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Artificial light at night (ALAN) pollution alters bat lunar chronobiology: Insights from broad-scale long-term acoustic monitoring

Abstract Background The timing of behavior and habitat associations of nocturnal animals can be influenced by the lunar cycle in nature. The prevalence of artificial light at night (ALAN) has been recognized as a source of environmental pollution. The interaction between ALAN pollution and the lunar cycle on bat behavior is important for understanding anthropogenic effects on bats. We utilized a decade (2012–2022) of acoustic monitoring data collected in North Carolina, United States, to investigate the relationship between bat activity, lunar cycle, and ALAN pollution in temperate insectivorous bats. We examined whether the amount of lunar illumination affected species-specific nightly activity and whether hourly bat activity patterns varied between nights with different moon phases. We further investigated if the relationship between bat activity and the lunar cycle might be altered by ALAN pollution. Results We found that seven bat species showed activity variation across nights in relation to the amount of moon illumination when ALAN pollution was absent. Generally, bats were less active on full moon nights compared to new moon nights. ALAN pollution interacted with the bat-lunar relationship in five of the seven species, masking the effect of the lunar cycle. We identified delayed bat activity patterns on nights with a full or waxing moon in seven species, and ALAN pollution altered that pattern in four species. Overall, ALAN pollution was associated with decreased bat activity independent of lunar cycle effects. Conclusions Our study demonstrated that at a broad spatial scale, ALAN pollution negatively affected many North American temperate bat species and altered their lunar chronobiology. As the cost of illumination declines and the economic benefits of nighttime farming and other activities increase, ALAN pollution is spreading to historically dark areas and habitats. ALAN pollution might couple with other threats, such as the white-nose syndrome or climate change, to cause cascading damage in the environment that depends on ecosystem services provided by bats. We argue that further research and conservation actions are needed to mitigate the impact of ALAN pollution.

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Biomarker testing rates among metastatic cancer patients with receipt of anti-cancer systemic therapy: A real-world data analysis.

550 Background: Biomarker testing to direct individualized therapy options can optimize cancer patient outcomes, particularly for patients with advanced disease. Guideline-recommended molecular testing, comprehensive genomic profiling [CGP] and non-CGP testing, is covered by both Medicare and commercial private insurers (at least non-CGP).. This study examined real-world utilization of biomarker testing among cancer patients with metastatic disease who received anti-cancer systemic therapy. Methods: A retrospective analysis was conducted using de-identified administrative claims data from the Optum Labs Data Warehouse. Adults identified with 1 of 6 advanced cancer types from 1/2018 to 8/2021 were identified; index date was the first claim date for advanced disease. Patients with diagnosis codes indicating only lymph node involvement around the primary cancer were excluded. Continuous enrollment in a commercial (COM) or Medicare Advantage (MA) health plan with both medical and pharmacy benefits was required for 12 months prior to the index date (baseline), and ≥6 months after the index date (follow-up); patients with <6 months follow-up due to death were included. Receipt of anti-cancer systemic therapy during the follow-up was required. Biomarker testing was captured using Current Procedural Terminology (CPT®) codes indicating CGP (> 50 gene panels) or non-CGP (≤50 gene panels or single gene tests) during the study period. Rates of biomarker testing by cancer and insurance type, and receipt of targeted therapy and/ were assessed. Results: Result: There were 27,434 metastatic cancer patients meeting study criteria: 10,320 non-small cell lung (NSCLC), 5,525 breast (BC), 5,429 colorectal (CRC), 2,314 ovarian (OC), 872 gastric (GC) and 2,974 pancreatic (PC) cancer patients. 66% of patients were MA enrollees. The median age was 70 years and ranged from 67 years for BC patients to 71 years for NSCLC and PC patients. The median follow-up was 383 days, ranging from 246 days (for PC patients) to 564 days (for BC patients). Overall biomarker testing rates in the follow-up period were: 47% for NSCLC, 34% BC, 58% CRC, 61% OC, 48% GC, and 47% PC. Testing rates were lower among MA patients compared to COM patients (46% vs 53%). Receipt of targeted/monoclonal antibody therapy was higher (47% vs 33%, p<0.01) among patients with biomarker testing compared to those without. Conclusions: Rates of biomarker testing across metastatic tumor types are far from optimal despite guideline recommendations and insurance coverage for testing, and may affect quality of care. To improve adherence to biomarker testing guidelines, interventions to help overcome obstacles to biomarker testing are needed. Future analysis with this cohort will examine patient management and outcomes by receipt of testing, timing of testing and type of therapy received.

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Real-world analysis of commercially insured and Medicare Advantage patients with advanced cancer and rates of molecular testing.

6633 Background: Guideline-recommended molecular testing has become essential for biomarker-guided clinical decision making, particularly for patients with advanced (adv) disease. Several biomarkers have indications that are tumor type-agnostic (starting with MSI in 2017, NTRK in 2018, TMB in 2020, and RET and BRAF in 2022). Biomarker testing is covered by insurers, both Medicare (covers comprehensive genomic profiling [CGP] and non-CGP panels) and commercial (at least non-CGP). This study aimed to understand utilization of biomarker testing across tumor types. Methods: This retrospective analysis used de-identified administrative claims from Optum Labs Data Warehouse. Adult Commercial (COM) and Medicare Advantage (MA) enrollees diagnosed with any 1 of 6 adv cancer types from 1/2018 to 8/2021 were identified; the date of the first claim indicating adv cancer was the index date. Continuous enrollment for 12 months prior to (baseline), and ≥6 months post-index date, unless they died (follow-up) was required. Biomarker testing was captured using Current Procedural Terminology (CPT) codes indicating CGP (> 50 gene panels), non-CGP (at most 5-50 gene panels), or CPT code 81479 (unlisted molecular pathology procedure) during the study period. The primary analysis evaluates testing in the follow-up only, with secondary analyses evaluating testing including the baseline (to account for testing prior to the index date). Results: We identified 16,931 breast (BC), 16,838 non-small cell lung (NSCLC), 8,755 colorectal (CRC), 4,244 pancreatic (PC), 2,610 ovarian (OC), and 1,231 gastric (GC) adv cancer patients meeting study criteria. Overall biomarker testing rates in the follow-up period were: 37% NSCLC, 19% BC, 41% CRC, 35% PC, 51% OC, 35% GC. The Table shows testing rates by cancer, insurance type, and panel size during follow-up. Testing rates were lower among MA patients compared to COM patients. Even considering baseline and follow-up periods, overall biomarker testing rates were low, and lower among MA compared to COM : 48% NSCLC (53% COM, 47% MA), 27% BC (34% COM, 22% BC), 56% OC (61% COM, 53% MA),42% PC (53% COM, 38% MA), 47% CRC (56% COM, 42% MA), 41% GC (54% COM, 35% MA). Conclusions: Considering guideline recommendations, rates of biomarker testing across tumor types are far from optimal despite insurance coverage for testing. Identification of barriers to biomarker testing and interventions to overcome these are needed to improve adherence to biomarker testing guidelines. [Table: see text]

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Understanding Skin Failure: A Scoping Review.

To map the use of the term "skin failure" in the literature over time and enhance understanding of this term as it is used in clinical practice. The databases searched for published literature included PubMed, Embase, the Cumulative Index for Nursing and Allied Health Literature, and Google Scholar. The search for unpublished literature encompassed two databases, Open Gray and ProQuest Dissertation and Theses. Search terms included "skin failure," "acute skin failure," "chronic skin failure," and "end stage skin." All qualitative and quantitative research designs, editorial, opinion pieces, and case studies were included, as well as relevant gray literature. Data collected included author, title, year of publication, journal name, whether the term "skin failure" was mentioned in the publication and/or in conjunction with other skin injury, study design, study setting, study population, sample size, main focus of the publication, what causes skin failure, skin failure definition, primary study aim, and primary outcome. Two main themes of skin failure were identified through this scoping review: the etiology of skin failure and the interchangeable use of definitions. Use of the term "skin failure" has increased significantly over the past 30 years. However, there remains a significant lack of empirical evidence related to skin failure across all healthcare settings. The lack of quality research has resulted in multiple lines of thinking on the cause of skin failure, as well as divergent definitions of the concept. These results illustrate substantial gaps in the current literature and an urgent need to develop a globally agreed-upon definition of skin failure, as well as a better understanding of skin failure etiology.

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