Reductions in PTSD severity precede reductions in pain intensity among veterans receiving intensive treatment.

OBJECTIVE: Chronic pain often co-occurs with posttraumatic stress disorder (PTSD). The mutual maintenance hypothesis proposes that there may be shared underlying mechanisms of symptoms of pain exacerbating PTSD, and vice versa. The association between PTSD and pain intensity remains understudied. To elucidate the relationship, the present study examined the temporality of changes in PTSD severity and pain intensity in veterans undergoing intensive PTSD treatment. METHOD: Data from 332 veterans undergoing intensive 2-week cognitive processing therapy- (CPT-) based treatment (ITP) with adjunctive components (i.e., mindfulness, art therapy). Random intercepts cross-lagged panel models (RI-CLPMs) were used to examine within-subjects relationships between pain intensity and PTSD severity over the course of the program. RESULTS: Veterans experienced large PTSD severity reductions (Essg = 1.20; p < .001) and small pain severity reductions (Essg = 0.21; p < .001) over the course of treatment, despite pain not being a treatment target. RI-CLPMs revealed that PTSD severity significantly predicted subsequent pain severity. Results indicate the absence of a bidirectional relationship in that changes in pain intensity did not predict later PTSD severity improvement during the ITP. Time trends for both PTSD severity and pain intensity were generally consistent with respect to baseline demographic characteristics. CONCLUSION: Our findings support the mutual maintenance regarding the association between PTSD and pain intensity. Future research should investigate temporal associations in other evidence-based PTSD treatments and formats and evaluate the long-term impacts of PTSD treatment on pain intensity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Functional stress responses in Glaucophyta: Evidence of ethylene and abscisic acid functions in Cyanophora paradoxa.

Glaucophytes, an enigmatic group of freshwater algae, occupy a pivotal position within the Archaeplastida, providing insights into the early evolutionary history of plastids and their host cells. These algae possess unique plastids, known as cyanelles that retain certain ancestral features, enabling a better understanding of the plastid transition from cyanobacteria. In this study, we investigated the role of ethylene, a potent hormone used by land plants to coordinate stress responses, in the glaucophyte alga Cyanophora paradoxa. We demonstrate that C. paradoxa produces gaseous ethylene when supplied with exogenous 1-aminocyclopropane-1-carboxylic acid (ACC), the ethylene precursor in land plants. In addition, we show that cells produce ethylene natively in response to abiotic stress, and that another plant hormone, abscisic acid (ABA), interferes with ethylene synthesis from exogenously supplied ACC, while positively regulating reactive oxygen species (ROS) accumulation. ROS synthesis also occurred following abiotic stress and ACC treatment, possibly acting as a second messenger in stress responses. A physiological response of C. paradoxa to ACC treatment is growth inhibition. Using transcriptomics, we reveal that ACC treatment induces the upregulation of senescence-associated proteases, consistent with the observation of growth inhibition. This is the first report of hormone usage in a glaucophyte alga, extending our understanding of hormone-mediated stress response coordination into the Glaucophyta, with implications for the evolution of signaling modalities across Archaeplastida.

Transcriptome sequencing of seven deep marine invertebrates.

We present 4k video and whole transcriptome data for seven deep-sea invertebrate animals collected in the Eastern Pacific Ocean during a research expedition onboard the Schmidt Ocean Institute's R/V Falkor in August of 2021. The animals include one jellyfish (Atolla sp.), three siphonophores (Apolemia sp., Praya sp., and Halistemma sp.), one larvacean (Bathochordaeus mcnutti), one tunicate (Pyrosomatidae sp.), and one ctenophore (Lampocteis sp.). Four of the animals were sequenced with long-read RNA sequencing technology, such that the reads themselves define a reference assembly for those animals. The larvacean tissues were successfully preserved in situ and has paired long-read reference data and short read quantitative transcriptomic data for within-specimen analyses of gene expression. Additionally, for three animals we provide quantitative image data, and a 3D model for one siphonophore. The paired image and transcriptomic data can be used for species identification, species description, and reference genetic data for these deep-sea animals.

The effects of telehealth-delivered mindfulness meditation, cognitive therapy, and behavioral activation for chronic low back pain: a randomized clinical trial.

BACKGROUND: Chronic low back pain (CLBP) is a significant problem affecting millions of people worldwide. Three widely implemented psychological techniques used for CLBP management are cognitive therapy (CT), mindfulness meditation (MM), and behavioral activation (BA). This study aimed to evaluate the relative immediate (pre- to post-treatment) and longer term (pre-treatment to 3- and 6-month follow-ups) effects of group, videoconference-delivered CT, BA, and MM for CLBP. METHODS: This is a secondary analysis of a three-arm, randomized clinical trial comparing the effects of three active treatments-CT, BA, and MM-with no inert control condition. Participants were N = 302 adults with CLBP, who were randomized to condition. The primary outcome was pain interference, and other secondary outcomes were also examined. The primary study end-point was post-treatment. Intent-to-treat analyses were undertaken for each time point, with the means of the changes in outcomes compared among the three groups using an analysis of variance (ANOVA). Effect sizes and confidence intervals are also reported. RESULTS: Medium-to-large effect size reductions in pain interference were found within BA, CT, and MM (ds from - .71 to - 1.00), with gains maintained at both follow-up time points. Effect sizes were generally small to medium for secondary outcomes for all three conditions (ds from - .20 to - .71). No significant between-group differences in means or changes in outcomes were found at any time point, except for change in sleep disturbance from pre- to post-treatment, improving more in BA than MM (d = - .49). CONCLUSIONS: The findings from this trial, one of the largest telehealth trials of psychological treatments to date, critically determined that group, videoconference-delivered CT, BA, and MM are effective for CLBP and can be implemented in clinical practice to improve treatment access. The pattern of results demonstrated similar improvements across treatments and outcome domains, with effect sizes consistent with those observed in prior research testing in-person delivered and multi-modal psychological pain treatments. Thus, internet treatment delivery represents a tool to scale up access to evidence-based chronic pain treatments and to overcome widespread disparities in healthcare. TRIAL REGISTRATION: Clinicaltrials.gov, NCT03687762.

A genetic atlas for the butterflies of continental Canada and United States.

Multi-locus genetic data for phylogeographic studies is generally limited in geographic and taxonomic scope as most studies only examine a few related species. The strong adoption of DNA barcoding has generated large datasets of mtDNA COI sequences. This work examines the butterfly fauna of Canada and United States based on 13,236 COI barcode records derived from 619 species. It compiles i) geographic maps depicting the spatial distribution of haplotypes, ii) haplotype networks (minimum spanning trees), and iii) standard indices of genetic diversity such as nucleotide diversity (π), haplotype richness (H), and a measure of spatial genetic structure (GST). High intraspecific genetic diversity and marked spatial structure were observed in the northwestern and southern North America, as well as in proximity to mountain chains. While species generally displayed concordance between genetic diversity and spatial structure, some revealed incongruence between these two metrics. Interestingly, most species falling in this category shared their barcode sequences with one at least other species. Aside from revealing large-scale phylogeographic patterns and shedding light on the processes underlying these patterns, this work also exposed cases of potential synonymy and hybridization.

The Brief Evaluation of Adolescents and Children Online (BEACON): Psychometric development of a mental health screening measure for school students.

This paper describes the development and psychometric evaluation of a brief self-report measure (BEACON) to inform universal mental health screening in schools. Items assess symptoms and impairment associated with anxiety and attention/hyperactivity problems (grades 4-11) as well as depression and eating difficulties (grades 6-11), with optional items for suicidality and self-harm (grades 7-11). Initial item examination based on Item Response Theory (IRT) and classical test theory involved 3844 students in grades 4 through 11 (Study 1) and identified 18 items for grades 4-5 and 31 items for grades 6-11 that fulfilled pre-set criteria. Study 2 extended testing with 10,479 students in grades 4-11 and added an additional four items assessing impairment associated with eating difficulties for older students (grades 6-11) creating a total of 35 items for grades 6-11. All items, for both grade-level versions, met the pre-set criteria for IRT and classical test theory analysis supporting their strength in the measurement of the dimensions of concern. The measure showed good reliability (subscale alphas .87 to .95). Validity was also demonstrated against standard symptom measures, school grades, school absenteeism, and help-seeking. The BEACON appears to be a psychometrically sound measure to use in the first stage of school-based screening for mental health problems.

Theory of radiologist interaction with instant messaging decision support tools: A sequential-explanatory study.

Radiology specific clinical decision support systems (CDSS) and artificial intelligence are poorly integrated into the radiologist workflow. Current research and development efforts of radiology CDSS focus on 4 main interventions, based around exam centric time points-after image acquisition, intra-report support, post-report analysis, and radiology workflow adjacent. We review the literature surrounding CDSS tools in these time points, requirements for CDSS workflow augmentation, and technologies that support clinician to computer workflow augmentation. We develop a theory of radiologist-decision tool interaction using a sequential explanatory study design. The study consists of 2 phases, the first a quantitative survey and the second a qualitative interview study. The phase 1 survey identifies differences between average users and radiologist users in software interventions using the User Acceptance of Information Technology: Toward a Unified View (UTAUT) framework. Phase 2 semi-structured interviews provide narratives on why these differences are found. To build this theory, we propose a novel solution called Radibot-a conversational agent capable of engaging clinicians with CDSS as an assistant using existing instant messaging systems supporting hospital communications. This work contributes an understanding of how radiologist-users differ from the average user and can be utilized by software developers to increase satisfaction of CDSS tools within radiology.

Concurrent and lagged associations among pain medication use, pain, and negative affect: a daily diary study of people with chronic low back pain.

ABSTRACT: People with chronic pain often attempt to manage pain and concurrent emotional distress with analgesic substances. Habitual use of such substances-even when not opioid-based-can pose side effect risks. A negative reinforcement model has been proposed whereby relief of pain and emotional distress following medication consumption increases the likelihood that the experience of elevated pain and distress will spur further medication use. People with chronic low back pain (N = 105) completed electronic diary assessments 5 times/day for 14 consecutive days. Lagged and cross-lagged analyses focused on links between time 1 pain and negative affect (NA) and time 2 analgesic medication use and vice versa. Sex differences were also explored. Primary results were as follows: (1) participants on average reported taking analgesic medication during 41.3% of the 3-hour reporting epochs (29 times over 14 days); (2) time 1 within-person increases in pain and NA predicted time 2 increases in the likelihood of ingesting analgesic medications; (3) time 1 within-person increases in medication use predicted time 2 decreases in pain and NA; and (4) lagged associations between time 1 pain/NA and time 2 medication use were strongest among women. Findings suggest that the use of analgesic medications for many people with chronic pain occurs frequently throughout the day. Results support the validity of a negative reinforcement model where pain and distress lead to pain medication use, which in turn leads to relief from pain and distress.

An in situ digital synthesis strategy for the discovery and description of ocean life.

Revolutionary advancements in underwater imaging, robotics, and genomic sequencing have reshaped marine exploration. We present and demonstrate an interdisciplinary approach that uses emerging quantitative imaging technologies, an innovative robotic encapsulation system with in situ RNA preservation and next-generation genomic sequencing to gain comprehensive biological, biophysical, and genomic data from deep-sea organisms. The synthesis of these data provides rich morphological and genetic information for species description, surpassing traditional passive observation methods and preserved specimens, particularly for gelatinous zooplankton. Our approach enhances our ability to study delicate mid-water animals, improving research in the world's oceans.

Cognitive Therapy, Mindfulness-Based Stress Reduction, and Behavior Therapy for the Treatment of Chronic Pain: Predictors and Moderators of Treatment Response.

Psychosocial interventions for people with chronic pain produce significant improvements in outcomes, but these effects on average are modest with much variability in the benefits conferred on individuals. To enhance the magnitude of treatment effects, characteristics of people that might predict the degree to which they respond more or less well could be identified. People with chronic low back pain (N = 521) participated in a randomized controlled trial which compared cognitive therapy, mindfulness-based stress reduction, behavior therapy and treatment as usual. Hypotheses regarding predictors and/or moderators were based on the Limit, Activate, and Enhance model; developed to predict and explain moderators/predictors of psychosocial pain treatments. Results were: 1) low levels of cognitive/behavioral function at pre-treatment predicted favorable pre- to post-treatment outcomes; 2) favorable expectations of benefit from treatment and sound working alliances predicted favorable pre- to post-treatment outcomes; 3) women benefited more than men. These effects emerged without regard to treatment condition. Of note, high levels of cognitive/behavioral function at pre-treatment predicted favorable outcomes only for people in the treatment as usual condition. Analyses identified a set of psychosocial variables that may act as treatment predictors across cognitive therapy, mindfulness-based stress reduction and behavior therapy, as hypothesized by the Limit, Activate, and Enhance model if these 3 treatments operate via similar mechanisms. Findings point toward people who may and who may not benefit fully from the 3 psychosocial treatments studied here, and so may guide future research on matching people to these kinds of psychosocial approaches or to other (eg, forced-based interventions) non-psychosocial approaches. TRIAL REGISTRATION: The ClinicalTrials.gov Identifier is NCT02133976. PERSPECTIVE: This article examines potential predictors/moderators of response to psychosocial treatments for chronic pain. Results could guide efforts to match people to the most effective treatment type or kind.

Improving multimodal physical function in adults with heterogeneous chronic pain; Protocol for a multisite feasibility RCT.

BACKGROUND: Chronic pain is associated with substantial impairment in physical function, which has been identified as a top concern among persons with pain. GetActive-Fitbit, a mind-body activity program, is feasible, acceptable, and associated with improvement in physical function among primarily White, sedentary individuals with pain. In preparation for a multisite efficacy trial, we must examine feasibility across multiple sites with diverse patient populations. Here we describe the protocol of a multisite, feasibility RCT comparing GetActive-Fitbit with a time- and attention-matched educational comparison (Healthy Living for Pain). We aim to 1) test multisite fidelity of clinician training; 2) evaluate multisite feasibility benchmarks, including recruitment of chronic pain patients taking <5000 steps/day and racial and ethnic minorities; and 3) optimize fidelity and study protocol in preparation for a future multisite efficacy trial. METHODS: Clinician training fidelity was assessed via roleplays and mock group sessions. Feasibility (i.e., recruitment, acceptability, credibility, adherence, satisfaction), multimodal physical function (e.g., self-report, 6-Minute Walk Test, step-count), and other psychosocial outcomes are assessed at baseline, posttest, and 6 months. Protocol optimization will be assessed using exit interviews and cross-site meetings. RESULTS: The trial is ongoing. Clinician training is complete. 87 participants have been recruited. 54 completed baseline assessments and randomization, 44 are mid-intervention, and 9 have completed the intervention and posttest. CONCLUSIONS: This study addresses the critical need for feasible, acceptable mind-body-activity interventions for chronic pain that follow evidence-based guidelines and improve all aspects of physical function across diverse populations. Results will inform a future fully-powered multisite efficacy trial. CLINICAL TRIAL REGISTRATION: NCT05700383.

The Influence of a Booster Seat on the Motion of the Reclined Small Female Anthropomorphic Test Device in Low-Acceleration Far-Side Lateral Oblique Impacts.

Belt-positioning booster (BPB) seats may prevent submarining in reclined child occupants in frontal impacts. BPB-seated child volunteers showed reduced lateral displacement in reclined seating in low-acceleration lateral-oblique impacts. As submarining was particularly evident in reclined small adult female occupants, we examined if a booster seat could provide similar effects on the kinematics of the small female occupant to the ones found on the reclined child volunteers in low-acceleration far-side lateral oblique impacts. The THOR-AV-5F was seated on a vehicle seat on a sled simulating a far-side lateral-oblique impact (80 deg from frontal, maximum acceleration ∼2 g, duration ∼170 ms). Lateral and forward head and trunk displacements, trunk rotation, knee-head distance, seatbelt loads, and head acceleration were recorded. Three seatback angles (25 deg, 45 deg, 60 deg) and two booster conditions were examined. Lateral peak head and trunk displacements decreased in more severe reclined seatback angles (25-36 mm decrease compared to nominal). Forward peak head, trunk displacements, and knee-head distance were greater with the seatback reclined and no BPB. Knee-head distance increased in the severe reclined angle also with the booster seat (>40 mm compared to nominal). Seat belt peak loads increased with increased recline angle with the booster, but not without the booster seat. Booster-like solutions may be beneficial for reclined small female adult occupants to reduce head and trunk displacements in far-side lateral-oblique impacts, and knee-head distance and motion variability in severe reclined seatback angles.

Empowered Relief, cognitive behavioral therapy, and health education for people with chronic pain: a comparison of outcomes at 6-month Follow-up for a randomized controlled trial.

Introduction: We previously conducted a 3-arm randomized trial (263 adults with chronic low back pain) which compared group-based (1) single-session pain relief skills intervention (Empowered Relief; ER); (2) 8-session cognitive behavioral therapy (CBT) for chronic back pain; and (3) single-session health and back pain education class (HE). Results suggested non-inferiority of ER vs. CBT at 3 months post-treatment on an array of outcomes. Methods: Here, we tested the durability of treatment effects at 6 months post-treatment. We examined group differences in primary and secondary outcomes at 6 months and the degree to which outcomes eroded or improved from 3-month to 6-month within each treatment group. Results: Empowered Relief remained non-inferior to CBT on most outcomes, whereas both ER and CBT remained superior to HE on most outcomes. Outcome improvements within ER did not decrease significantly from 3-month to 6-month, and indeed ER showed additional 3- to 6-month improvements on pain catastrophizing, pain bothersomeness, and anxiety. Effects of ER at 6 months post-treatment (moderate term outcomes) kept pace with effects reported by participants who underwent 8-session CBT. Conclusions: The maintenance of these absolute levels implies strong stability of ER effects. Results extend to 6 months post-treatment previous findings documenting that ER and CBT exhibit similarly potent effects on outcomes.

Treating a common comorbidity: Pain outcomes following a 3-week cognitive processing therapy-based intensive treatment for posttraumatic stress disorder address.

Posttraumatic stress disorder (PTSD) commonly co-occurs with pain and has been implicated in the maintenance of chronic pain. However, limited research has examined whether intervening for PTSD can hinder or optimize treatment outcomes for co-occurring pain and PTSD. In the present study, we examined changes in pain, PTSD, and depressive symptoms among 125 veterans completing a 3-week cognitive processing therapy (CPT)-based intensive treatment program (ITP) for PTSD. We also explored whether pretreatment pain interference predicted changes in PTSD and depressive symptom severity and whether larger changes in pain interference over the course of treatment were associated with larger changes in PTSD and depressive symptom severity. Linear mixed models revealed that participants' pain interference decreased throughout treatment, d = 0.15, p = .039. Higher levels of pretreatment pain interference were associated with higher PTSD, p = .001, and depressive symptom severity, p = .014, over time. Larger reductions in pain interference corresponded to more improvement in PTSD symptoms, ß = -.03; p < .001, but not depressive symptoms. These findings indicate that ITPs for PTSD can reduce pain interferences, albeit to a small degree, and that reductions in pain interference can contribute to reductions in PTSD symptom severity. Future studies should examine which treatment components contribute to larger changes in symptom severity for veterans with co-occurring pain and PTSD.

The diagnostic journey for patients with late-onset GM2 Gangliosidoses.

Late-onset forms of GM2 gangliosidosis-mainly, Tay-Sachs disease and Sandhoff disease-are under-recognized in clinical practice. In these rare lysosomal storage disorders, deficiency of ß-hexosaminidase A results in excessive accumulation of GM2 ganglioside primarily within neurons, leading to cell death and progressive neurodegenerative symptoms, including ataxia, dysarthria, muscle weakness, tremors, atrophy, and psychosis. Presentation is variable and often mimics more common neurodegenerative disorders. We conducted semi-structured interviews on GM2 gangliosidoses diagnosis and treatment with five experts, 30 neurologists, and 28 patients and caregivers. Symptom onset occurred during adolescence/early adulthood in 92% of patients (median age: 14 years). Patients first visited a healthcare provider at a median age of 20 years and received a GM2 diagnosis at a median age of 26 years. Nearly all patients reported problems with their legs and balance starting from symptom onset. Problems with memory, attention span, speech and fatigue were reported more after diagnosis. Patients visited an average of eight healthcare providers before receiving a diagnosis; 64% were diagnosed by a neurologist. Four neurologists (13%) in our sample were aware that there are late-onset forms of GM2 gangliosidosis. The path to diagnosis is long for this late-onset form of a classically fatal infantile disease.

Long-Read-Based Genome Assembly Reveals Numerous Endogenous Viral Elements in the Green Algal Bacterivore Cymbomonas tetramitiformis.

The marine tetraflagellate Cymbomonas tetramitiformis has drawn attention as an early diverging green alga that uses a phago-mixotrophic mode of nutrition (i.e., the ability to derive nourishment from both photosynthesis and bacterial prey). The Cymbomonas nuclear genome was sequenced previously, but due to the exclusive use of short-read (Illumina) data, the assembly suffered from missing a large proportion of the genome's repeat regions. For this study, we generated Oxford Nanopore long-read and additional short-read Illumina data and performed a hybrid assembly that significantly improved the total assembly size and contiguity. Numerous endogenous viral elements were identified in the repeat regions of the new assembly. These include the complete genome of a giant Algavirales virus along with many genomes of integrated Polinton-like viruses (PLVs) from two groups: Gezel-like PLVs and a novel group of prasinophyte-specific PLVs. The integrated ∼400 kb genome of the giant Algavirales virus is the first account of the association of the uncultured viral family AG_03 with green algae. The complete PLV genomes from C. tetramitiformis ranged between 15 and 25 kb in length and showed a diverse gene content. In addition, heliorhodopsin gene-containing repeat elements of putative mirusvirus origin were identified. These results illustrate past (and possibly ongoing) multiple alga-virus interactions that accompanied the genome evolution of C. tetramitiformis.

A revision of the parasitoid wasp genus Alphomelon Mason with the description of 30 new species (Hymenoptera, Braconidae).

The parasitoid wasp genus Alphomelon Mason, 1981 is revised, based on a combination of basic morphology (dichotomous key and brief diagnostic descriptions), DNA barcoding, biology (host data and wasp cocoons), and distribution data. A total of 49 species is considered; the genus is almost entirely Neotropical (48 species recorded from that region), but three species reach the Nearctic, with one of them extending as far north as 45° N in Canada. Alphomelon parasitizes exclusively Hesperiinae caterpillars (Lepidoptera: Hesperiidae), mostly feeding on monocots in the families Arecaceae, Bromeliaceae, Cannaceae, Commelinaceae, Heliconiaceae, and Poaceae. Most wasp species parasitize either on one or very few (2-4) host species, usually within one or two hesperiine genera; but some species can parasitize several hosts from up to nine different hesperiine genera. Among species with available data for their cocoons, roughly half weave solitary cocoons (16) and half are gregarious (17); cocoons tend to be surrounded by a rather distinctive, coarse silk (especially in solitary species, but also distinguishable in some gregarious species). Neither morphology nor DNA barcoding alone was sufficient on its own to delimit all species properly; by integrating all available evidence (even if incomplete, as available data for every species is different) a foundation is provided for future studies incorporating more specimens, especially from South America. The following 30 new species are described: cruzi, itatiaiensis, and palomae, authored by Shimbori & Fernandez-Triana; and adrianguadamuzi, amazonas, andydeansi, calixtomoragai, carolinacanoae, christerhanssoni, diniamartinezae, duvalierbricenoi, eldaarayae, eliethcantillanoae, gloriasihezarae, guillermopereirai, hazelcambroneroae, josecortesi, keineraragoni, luciarosae, manuelriosi, mikesharkeyi, osvaldoespinozai, paramelanoscelis, paranigriceps, petronariosae, ricardocaleroi, rigoi, rostermoragai, sergioriosi, and yanayacu, authored by Fernandez-Triana & Shimbori.

Ability of artificial intelligence to identify self-reported race in chest x-ray using pixel intensity counts.

Purpose: Prior studies show convolutional neural networks predicting self-reported race using x-rays of chest, hand and spine, chest computed tomography, and mammogram. We seek an understanding of the mechanism that reveals race within x-ray images, investigating the possibility that race is not predicted using the physical structure in x-ray images but is embedded in the grayscale pixel intensities. Approach: Retrospective full year 2021, 298,827 AP/PA chest x-ray images from 3 academic health centers across the United States and MIMIC-CXR, labeled by self-reported race, were used in this study. The image structure is removed by summing the number of each grayscale value and scaling to percent per image (PPI). The resulting data are tested using multivariate analysis of variance (MANOVA) with Bonferroni multiple-comparison adjustment and class-balanced MANOVA. Machine learning (ML) feed-forward networks (FFN) and decision trees were built to predict race (binary Black or White and binary Black or other) using only grayscale value counts. Stratified analysis by body mass index, age, sex, gender, patient type, make/model of scanner, exposure, and kilovoltage peak setting was run to study the impact of these factors on race prediction following the same methodology. Results: MANOVA rejects the null hypothesis that classes are the same with 95% confidence (F 7.38, P<0.0001) and balanced MANOVA (F 2.02, P<0.0001). The best FFN performance is limited [area under the receiver operating characteristic (AUROC) of 69.18%]. Gradient boosted trees predict self-reported race using grayscale PPI (AUROC 77.24%). Conclusions: Within chest x-rays, pixel intensity value counts alone are statistically significant indicators and enough for ML classification tasks of patient self-reported race.

Prediction of habitat complexity using a trait-based approach on coral reefs in Guam.

Scleractinian corals are primary contributors to the structural complexity of coral reef ecosystems. The structure derived from their carbonate skeletons underpins the biodiversity and myriad of ecosystem services provided by coral reefs. This study used a trait-based approach to provide new insights into the relationships between habitat complexity and coral morphology. Three-Dimensional (3D) photogrammetry techniques were used to survey 208 study plots on the island of Guam, from which structural complexity metrics were derived and physical traits of corals were quantified. Three traits at the individual colony level (e.g., morphology, size, and genera) and two site-level environmental characteristics (e.g., wave exposure and substratum-habitat type) were examined. Standard taxonomy-based metrics were also included at the reef-plot level (e.g., coral abundance, richness, and diversity). Different traits disproportionately contributed to 3D metrics of habitat complexity. Larger colonies with a columnar morphology have the highest contribution to surface complexity, slope, and vector ruggedness measure, whereas branching and encrusting columnar colonies have the highest contribution to planform and profile curvature. These results highlight the importance of considering colony morphology and size in addition to conventional taxonomic metrics for the understanding and monitoring reef structural complexity. The approach presented here provides a framework for studies in other locations to predict the trajectory of reefs under changing environmental conditions.

"Shortcuts" Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation.

Despite the expert-level performance of artificial intelligence (AI) models for various medical imaging tasks, real-world performance failures with disparate outputs for various subgroups limit the usefulness of AI in improving patients' lives. Many definitions of fairness have been proposed, with discussions of various tensions that arise in the choice of an appropriate metric to use to evaluate bias; for example, should one aim for individual or group fairness? One central observation is that AI models apply "shortcut learning" whereby spurious features (such as chest tubes and portable radiographic markers on intensive care unit chest radiography) on medical images are used for prediction instead of identifying true pathology. Moreover, AI has been shown to have a remarkable ability to detect protected attributes of age, sex, and race, while the same models demonstrate bias against historically underserved subgroups of age, sex, and race in disease diagnosis. Therefore, an AI model may take shortcut predictions from these correlations and subsequently generate an outcome that is biased toward certain subgroups even when protected attributes are not explicitly used as inputs into the model. As a result, these subgroups became nonprivileged subgroups. In this review, the authors discuss the various types of bias from shortcut learning that may occur at different phases of AI model development, including data bias, modeling bias, and inference bias. The authors thereafter summarize various tool kits that can be used to evaluate and mitigate bias and note that these have largely been applied to nonmedical domains and require more evaluation for medical AI. The authors then summarize current techniques for mitigating bias from preprocessing (data-centric solutions) and during model development (computational solutions) and postprocessing (recalibration of learning). Ongoing legal changes where the use of a biased model will be penalized highlight the necessity of understanding, detecting, and mitigating biases from shortcut learning and will require diverse research teams looking at the whole AI pipeline.