Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex.

In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS). We tested the model using data from toxicokinetic and toxicity experiments with Gammarus pulex exposed to the insecticides imidacloprid and flupyradifurone. The experiments revealed increased TK rates with increasing temperature and increased toxicity under chronic exposures. Using the widely used Arrhenius equation, we could include the temperature influence into the modeling. By further testing of different model approaches, differences in the temperature scaling of TK and TD model parameters could be identified, urging further investigations of the underlying mechanisms. Finally, our results show that predictions of TK-TD models improve if we include the toxicity modulating effect of temperature explicitly.

Comparing the acute and chronic toxicity of flupyradifurone and imidacloprid to non-target aquatic arthropod species.

Flupyradifurone (FPF) is a new type of butenolide insecticide. It was launched on the market in 2015 and is considered an alternative to the widely used neonicotinoids, like imidacloprid (IMI), some of which are banned from outdoor use in the European Union. FPF is claimed to be safe for bees, but its safety for aquatic organisms is unknown. Its high water solubility, persistence in the environment, and potential large-scale use make it urgent to evaluate possible impacts on aquatic systems. The current study assessed the acute and chronic toxicity of FPF for aquatic arthropod species and compared these results with those of imidacloprid. Besides, toxicokinetics and toxicokinetic-toxicodynamic models were used to understand the mechanisms of the toxicity of FPF. The present study results showed that organisms take up FPF slower than IMI and eliminate it faster. In addition, the hazardous concentration 5th percentiles (HC05) value of FPF derived from a species sensitivity distribution (SSD) based on acute toxicity was found to be 0.052 µmol/L (corresponding to 15 µg/L), which was 37 times higher than IMI (0.0014 µmol/L, corresponding to 0.36 µg/L). The chronic 28 days EC10 of FPF for Cloeon dipterum and Gammarus pulex were 7.5 µg/L and 2.9 µg/L, respectively. For G. pulex, after 28 days of exposure, the no observed effect concentration (NOEC) of FPF for food consumption was 0.3 µg/L. A toxicokinetic-toxicodynamic (TKTD) model parameterised on the acute toxicity data well predicted the observed chronic effects of FPF on G. pulex, indicating that toxicity mechanisms of FPF did not change with prolonged exposure time, which is not the case for IMI.

Size- and sex-related sensitivity differences of aquatic crustaceans to imidacloprid.

Field collected aquatic invertebrates are often used as test organisms in the refinement of the standard Tier 1 risk assessment of various pollutants. This approach can provide insights into the effects of pollutants on the natural environment. However, researchers often pragmatically select test organisms of a specific sex and/or size, which may not represent the sensitivity of the whole population. To investigate such intraspecies sensitivity differences, we performed standard acute toxicity and toxicokinetic tests with different size classes and sex of Gammarus pulex and Asellus aquaticus. Furthermore, toxicokinetics and toxicodynamics models were used to understand the mechanism of the intraspecies sensitivity differences. We used neonates, juveniles and male and female adults in separate dedicated experiments, in which we exposed the animals to imidacloprid and its bioactive metabolite, imidacloprid-olefin. For both species, we found that neonates were the most sensitive group. For G. pulex, the sensitivity decreased linearly with size, which can be explained by the size-related uptake rate constant in the toxicokinetic process and size-related threshold value in the toxicodynamic process. For A. aquaticus, female adults were least sensitive to imidacloprid, which could be explained by a low internal biotransformation of imidacloprid to imidacloprid-olefin. Besides, imidacloprid-olefin was more toxic than imidacloprid to A. aquaticus, with differences being 8.4 times for females and 2.7 times for males. In conclusion, we established size-related sensitivity differences for G. pulex and sex-related sensitivity for A. aquaticus, and intraspecies differences can be explained by both toxicokinetic and toxicodynamic processes. Our findings suggest that to protect populations in the field, we should consider the size and sex of focal organisms and that a pragmatic selection of test organisms of equal size and/or sex can underestimate the sensitivities of populations in the field.

Characterizing effects of age, sex and psychosis symptoms on thalamocortical functional connectivity in youth.

The thalamus is composed of multiple nuclei densely connected with the cortex in an organized manner, forming parallel thalamocortical networks critical to sensory, motor, and cognitive functioning. Thalamocortical circuit dysfunction has been implicated in multiple neurodevelopmental disorders, including schizophrenia, which also often exhibit sex differences in prevalence, clinical characteristics, and neuropathology. However, very little is known about developmental and sex effects on thalamocortical networks in youth. The present study characterized the effects of age, sex and psychosis symptomatology in anatomically constrained thalamocortical networks in a large community sample of youth (n = 1100, aged 8-21) from the Philadelphia Neurodevelopmental Cohort (PNC). Cortical functional connectivity of seven anatomically defined thalamic nuclear groups were examined: anterior, mediodorsal, ventral lateral, ventral posterolateral, pulvinar, medial and lateral geniculate nuclear groups. Age and sex effects were characterized using complementary thalamic region-of-interest (ROI) to cortical ROI and voxel-wise analyses. Effects of clinical symptomatology were analyzed by separating youth into three groups based on their clinical symptoms; typically developing youth (n = 298), psychosis spectrum youth (n = 320), and youth with other psychopathologies (n = 482). As an exploratory analysis, association with PRIME scores were used as a dimensional measure of psychopathology. Age effects were broadly characterized by decreasing connectivity with sensory/motor cortical areas, and increasing connectivity with heteromodal prefrontal and parietal cortical areas. This pattern was most pronounced for thalamic motor and sensory nuclei. Females showed greater connectivity between multiple thalamic nuclear groups and the visual cortex compared to males, while males showed greater connectivity with the inferior frontal and orbitofrontal cortices. Youth with psychosis spectrum symptoms showed a subtle decrease in thalamic connectivity with the premotor and prefrontal cortices. Across all youth, greater PRIME scores were associated with lower connectivity between the prefrontal cortex and mediodorsal thalamus. By characterizing typical development in anatomically constrained thalamocortical networks, this study provides an anchor for conceptualizing disruptions to the integrity of these networks observed in neurodevelopmental disorders.

Cerebrovascular Complications in Early Survivors of Civilian Penetrating Brain Injury.

BACKGROUND: This study investigates the presence of cerebrovascular injuries in a large sample of civilian penetrating brain injury (PBI) patients, determining the prevalence, radiographic characteristics, and impact on short-term outcome. METHODS: We retrospectively reviewed patients with PBI admitted to our institution over a 2-year period. Computed tomography head scans, computer tomography angiograms and venograms of the intracranial vessels were evaluated to determine the wound trajectory, intracranial injury characteristics, and presence of arterial (AI) and venous sinus (VSI) injuries. Demographics, clinical presentation, and treatment were also reviewed. Discharge disposition was used as surrogate of short-term outcome. RESULTS: Seventy-two patients were included in the study. The mechanism of injury was gunshot wounds in 71 patients and stab wound in one. Forty-one of the 72 patients (60%) had at least one vascular injury. Twenty-six out of 72 patients suffered an AI (36%), mostly pseudoaneurysms and occlusions, involving the anterior and middle cerebral arteries. Of the 72 patients included, 45 had dedicated computed tomography venograms, and of those 22 had VSI (49%), mainly manifesting as superior sagittal sinus occlusion. In a multivariable regression model, intraventricular hemorrhage at presentation was associated with AI (OR 9.9, p = 0.004). The same was not true for VSI. CONCLUSION: Acute traumatic cerebrovascular injury is a prevalent complication in civilian PBI, frequently involving both the arterial and venous sinus systems. Although some radiographic features might be associated with presence of vascular injury, assessment of the intracranial vasculature in the acute phase of all PBI is essential for early diagnosis. Treatment of vascular injury remains variable depending on local practice.

A Positive Regulatory Feedback Loop between EKLF/KLF1 and TAL1/SCL Sustaining the Erythropoiesis.

The erythroid Krüppel-like factor EKLF/KLF1 is a hematopoietic transcription factor binding to the CACCC DNA motif and participating in the regulation of erythroid differentiation. With combined use of microarray-based gene expression profiling and the promoter-based ChIP-chip assay of E14.5 fetal liver cells from wild type (WT) and EKLF-knockout (Eklf-/-) mouse embryos, we identified the pathways and direct target genes activated or repressed by EKLF. This genome-wide study together with the molecular/cellular analysis of the mouse erythroleukemic cells (MEL) indicate that among the downstream direct target genes of EKLF is Tal1/Scl. Tal1/Scl encodes another DNA-binding hematopoietic transcription factor TAL1/SCL, known to be an Eklf activator and essential for definitive erythroid differentiation. Further identification of the authentic Tal gene promoter in combination with the in vivo genomic footprinting approach and DNA reporter assay demonstrate that EKLF activates the Tal gene through binding to a specific CACCC motif located in its promoter. These data establish the existence of a previously unknow positive regulatory feedback loop between two DNA-binding hematopoietic transcription factors, which sustains mammalian erythropoiesis.

Early Childhood Parenting Predicts Late Childhood Brain Functional Connectivity During Emotion Perception and Reward Processing.

Seventy-nine 3-year olds and their mothers participated in a laboratory-based task to assess maternal hostility. Mothers also reported their behavioral regulation of their child. Seven years later, functional magnetic resonance imaging data were acquired while viewing emotional faces and completing a reward processing task. Maternal hostility predicted more negative amygdala connectivity during exposure to sad relative to neutral faces with frontal and parietal regions as well as more negative left ventral striatal connectivity during monetary gain relative to loss feedback with the right posterior orbital frontal cortex and right inferior frontal gyrus. In contrast, maternal regulation predicted enhanced cingulo-frontal connectivity during monetary gain relative to loss feedback. Results suggest parenting is associated with alterations in emotion and reward processing circuitry 7-8 years later.

Negative Regulation of the Differentiation of Flk2- CD34- LSK Hematopoietic Stem Cells by EKLF/KLF1.

Erythroid Krüppel-like factor (EKLF/KLF1) was identified initially as a critical erythroid-specific transcription factor and was later found to be also expressed in other types of hematopoietic cells, including megakaryocytes and several progenitors. In this study, we have examined the regulatory effects of EKLF on hematopoiesis by comparative analysis of E14.5 fetal livers from wild-type and Eklf gene knockout (KO) mouse embryos. Depletion of EKLF expression greatly changes the populations of different types of hematopoietic cells, including, unexpectedly, the long-term hematopoietic stem cells Flk2- CD34- Lin- Sca1+ c-Kit+ (LSK)-HSC. In an interesting correlation, Eklf is expressed at a relatively high level in multipotent progenitor (MPP). Furthermore, EKLF appears to repress the expression of the colony-stimulating factor 2 receptor ß subunit (CSF2RB). As a result, Flk2- CD34- LSK-HSC gains increased differentiation capability upon depletion of EKLF, as demonstrated by the methylcellulose colony formation assay and by serial transplantation experiments in vivo. Together, these data demonstrate the regulation of hematopoiesis in vertebrates by EKLF through its negative regulatory effects on the differentiation of the hematopoietic stem and progenitor cells, including Flk2- CD34- LSK-HSCs.

A dynamic energy budget (DEB) model to assess the sublethal effects of imidacloprid toward Gammarus pulex at different temperatures.

Environmental ambient temperature significantly impacts the metabolic activities of aquatic ectotherm organisms and influences the fate of various chemicals. Although numerous studies have shown that the acute lethal toxicity of most chemicals increases with increasing temperature, the impact of temperature on chronic effects - encompassing both lethal and sublethal endpoints - has received limited attention. Furthermore, the mechanisms linking temperature and toxicity, potentially unveiled by toxicokinetic-toxicodynamic models (TKTD), remains inadequately explored. This study investigated the effects of environmentally relevant concentrations of the insecticide imidacloprid (IMI) on the growth and survival of the freshwater amphipod Gammarus pulex at two different temperatures. Our experimental design was tailored to fit a TKTD model, specifically the Dynamic Energy Budget (DEB) model. We conducted experiments spanning three and six months, utilizing small G. pulex juveniles. We observed effects endpoints at least five times, employing both destructive and non-destructive methods, crucial for accurate model fittings. Our findings reveal that IMI at environmental concentrations (up to 0.3 µg/L) affects the growth and survival of G. pulex, albeit with limited effects, showing a 10% inhibition compared to the control group. These limited effects, observed in both lethal and sublethal aspects, suggest a different mode of action at low, environmentally-relevant concentrations in long-term exposure (3 months), in contrast to previous studies which applied higher concentrations and found that sublethal effects occurred at significantly lower levels than lethal effects in an acute test setting (4 days). Moreover, after parameterizing the DEB model for various temperatures, we identified a lower threshold for both lethal and sublethal effects at higher temperatures, indicating increased intrinsic sensitivity. Overall, this study contributes to future risk assessments considering temperature as a crucial factor and exemplifies the integration of the DEB model into experimental design for comprehensive toxicity evaluations.

Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling.

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Using machine learning to identify key subject categories predicting the pre-clerkship and clerkship performance: 8-year cohort study.

BACKGROUND: Medical students need to build a solid foundation of knowledge to become physicians. Clerkship is often considered the first transition point, and clerkship performance is essential for their development. We hope to identify subjects that could predict the clerkship performance, thus helping medical students learn more efficiently to achieve high clerkship performance. METHODS: This cohort study collected background and academic data from medical students who graduated between 2011 and 2019. Prediction models were developed by machine learning techniques to identify the affecting features in predicting the pre-clerkship performance and clerkship performance. Following serial processes of data collection, data preprocessing before machine learning, and techniques and performance of machine learning, different machine learning models were trained and validated using the 10-fold cross-validation method. RESULTS: Thirteen subjects from the pre-med stage and 10 subjects from the basic medical science stage with an area under the ROC curve (AUC) >0.7 for either pre-clerkship performance or clerkship performance were found. In each subject category, medical humanities and sociology in social science, chemistry, and physician scientist-related training in basic science, and pharmacology, immunology-microbiology, and histology in basic medical science have predictive abilities for clerkship performance above the top tertile. Using a machine learning technique based on random forest, the prediction model predicted clerkship performance with 95% accuracy and 88% AUC. CONCLUSION: Clerkship performance was predicted by selected subjects or combination of different subject categories in the pre-med and basic medical science stages. The demonstrated predictive ability of subjects or categories in the medical program may facilitate students' understanding of how these subjects or categories of the medical program relate to their performance in the clerkship to enhance their preparedness for the clerkship.

Learning pathways composed of core subjects with features of reducing cognitive load have better learning outcomes.

BACKGROUND: Changing the course duration or timing of subjects in learning pathways would influence medical students' learning outcomes. Curriculum designers need to consider the strategy of reducing cognitive load and evaluate it continuously. Our institution underwent gradual curricular changes characterized by reducing cognitive load since 2000. Therefore, we wanted to explore the impact of this strategy on our previous cohorts. METHODS: This cohort study explored learning pathways across academic years of more than a decade since 2000. Eight hundred eighty-two medical students between 2006 and 2012 were included eventually. Learning outcomes included an average and individual scores of subjects in different stages. Core subjects were identified as those where changes in duration or timing would influence learning outcomes and constitute different learning pathways. We examined whether the promising learning pathway defined as the pathway with the most features of reducing cognitive load has higher learning outcomes than other learning pathways in the exploring dataset. The relationship between features and learning outcomes was validated by learning pathways selected in the remaining dataset. RESULTS: We found nine core subjects, constituting four different learning pathways. Two features of extended course duration and increased proximity between core subjects of basic science and clinical medicine were identified in the promising learning pathway 2012, which also had the highest learning outcomes. Other pathways had some of the features, and pathway 2006 without such features had the lowest learning outcomes. The relationship between higher learning outcomes and cognitive load-reducing features was validated by comparing learning outcomes in two pathways with and without similar features of the promising learning pathway. CONCLUSION: An approach to finding a promising learning pathway facilitating students' learning outcomes was validated. Curricular designers may implement similar design to explore the promising learning pathway while considering potential confounding factors, including students, medical educators, and learning design of the course.

A New Paradigm for High-dimensional Data: Distance-Based Semiparametric Feature Aggregation Framework via Between-Subject Attributes.

This article proposes a distance-based framework incentivized by the paradigm shift towards feature aggregation for high-dimensional data, which does not rely on the sparse-feature assumption or the permutation-based inference. Focusing on distance-based outcomes that preserve information without truncating any features, a class of semiparametric regression has been developed, which encapsulates multiple sources of high-dimensional variables using pairwise outcomes of between-subject attributes. Further, we propose a strategy to address the interlocking correlations among pairs via the U-statistics-based estimating equations (UGEE), which correspond to their unique efficient influence function (EIF). Hence, the resulting semiparametric estimators are robust to distributional misspecification while enjoying root-n consistency and asymptotic optimality to facilitate inference. In essence, the proposed approach not only circumvents information loss due to feature selection but also improves the model's interpretability and computational feasibility. Simulation studies and applications to the human microbiome and wearables data are provided, where the feature dimensions are tens of thousands.

Real-world outcomes of atypical EGFR-mutated metastatic non-small cell lung cancer (mNSCLC)treated with osimertinib (osi) vs. Afatinib or erlotinib.

OBJECTIVES: Limited data are available comparing the efficacy of osi versus earlier generation TKIs for mNSCLC with atypical EGFR mutations (AMs) such as L861Q, G719X, S768I and exon20. METHODS: We performed a single-institution retrospective analysis of patients with EGFR-mutated mNSCLC treated from 2007 to 2023 with 1L TKIs, comparing outcomes for AM patients treated with osi, afatinib, and erlotinib. Baseline demographics, disease characteristics, treatment history, toxicity, and clinical outcomes were abstracted from the electronic medical record and compared between TKIs using independent sample t-tests and chi-square analyses. Median progression free survival (mPFS) and overall survival (mOS) were compared via Kaplan-Meier log-rank analysis and Cox multivariable regression. RESULTS: Among 355 patients with EGFR-mutated mNSCLC, 36 (10 %) harbored AMs in G719X (N=21; 6 %), Exon 20 (N=11; 3 %), L861Q (N=7; 2 %), S768I (N=4; 1 %), C797S (N=1; 0.3 %); 6 patients had compound mutations. Patients with classical mutations (CMs) vs AMs had similar baseline demographic and disease characteristics and usage of TKIs (p = 0.124). Among AM patients, osi yielded superior mPFS (22 m) vs afatinib (12 m; p = 0.005) or erlotinib (9 m; p = 0.001). mOS was likewise superior for osi (32 m) vs afatinib (21 m; p = 0.032) or erlotinib (17 m; p = 0.011). Dose-reduction rates due to AEs were lower for osi (19 %) vs afatinib (24 %; p = 0.003) or erlotinib (23 %; p = 0.002). Discontinuation rates due to AEs were lower for osi vs afatinib (1 % vs 2 %; p < 0.001) or erlotinib (2 %; p = 0.004). CONCLUSIONS: In a large real-world analysis, osi demonstrated superior progression-free and overall survival and improved tolerability compared to afatinib or erlotinib for atypical EGFR-mutated mNSCLC.

Energy consumption prediction using the GRU-MMattention-LightGBM model with features of Prophet decomposition.

The prediction of energy consumption is of great significance to the stability of the regional energy supply. In previous research on energy consumption forecasting, researchers have constantly proposed improved neural network prediction models or improved machine learning models to predict time series data. Combining the well-performing machine learning model and neural network model in energy consumption prediction, we propose a hybrid model architecture of GRU-MMattention-LightGBM with feature selection based on Prophet decomposition. During the prediction process, first, the prophet features are extracted from the original time series. We select the best LightGBM model in the training set and save the best parameters. Then, the Prophet feature is input to GRU-MMattention for training. Finally, MLP is used to learn the final prediction weight between LightGBM and GRU-MMattention. After the prediction weights are learned, the final prediction result is determined. The innovation of this paper lies in that we propose a structure to learn the internal correlation between features based on Prophet feature extraction combined with the gating and attention mechanism. The structure also has the characteristics of a strong anti-noise ability of the LightGBM method, which can reduce the impact of the energy consumption mutation point on the overall prediction effect of the model. In addition, we propose a simple method to select the hyperparameters of the time window length using ACF and PACF diagrams. The MAPE of the GRU-MMattention-LightGBM model is 1.69%, and the relative error is 8.66% less than that of the GRU structure and 2.02% less than that of the LightGBM prediction. Compared with a single method, the prediction accuracy and stability of this hybrid architecture are significantly improved.

The effect of temperature on toxicokinetics and the chronic toxicity of insecticides towards Gammarus pulex.

A comprehensive understanding of chemical toxicity and temperature interaction is essential to improve ecological risk assessment under climate change. However, there is only limited knowledge about the effect of temperature on the toxicity of chemicals. To fill this knowledge gap and to improve our mechanistic understanding of the influence of temperature, the current study explored toxicokinetics and the chronic toxicity effects of two insecticides, imidacloprid (IMI) and flupyradifurone (FPF), on Gammarus pulex at different temperatures (7-24 °C). In the toxicokinetics tests, organisms were exposed to IMI or FPF for 2 days and then transferred to clean water for 3 days of elimination at 7, 18, or 24 °C. In the chronic tests, organisms were exposed to the individual insecticides for 28 days at 7, 11, or 15 °C. Our research found that temperature impacted the toxicokinetics and the chronic toxicity of both IMI and FPF, while the extent of such impact differed for each insecticide. For IMI, the uptake rate and biotransformation rate increased with temperature, and mortality and food consumption inhibition was enhanced by temperature. While for FPF, the elimination rate increased with temperature at a higher rate than the increasing uptake rate, resulting in a smaller pronounced effect of temperature on mortality compared to IMI. In addition, the adverse effects of the insecticides on sublethal endpoints (food consumption and dry weight) were exacerbated by elevated temperatures. Our results highlight the importance of including temperature in the ecological risk assessment of insecticides in light of global climate change.

Evaluation of resampling-based inference for topological features of neuroimages.

Many recent studies have demonstrated the inflated type 1 error rate of the original Gaussian random field (GRF) methods for inference of neuroimages and identified resampling (permutation and bootstrapping) methods that have better performance. There has been no evaluation of resampling procedures when using robust (sandwich) statistical images with different topological features (TF) used for neuroimaging inference. Here, we consider estimation of distributions TFs of a statistical image and evaluate resampling procedures that can be used when exchangeability is violated. We compare the methods using realistic simulations and study sex differences in life-span age-related changes in gray matter volume in the Nathan Kline Institute Rockland sample. We find that our proposed wild bootstrap and the commonly used permutation procedure perform well in sample sizes above 50 under realistic simulations with heteroskedasticity. The Rademacher wild bootstrap has fewer assumptions than the permutation and performs similarly in samples of 100 or more, so is valid in a broader range of conditions. We also evaluate the GRF-based pTFCE method and show that it has inflated error rates in samples less than 200. Our R package, pbj , is available on Github and allows the user to reproducibly implement various resampling-based group level neuroimage analyses.

"We're playing on the same team": Communication (dis)connections between trauma patients and surgical residents.

BACKGROUND: Patient-physician communication is key to better clinical outcomes and patient well-being. Communication between trauma patients and their physicians remains relatively unexplored. We aimed to identify and characterize the range of strengths and challenges in patient-physician communication in the setting of trauma care. METHODS: A qualitative, grounded theory approach was used to explore communication strengths and challenges for patients and residents. Patients previously admitted to the trauma service for violent injuries were recruited and interviewed in-person during their trauma clinic appointments. Surgical residents were recruited via email and interviewed virtually via Zoom. Anonymous, semistructured interviews were conducted until thematic saturation was reached. RESULTS: Twenty-nine interviews with patients and 14 interviews with residents were conducted. Patients reported feeling ignored and misunderstood and having inadequate communication with physicians. Residents cited lack of time, patients' lack of health literacy, differences in background, and emotional responses to trauma as barriers to effective communication with patients. Patients and residents reported an understanding of each other's stressors, similar emotional experiences regarding traumatic stress, and a desire to communicate with each other in greater depth both inside and outside of the hospital. CONCLUSION: Trauma patients and residents can feel disconnected due to the lack of time for thorough communication and differences in background; however, they understand each other's stressors and share similar emotional responses regarding trauma and a desire for increased communication, connection, and solidarity. Leveraging these shared values to guide interventions, such as a resident curriculum, may help bridge disconnects and improve their communication. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level IV.

Cerebellar Structure and Cognitive Ability in Psychosis.

BACKGROUND: Dysconnectivity theories, combined with advances in fundamental cognitive neuroscience, have led to increased interest in characterizing cerebellar abnormalities in psychosis. Smaller cerebellar gray matter volume has been found in schizophrenia spectrum disorders. However, the course of these deficits across illness stage, specificity to schizophrenia (vs. psychosis more broadly), and relationship to clinical phenotypes, primarily cognitive impairment, remain unclear. METHODS: The Spatially Unbiased Infratentorial toolbox, a gold standard for analyzing human neuroimaging data of the cerebellum, was used to quantify cerebellar volumes and conduct voxel-based morphometry on structural magnetic resonance images obtained from 574 individuals (249 schizophrenia spectrum, 108 bipolar with psychotic features, 217 nonpsychiatric control). Analyses examining diagnosis (schizophrenia spectrum, bipolar disorder), illness stage (early, chronic), and cognitive effects on cerebellum structure in psychosis were performed. RESULTS: Cerebellar structure in psychosis did not differ significantly from healthy participants, regardless of diagnosis and illness stage (effect size = 0.01-0.14). In contrast, low premorbid cognitive functioning was associated with smaller whole and regional cerebellum volumes, including cognitive (lobules VI and VII, Crus I, frontoparietal and attention networks) and motor (lobules I-IV, V, and X; somatomotor network) regions in psychosis (effect size = 0.36-0.60). These effects were not present in psychosis cohorts with average estimated premorbid cognition. CONCLUSIONS: Cerebellar structural abnormalities in psychosis are related to lower premorbid cognitive functioning implicating early antecedents, atypical neurodevelopment, or both in cerebellar dysfunction. Future research focused on identifying the impact of early-life risk factors for psychosis on the development of the cerebellum and cognition is warranted.