Responsible north-south research and innovation: A framework for transdisciplinary research leadership and management.

The number, scale and ambition of transdisciplinary research initiatives between the global north and the global south is increasing, yet there is very little theoretical or empirical scholarship on how to lead and manage implementation to promote responsible practice. Within science, technology and innovation (STI) studies and decolonising research frameworks, and utilising collaborative autoethnography, this study codifies experience with implementing the 'Revitalising Informal Settlements and their Environments' (RISE) program (2017-2020). Our specific aim is to explore the leadership and management tensions and challenges of implementing transboundary transdisciplinary research. The findings reaffirm the importance of research leaders and managers carefully operationalising north-south research by critically reflecting on power asymmetries between disciplines, partners and locations, leveraging the potential for transdisciplinary consortia to build research capabilities in the global south, and creating a culture of reflexivity on the historical and social positionality in which research is designed, funded, implemented and evaluated. The findings foreground the role of boundary-spanning 'integrators' and 'pracademics', roles that have received little attention to date but are essential for effective delivery and societal impact beyond scientific advances. A framework for implementing north-south transdisciplinary research is outlined with five domains: (1) collaborative leadership; (2) agile management; (3) flexible consortia; (4) researcher positionality; and (5) co-design and participation. The framework can support efforts for responsibly designing and implementing large, transdisciplinary, cross-country research programs in line with ambitions for decolonising north-south research.

Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures.

PURPOSE: We wished to evaluate if an open-source artificial intelligence (AI) algorithm ( https://www.childfx.com ) could improve performance of (1) subspecialized musculoskeletal radiologists, (2) radiology residents, and (3) pediatric residents in detecting pediatric and young adult upper extremity fractures. MATERIALS AND METHODS: A set of evaluation radiographs drawn from throughout the upper extremity (elbow, hand/finger, humerus/shoulder/clavicle, wrist/forearm, and clavicle) from 240 unique patients at a single hospital was constructed (mean age 11.3 years, range 0-22 years, 37.9% female). Two fellowship-trained musculoskeletal radiologists, three radiology residents, and two pediatric residents were recruited as readers. Each reader interpreted each case initially without and then subsequently 3-4 weeks later with AI assistance and recorded if/where fracture was present. RESULTS: Access to AI significantly improved area under the receiver operator curve (AUC) of radiology residents (0.768 [0.730-0.806] without AI to 0.876 [0.845-0.908] with AI, P < 0.001) and pediatric residents (0.706 [0.659-0.753] without AI to 0.844 [0.805-0.883] with AI, P < 0.001) in identifying fracture, respectively. There was no evidence of improvement for subspecialized musculoskeletal radiology attendings in identifying fracture (AUC 0.867 [0.832-0.902] to 0.890 [0.856-0.924], P = 0.093). There was no evidence of difference between overall resident AUC with AI and subspecialist AUC without AI (resident with AI 0.863, attending without AI AUC 0.867, P = 0.856). Overall physician radiograph interpretation time was significantly lower with AI (38.9 s with AI vs. 52.1 s without AI, P = 0.030). CONCLUSION: An openly accessible AI model significantly improved radiology and pediatric resident accuracy in detecting pediatric upper extremity fractures.

Numerical Simulation of the Transient Flow around the Combined Morphing Leading-Edge and Trailing-Edge Airfoil.

An integrated approach to active flow control is proposed by finding both the drooping leading edge and the morphing trailing edge for flow management. This strategy aims to manage flow separation control by utilizing the synergistic effects of both control mechanisms, which we call the combined morphing leading edge and trailing edge (CoMpLETE) technique. This design is inspired by a bionic porpoise nose and the flap movements of the cetacean species. The motion of this mechanism achieves a continuous, wave-like, variable airfoil camber. The dynamic motion of the airfoil's upper and lower surface coordinates in response to unsteady conditions is achieved by combining the thickness-to-chord (t/c) distribution with the time-dependent camber line equation. A parameterization model was constructed to mimic the motion around the morphing airfoil at various deflection amplitudes at the stall angle of attack and morphing actuation start times. The mean properties and qualitative trends of the flow phenomena are captured by the transition SST (shear stress transport) model. The effectiveness of the dynamically morphing airfoil as a flow control approach is evaluated by obtaining flow field data, such as velocity streamlines, vorticity contours, and aerodynamic forces. Different cases are investigated for the CoMpLETE morphing airfoil, which evaluates the airfoil's parameters, such as its morphing location, deflection amplitude, and morphing starting time. The morphing airfoil's performance is analyzed to provide further insights into the dynamic lift and drag force variations at pre-defined deflection frequencies of 0.5 Hz, 1 Hz, and 2 Hz. The findings demonstrate that adjusting the airfoil camber reduces streamwise adverse pressure gradients, thus preventing significant flow separation. Although the trailing-edge deflection and its location along the chord influence the generation and separation of the leading-edge vortex (LEV), these results show that the combined effect of the morphing leading edge and trailing edge has the potential to mitigate flow separation. The morphing airfoil successfully contributes to the flow reattachment and significantly increases the maximum lift coefficient (cl,max)). This work also broadens its focus to investigate the aerodynamic effects of a dynamically morphing leading and trailing edge, which seamlessly transitions along the side edges. The aerodynamic performance analysis is investigated across varying morphing frequencies, amplitudes, and actuation times.

Preclinical Ultra-High Dose Rate (FLASH) Proton Radiation Therapy System for Small Animal Studies.

Purpose: Animal studies with ultrahigh dose-rate radiation therapy (FLASH, >40 Gy/s) preferentially spare normal tissues without sacrificing antitumor efficacy compared with conventional dose-rate radiation therapy (CONV). At the University of Washington, we developed a cyclotron-generated preclinical scattered proton beam with FLASH dose rates. We present the technical details of our FLASH radiation system and preliminary biologic results from whole pelvis radiation. Methods and Materials: A Scanditronix MC50 compact cyclotron beamline has been modified to produce a 48.7 MeV proton beam at dose rates between 0.1 and 150 Gy/s. The system produces a 6 cm diameter scattered proton beam (flat to ± 3%) at the target location. Female C57BL/6 mice 5 to 6 weeks old were used for all experiments. To study normal tissue effects in the distal colon, mice were irradiated using the entrance region of the proton beam to the whole pelvis, 18.5 Gy at different dose rates: control, CONV (0.6-1 Gy/s) and FLASH (50-80 Gy/s). Survival was monitored daily and EdU (5-ethynyl-2´-deoxyuridine) staining was performed at 24- and 96-hours postradiation. Cleaved caspase-3 staining was performed 24-hours postradiation. To study tumor control, allograft B16F10 tumors were implanted in the right flank and received 18 Gy CONV or FLASH proton radiation. Tumor growth and survival were monitored. Results: After 18.5 Gy whole pelvis radiation, survival was 100% in the control group, 0% in the CONV group, and 44% in the FLASH group (P < .01). EdU staining showed cell proliferation was significantly higher in the FLASH versus CONV group at both 24-hours and 96-hours postradiation in the distal colon, although both radiation groups showed decreased proliferation compared with controls (P < .05). Lower cleaved caspase-3 staining was seen in the FLASH versus conventional group postradiation (P < .05). Comparable flank tumor control was observed in the CONV and FLASH groups. Conclusions: We present our preclinical FLASH proton radiation system and biologic results showing improved survival after whole pelvis radiation, with equivalent tumor control.

Acute patellar dislocation: how skeletal maturity affects patterns of injury.

OBJECTIVE: The main objective of this study was to understand the role of skeletal maturity in the different patterns of osteochondral and ligamentous injuries after an acute lateral patellar dislocation. MATERIALS AND METHODS: Two radiologists independently reviewed MRIs of 212 knees performed after an acute lateral patellar dislocation to evaluate the presence of high-grade patellar osteochondral injury, femoral osteochondral injury, and medial patellofemoral ligament injury. The association of skeletal maturity (indicated by a closed distal femoral physis), age, sex, and first-time versus recurrent dislocation with each of these various lesions was analyzed using Chi-square or T test, and multivariable logistic regression with estimation of odds ratios (OR). RESULTS: Skeletal maturity was significantly associated with high-grade patellar osteochondral injury [OR=2.72 (95% CI 1.00, 7.36); p=0.049] and femoral-side MPFL tear [OR=2.34 (95% CI 1.05, 5.25); p=0.039]. Skeletal immaturity was significantly associated with patellar-side MPFL tear [OR=0.35 (95% CI 0.14, 0.90); p=0.029]. CONCLUSION: Patterns of injury to the patella and medial patellofemoral ligament vary notably between the skeletally immature and mature, and these variations may be explained by the inherent weakness of the patellar secondary physis.

Utility of Zero-Echo time sequence as an adjunct for MR evaluation of degenerative disease in the cervical spine.

OBJECTIVE: Determine the utility of ZTE as an adjunct to routine MR for assessing degenerative disease in the cervical spine. METHODS: Retrospective study on 42 patients with cervical MR performed with ZTE from 1/1/2022 to 4/30/22. Fellowship trained radiologists evaluated each cervical disc level for neural foraminal (NF) narrowing, canal stenosis (CS), facet arthritis (FA), and presence of ossification of the posterior longitudinal ligament (OPLL). When NF narrowing and CS were present, the relative contributions of bone and soft disc were determined and a confidence level for doing so was assigned. Comparisons were made between assessments on routine MR without and with ZTE. RESULTS: With ZTE added, bone contribution as a cause of NF narrowing increased in 47% (n = 110) of neural foramina and decreased in 12% (n = 29) (p = < 0.001). Bone contribution as a cause of CS increased in 25% (n = 33) of disc levels and decreased in 10% (n = 13) (p = 0.013). Confidence increased in identifying the cause of NF narrowing (p = < 0.001)) and CS (p = 0.009) with ZTE. The cause of NF narrowing (p = 0.007) and CS (p = 0.041) changed more frequently after ZTE was added when initial confidence in making the determination was low. There was no change in detection of FA or presence of OPLL with ZTE. CONCLUSION: Addition of ZTE to a routine cervical spine MR changes the assessment of the degree of bone involvement in degenerative cervical spine pathology.

UTE T2* cartilage mapping in the hip: a pilot study assessing cartilage in patients with femoroacetabular impingement.

BACKGROUND: UTE T2* cartilage mapping use in patients undergoing femoroacetabular impingement (FAI) has been lacking but may allow the detection of early cartilage damage. PURPOSE: To assess the reproducibility of UTE T2* cartilage mapping and determine the difference in UTE T2* values between FAI and asymptomatic patients and to evaluate the correlation between UTE T2* values and patient-reported symptoms. MATERIAL AND METHODS: Prospective evaluation of both hips (7 FAI and 7 asymptomatic patients). Bilateral hip 3-T MRI scans with UTE T2* cartilage maps were acquired. A second MRI scan was acquired 1-9 months later. Cartilage was segmented into anterosuperior, superior, and posterosuperior regions. Assessment was made of UTE T2* reproducibility (ICC). Mean UTE T2* values in patients were compared (t-tests) and correlation was made with patient-reported outcomes (Spearman's). RESULTS: ICCs of mean UTE T2* were as follows: acetabular, 0.82 (95% CI=0.50-0.95); femoral, 0.76 (95% CI=0.35-0.92). Significant strong correlation was found between mean acetabular UTE T2* values and iHOT12 (ρ = -0.63) and moderate correlation with mHHS (ρ = -0.57). There was no difference in mean UTE T2* values between affected vs. non-affected FAI hips. FAI-affected hips had significantly higher values in acetabulum vs. asymptomatic patients (13.47 vs. 12.55 ms). There was no difference in mean femoral cartilage values between the FAI-affected hips vs. asymptomatic patients. The posterosuperior femoral region had a higher mean value in non-affected FAI hips vs. asymptomatic patients (12.60 vs. 11.53 ms). CONCLUSION: UTE T2* cartilage mapping had excellent reproducibility. Affected FAI hips had higher mean acetabular UTE T2* values than asymptomatic patients. Severity of patient-reported symptoms correlates with UTE T2* acetabular cartilage values.

Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs.

BACKGROUND: Pediatric fractures are challenging to identify given the different response of the pediatric skeleton to injury compared to adults, and most artificial intelligence (AI) fracture detection work has focused on adults. OBJECTIVE: Develop and transparently share an AI model capable of detecting a range of pediatric upper extremity fractures. MATERIALS AND METHODS: In total, 58,846 upper extremity radiographs (finger/hand, wrist/forearm, elbow, humerus, shoulder/clavicle) from 14,873 pediatric and young adult patients were divided into train (n = 12,232 patients), tune (n = 1,307), internal test (n = 819), and external test (n = 515) splits. Fracture was determined by manual inspection of all test radiographs and the subset of train/tune radiographs whose reports were classified fracture-positive by a rule-based natural language processing (NLP) algorithm. We trained an object detection model (Faster Region-based Convolutional Neural Network [R-CNN]; "strongly-supervised") and an image classification model (EfficientNetV2-Small; "weakly-supervised") to detect fractures using train/tune data and evaluate on test data. AI fracture detection accuracy was compared with accuracy of on-call residents on cases they preliminarily interpreted overnight. RESULTS: A strongly-supervised fracture detection AI model achieved overall test area under the receiver operating characteristic curve (AUC) of 0.96 (95% CI 0.95-0.97), accuracy 89.7% (95% CI 88.0-91.3%), sensitivity 90.8% (95% CI 88.5-93.1%), and specificity 88.7% (95% CI 86.4-91.0%), and outperformed a weakly-supervised model (AUC 0.93, 95% CI 0.92-0.94, P < 0.0001). AI accuracy on cases preliminary interpreted overnight was higher than resident accuracy (AI 89.4% vs. 85.1%, 95% CI 87.3-91.5% vs. 82.7-87.5%, P = 0.01). CONCLUSION: An object detection AI model identified pediatric upper extremity fractures with high accuracy.

Improving models for student retention and graduation using Markov chains.

Graduation rates are a key measure of the long-term efficacy of academic interventions. However, challenges to using traditional estimates of graduation rates for underrepresented students include inherently small sample sizes and high data requirements. Here, we show that a Markov model increases confidence and reduces biases in estimated graduation rates for underrepresented minority and first-generation students. We use a Learning Assistant program to demonstrate the Markov model's strength for assessing program efficacy. We find that Learning Assistants in gateway science courses are associated with a 9% increase in the six-year graduation rate. These gains are larger for underrepresented minority (21%) and first-generation students (18%). Our results indicate that Learning Assistants can improve overall graduation rates and address inequalities in graduation rates for underrepresented students.

Assessing parameter sensitivity in a university campus COVID-19 model with vaccinations.

From the beginning of the COVID-19 pandemic, universities have experienced unique challenges due to their dual nature as a place of education and residence. Current research has explored non-pharmaceutical approaches to combating COVID-19, including representing in models different categories such as age groups. One key area not currently well represented in models is the effect of pharmaceutical preventative measures, specifically vaccinations, on COVID-19 spread on college campuses. There remain key questions on the sensitivity of COVID-19 infection rates on college campuses to potentially time-varying vaccine immunity. Here we introduce a compartment model that decomposes a campus population into constituent subpopulations and implements vaccinations with time-varying efficacy. We use this model to represent a campus population with both vaccinated and unvaccinated individuals, and we analyze this model using two metrics of interest: maximum isolation population and symptomatic infection. We demonstrate a decrease in symptomatic infections occurs for vaccinated individuals when the frequency of testing for unvaccinated individuals is increased. We find that the number of symptomatic infections is insensitive to the frequency of testing of the unvaccinated subpopulation once about 80% or more of the population is vaccinated. Through a Sobol' global sensitivity analysis, we characterize the sensitivity of modeled infection rates to these uncertain parameters. We find that in order to manage symptomatic infections and the maximum isolation population campuses must minimize contact between infected and uninfected individuals, promote high vaccine protection at the beginning of the semester, and minimize the number of individuals developing symptoms.