Routine ICU Surveillance after Brain Tumor Surgery: Patient Selection Using Machine Learning.

Background/Objectives: Routine postoperative ICU admission following brain tumor surgery may not benefit selected patients. The objective of this study was to develop a risk prediction instrument for early (within 24 h) postoperative adverse events using machine learning techniques. Methods: Retrospective cohort of 1000 consecutive adult patients undergoing elective brain tumor resection. Nine events/interventions (CPR, reintubation, return to OR, mechanical ventilation, vasopressors, impaired consciousness, intracranial hypertension, swallowing disorders, and death) were chosen as target variables. Potential prognostic features (n = 27) from five categories were chosen and a gradient boosting algorithm (XGBoost) was trained and cross-validated in a 5 × 5 fashion. Prognostic performance, potential clinical impact, and relative feature importance were analyzed. Results: Adverse events requiring ICU intervention occurred in 9.2% of cases. Other events not requiring ICU treatment were more frequent (35% of cases). The boosted decision trees yielded a cross-validated ROC-AUC of 0.81 ± 0.02 (mean ± CI95) when using pre- and post-op data. Using only pre-op data (scheduling decisions), ROC-AUC was 0.76 ± 0.02. PR-AUC was 0.38 ± 0.04 and 0.27 ± 0.03 for pre- and post-op data, respectively, compared to a baseline value (random classifier) of 0.092. Targeting a NPV of at least 95% would require ICU admission in just 15% (pre- and post-op data) or 30% (only pre-op data) of cases when using the prediction algorithm. Conclusions: Adoption of a risk prediction instrument based on boosted trees can support decision-makers to optimize ICU resource utilization while maintaining adequate patient safety. This may lead to a relevant reduction in ICU admissions for surveillance purposes.

CTLA4 blockade abrogates KEAP1/STK11-related resistance to PD-(L)1 inhibitors.

For patients with advanced non-small-cell lung cancer (NSCLC), dual immune checkpoint blockade (ICB) with CTLA4 inhibitors and PD-1 or PD-L1 inhibitors (hereafter, PD-(L)1 inhibitors) is associated with higher rates of anti-tumour activity and immune-related toxicities, when compared with treatment with PD-(L)1 inhibitors alone. However, there are currently no validated biomarkers to identify which patients will benefit from dual ICB1,2. Here we show that patients with NSCLC who have mutations in the STK11 and/or KEAP1 tumour suppressor genes derived clinical benefit from dual ICB with the PD-L1 inhibitor durvalumab and the CTLA4 inhibitor tremelimumab, but not from durvalumab alone, when added to chemotherapy in the randomized phase III POSEIDON trial3. Unbiased genetic screens identified loss of both of these tumour suppressor genes as independent drivers of resistance to PD-(L)1 inhibition, and showed that loss of Keap1 was the strongest genomic predictor of dual ICB efficacy-a finding that was confirmed in several mouse models of Kras-driven NSCLC. In both mouse models and patients, KEAP1 and STK11 alterations were associated with an adverse tumour microenvironment, which was characterized by a preponderance of suppressive myeloid cells and the depletion of CD8+ cytotoxic T cells, but relative sparing of CD4+ effector subsets. Dual ICB potently engaged CD4+ effector cells and reprogrammed the tumour myeloid cell compartment towards inducible nitric oxide synthase (iNOS)-expressing tumoricidal phenotypes that-together with CD4+ and CD8+ T cells-contributed to anti-tumour efficacy. These data support the use of chemo-immunotherapy with dual ICB to mitigate resistance to PD-(L)1 inhibition in patients with NSCLC who have STK11 and/or KEAP1 alterations.

How to elicit a negative bias? Manipulating contrast and saturation with the facial emotion salience task.

Introduction: Emotion recognition impairments and a tendency to misclassify neutral faces as negative are common in schizophrenia. A possible explanation for these deficits is aberrant salience attribution. To explore the possibility of salience driven emotion recognition deficits, we implemented a novel facial emotion salience task (FEST). Methods: Sixty-six healthy participants with variations in psychometric schizotypy completed the FEST. In the FEST, we manipulated physical salience (FEST-1: contrast, FEST-2: saturation) of emotionally salient (positive, i.e., happy and negative, i.e., fearful) and non-salient (neutral) facial expressions. Results: When salience was high (increased contrast), participants recognized negative facial expressions faster, whereas neutral faces were recognized more slowly and were more frequently misclassified as negative. When salience was low (decreased saturation), positive expressions were recognized more slowly. These measures were not associated with schizotypy in our sample. Discussion: Our findings show that the match between physical and emotional salience influences emotion recognition and suggest that the FEST is suitable to simulate aberrant salience processing during emotion recognition in healthy participants.

Nothing to lose? Neural correlates of decision, anticipation, and feedback in the balloon analog risk task.

Understanding the subprocesses of risky decision making is a prerequisite for understanding (dys-)functional decisions. For the present fMRI study, we designed a novel variant of the balloon-analog-risk task (BART) that measures three phases: decision making, reward anticipation, and feedback processing. Twenty-nine healthy young adults completed the BART. We analyzed neural activity and functional connectivity. Parametric modulation allowed assessing changes in brain functioning depending on the riskiness of the decision. Our results confirm involvement of nucleus accumbens, insula, anterior cingulate cortex, and dorsolateral prefrontal cortex in all subprocesses of risky decision-making. In addition, subprocesses were differentiated by the strength of activation in these regions, as well as by changes in activity and nucleus accumbens-connectivity by the riskiness of the decision. The presented fMRI-BART variant allows distinguishing activity and connectivity during the subprocesses of risky decision making and shows how activation and connectivity patterns relate to the riskiness of the decision. Hence, it is a useful tool for unraveling impairments in subprocesses of risky decision making in people with high risk behavior.

Joint multi-omics discriminant analysis with consistent representation learning using PANDA.

Integrative multi-omics analysis provides deeper insight and enables better and more realistic modeling of the underlying biology and causes of diseases than does single omics analysis. Although several integrative multi-omics analysis methods have been proposed and demonstrated promising results in integrating distinct omics datasets, inconsistent distribution of the different omics data, which is caused by technology variations, poses a challenge for paired integrative multi-omics methods. In addition, the existing discriminant analysis-based integrative methods do not effectively exploit correlation and consistent discriminant structures, necessitating a compromise between correlation and discrimination in using these methods. Herein we present PAN-omics Discriminant Analysis (PANDA), a joint discriminant analysis method that seeks omics-specific discriminant common spaces by jointly learning consistent discriminant latent representations for each omics. PANDA jointly maximizes between-class and minimizes within-class omics variations in a common space and simultaneously models the relationships among omics at the consistency representation and cross-omics correlation levels, overcoming the need for compromise between discrimination and correlation as with the existing integrative multi-omics methods. Because of the consistency representation learning incorporated into the objective function of PANDA, this method seeks a common discriminant space to minimize the differences in distributions among omics, can lead to a more robust latent representations than other methods, and is against the inconsistency of the different omics. We compared PANDA to 10 other state-of-the-art multi-omics data integration methods using both simulated and real-world multi-omics datasets and found that PANDA consistently outperformed them while providing meaningful discriminant latent representations. PANDA is implemented using both R and MATLAB, with codes available at https://github.com/WuLabMDA/PANDA.

Comprehensive Myocardial Assessment by Computed Tomography: Impact on Short-Term Outcomes After Transcatheter Aortic Valve Replacement.

BACKGROUND: Quantification of myocardial changes in severe aortic stenosis (AS) is prognostically important. The potential for comprehensive myocardial assessment pre-transcatheter aortic valve replacement (TAVR) by computed tomography angiography (CTA) is unknown. OBJECTIVES: This study sought to evaluate whether quantification of left ventricular (LV) extracellular volume-a marker of myocardial fibrosis-and global longitudinal strain-a marker of myocardial deformation-at baseline CTA associate with post-TAVR outcomes. METHODS: Consecutive patients with symptomatic severe AS between January 2021 and June 2022 who underwent pre-TAVR CTA were included. Computed tomography extracellular volume (CT-ECV) was derived from septum tracing after generating the 3-dimensional CT-ECV map. Computed tomography global longitudinal strain (CT-GLS) used semi-automated feature tracking analysis. The clinical endpoint was the composite outcome of all-cause mortality and heart failure hospitalization. RESULTS: Among the 300 patients (80.0 ± 9.4 years of age, 45% female, median Society of Thoracic Surgeons Predicted Risk of Mortality score 2.80%), the left ventricular ejection fraction (LVEF) was 58% ± 12%, the median CT-ECV was 28.5% (IQR: 26.2%-32.1%), and the median CT-GLS was -20.1% (IQR: -23.8% to -16.3%). Over a median follow-up of 16 months (IQR: 12-22 months), 38 deaths and 70 composite outcomes occurred. Multivariable Cox proportional hazards model, accounting for clinical and echocardiographic variables, demonstrated that CT-ECV (HR: 1.09 [95% CI: 1.02-1.16]; P = 0.008) and CT-GLS (HR: 1.07 [95% CI: 1.01-1.13]; P = 0.017) associated with the composite outcome. In combination, elevated CT-ECV and CT-GLS (above median for each) showed a stronger association with the outcome (HR: 7.14 [95% CI: 2.63-19.36]; P < 0.001). CONCLUSIONS: Comprehensive myocardial quantification of CT-ECV and CT-GLS associated with post-TAVR outcomes in a contemporary low-risk cohort with mostly preserved LVEF. Whether these imaging biomarkers can be potentially used for the decision making including timing of AS intervention and post-TAVR follow-up will require integration into future clinical trials.

Water depth influences survival and predator-specific patterns of nest loss in three secretive marsh bird species.

Wetlands have become increasingly rare in the United States, negatively influencing wetland-dependent birds, and many remaining wetlands are intensively managed through seasonal dewatering mimicking historic flood pulses during spring and summer. However, water around nests may provide protection from terrestrial predators, and lowering water levels during the breeding season of wetland birds may increase predation risk and exacerbate marsh bird population declines. Understanding interactions between water depth, nesting marsh birds, and nest predators is critical to aid managers in developing a multi-species management approach in emergent wetlands. During the 2020 and 2021 breeding seasons, we examined nest survival of 148 marsh bird nests (American Coot, Fulica americana, n = 1; Common Gallinule, Gallinula galeata, n = 64; and Least Bittern; Ixobrychus exilis, n = 83) and installed cameras at 78 nests to identify predators at a large, restored floodplain wetland in Illinois where the primary management technique is seasonal water removal to stimulate germination of moist soil plants. We found nest predation of, and abandonment by, Least Bittern and Common Gallinule were related to shallower water, and early season, high volume dewatering. Least Bitterns nested more commonly along wetland edges and nests farther from the shore were more likely to survive. Similarly, we found mammalian depredation of nests and nest abandonment decreased when deeper water was present around nests. Alternatively, snake predation was observed earlier in the year prior to water removal from inundated emergent vegetation. Our results demonstrate water depth may be an important deterrent of nest predators, especially mammals, during the breeding season. Further, we recommend managers delay dewatering until after the nesting season at sites where management for conservation-priority marsh birds is a focus.

Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer.

Non-small cell lung cancers that harbor concurrent KRAS and TP53 (KP) mutations are immunologically warm tumors with partial responsiveness to anti-PD-(L)1 blockade; however, most patients observe little or no durable clinical benefit. To identify novel tumor-driven resistance mechanisms, we developed a panel of KP murine lung cancer models with intrinsic resistance to anti-PD-1 and queried differential gene expression between these tumors and anti-PD-1-sensitive tumors. We found that the enzyme autotaxin (ATX), and the metabolite it produces, lysophosphatidic acid (LPA), were significantly upregulated in resistant tumors and that ATX directly modulated antitumor immunity, with its expression negatively correlating with total and effector tumor-infiltrating CD8+ T cells. Pharmacological inhibition of ATX, or the downstream receptor LPAR5, in combination with anti-PD-1 was sufficient to restore the antitumor immune response and efficaciously control lung tumor growth in multiple KP tumor models. Additionally, ATX was significantly correlated with inflammatory gene signatures, including a CD8+ cytolytic score in multiple lung adenocarcinoma patient data sets, suggesting that an activated tumor-immune microenvironment upregulates ATX and thus provides an opportunity for cotargeting to prevent acquired resistance to anti-PD-1 treatment. These data reveal the ATX/LPA axis as an immunosuppressive pathway that diminishes the immune checkpoint blockade response in lung cancer.

ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC.

PURPOSE: Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated. EXPERIMENTAL DESIGN: Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models. RESULTS: Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy. CONCLUSIONS: ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

Routine ICU admission after brain tumor surgery: retrospective validation and critical appraisal of two prediction scores.

BACKGROUND: Routine admission to an intensive care unit (ICU) following brain tumor surgery has been a common practice for many years. Although this practice has been challenged by many authors, it has still not changed widely, mainly due to the lack of reliable data for preoperative risk assessment. Motivated by this dilemma, risk prediction scores for postoperative complications following brain tumor surgery have been developed recently. In order to improve the ICU admission policy at our institution, we assessed the applicability, performance, and safety of the two most appropriate risk prediction scores. METHODS: One thousand consecutive adult patients undergoing elective brain tumor resection within 19 months were included. Patients with craniotomy for other causes, i.e., cerebral aneurysms and microvascular decompression, were excluded. The decision for postoperative ICU-surveillance was made by joint judgment of the operating surgeon and the anesthesiologist. All data and features relevant to the scores were extracted from clinical records and subsequent ICU or neurosurgical floor documentation was inspected for any postoperative adverse events requiring ICU admission. The CranioScore derived by Cinotti et al. (Anesthesiology 129(6):1111-20, 5) and the risk assessment score of Munari et al. (Acta Neurochir (Wien) 164(3):635-641, 15) were calculated and prognostic performance was evaluated by ROC analysis. RESULTS: In our cohort, both scores showed only a weak prognostic performance: the CranioScore reached a ROC-AUC of 0.65, while Munari et al.'s score achieved a ROC-AUC of 0.67. When applying the recommended decision thresholds for ICU admission, 64% resp. 68% of patients would be classified as in need of ICU surveillance, and the negative predictive value (NPV) would be 91% for both scores. Lowering the thresholds in order to increase patient safety, i.e., 95% NPV, would lead to ICU admission rates of over 85%. CONCLUSION: Performance of both scores was limited in our cohort. In practice, neither would achieve a significant reduction in ICU admission rates, whereas the number of patients suffering complications at the neurosurgical ward would increase. In future, better risk assessment measures are needed.

Cerebellar Mutism Syndrome After Posterior Fossa Tumor Surgery in Children-A Retrospective Single-Center Study.

OBJECTIVE: Cerebellar mutism syndrome (CMS) is a well-known complication after posterior fossa tumor surgery in pediatric patients. We evaluated the incidence of CMS in our institute and analyzed its association with multiple risk factors, such as tumor entity, surgical approach, and hydrocephalus. METHODS: All pediatric patients who had undergone intra-axial tumor resection in the posterior fossa between January 2010 and March 2021 were included in the retrospective analysis. Various data points, including demographic, tumor-associated, clinical, radiological, surgery-associated, complications, and follow-up data, were collected and statistically evaluated for an association with CMS. RESULTS: A total of 63 surgeries in 60 patients were included. The median patient age was 8 years. Pilocytic astrocytoma was the most common tumor type (50%), followed by medulloblastoma (28%) and ependymomas (10%). Complete, subtotal, and partial resection was achieved in 67%, 23%, and 10%, respectively. A telovelar approach had been used the most often (43%) compared with a transvermian approach (8%). Of the 60 children, 10 (17%) had developed CMS and showed marked improvement but with residual deficits. The significant risk factors were a transvermian approach (P = 0.03), vermian splitting when added to another approach (P = 0.002), an initial presentation with acute hydrocephalus (P = 0.02), and hydrocephalus present after tumor surgery (P = 0.004). CONCLUSIONS: Our CMS rate is comparable to those described in the literature. Despite the limitations of the retrospective study design, we found that CMS was not only associated with a transvermian approach but was also associated with a telovelar approach, although to a lesser extent. Acute hydrocephalus at the initial presentation necessitating urgent management was significantly associated with a greater incidence of CMS.

A protocol for digitizing colors: the case of measuring color variables for forested wetland soils.

A procedure is presented and discussed that highlights the use of the Nix Pro Color Sensor ("Nix") in digitizing soil colors with applications for forested wetland soils. Informed by our soil color investigations using both the Munsell Soil Color Chart (MSCC) and the Nix in forested wetlands of the northern Virginia area, we crafted a standard operating procedure (SOP), adaptable to various locations and/or soil types, that guides users-regardless of knowledge of soil ecology or familiarity with the Nix-to successfully assess and monitor soil colors at various depths. Our SOP outlines steps for digitally collecting, storing, and sharing soil color data. Through the implementation of this procedure, soil color monitoring can enter the digital age, removing barriers of entry to soil color determination and enhancing individuals' interest in monitoring and understanding of the importance of soil color as an environmental and ecological indicator. With continued refinement and adaptation to intended use, the SOP herein presented has the potential to aid wetland/watershed assessment by providing data on soil colors that can be tracked over time while also encouraging public engagement in environmental monitoring of soils.

Shared Nearest Neighbors Approach and Interactive Browser for Network Analysis of a Comprehensive Non-Small-Cell Lung Cancer Data Set.

PURPOSE: Advances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining. METHODS: We present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project. RESULTS: Benchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype. CONCLUSION: The network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.

Cutting Edge: l-Arginine Transfer from Antigen-Presenting Cells Sustains CD4+ T Cell Viability and Proliferation.

Metabolomics analyses suggest changes in amino acid abundance, particularly l-arginine (L-ARG), occur in patients with tuberculosis. Immune cells require L-ARG to fuel effector functions following infection. We have previously described an L-ARG synthesis pathway in immune cells; however, its role in APCs has yet to be uncovered. Using a coculture system with mycobacterial-specific CD4+ T cells, we show APC L-ARG synthesis supported T cell viability and proliferation, and activated T cells contained APC-derived L-ARG. We hypothesize that APCs supply L-ARG to support T cell activation under nutrient-limiting conditions. This work expands the current model of APC-T cell interactions and provides insight into the effects of nutrient availability in immune cells.

Effective connectivity of the human mirror neuron system during social cognition.

The human mirror neuron system (MNS) can be considered the neural basis of social cognition. Identifying the global network structure of this system can provide significant progress in the field. In this study, we use dynamic causal modeling (DCM) to determine the effective connectivity between central regions of the MNS for the first time during different social cognition tasks. Sixty-seven healthy participants completed fMRI scanning while performing social cognition tasks, including imitation, empathy and theory of mind. Superior temporal sulcus (STS), inferior parietal lobule (IPL) and Brodmann area 44 (BA44) formed the regions of interest for DCM. Varying connectivity patterns, 540 models were built and fitted for each participant. By applying group-level analysis, Bayesian model selection and Bayesian model averaging, the optimal family and model for all experimental tasks were found. For all social-cognitive processes, effective connectivity from STS to IPL and from STS to BA44 was found. For imitation, additional mutual connections occurred between STS and BA44, as well as BA44 and IPL. The results suggest inverse models in which the motor regions BA44 and IPL receive sensory information from the STS. In contrast, for imitation, a sensory loop with an exchange of motor-to-sensory and sensory-to-motor information seems to exist.

Predicting forested wetland soil carbon using quantitative color sensor measurements in the region of northern Virginia, USA.

Forested wetland soils within the Piedmont and Coastal Plain physiographic provinces of Northern Virginia (NOVA) were investigated to determine the utility of a handheld colorimeter, the Nix Pro Color Sensor ("Nix"), for predicting carbon contents (TC) and stocks (TC stocks) from on-site color measurements. Both the color variables recorded with each Nix scan ("Nix color variables"; n = 15) and carbon contents significantly differed between sites, with redder soils (higher a and h) at Piedmont sites, and higher TC at sites with darker soils (lower values of L, or lightness; p < 0.05). Nix-carbon correlation analysis revealed strong relationships between L (lightness), X (a virtual spectral variable), R (additive red), and KK (black) and log-transformed TC (Ln[TC]; |r| = 0.70; p < 0.01 for all). Simple linear regressions were conducted to identify how well these four final Nix variables could predict soil carbon. Using all color measurements, about 50% of Ln(TC) variability could be explained by L, X, R, or KK (p < 0.01), yet with higher predictive power obtained for Coastal Plain soils (0.55 < R2 < 0.65; p < 0.01). Regression model strength was maximized between Ln(TC) and the four final Nix variables using simple linear regressions when color measurements observed at a specific depth were first averaged (0.66 < R2 < 0.70; p < 0.01). While further study is warranted to investigate Nix applicability within various soil settings, these results demonstrate potential for the Nix and its soil color measurements to assist with rapid field-based assessments of soil carbon in forested wetlands.

Promotion of Anti-Tuberculosis Macrophage Activity by L-Arginine in the Absence of Nitric Oxide.

Macrophages are indispensable immune cells tasked at eliminating intracellular pathogens. Mycobacterium tuberculosis (Mtb), one of the most virulent intracellular bacterial pathogens known to man, infects and resides within macrophages. While macrophages can be provoked by extracellular stimuli to inhibit and kill Mtb bacilli, these host defense mechanisms can be blocked by limiting nutritional metabolites, such as amino acids. The amino acid L-arginine has been well described to enhance immune function, especially in the context of driving macrophage nitric oxide (NO) production in mice. In this study, we aimed to establish the necessity of L-arginine on anti-Mtb macrophage function independent of NO. Utilizing an in vitro system, we identified that macrophages relied on NO for only half of their L-arginine-mediated host defenses and this L-arginine-mediated defense in the absence of NO was associated with enhanced macrophage numbers and viability. Additionally, we observed macrophage glycolysis to be driven by both L-arginine and mechanistic target of rapamycin (mTOR), and inhibition of glycolysis or mTOR reduced macrophage control of Mtb as well as macrophage number and viability in the presence of L-arginine. Our data underscore L-arginine as an essential nutrient for macrophage function, not only by fueling anti-mycobacterial NO production, but also as a central regulator of macrophage metabolism and additional host defense mechanisms.

Analysis of soil color variables and their relationships between two field-based methods and its potential application for wetland soils.

While the Munsell Soil Color Chart (MSCC) is the most frequently used, well-established field method for reading soil color, the Nix Color Sensor (NCS) is an inexpensive, app-based alternative that can complement or potentially substitute for the MSCC. Soils were collected and their colors were measured from four forested sites across Northern Virginia within the Chesapeake Bay Watershed using both the MSCC and NCS. Three MSCC variables and 15 NCS variables were collected in the field; a methodology was established to use these "measured" (M) variables to derive 9 NCS calculated (C) variables. A stepwise correlation identified NCS variables most suitable for relating the NCS to each of the MSCC attributes: hue (H), value (V), and chroma (CM). Ultimately, H, V, and CM were deemed to be best represented by HRGB calculated from the RGB color space (ρ = 0.56), L from the CIE-Lab color space (ρ = 0.73), and z = Z/(X + Y + Z) from the XYZ color space (ρ = -0.80), respectively (p < 0.001). The corresponding explanatory powers of final NCS variables (i.e., HRGB, L, and z) for H, V, and CM were 26%, 54%, and 62%, respectively (p <0.01). Significant differences in z between soils identified as hydric and nonhydric, but lack of nonoverlapping ranges, indicate a potential for the NCS to complement the MSCC in assessing wetland soil color in an accessible and reproducible manner, including hydric soil identifications for wetland delineation practices. Further study with more data over various types of soils is necessary to establish stronger relationships between the NCS and MSCC. Nonetheless, the method of characterizing soil color variables from the two field methods presented in the study can serve as a template for future studies or environmental education programs desiring to use the NCS as a complement to the MSCC.

The human mirror neuron system-A common neural basis for social cognition?

According to the theory of embodied simulation, mirror neurons (MN) in our brain's motor system are the neuronal basis of all social-cognitive processes. The assumption of such a mirroring process in humans could be supported by results showing that within one person the same region is involved in different social cognition tasks. We conducted an fMRI-study with 75 healthy participants who completed three tasks: imitation, empathy, and theory of mind. We analyzed the data using group conjunction analyses and individual shared voxel counts. Across tasks, across and within participants, we find common activation in inferior frontal gyrus, inferior parietal cortex, fusiform gyrus, posterior superior temporal sulcus, and amygdala. Our results provide evidence for a shared neural basis for different social-cognitive processes, indicating that interpersonal understanding might occur by embodied simulation.

Intervendor Agreement for Right Ventricular Global Longitudinal Strain in Children.

BACKGROUND: Right ventricular global longitudinal strain (RVGLS) has emerged as an important technique for clinical evaluation of (RV) function. The routine application of RVGLS in pediatrics remains limited by a lack of data on agreement between vendors. The aim of this study was to investigate intervendor agreement for RVGLS between the two commonly used analysis vendors in pediatrics, hypothesizing that RVGLS has good intervendor agreement, although it is likely lower than intravendor agreement (inter- and intraobserver reproducibility). METHODS: Seventy infants and children with normal cardiac anatomy and varying ventricular function were included after prospectively obtaining RV-focused four-chamber apical images on the GE Vivid E95. Images were analyzed for RVGLS at acquired frame rates in EchoPAC (GE) and TomTec (TT) and in the compressed Digital Imaging and Communications in Medicine format in TT. Intraclass correlation coefficients and Bland-Altman plots were used to test intervendor agreement and intravendor reproducibility. RESULTS: RVGLS measurements were equally feasible using TT and EchoPAC analysis (92%). There was good to excellent agreement for RVGLS between TT and EchoPAC analysis, with a relatively higher intraclass correlation coefficient between GE and TT at the acquired frame rate (0.85) than between GE and TT at the compressed frame rate (0.75) and significantly higher agreement in patients with abnormal RV function (0.7-0.9) than those with normal function (0.4-0.6). Intra- andinterobserver reproducibility for RVGLS was excellent (intraclass correlation coefficient = 0.74-0.96). Heart rate ≥ 100 beats/min and acquisition frame rate/heart rate ≤ 0.7 were associated with diminished agreement, especially when compressed data were involved. CONCLUSIONS: RVGLS analyzed using EchoPAC and TT show good agreement, especially when analyzed at acquisition frame rates and in the setting of abnormal RV function. Otherwise, RVGLS should ideally be analyzed using the same vendor, and intervendor comparisons should be undertaken with caution, particularly if data are in a compressed format.