Using recurrent neural networks to detect supernumerary chromosomes in fungal strains causing blast diseases.

The genomes of the fungus Magnaporthe oryzae that causes blast diseases on diverse grass species, including major crops, have indispensable core-chromosomes and may contain supernumerary chromosomes, also known as mini-chromosomes. These mini-chromosomes are speculated to provide effector gene mobility, and may transfer between strains. To understand the biology of mini-chromosomes, it is valuable to be able to detect whether a M. oryzae strain possesses a mini-chromosome. Here, we applied recurrent neural network models for classifying DNA sequences as arising from core- or mini-chromosomes. The models were trained with sequences from available core- and mini-chromosome assemblies, and then used to predict the presence of mini-chromosomes in a global collection of M. oryzae isolates using short-read DNA sequences. The model predicted that mini-chromosomes were prevalent in M. oryzae isolates. Interestingly, at least one mini-chromosome was present in all recent wheat isolates, but no mini-chromosomes were found in early isolates collected before 1991, indicating a preferential selection for strains carrying mini-chromosomes in recent years. The model was also used to identify assembled contigs derived from mini-chromosomes. In summary, our study has developed a reliable method for categorizing DNA sequences and showcases an application of recurrent neural networks in predictive genomics.

Transcriptional regulation of the postnatal cardiac conduction system heterogeneity.

The cardiac conduction system (CCS) is a network of specialized cardiomyocytes that coordinates electrical impulse generation and propagation for synchronized heart contractions. Although the components of the CCS, including the sinoatrial node, atrioventricular node, His bundle, bundle branches, and Purkinje fibers, were anatomically discovered more than 100 years ago, their molecular constituents and regulatory mechanisms remain incompletely understood. Here, we demonstrate the transcriptomic landscape of the postnatal mouse CCS at a single-cell resolution with spatial information. Integration of single-cell and spatial transcriptomics uncover region-specific markers and zonation patterns of expression. Network inference shows heterogeneous gene regulatory networks across the CCS. Notably, region-specific gene regulation is recapitulated in vitro using neonatal mouse atrial and ventricular myocytes overexpressing CCS-specific transcription factors, Tbx3 and/or Irx3. This finding is supported by ATAC-seq of different CCS regions, Tbx3 ChIP-seq, and Irx motifs. Overall, this study provides comprehensive molecular profiles of the postnatal CCS and elucidates gene regulatory mechanisms contributing to its heterogeneity.

PTEN loss shapes macrophage dynamics in high grade serous ovarian carcinoma.

High-grade serous ovarian carcinoma (HGSC) remains a disease of poor prognosis that is unresponsive to current immune checkpoint inhibitors. Although PI3K pathway alterations, such as PTEN loss, are common in HGSC, attempts to target this pathway have been unsuccessful. We hypothesized that aberrant PI3K pathway activation may alter the HGSC immune microenvironment and present a targeting opportunity. Single-cell RNA sequencing identified populations of resident macrophages specific to Pten-null omental tumors in murine models, which were confirmed by flow cytometry. These macrophages derived from peritoneal fluid macrophages and had a unique gene expression program, marked by high expression of the enzyme heme oxygenase-1 (HMOX1). Targeting resident peritoneal macrophages prevented the appearance of HMOX1hi macrophages and reduced tumor growth. Furthermore, direct inhibition of HMOX1 extended survival in vivo. RNA sequencing identified IL33 in Pten-null tumor cells as a likely candidate driver leading to the appearance of HMOX1hi macrophages. Human HGSC tumors also contained HMOX1hi macrophages with a corresponding gene expression program. Moreover, the presence of these macrophages correlated with activated tumoral PI3K/mTOR signaling and poor overall survival in HGSC patients. In contrast, tumors with low numbers of HMOX1hi macrophages were marked by increased adaptive immune response gene expression. These data suggest targeting HMOX1hi macrophages as a potential therapeutic strategy for treating poor prognosis HGSC.

Peripheral liver metastases are more frequently missed than central metastases in contrast-enhanced CT: insights from a 25-reader performance study.

PURPOSE: Subtle liver metastases may be missed in contrast enhanced CT imaging. We determined the impact of lesion location and conspicuity on metastasis detection using data from a prior reader study. METHODS: In the prior reader study, 25 radiologists examined 40 CT exams each and circumscribed all suspected hepatic metastases. CT exams were chosen to include a total of 91 visually challenging metastases. The detectability of a metastasis was defined as the fraction of radiologists that circumscribed it. A conspicuity index was calculated for each metastasis by multiplying metastasis diameter with its contrast, defined as the difference between the average of a circular region within the metastasis and the average of the surrounding circular region of liver parenchyma. The effects of distance from liver edge and of conspicuity index on metastasis detectability were measured using multivariable linear regression. RESULTS: The median metastasis was 1.4 cm from the edge (interquartile range [IQR], 0.9-2.1 cm). Its diameter was 1.2 cm (IQR, 0.9-1.8 cm), and its contrast was 38 HU (IQR, 23-68 HU). An increase of one standard deviation in conspicuity index was associated with a 6.9% increase in detectability (p = 0.008), whereas an increase of one standard deviation in distance from the liver edge was associated with a 5.5% increase in detectability (p = 0.03). CONCLUSION: Peripheral liver metastases were missed more frequently than central liver metastases, with this effect depending on metastasis size and contrast.

Can the Necrophagous Blow Fly Calliphora vicina (Diptera: Calliphoridae) Be Reared on Plant-Based Meal?

The use of the blow fly Calliphora vicina as a potential pollination species to augment the current reliance on honeybees (Apis mellifera) in Australian horticulture requires knowledge of how best to mass-rear this fly species. Calliphora vicina lays eggs onto carrion soon after death, and the resultant larvae that hatch are necrophagous and feed on the decomposing tissues of the dead animal. Newly hatched larvae of this fly were provided with plant-based meals (soya bean and canola) and compared with larvae provided with livestock-derived meatmeal to determine if plant-based meal could be used to mass-rear this blow fly species. Both soya bean and canola meal media did not support larval survival through to adult emergence. The addition of only 10% whole egg powder to the plant-based meals enabled survival to eclosion of 39% and 13% on soya bean and canola-based media, respectively, compared with 76% on livestock-based meatmeal with 10% whole egg powder. Larvae fed a diet of livestock-based meatmeal with 10% whole dried egg powder had the fastest development to the pupal stage, the highest pupation rate, the heaviest pupae, and the highest subsequent adult eclosion. This study concluded that the use of plant-based meals as a diet for the mass-rearing of the blow fly C. vicina was not a viable option.

Creating virtual patients using large language models: scalable, global, and low cost.

Virtual patients (VPs) have long been used to teach and assess clinical reasoning. VPs can be programmed to simulate authentic patient-clinician interactions and to reflect a variety of contextual permutations. However, their use has historically been limited by the high cost and logistical challenges of large-scale implementation. We describe a novel globally-accessible approach to develop low-cost VPs at scale using artificial intelligence (AI) large language models (LLMs). We leveraged OpenAI Generative Pretrained Transformer (GPT) to create and implement two interactive VPs, and created permutations that differed in contextual features. We used systematic prompt engineering to refine a prompt instructing ChatGPT to emulate the patient for a given case scenario, and then provide feedback on clinician performance. We implemented the prompts using GPT-3.5-turbo and GPT-4.0, and created a simple text-only interface using the OpenAI API. GPT-4.0 was far superior. We also conducted limited testing using another LLM (Anthropic Claude), with promising results. We provide the final prompt, case scenarios, and Python code. LLM-VPs represent a 'disruptive innovation' - an innovation that is unmistakably inferior to existing products but substantially more accessible (due to low cost, global reach, or ease of implementation) and thereby able to reach a previously underserved market. LLM-VPs will lay the foundation for global democratization via low-cost-low-risk scalable development of educational and clinical simulations. These powerful tools could revolutionize the teaching, assessment, and research of management reasoning, shared decision-making, and AI evaluation (e.g. 'software as a medical device' evaluations).

Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal-external validation.

BACKGROUND: Binary classification models are frequently used to predict clinical deterioration, however they ignore information on the timing of events. An alternative is to apply time-to-event models, augmenting clinical workflows by ranking patients by predicted risks. This study examines how and why time-to-event modelling of vital signs data can help prioritise deterioration assessments using lift curves, and develops a prediction model to stratify acute care inpatients by risk of clinical deterioration. METHODS: We developed and validated a Cox regression for time to in-hospital mortality. The model used time-varying covariates to estimate the risk of clinical deterioration. Adult inpatient medical records from 5 Australian hospitals between 1 January 2019 and 31 December 2020 were used for model development and validation. Model discrimination and calibration were assessed using internal-external cross validation. A discrete-time logistic regression model predicting death within 24 h with the same covariates was used as a comparator to the Cox regression model to estimate differences in predictive performance between the binary and time-to-event outcome modelling approaches. RESULTS: Our data contained 150,342 admissions and 1016 deaths. Model discrimination was higher for Cox regression than for discrete-time logistic regression, with cross-validated AUCs of 0.96 and 0.93, respectively, for mortality predictions within 24 h, declining to 0.93 and 0.88, respectively, for mortality predictions within 1 week. Calibration plots showed that calibration varied by hospital, but this can be mitigated by ranking patients by predicted risks. CONCLUSION: Time-varying covariate Cox models can be powerful tools for triaging patients, which may lead to more efficient and effective care in time-poor environments when the times between observations are highly variable.

PD-L1 promotes oncolytic virus infection via a metabolic shift that inhibits the type I IFN pathway.

While conventional wisdom initially postulated that PD-L1 serves as the inert ligand for PD-1, an emerging body of literature suggests that PD-L1 has cell-intrinsic functions in immune and cancer cells. In line with these studies, here we show that engagement of PD-L1 via cellular ligands or agonistic antibodies, including those used in the clinic, potently inhibits the type I interferon pathway in cancer cells. Hampered type I interferon responses in PD-L1-expressing cancer cells resulted in enhanced efficacy of oncolytic viruses in vitro and in vivo. Consistently, PD-L1 expression marked tumor explants from cancer patients that were best infected by oncolytic viruses. Mechanistically, PD-L1 promoted a metabolic shift characterized by enhanced glycolysis rate that resulted in increased lactate production. In turn, lactate inhibited type I IFN responses. In addition to adding mechanistic insight into PD-L1 intrinsic function, our results will also help guide the numerous ongoing efforts to combine PD-L1 antibodies with oncolytic virotherapy in clinical trials.

Phase-changing citrate macromolecule combats oxidative pancreatic islet damage, enables islet engraftment and function in the omentum.

Clinical outcomes for total-pancreatectomy followed by intraportal islet autotransplantation (TP-IAT) to treat chronic pancreatitis (CP) are suboptimal due to pancreas inflammation, oxidative stress during islet isolation, and harsh engraftment conditions in the liver's vasculature. We describe a thermoresponsive, antioxidant macromolecule poly(polyethylene glycol citrate-co-N-isopropylacrylamide) (PPCN) to protect islet redox status and function and to enable extrahepatic omentum islet engraftment. PPCN solution transitions from a liquid to a hydrogel at body temperature. Islets entrapped in PPCN and exposed to oxidative stress remain functional and support long-term euglycemia, in contrast to islets entrapped in a plasma-thrombin biologic scaffold. In the nonhuman primate (NHP) omentum, PPCN is well-tolerated and mostly resorbed without fibrosis at 3 months after implantation. In NHPs, autologous omentum islet transplantation using PPCN restores normoglycemia with minimal exogenous insulin requirements for >100 days. This preclinical study supports TP-IAT with PPCN in patients with CP and highlights antioxidant properties as a mechanism for islet function preservation.

Diazepam nasal spray administration is effective to control seizure clusters irrespective of time of day.

Introduction: Neurologic circadian influences, including sleep/wake transitions, processes (e.g., hormonal variation), and behavioral patterns (e.g., consumption of food and oral medications), may affect seizure patterns. Specific circadian patterns of seizures have been reported depending on type, onset location, and severity; however, data on patterns for patients with seizure clusters and effectiveness of rescue therapy by time of day are limited. Methods: We conducted post hoc analyses using patient diary data from the phase 3 safety study of diazepam nasal spray, which is indicated for acute treatment of seizure clusters in patients with epilepsy aged ≥6 years. Patients were administered age- and weight-based doses; second doses could be administered if needed to control a seizure cluster. We assessed clock timing of seizure-cluster onset along with second-dose use as a proxy for effectiveness. Treatment-emergent adverse events were recorded. Results: Seizure-cluster onset was observed to be generally highest during mornings and late evenings and lowest in the early evening and middle of the night. Second-dose use was not consistently associated with a specific time of day. The safety profile was consistent with that expected from previous studies of diazepam nasal spray. Conclusion: These results suggest that diazepam nasal spray can be effectively administered at any time of day.

External vs Internal Focus of Attention in Procedural Skills Learning: A Randomized Study.

PURPOSE: The Optimizing Performance Through Intrinsic Motivation and Attention for Learning theory postulates that directing attention to the intended movement effect or outcome (external focus) is more effective than directing attention to the internal body motion or body part (internal focus). This study compared external vs internal focus of attention as novice students learned ultrasound-guided peripheral cannulation. The authors hypothesized that conditions promoting an external (vs internal) focus of attention would result in better performance on immediate and delayed (retention) testing. METHOD: The authors conducted a randomized, experimental study from October 2022 to February 2023 comparing external and internal focus using ultrasound-guided peripheral venous cannulation followed by practice using an ultrasound training block. Undergraduate health science students performed 4 practice trials with instructions to focus on the needle tip (external focus) or their hands (internal focus), followed by an immediate assessment and a retention assessment 2 weeks later. The primary outcome was time to successful cannulation. Results were compared using Kaplan-Meier curves and parametric survival analysis regression (accelerated failure time) models. RESULTS: Seventy participants completed the immediate assessment. The external focus group completed successful cannulation a mean of 2.33 times faster (95% CI = 1.47, 3.67; P < .001) than those in the internal focus group (median time, 12.0 vs 29.5 seconds). Results also favored the external focus group during practice, with the external focus group successfully completing the task a mean of 1.83 times faster (95% CI = 1.04, 3.21; P = .04) than the internal focus group. In the retention assessment, the external focus group successfully completed the task a mean of 2.37 times faster (95% CI = 1.19, 4.74; P = .02) than the internal focus group. CONCLUSIONS: External focus of attention compared with internal focus of attention improves medical motor skill learning in novice learners.

Developing a Novel Ontology for Cybersecurity in Internet of Medical Things-Enabled Remote Patient Monitoring.

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. IoMT is a collection of various medical devices and their applications within the research domain. On the other hand, MIoT ontology refers to the proposed ontology that defines various concepts, roles, and individuals. MIoT ontology utilizes the knowledge engineering methodology outlined in Ontology Development 101, along with the structured life cycle, and establishes semantic interoperability among medical devices to secure IoMT assets from vulnerabilities and cyberattacks. By defining key concepts and relationships, it becomes easier to understand and analyze the complex network of information within the IoMT. The MIoT ontology captures essential key terms and security-related entities for future extensions. A conceptual model is derived from the MIoT ontology and validated through a case study. Furthermore, this paper outlines a roadmap for future research, highlighting potential impacts on security automation in healthcare applications.

Macroscopic changes in aquaporin-4 underlie blast traumatic brain injury-related impairment in glymphatic function.

Mild traumatic brain injury (mTBI) has emerged as a potential risk factor for the development of neurodegenerative conditions such as Alzheimer's disease and chronic traumatic encephalopathy. Blast mTBI, caused by exposure to a pressure wave from an explosion, is predominantly experienced by military personnel and has increased in prevalence and severity in recent decades. Yet the underlying pathology of blast mTBI is largely unknown. We examined the expression and localization of AQP4 in human post-mortem frontal cortex and observed distinct laminar differences in AQP4 expression following blast exposure. We also observed similar laminar changes in AQP4 expression and localization and delayed impairment of glymphatic function that emerged 28 days following blast injury in a mouse model of repetitive blast mTBI. In a cohort of veterans with blast mTBI, we observed that blast exposure was associated with an increased burden of frontal cortical MRI-visible perivascular spaces, a putative neuroimaging marker of glymphatic perivascular dysfunction. These findings suggest that changes in AQP4 and delayed glymphatic impairment following blast injury may render the post-traumatic brain vulnerable to post-concussive symptoms and chronic neurodegeneration.

Estimating human pharmacokinetic parameters forelectronic nicotine delivery system products from chemical analyses of their aerosols.

The ability of Electronic Nicotine Delivery Systems (ENDS) to deliver nicotine is central to their function to substitute for cigarettes, allowing people who smoke to switch away from smoking, thus reducing their exposure to harmful chemicals in cigarette smoke. The nicotine concentration in ENDS e-liquid has proved to be a poor predictor of nicotine uptake in users. Using meta-analytic methods to analyze 12 pharmacokinetic studies of nicotine-salt closed-system ENDS, this paper examines whether the mass of nicotine/puff of aerosol can predict Cmax in pharmacokinetic studies. Cmax values were available for 38 products, in 58 use conditions (including both controlled [3 s] and ad libitum puffing), comprising 1769 participant observations. Nicotine/puff data reflected chemical analyses of aerosol obtained under nonintense (3 s) or intense (6 s) machine puffing. Meta-regression analyses (weighted by reliability of Cmax estimate) assessed the relationship of nicotine/puff to Cmax. In some models, empirical data were used to impute the variation in Cmax or the nicotine/puff value under intense puffing. In simple linear models, Cmax was significantly associated with nicotine/puff under all combinations of intense/nonintense and controlled/ad-libitum conditions, with R2 values of 0.71-0.77. More complex models based on quadratic effects or log[nicotine/puff] did not generally improve upon more parsimonious linear models. Application of the model illustrates the divergence between nicotine concentration in e-liquids and expected Cmax when other ENDS parameters vary. The meta-analytic model may have utility in settings where clinical pharmacokinetic data are not available, including product development.

Validation of the motivated strategies for learning questionnaire and instructional materials motivation survey.

PURPOSE: To validate the Motivated Strategies for Learning Questionnaire (MSLQ), which measures learner motivations; and the Instructional Materials Motivation Survey (IMMS), which measures the motivational properties of educational activities. METHODS: Participants (333 pharmacists, physicians, and advanced practice providers) completed the MSLQ, IMMS, Congruence-Personalization Questionnaire (CPQ), and a knowledge test immediately following an online learning module (April 2021). We randomly divided data for split-sample analysis using confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and the multitrait-multimethod matrix. RESULTS: Cronbach alpha was ≥0.70 for most domains. CFA using sample 1 demonstrated suboptimal fit for both instruments, including 3 negatively-worded IMMS items with particularly low loadings. Revised IMMS (RIMMS) scores (which omit negatively-worded items) demonstrated better fit. Guided by EFA, we identified a novel 3-domain, 11-item 'MSLQ-Short Form-Revised' (MSLQ-SFR, with domains: Interest, Self-efficacy, and Attribution) and the 4-domain, 12-item RIMMS as the best models. CFA using sample 2 confirmed good fit. Correlations among MSLQ-SFR, RIMMS, and CPQ scores aligned with predictions; correlations with knowledge scores were small. CONCLUSIONS: Original MSLQ and IMMS scores show poor model fit, with negatively-worded items notably divergent. Revised, shorter models-the MSLQ-SFR and RIMMS-show satisfactory model fit (internal structure) and relations with other variables.

Validation of the Learner Engagement Instrument for Continuing Professional Development.

PURPOSE: Learner engagement is the energy learners exert to remain focused and motivated to learn. The Learner Engagement Instrument (LEI) was developed to measure learner engagement in a short continuing professional development (CPD) activity. The authors validated LEI scores using validity evidence of internal structure and relationships with other variables. METHOD: Participants attended 1 of 4 CPD courses (1 in-person, 2 online livestreamed, and 1 either in-person or livestreamed) in 2018, 2020, 2021, and 2022. Confirmatory factor analysis was used to examine model fit for several alternative structural models, separately for each course. The authors also conducted a generalizability study to estimate score reliability. Associations were evaluated between LEI scores and Continuing Medical Education Teaching Effectiveness (CMETE) scores and participant demographics. Statistical methods accounted for repeated measures by participants. RESULTS: Four hundred fifteen unique participants attended 203 different CPD presentations and completed the LEI 11,567 times. The originally hypothesized 4-domain model of learner engagement (domains: emotional, behavioral, cognitive in-class, cognitive out-of-class) demonstrated best model fit in all 4 courses, with comparative fit index ≥ 0.99, standardized root mean square residual ≤ 0.031, and root mean square error of approximation ≤ 0.047. The reliability for overall scores and domain scores were all acceptable (50-rater G-coefficient ≥ 0.74) except for the cognitive in-class domain (50-rater G-coefficient of 0.55 to 0.66). Findings were similar for both in-person and online delivery modalities. Correlation of LEI scores with teaching effectiveness was confirmed (rho=0.58), and a small correlation was found with participant age (rho=0.19); other associations were small and not statistically significant. Using these findings, we generated a shortened 4-item instrument, the LEI Short Form. CONCLUSIONS: This study confirms a 4-domain model of learner engagement and provides validity evidence that supports using LEI scores to measure learner engagement in both in-person and livestreamed CPD activities.

Single-Cell RNA Sequencing Reveals Repair Features of Human Umbilical Cord Mesenchymal Stromal Cells.

Rationale: The chronic lung disease bronchopulmonary dysplasia (BPD) is the most severe complication of extreme prematurity. BPD results in impaired lung alveolar and vascular development and long-term respiratory morbidity, for which only supportive therapies exist. Umbilical cord-derived mesenchymal stromal cells (UC-MSCs) improve lung structure and function in experimental BPD. Results of clinical trials with MSCs for many disorders do not yet match the promising preclinical studies. A lack of specific criteria to define functionally distinct MSCs persists. Objectives: To determine and correlate single-cell UC-MSC transcriptomic profiles with therapeutic potential. Methods: UC-MSCs from five term donors and human neonatal dermal fibroblasts (HNDFs; control cells of mesenchymal origin) transcriptomes were investigated using single-cell RNA sequencing (scRNA-seq) analysis. The lung-protective effect of UC-MSCs with a distinct transcriptome and control HNDFs was tested in vivo in hyperoxia-induced neonatal lung injury in rats. Measurements and Main Results: UC-MSCs showed limited transcriptomic heterogeneity but were different from HNDFs. Gene Ontology enrichment analysis revealed distinct (progenitor-like and fibroblast-like) UC-MSC subpopulations. Only treatment with progenitor-like UC-MSCs improved lung function and structure and attenuated pulmonary hypertension in hyperoxia-exposed rat pups. Moreover, scRNA-seq identified major histocompatibility complex class I as a molecular marker of nontherapeutic cells and associated with decreased lung retention. Conclusions: UC-MSCs with a progenitor-like transcriptome, but not with a fibroblast-like transcriptome, provide lung protection in experimental BPD. High expression of major histocompatibility complex class I is associated with reduced therapeutic benefit. scRNA-seq may be useful to identify subsets of MSCs with superior repair capacity for clinical application.

Assessment of management reasoning: Design considerations drawn from analysis of simulated outpatient encounters.

PURPOSE: Management reasoning is a distinct subset of clinical reasoning. We sought to explore features to be considered when designing assessments of management reasoning. METHODS: This is a hybrid empirical research study, narrative review, and expert perspective. In 2021, we reviewed and discussed 10 videos of simulated (staged) physician-patient encounters, actively seeking actions that offered insights into assessment of management reasoning. We analyzed our own observations in conjunction with literature on clinical reasoning assessment, using a constant comparative qualitative approach. RESULTS: Distinguishing features of management reasoning that will influence its assessment include management scripts, shared decision-making, process knowledge, illness-specific knowledge, and tailoring of the encounter and management plan. Performance domains that merit special consideration include communication, integration of patient preferences, adherence to the management script, and prognostication. Additional facets of encounter variation include the clinical problem, clinical and nonclinical patient characteristics (including preferences, values, and resources), team/system characteristics, and encounter features. We cataloged several relevant assessment approaches including written/computer-based, simulation-based, and workplace-based modalities, and a variety of novel response formats. CONCLUSIONS: Assessment of management reasoning could be improved with attention to the performance domains, facets of variation, and variety of approaches herein identified.

Kink bands promote exceptional fracture resistance in a NbTaTiHf refractory medium-entropy alloy.

Single-phase body-centered cubic (bcc) refractory medium- or high-entropy alloys can retain compressive strength at elevated temperatures but suffer from extremely low tensile ductility and fracture toughness. We examined the strength and fracture toughness of a bcc refractory alloy, NbTaTiHf, from 77 to 1473 kelvin. This alloy's behavior differed from that of comparable systems by having fracture toughness over 253 MPa·m1/2, which we attribute to a dynamic competition between screw and edge dislocations in controlling the plasticity at a crack tip. Whereas the glide and intersection of screw and mixed dislocations promotes strain hardening controlling uniform deformation, the coordinated slip of <111> edge dislocations with {110} and {112} glide planes prolongs nonuniform strain through formation of kink bands. These bands suppress strain hardening by reorienting microscale bands of the crystal along directions of higher resolved shear stress and continually nucleate to accommodate localized strain and distribute damage away from a crack tip.