polysubstance: N = 103; final total across groups N = 382). Using Bayesian model comparison, we identified the best fitting model, which was then used to identify differences in cognitive model parameters between groups., Results: The cognitive modeling approach revealed differences in quality of decision making and impulsivity between controls and individuals with substance use disorders that traditional methods alone did not detect. Crucially, convergent validity between traditional measures and cognitive model parameters was strong across all groups., Conclusion: The cognitive modeling approach is a viable method of measuring the latent mechanisms that give rise to choice behavior in the CGT, which allows for stronger statistical inferences and a better understanding of impulsive and risk-seeking behavior., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Almost all forms of psychopathology, including personality disorders, are arrived at through complex interactions among neurobiological vulnerabilities and environmental risk factors across development. Yet despite increasing recognition of etiological complexity, psychopathology research is still dominated by searches for large main effects causes. This derives in part from reliance on traditional inferential methods, including ordinary factor analysis, regression, ANCOVA, and other techniques that use statistical partialing to isolate unique effects. In principle, some of these methods can accommodate etiological complexity, yet as typically applied they are insensitive to interactive functional dependencies (modulating effects) among etiological influences. Here, we use our developmental model of antisocial and borderline traits to illustrate challenges faced when modeling complex etiological mechanisms of psychopathology. We then consider how computational models, which are rarely used in the personality disorders literature, remedy some of these challenges when combined with hierarchical Bayesian analysis., (© 2020 S. Karger AG, Basel.)

Sexual discounting, which describes delay discounting of later protected sex vs. immediate unprotected sex (e.g., sex now without a condom vs. waiting an hour to have sex with a condom), is consistently linked to sexual risk behavior. Estimates suggest that over two-thirds of HIV transmissions occur between individuals in committed relationships, but current sexual discounting tasks examine sexual discounting only with hypothetical strangers, leaving a gap in our understanding of sexual discounting with committed sexual partners. We used the Sexual Discounting Task (SDT) to compare discounting rates between men who have sex with men (MSM; n = 99) and heterosexual men (n = 144) and tested a new SDT condition evaluating sexual discounting with main partners. MSM in committed relationships discounted protected sex with their main partner at higher rates than heterosexual men, and discounting rates correlated with self-report measures of condom use, impulsivity/sensation seeking, and substance use. These findings suggest that sexual discounting is a critical factor potentially related to increased HIV transmission between MSM in committed relationships and may be an important target for intervention and prevention.

As early as infancy, caregivers' facial expressions shape children's behaviors, help them regulate their emotions, and encourage or dissuade their interpersonal agency. In childhood and adolescence, proficiencies in producing and decoding facial expressions promote social competence, whereas deficiencies characterize several forms of psychopathology. To date, however, studying facial expressions has been hampered by the labor-intensive, time-consuming nature of human coding. We describe a partial solution: automated facial expression coding (AFEC), which combines computer vision and machine learning to code facial expressions in real time. Although AFEC cannot capture the full complexity of human emotion, it codes positive affect, negative affect, and arousal-core Research Domain Criteria constructs-as accurately as humans, and it characterizes emotion dysregulation with greater specificity than other objective measures such as autonomic responding. We provide an example in which we use AFEC to evaluate emotion dynamics in mother-daughter dyads engaged in conflict. Among other findings, AFEC (a) shows convergent validity with a validated human coding scheme, (b) distinguishes among risk groups, and (c) detects developmental increases in positive dyadic affect correspondence as teen daughters age. Although more research is needed to realize the full potential of AFEC, findings demonstrate its current utility in research on emotion dysregulation.

Facial expressions are fundamental to interpersonal communication, including social interaction, and allow people of different ages, cultures, and languages to quickly and reliably convey emotional information. Historically, facial expression research has followed from discrete emotion theories, which posit a limited number of distinct affective states that are represented with specific patterns of facial action. Much less work has focused on dimensional features of emotion, particularly positive and negative affect intensity. This is likely, in part, because achieving inter-rater reliability for facial action and affect intensity ratings is painstaking and labor-intensive. We use computer-vision and machine learning (CVML) to identify patterns of facial actions in 4,648 video recordings of 125 human participants, which show strong correspondences to positive and negative affect intensity ratings obtained from highly trained coders. Our results show that CVML can both (1) determine the importance of different facial actions that human coders use to derive positive and negative affective ratings when combined with interpretable machine learning methods, and (2) efficiently automate positive and negative affect intensity coding on large facial expression databases. Further, we show that CVML can be applied to individual human judges to infer which facial actions they use to generate perceptual emotion ratings from facial expressions., Competing Interests: The authors have declared that no competing interests exist.

The Iowa Gambling Task (IGT) is widely used to study decision-making within healthy and psychiatric populations. However, the complexity of the IGT makes it difficult to attribute variation in performance to specific cognitive processes. Several cognitive models have been proposed for the IGT in an effort to address this problem, but currently no single model shows optimal performance for both short- and long-term prediction accuracy and parameter recovery. Here, we propose the Outcome-Representation Learning (ORL) model, a novel model that provides the best compromise between competing models. We test the performance of the ORL model on 393 subjects' data collected across multiple research sites, and we show that the ORL reveals distinct patterns of decision-making in substance-using populations. Our work highlights the importance of using multiple model comparison metrics to make valid inference with cognitive models and sheds light on learning mechanisms that play a role in underweighting of rare events., (© 2018 Cognitive Science Society, Inc.)

Objective: Wrist arthroscopy is a challenging discipline with limited training exposure during residency. The purpose of this study was to evaluate the effectiveness of virtual knee arthroscopy simulation training for gaining proficiency in wrist arthroscopy., Design: Participants were recorded performing a cadaveric wrist arthroscopy simulation. The residents then practiced knee arthroscopy on a virtual reality simulator and repeated the wrist arthroscopy simulation. All videos were blinded prior to assessment. Proficiency was graded using the Arthroscopic Surgery Skill Evaluation Tool global rating scale. In addition, participants were asked to complete a survey assessing the value of the virtual reality knee arthroscopy simulator for wrist arthroscopy., Setting: Orthopaedic Surgery Residency Program, Carolinas Medical Center, a large, public, nonprofit hospital located in Charlotte, North Carolina., Participants: Orthopaedic residents at our center were asked to participate in the simulation training. Participation was voluntary and nonincentivized. All orthopaedic residents at our institution (N = 27) agreed to participate. In total, there were 10 Intern (PGY-0 and PGY-1), 10 Junior (PGY-2 and PGY-3), and 7 Senior (PGY-4 and PGY-5) residents. In addition, a fellowship-trained hand surgeon was recruited to participate in the study, performing the wrist arthoscopy simulation. Two additional fellowship-trained hand surgeons, for a total of 3, assessed the blinded videos., Results: There was a trend toward better wrist Arthroscopic Surgery Skill Evaluation Tool scores by training level, although the difference was not statistically significant. Interns improved by an average of 1.8 points between baseline and postknee simulation tests. Junior and senior residents decreased by 1.6 and 5.0 points, respectively., Conclusions: Knee arthroscopy simulation training did not objectively improve wrist arthroscopy proficiency among residents. A wrist-specific arthroscopy simulation program is needed if measurable competence through simulation is desired., (Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.)

Lesbian, gay, and bisexual (LGB) individuals report higher levels of problematic alcohol and substance use than their heterosexual peers. This disparity is linked to the experience of LGB-specific stressors, termed minority stress. Additionally, bisexual individuals show increased rates of psychopathology, including problematic alcohol and substance use, above and beyond lesbian and gay individuals. However, not everyone experiencing minority stress reports increased rates of alcohol and substance misuse. Emotion regulation (ER), which plays a critical role in psychopathology in general, is theorized to modulate the link between minority stress and psychopathology. However, it remains largely unknown whether ER plays a role in linking instances of minority stress with substance and alcohol use outcomes. To address the gap, the current study assessed 305 LGB individuals' instances of minority stress, ER, and substance and alcohol use outcomes. We assessed the role of ER in problematic alcohol and substance use among LGB individuals using moderated mediation, where sexual minority status was entered as the moderator, and ER difficulties was entered as the mediator. The results indicated significant indirect effects of minority stress, through ER difficulties, on both problematic alcohol and substance use. However, there was no significant interaction with sexual orientation status, suggesting that ER may be important for all LGB individuals in predicting problematic alcohol and substance use. These results highlight the important role that ER plays between instances of minority stress and substance and alcohol use in LGB individuals, suggesting that ER skills may serve as a novel target for intervention.

Reinforcement learning and decision-making (RLDM) provide a quantitative framework and computational theories with which we can disentangle psychiatric conditions into the basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assessing and potentially diagnosing psychiatric patients, and there is growing enthusiasm for both RLDM and computational psychiatry among clinical researchers. Such a framework can also provide insights into the brain substrates of particular RLDM processes, as exemplified by model-based analysis of data from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). However, researchers often find the approach too technical and have difficulty adopting it for their research. Thus, a critical need remains to develop a user-friendly tool for the wide dissemination of computational psychiatric methods. We introduce an R package called hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), which offers computational modeling of an array of RLDM tasks and social exchange games. The hBayesDM package offers state-of-the-art hierarchical Bayesian modeling, in which both individual and group parameters (i.e., posterior distributions) are estimated simultaneously in a mutually constraining fashion. At the same time, the package is extremely user-friendly: users can perform computational modeling, output visualization, and Bayesian model comparisons, each with a single line of coding. Users can also extract the trial-by-trial latent variables (e.g., prediction errors) required for model-based fMRI/EEG. With the hBayesDM package, we anticipate that anyone with minimal knowledge of programming can take advantage of cutting-edge computational-modeling approaches to investigate the underlying processes of and interactions between multiple decision-making (e.g., goal-directed, habitual, and Pavlovian) systems. In this way, we expect that the hBayesDM package will contribute to the dissemination of advanced modeling approaches and enable a wide range of researchers to easily perform computational psychiatric research within different populations., Competing Interests: Competing Interests: The author declares no conflict of interest

Soft tissue sarcomas are a rare but heterogeneous family of malignant tumors that are predominantly found deep to the integumentary layer. Only a small number of these primary mesenchymal tumors actually originate from the dermal layers. A systematic approach to the evaluation and workup of these neoplasms can prevent inappropriate management. After staging evaluation, most of these tumors are primarily managed with en-bloc surgical resection. Other adjuvant therapies routinely employed include chemotherapy and radiation therapy. Proper treatment typically involves participation of a multidisciplinary care team for optimal outcome. General principles and treatment strategies will be discussed along with a review of the more common cutaneous manifestations of sarcoma., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objectives: The purpose of this study was to characterize demographics, healing time, and complications of a large series of operatively treated atypical femur fractures., Design: Retrospective multicenter review., Setting: Seventeen academic medical centers., Patients: Bisphosphonate-related fractures as defined by American Society of Bone and Mineral Research. Fractures had to be followed for at least 6 months or to union or revision., Intervention: Operative treatment of bisphosphonate-related fracture., Main Outcome Measurements: Union time and complications of treatment, as well as information about the contralateral limb., Results: There were 179 patients, average age 72, average body mass index 27.2. Average follow-up was 17 months. Twenty-one percent had a previous history of fragility fracture; 34% had prodromal pain. Most (88%) lived independently before injury. Thirty-one percent had radiographic changes suggesting stress reaction. Surgical fixation was with cephalomedullary nail (51%), IM nail (48%), or plate (1%). Complications included death (4), PE (3), and wound infection (6). Twenty (12%) patients underwent revision at an average of 11 months. Excluding revisions, average union time was 5.2 months. For revisions, union occurred at an average of 10.2 months after intervention. No association was identified between discontinuation of bisphosphonates and union time (P = 0.5) or need for revision (P = 0.7). Twenty-one percent sustained contralateral femur fractures; 32% of these had pain and 59% had stress reaction before contralateral fracture., Conclusions: In this series, surgery had a 12% failure rate and delayed average time to union. Twenty-one percent developed contralateral femur fractures within 2 years, underscoring the need to evaluate the contralateral extremity., Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Objectives. Management of mechanically ventilated patients may pose a challenge to novice residents, many of which may not have received formal dedicated critical care instruction prior to starting their residency training. There is a paucity of data regarding simulation and mechanical ventilation training in the medical education literature. The purpose of this study was to develop a curriculum to educate first-year residents on addressing and troubleshooting ventilator alarms. Methods. Prospective evaluation was conducted of seventeen residents undergoing a twelve-hour three-day curriculum. Residents were assessed using a predetermined critical action checklist for each case, as well as pre- and postcurriculum multiple-choice cognitive knowledge questionnaires and confidence surveys. Results. Significant improvements in cognitive knowledge, critical actions, and self-reported confidence were demonstrated. The mean change in test score from before to after intervention was +26.8%, and a median score increase of 25% was noted. The ARDS and the mucus plugging cases had statistically significant improvements in critical actions, p < 0.001. A mean increase in self-reported confidence was realized (1.55 to 3.64), p = 0.049. Conclusions. A three-day simulation curriculum for residents was effective in increasing competency, knowledge, and confidence with ventilator management.

Background: It is believed that phosphocitrate (PC) exerts its disease-modifying effects on osteoarthritis (OA) by inhibiting the formation of crystals. However, recent findings suggest that PC exerts its disease-modifying effect, at least in part, through a crystal-independent action. This study sought to examine the disease-modifying effects of PC and its analogue PC-β-ethyl ester (PC-E) on partial meniscectomy-induced OA and the structure-activity relationship., Methods: Calcification- and proliferation-inhibitory activities were examined in OA fibroblast-like synoviocytes (FLSs) culture. Disease-modifying effects were examined using Hartley guinea pigs undergoing partial meniscectomy. Cartilage degeneration was examined with Indian ink, safranin-O, and picrosirius red. Levels of matrix metalloproteinase-13 (MMP-13), ADAM metallopeptidase with thrombospondin type 1 motif 5 (ADAMTS5), chemokine (C-C motif) ligand 5 (CCL5), and cyclooxygenase-2 (Cox-2) were examined with immunostaining. The effects of PC-E and PC on gene expressions in OA FLSs were examined with microarray. Results are expressed as mean ± standard deviation and analyzed using Student's t test or Wilcoxon rank sum test., Results: PC-E was slightly less powerful than PC as a calcification inhibitor but as powerful as PC in the inhibition of OA FLSs proliferation. PC significantly inhibited cartilage degeneration in the partial meniscectomied right knee. PC-E was less powerful than PC as a disease-modifying drug, especially in the inhibition of cartilage degeneration in the non-operated left knee. PC significantly reduced the levels of ADAMTS5, MMP-13 and CCL5, whereas PC-E reduced the levels of ADAMTS5 and CCL5. Microarray analyses revealed that PC-E failed to downregulate the expression of many PC-downregulated genes classified in angiogenesis and inflammatory response., Conclusions: PC is a disease-modifying drug for posttraumatic OA therapy. PC exerts its disease-modifying effect through two independent actions: inhibiting pathological calcification and modulating the expression of many genes implicated in OA. The β-carboxyl group of PC plays an important role in the inhibition of cartilage degeneration, little role in the inhibition of FLSs proliferation, and a moderate role in the inhibition of FLSs-mediated calcification.

Background: In accordance with the American Academy of Orthopaedic Surgeons' strategic goal of enriching our field by building a more diverse orthopaedic workforce, the specialty needs further information delineating the factors important to the applicant pool as a whole and more specifically to women and other underrepresented minority groups., Questions/purposes: This study aims to identify (1) factors important to residency applicants selecting an orthopaedic residency program; (2) differences in factor importance for men, women, and minorities, and (3) the importance of different information sources used when making his or her rank list., Methods: All 742 applicants who applied to the authors' orthopaedic surgery residency program in the 2013 National Resident Matching Program were queried. The response rate was 28% (207 of 742). Respondents were asked to rank, on a 5-point Likert scale, 37 factors that may have affected their rank lists to differing degrees. Respondents also identified the importance of sources of information used to make their rank lists, factors that residency programs considered important when ranking applicants, and their level of agreement with various sex- and racial-specific statements regarding orthopaedic training., Results: The most important factors affecting rank lists were perceived happiness/quality of life of current residents, resident camaraderie, and impression after an away rotation. Women weighed their personal interactions and a program's proximity to family and friends more heavily when determining a rank list. Sixty-eight percent of women eliminated residency programs from their options based on perceived sex biases versus less than 1% of men. Applicants valued information obtained from away rotations at an institution and in talking with current residents most when determining his or her rank list., Conclusions: Programs should consider interpersonal factors, like quality of life and resident camaraderie as factors in attracting applicants. They also should minimize perceived biases and emphasize interactions with current residents during the application process to meet their goals of attracting an exceptional and more diverse orthopaedic workforce.

Background: We previously found no reduction in heterotopic ossification (HO) rates after acetabular surgery with indomethacin compared with a placebo. We subsequently abandoned routine indomethacin therapy after acetabular surgery but questioned whether the incidence had changed using a posterior approach., Questions/purposes: We therefore determined (1) the incidence of HO after acetabular fracture surgery through a posterior approach; (2) the incidence of symptoms attributable to HO; and (3) the rate of reoperation for HO., Methods: We retrospectively reviewed the records of all 423 patients with acetabular fractures following our clinical protocol change; of these, 120 were treated with a Kocher-Langenbeck approach and included. The presence of radiographic HO was documented a minimum of 10 weeks postoperatively using the classification of Brooker et al. Symptoms and reoperations were recorded., Results: The overall incidence of radiographic HO was 47% (56 of 120 patients): 26% Class I-II 13% Class III, and 8% Class IV. Overall, 15% of patients developed symptoms; 3.3% underwent reoperations for excision of HO. There were no major differences between the incidence of moderate and severe HO in this study when compared with the indomethacin and placebo groups from the prior study., Conclusions: Our incidence of moderate and severe HO has not changed since discontinuing indomethacin. These findings support our institutional decision to abandon routine indomethacin prophylaxis after acetabular surgery. We recommend improved surgical techniques to limit damage to the abductors and improved risk stratification of patients when considering treatment options for HO prophylaxis.

Over the past 6 years at Penn State Hershey, we have established the pediatric cardiovascular research center with a multidisciplinary research team with the goal to improve the outcomes for children undergoing cardiac surgery with cardiopulmonary bypass (CPB) and extracorporeal life support (ECLS). Due to the variety of commercially available pediatric CPB and ECLS devices, both in vitro and in vivo translational research have been conducted to achieve the optimal choice for our patients. By now, every component being used in our clinical settings in Penn State Hershey has been selected based on the results of our translational research. The objective of this review is to summarize our translational research in Penn State Hershey Pediatric Cardiovascular Research Center and to share the latest results with all the interested centers.

Mutations that diminish the function of the extracellular matrix receptor Dystroglycan (DG) result in muscular dystrophies, with associated neuronal migration defects in the brain and mental retardation e.g. Muscle Eye Brain Disease. To gain insight into the function of DG in the nervous system we initiated a study to examine its contribution to development of the eye of Drosophila melanogaster. Immuno-histochemistry showed that DG is concentrated on the apical surface of photoreceptors (R) cells during specification of cell-fate in the third instar larva and is maintained at this location through early pupal stages. In point mutations that are null for DG we see abortive R cell elongation during differentiation that first appears in the pupa and results in stunted R cells in the adult. Overexpression of DG in R cells results in a small but significant increase in their size. R cell differentiation defects appear at the same stage in a deficiency line Df(2R)Dg(248) that affects Dg and the neighboring mitochondrial ribosomal gene, mRpL34. In the adult, these flies have severely disrupted R cells as well as defects in the lens and ommatidia. Expression of an mRpL34 transgene rescues much of this phenotype. We conclude that DG does not affect neuronal commitment but functions R cell autonomously to regulate neuronal elongation during differentiation in the pupa. We discuss these findings in view of recent work implicating DG as a regulator of cell metabolism and its genetic interaction with mRpL34, a member of a class of mitochondrial genes essential for normal metabolic function.

We compared the effects of two neonatal extracorporeal life support (ECLS) systems on circuit pressures and surplus hemodynamic energy levels in a simulated ECLS model. The clinical set-up included the Jostra HL-20 heart-lung machine, either the Medtronic ECMO (0800) or the MEDOS 800LT systems with company-provided circuit components, a 10 Fr arterial cannula, and a pseudo-patient. We tested the system in nonpulsatile and pulsatile flow modes at two flow rates using a 40/60 glycerin/water blood analog, for a total of 48 trials, with n = 6 for each set-up. The pressure drops over the Medtronic ECLS were significantly higher than those over the MEDOS system regardless of the flow rate or perfusion mode (144.8 +/- 0.2 mm Hg vs. 35.7 +/- 0.2 mm Hg, respectively, at 500 mL/min in nonpulsatile mode, P < 0.001). The preoxygenator mean arterial pressures were significantly increased and the precannula hemodynamic energy values were decreased with the Medtronic ECLS circuit. These results suggest that the MEDOS ECLS circuit better transmits hemodynamic energy to the patient, keeps mean circuit pressures lower, and has lower pressure drops than the Medtronic Circuit.

This study tested the impact of different postpump resistances on pulsatile pressure-flow waveforms and hemodynamic energy output in a mock extracorporeal system. The circuit was primed with a 40% glycerin-water mixture, and a PediVAS centrifugal pump was used. The pre- and postpump pressures and flow rates were monitored via a data acquisition system. The postpump resistance was adjusted using a Hoffman clamp at the outlet of the pump. Five different postpump resistances and rotational speeds were tested with nonpulsatile (NP: 5000 RPM) and pulsatile (P: 4000 RPM) modes. No backflow was found when using pulsatile flow. With isoresistance, increased arterial resistances decreased pump flow rates (NP: from 1,912 ml/min to 373 ml/min; P: from 1,485 ml/min to 288 ml/min), increased postpump pressures (NP: from 333 mm Hg to 402 mm Hg; P: from 223 mm Hg to 274 mm Hg), and increased hemodynamic energy output with pulsatile mode. Pump flow rate correlated linearly with rotational speed (RPMs) of the pump, whereas postpump pressures and hemodynamic energy outputs showed curvilinear relationships with RPMs. The maximal pump flow rate also increased from 618 ml/min to 4,293 ml/min with pulsatile mode and from 581 ml/min to 5,665 ml/min with nonpulsatile mode. Results showed that higher postpump resistance reduced the pump flow range, and increased postpump pressure and surplus hemodynamic energy output with pulsatile mode. Higher rotational speeds also generated higher pump flow rates, postpump pressures, and increased pulsatility.