Distinguishing Variability Regimes of Hawaiian Summer Rainfall: Quasi-Biennial and Interdecadal Oscillations

Summer precipitation in Hawai\u27i accounts for 40% of the annual total and provides important water sources. However, our knowledge about its variability remains limited. Here we show that statewide Hawai\u27i summer rainfall (HSR) variability exhibits two distinct regimes: quasi-biennial (QB, ~2 years) and interdecadal (~30–40 years). The QB variation is linked to alternating occurrences of the Western North Pacific (WNP) cyclone and anticyclone in successive years, which is modulated by the intrinsic El Niño–Southern Oscillation biennial variability and involves a positive feedback between atmospheric Rossby waves and underlying sea surface temperature (SST) anomalies. The interdecadal variation of HSR is largely modulated by the Pacific Decadal Oscillation through affecting upstream low-level humidity that affects topographic rainfall. HSR shows weak long-term drying trend during 1920–2019. This first description of the major physical drivers of summer rainfall variability provides key information for seasonal rainfall prediction in Hawai\u27i

Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies

The associated uncertainties of future climate projections are one of the biggest obstacles to overcome in studies exploring the potential regional impacts of future climate shifts. In remote and climatically complex regions, the limited number of available downscaled projections may not provide an accurate representation of the underlying uncertainty in future climate or the possible range of potential scenarios. Consequently, global downscaled projections are now some of the most widely used climate datasets in the world. However, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we explore the utility of two such global datasets (CHELSA and WorldClim2) in providing plausible future climate scenarios for regional climate change impact studies. Our analysis was based on three steps: (1) standardizing a baseline period to compare available global downscaled projections with regional observation-based datasets and regional downscaled datasets; (2) bias correcting projections using a single observation-based baseline; and (3) having controlled differences in baselines between datasets, exploring the patterns and magnitude of projected climate shifts from these datasets to determine their plausibility as future climate scenarios, using Hawaiʻi as an example region. Focusing on mean annual temperature and precipitation, we show projected climate shifts from these commonly used global datasets not only may vary significantly from one another but may also fall well outside the range of future scenarios derived from regional downscaling efforts. As species distribution models are commonly created from these datasets, we further illustrate how a substantial portion of variability in future species distribution shifts can arise from the choice of global dataset used. Hence, projected shifts between baseline and future scenarios from these global downscaled projections warrant careful evaluation before use in climate impact studies, something rarely done in the existing literature. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply

Bipolar and ADHD Comorbidity: Both Artifact and Outgrowth of Shared Mechanisms

Published rates of comorbidity between pediatric bipolar disorder (PBD) and attention-deficit/hyperactivity disorder (ADHD) have been higher than would be expected if they were independent conditions, but also dramatically different across different studies. This review examines processes that could artificially create the appearance of comorbidity or substantially bias estimates of the ADHD-BPD comorbidity rate, including: categorization of dimensional constructs, overlap among diagnostic criteria, over-splitting, developmental sequencing, and referral or surveillance biases. Evidence also suggests some mechanisms for “true” BPD-ADHD comorbidity, including shared risk factors, distinct subtypes, and weak causal relationships. Keys to differential diagnosis include focusing on episodic presentation and non-overlapping symptoms unique to mania

Comparative evaluation of [(99m)tc]tilmanocept for sentinel lymph node mapping in breast cancer patients: results of two phase 3 trials.

BackgroundSentinel lymph node (SLN) surgery is used worldwide for staging breast cancer patients and helps limit axillary lymph node dissection. [(99m)Tc]Tilmanocept is a novel receptor-targeted radiopharmaceutical evaluated in 2 open-label, nonrandomized, within-patient, phase 3 trials designed to assess the lymphatic mapping performance.MethodsA total of 13 centers contributed 148 patients with breast cancer. Each patient received [(99m)Tc]tilmanocept and vital blue dye (VBD). Lymph nodes identified intraoperatively as radioactive and/or blue stained were excised and histologically examined. The primary endpoint, concordance (lower boundary set point at 90 %), was the proportion of nodes detected by VBD and [(99m)Tc]tilmanocept.ResultsA total of 13 centers contributed 148 patients who were injected with both agents. Intraoperatively, 207 of 209 nodes detected by VBD were also detected by [(99m)Tc]tilmanocept for a concordance rate of 99.04 % (p < 0.0001). [(99m)Tc]tilmanocept detected a total of 320 nodes, of which 207 (64.7 %) were detected by VBD. [(99m)Tc]Tilmanocept detected at least 1 SLN in more patients (146) than did VBD (131, p < 0.0001). In 129 of 131 patients with ≥1 blue node, all blue nodes were radioactive. Of 33 pathology-positive nodes (18.2 % patient pathology rate), [(99m)Tc]tilmanocept detected 31 of 33, whereas VBD detected only 25 of 33 (p = 0.0312). No pathology-positive SLNs were detected exclusively by VBD. No serious adverse events were attributed to [(99m)Tc]tilmanocept.Conclusion[(99m)Tc]Tilmanocept demonstrated success in detecting a SLN while meeting the primary endpoint. Interestingly, [(99m)Tc]tilmanocept was additionally noted to identify more SLNs in more patients. This localization represented a higher number of metastatic breast cancer lymph nodes than that of VBD

Is the finding too good to be true?:Moving from “more is better” to thinking in terms of simple predictions and credibility

In 2018, De Los Reyes and Langer expanded the scope of the Evidence Base Updates series to include reviews of psychological assessment techniques. In keeping with the goal of offering clear "take-home messages" about the evidence underlying the technique, experts have proposed a rubric for evaluating the reliability and validity support. Changes in the research environment and pressures in the peer review process, as well as a lack of familiarity with some statistical methods, have created a situation where many findings that appear “excellent” in the rubric are likely to be “too good to be true,” in the sense that they are unlikely to generalize to clinical settings or are unlikely to be reproduced in independent samples. We describe several common scenarios where published results are often too good to be true, including internal consistency, inter-rater reliability, correlation, standardized mean differences, diagnostic accuracy, and global model fit statistics. Simple practices could go a long way towards improving design, reporting, and interpretation of findings. When effect sizes are in the “excellent” range for issues that have been challenging, scrutinize before celebrating. When benchmarks are available base on theory or meta-analyses, results that are moderately better than expected in the favorable direction (i.e., Cohen’s q≥+.30) also invite critical appraisal and replication before application. If readers and reviewers pull for transparency and do not unduly penalize authors who provide it, then change in research quality will be faster and both generalizability and reproducibility are likely to benefit

Affective Processing in Pediatric Bipolar Disorder and Offspring of Bipolar Parents

Background: Bipolar disorder (BD) is characterized by biased processing of emotional information. However, little research in this area has been conducted in youth with BD and at-risk individuals. The goal of this study was to determine whether children with BD displayed comparable or more severe manifestations of this bias relative to offspring of parents with BD

Evaluating and Validating General Behavior Inventory Mania and Depression Short Forms for Self-Report of Mood Symptoms

Objective: To evaluate short forms of free self-report mania and depression scales, evaluating their reliability, content coverage, criterion validity, and diagnostic accuracy. Method: Youths age 11 to 18 years seeking outpatient mental health services at either an Academic medical clinic (N=427) or urban Community mental health center (N=313), completed the General Behavior Inventory (GBI) and other rating scales. Youths and caregivers completed semi-structured interviews to establish diagnoses and mood symptom severity, with GBI scores masked during diagnosis. Ten- and seven-item short forms, psychometric projections, and observed performance were tested first in the Academic sample and then externally cross-validated in the Community sample. Results: All short forms maintained high reliability (all alphas >.80 across both samples), high correlations with the full length scales (r .85 to .96), excellent convergent and discriminant validity with mood, behavior, and demographic criteria, and diagnostic accuracy undiminished compared to using the full length scales. Ten-item scales showed advantages in terms of coverage; the 7 Up showed slightly weaker performance. Conclusions: Present analyses evaluated and externally cross-validated short forms that maintain high reliability and content coverage, and show strong criterion validity and diagnostic accuracy – even when used in an independent sample with very different demographics and referral patterns. The short forms appear useful in clinical applications including initial evaluation, as well as in research settings where they offer an inexpensive quantitative score. Short forms are available in more than two dozen languages. Future work should further evaluate sensitivity to treatment effects and cultural invariance

Improving Clinical Prediction of Bipolar Spectrum Disorders in Youth.

This report evaluates whether classification tree algorithms (CTA) may improve the identification of individuals at risk for bipolar spectrum disorders (BPSD). Analyses used the Longitudinal Assessment of Manic Symptoms (LAMS) cohort (629 youth, 148 with BPSD and 481 without BPSD). Parent ratings of mania symptoms, stressful life events, parenting stress, and parental history of mania were included as risk factors. Comparable overall accuracy was observed for CTA (75.4%) relative to logistic regression (77.6%). However, CTA showed increased sensitivity (0.28 vs. 0.18) at the expense of slightly decreased specificity and positive predictive power. The advantage of CTA algorithms for clinical decision making is demonstrated by the combinations of predictors most useful for altering the probability of BPSD. The 24% sample probability of BPSD was substantially decreased in youth with low screening and baseline parent ratings of mania, negative parental history of mania, and low levels of stressful life events (2%). High screening plus high baseline parent-rated mania nearly doubled the BPSD probability (46%). Future work will benefit from examining additional, powerful predictors, such as alternative data sources (e.g., clinician ratings, neurocognitive test data); these may increase the clinical utility of CTA models further