Faculty Bibliography

BACKGROUND:We sought to estimate the prevalence of synthetic cannabinoid use and characteristics of people who use in the US general population. METHODS:We compared the prevalence of past-year synthetic cannabinoid use in 2023 to 2021 among individuals ages ≥ 12 surveyed via the National Survey on Drug Use and Health (N = 173,808). We also compared prevalence according to demographic and drug use characteristics and delineated correlates of past-year use. RESULTS:Synthetic cannabinoid use increased from 0.17 % in 2021 to 0.26 % in 2023, a 50.0 % increase (p = .042) (0.25 % prevalence in 2021-2023 overall). The largest increases were among those aged ≥ 35 (by 255.3 %), those with an annual family income of < $20,000 (by 242.1 %), and those who used methamphetamine in the past year (by 184.6 %) (Ps < .05). In our final multivariable model, those with less than a high school diploma (aOR=2.20, 95 % CI: 1.12-4.32) and those with past-year cannabis use (aOR=13.55, 95 % CI: 8.36-21.95) and use disorder (aOR=26.03, 95 % CI: 17.70-38.29) were at higher odds for synthetic cannabinoid use, as were people with methamphetamine use (aOR=3.08, 95 % CI: 1.18-8.01) and use disorder (aOR=4.74, 95 % CI: 2.17-10.37), and prescription opioid misuse (aOR=1.75, 95 % CI: 1.05-2.93) and use disorder (aOR=3.22, 95 % CI: 1.78-5.82). CONCLUSION/CONCLUSIONS:Survey data suggest that synthetic cannabinoid use is rare but increasing, particularly among people of lower socioeconomic status and people who use other drugs. Cannabis use disorder in particular is associated with higher odds for use. Research is needed to determine if overreporting is occurring due to confusion with emerging cannabis products.

This article highlights the gender data gaps in clinical trial inclusion and funding, with a particular focus on gynecologic oncology. Female patients have historically been excluded from clinical trials across all medical domains. Despite recent improvements, female patients remain underrepresented in key diseases, including several cancer types, despite experiencing increased burden of disease. Lack of representation is particularly stark for patients in racial, ethnic, and gender minoritized populations, including in gynecologic cancer trials. Furthermore, female health conditions receive disproportionately small amounts of funding relative to their disease burden. Despite their high lethality, gynecologic cancers, including ovarian, cervical, and uterine malignancies, rank among the lowest funded cancer sites from the National Cancer Institute. Likewise, there is significant bias against female investigators with regard to funding, publication, and academic advancement, which affects the prioritization of women's health. In combination, gender disparities at multiple steps along the research pathway from investigator and disease funding to trial inclusion to publication and dissemination of research perpetuate a significant data gap in the diagnosis, treatment, and prevention of diseases affecting female patients, including gynecologic cancers. Strategies to improve this gender gap and prioritize women's health funding include increasing female representation in clinical trials with a specific focus on inclusion of patients from historically marginalized backgrounds, considering disease burden-based funding policies, and prioritizing female academic leadership opportunities.

Postural orthostatic tachycardia syndrome (POTS) is a chronic, debilitating condition that is characterized by an excessive increase in heart rate upon orthostatic challenge. Before the COVID-19 pandemic, POTS affected 0.5 % to 1 % of the U.S. population. Since the pandemic, the incidence has risen sharply, adding an estimated 6-7 million new cases in the U.S. Despite its importance, there is currently no reliable biomarker for POTS, leading to significant diagnostic delays. A major hurdle in identifying biomarkers is the heterogeneous nature of the syndrome. To address this, we focused on a homogeneous subgroup of post-COVID-19 POTS (PC-POTS) patients. We conducted quantitative proteomics on sera from 9 PC-POTS patients and 9 healthy controls, identifying 31 proteins with significantly different abundances in PC-POTS patients. Most elevated proteins were linked to actin filaments or immune functions/inflammation. Weighted Gene Co-Expression Network Analysis revealed module 7 (M7) correlated strongly with PC-POTS diagnosis and related traits. The key proteins in M7 included MTPN, TAGLN2, ADP-ribosylation factor 1, PDLIM1, PPIA, CNN2, LGALSL, TXN, TLN1, TUBA4A, IL4, TREML1, GP1BA, and, all highly correlated with these traits. Cell-type enrichment analysis revealed that M7 was highly associated with immune and neuronal cells. The main pathways identified in M7 included the integrin signaling pathway, blood coagulation, and glycolysis. These findings suggest that the key proteins in M7 could serve as biomarkers for PC-POTS. This study uses quantitative proteomics to identify potential biomarkers that differentiate PC-POTS patients from healthy controls, establishing a foundation for further research and validation.

Policies to implement climate-forcing pollution emission reductions have often been stymied by economic and political divisiveness. However, certain uncontested nonregret public health policies that also carry climate-forcing cobenefits with them could provide more achievable policy pathways to accelerate the implementation of climate mitigation. An International Society for Environmental Epidemiology Policy Committee endorsed pre-28th Conference of the Parties climate meeting workshop brought together experts on environment, diet, civic planning, and health to review current understanding of public health policy approaches that provide climate change mitigation cobenefits by also reducing greenhouse gas emissions. Promising public health policy areas identified as also providing climate mitigation cobenefits included: improving air quality through stronger regulation of harmful combustion-related air pollutants, advancing healthier plant-based public food procurement programs, promoting more sustainable transport options, developing healthier infrastructure (e.g., combustion-free buildings), and reducing the use of climate forcing substances in healthcare. It is concluded that cities, states, and nations, when aided by involved health professionals, can advance many practical public health, diet, and civic planning policies to improve health and well-being that will also serve to translate climate mitigation ambitions into action.

Growing evidence suggests exposure to high temperatures may result in increased urban crime, a known driver of health and health inequity. Theoretical explanations have been developed to describe the heat-crime relationship without consensus yet achieved among experts. This scoping review aims to summarize evidence of heat-crime associations in U.S. cities. Further examination of empirical and translational inconsistencies in this literature will ensure future studies of urban heat-crime relationships in the U.S., and their policy impacts are informed by a thorough understanding of existing evidence. We performed a comprehensive literature search of empirical studies on heat-crime relationships in U.S. cities published between January 2000 and August 2023. The included studies were qualitatively synthesized based on operationalized exposures, outcomes, covariates, methodologies, theoretical framing, and policy implications. In total, 46 studies were included in this review. Most studies (93%) reported significant, positive associations between urban heat exposure and both violent and non-violent crime outcomes. The shape and strength of these associations varied based on operational definitions of urban heat exposures, crime outcomes, and relevant covariates in employed methods. We also found inconsistencies in the theoretical explanations and policy implications reported across studies. Climate-driven extreme heat events are projected to increase in frequency and severity. Our findings underscore the urgency of refining the understanding and translation of the complex relationship between urban heat and crime. In this review, we highlight opportunities to improve the methodological quality and responsible policy translation of future research in U.S. cities, which has implications for research globally.

OBJECTIVES/OBJECTIVE:To assess the reliability of rectal MRI radiomic features across reader expertise level, image segmentation technique, and timing of rectal MRI. MATERIAL AND METHODS/METHODS:This retrospective single-institutional study included consecutive patients with rectal adenocarcinoma who underwent total neoadjuvant therapy from January 2018 to June 2018. Baseline and restaging rectal MRI T2-weighted images were segmented independently by six radiologists (two fellows, two non-rectal radiologists, and two rectal radiologists). Four segmentation strategies were used and varied by image segmentation technique and timing of rectal MRI: (a) baseline volume of interest (VOI), (b) baseline region of interest (ROI), (c) restaging VOI, and (d) restaging ROI. Inter-reader agreement on each extracted radiomic feature was evaluated using the intra-class correlation coefficient (ICC). RESULTS:Among 24 patients (16 men; median age, 56 years [interquartile range: 49-62]), 1,595 radiomic features were extracted. Baseline VOI segmentation achieved the highest inter-reader agreement rate, with 68 % (1,079/1,595) of radiomic features having an ICC > 0.7. Restaging ROI segmentation achieved the worst inter-reader agreement rate, with only 26 % (415/1,595) of radiomic features having an ICC > 0.7. First-order statistics and Gray Level Co-occurrence Matrix (GLCM) feature subgroups showed high inter-reader agreement rates, and the application of 'Square Root' and 'LOG Sigma' filters resulted in improved inter-reader agreement rates relative to original images. The expertise level of radiologists performing the segmentations did not affect the distribution of inter-agreement rates according to image segmentation technique or timing of rectal MRI. CONCLUSIONS:Radiomic features were more reliable when extracted from baseline (vs. restaging) rectal MRIs and using 3D volume of interest (vs. 2D region of interest) segmentation, independent of the expertise level of the radiologists performing the segmentation. CLINICAL RELEVANCE STATEMENT/CONCLUSIONS:Radiomic studies on rectal MRI employ various segmentation strategies and few assess their impact on reproducibility. Establishing the optimal segmentation method enhances radiomics model generalizability, potentially bridging the gap in clinical translation and improving clinical management of patients.

Amyotrophic lateral sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this heterogeneity, large-scale genomics studies revealed that ALS postmortem samples can be grouped into a small number of subtypes, defined by transcriptomic signatures of mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or TDP-43 pathology and associated transposable elements (ALS-TE). In this study, we present a deep ALS neural net classifier (DANCer) for ALS molecular subtypes. Applying DANCer to an expanded cohort from the NYGC ALS Consortium highlights two subtypes that strongly correlate with disease duration: ALS-TE in cortex and ALS-Glia in spinal cord. Finally, single-nucleus transcriptomes demonstrate that ALS subtypes are recapitulated in neurons and glia, with both ALS-wide and subtype-specific alterations in all cell types. In summary, ALS molecular subtypes represent a combination of cellular and pathological features that correlate with clinical features of ALS.

Pathogenic variants resulting in protein phosphatase 2A (PP2A) dysfunction result in mild to severe neurodevelopmental delay. PP2A is a trimer of a catalytic (C) subunit, scaffolding (A) subunit, and substrate binding/regulatory (B) subunit, encoded by 19 different genes. De novo missense variants in PPP2R5D (B56δ) or PPP2R1A (Aα) and de novo missense and loss-of-function variants in PPP2CA (Cα) lead to syndromes with overlapping phenotypic features, known as Houge-Janssens syndrome (HJS) types 1, 2, and 3, respectively. Here, we describe an additional condition in the HJS spectrum in 26 individuals with variants in PPP2R5C, encoding the regulatory B56γ subunit. Most changes were de novo and of the missense type. The clinical features were well within the HJS spectrum with strongest resemblance to HJS type 1, caused by B56δ variants. Common features were neurodevelopmental delay and hypotonia, with a high risk of epilepsy, behavioral problems, and mildly dysmorphic facial features. Head circumferences were above average or macrocephalic. The degree of intellectual disability was, on average, milder than in other HJS types. All variants affected either substrate binding (2/19), C-subunit binding (2/19), or both (15/19). Five variants were recurrent. Catalytic activity of the phosphatase was variably affected by the variants. Of note, PPP2R5C total loss-of-function variants could be inherited from a non-symptomatic parent. This implies that a dominant-negative mechanism on substrate dephosphorylation or general PP2A function is the most likely pathogenic mechanism.