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Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated (R 2 = 0.62-0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution.

The designer benzodiazepine bromazolam is increasingly encountered in forensic casework, including impaired driving investigations. A series of suspected impaired driving cases that tested positive for bromazolam are described herein along with information about driving performance, driver appearance, and observed behavior. Bromazolam was indicated in casework either through screening by liquid chromatography–time of flight mass spectrometry (LC–TOF-MS) and/or a positive benzodiazepine immunoassay screen. Blood samples were forwarded for quantitative confirmatory analysis using a liquid chromatography–tandem mass spectrometry (LC–MS–MS) method with a reporting limit of 2.0 ng/mL. Bromazolam was reported in 98 impaired driving cases from samples reported between January 2021 and December 2023, with the earliest detection from September 2020. Mean and median blood concentrations were 125 ± 145 and 84 ng/mL respectively, with a range of 4.2–990 ng/mL. Additional positive findings were reported in almost all cases, with the highest result (990 ng/mL) being the only case in which bromazolam was the only finding. Fentanyl was the most frequent drug found in combination with bromazolam. Driving behaviors reported in these cases included erratic driving, errors in Standardized Field Sobriety Tests, and symptoms consistent with central nervous system depressants, including slurred speech, incoordination, and lethargic behavior. Based on its prevalence and demonstrated impairing effects, bromazolam should be included in the scope of impaired driving testing as long as it continues to be prevalent in the drug supply. [ABSTRACT FROM AUTHOR]

Drug-impaired driving is a significant public health and safety concern in the USA. To help assess current patterns of drug use in drivers, we evaluated 4 years of drug positivity in a large cohort of suspected impaired drivers. Samples collected between January 2017 and December 2020 were tested via a method compliant with the National Safety Council's Alcohol, Drugs, and Impairment Division's Tier I scope of recommended drugs. In 2017, NMS Labs received 17 346 driving under the influence of drugs cases, 17 471 in 2018, 19 050 in 2019, and 16 539 in 2020. The most common drug class detected was cannabinoids in ∼50% of the cases each year. The most common drugs detected over the 4 years were delta-9 tetrahydrocannabinol (delta-9 THC), ethanol, amphetamine/methamphetamine, fentanyl, and alprazolam. Delta-9 THC increased in positivity over the study, having been identified in 45% of cases in 2017, 46% in 2018, 46% in 2019, and 49% in 2020. Ethanol was found in 59% of cases in 2017, 59% in 2018, 61% in 2019, and 53% in 2020. Delta-9 THC and ethanol were the most common drug combination, found together in ∼19% of the cases every year of the study. Statistically significant increases in the average concentration of the following drugs were observed: fentanyl (5.7 ng/mL in 2017 to 9.6 ng/mL in 2020), methamphetamine (301 ng/mL in 2017 to 381 ng/mL in 2020), and delta-9-THC (6.4 ng/mL in 2017 to 7.3 ng/mL in 2020). Other findings included increases in the maximum reported concentrations between 2017 and 2020 for amphetamine (1400 to 2700 ng/mL), methamphetamine (5550 to 13 000 ng/mL), and fentanyl (56 to 310 ng/mL). Statistically significant concentration decreases were noted for several central nervous system depressants, notably prescription benzodiazepines, and several prescription narcotic analgesics. [ABSTRACT FROM AUTHOR]

Background: In 2020, there were 36.7 million reported falls among older adults (65+) in the United States. Ethanol and other sedating substances may increase fall risk among older adults due to their effect on cognitive and physical function. We estimate the prevalence of these substances in blood specimens of older adults presenting with a fall injury at selected trauma centers. Methods: The initial study collected blood specimens from May 2020 through July 2021 from adults undergoing a trauma team evaluation at selected United States Level 1 trauma centers. We limited our study to older adults evaluated after a fall (n = 1,365) and selected a random sample (n = 300) based on age, sex, and trauma-center quotas. Medical health records and blood specimens obtained at trauma center presentation were analyzed. We estimated the prevalence of ethanol, benzodiazepines, cannabinoids, and opioids in the blood specimens. Two-sample tests of binomial proportions and Chi-square two-tailed tests were used to compare prevalence estimates of substances by demographic characteristics. Results: At least one substance was detected among 31.3% of samples analyzed. Prevalences of specific substances detected were 9.3% (95% CI: 6.0–12.6%) for benzodiazepines, 4.3% (95% CI: 2.0–6.7%) for cannabinoids, 8.0% (95% CI: 5.2–11.7%) for ethanol, and 15.0% (95% CI: 10.9–19.1%) for opioids. There were 18 deaths (6%; 95% CI: 3.6–9.3%). One-third of decedents had at least one substance detected in their blood. Discussion: Opioids were the most frequently detected substance, followed by benzodiazepines, ethanol, and cannabinoids. Substance use prevalence was not uniform across demographics, with differences observed by sex and age. Conclusions: This study provides insight into the frequency of the presence of substances that may contribute to fall risk and serious injury among older adults. Screening older adults for substances that impair cognitive and physical function can enhance clinical fall prevention efforts. [ABSTRACT FROM AUTHOR]

The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive "greenness" of these systems. We combine continuous needle‐scale chlorophyll fluorescence measurements with tower‐based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar‐induced chlorophyll fluorescence (SIF) and solar intensity‐normalized SIF (SIFrelative) under snow‐covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near‐infrared vegetation index [NIRv] under 50% snow cover). Needle‐scale fluorescence and photochemistry strongly correlated (r2 = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower‐based estimates of LUEP and SIFrelative which were well correlated across all sites (r2 = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data‐driven and process‐based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems. [ABSTRACT FROM AUTHOR]

A quantitative gas chromatography mass spectrometry (GC/MS) method was developed for delta‐9‐tetrahydrocannabinol (delta‐9‐THC), delta‐8‐tetrahydrocannabinol (delta‐8‐THC), tetrahydrocannabinolic acid (THCA), and cannabidiol (CBD) in matrices including plant material, liquids and oils, waxes, edibles, and bath and body products. Samples were prepared by homogenization, extraction of the cannabinoids into solvent, liquid/liquid extraction, and derivatization. The GC/MS method was validated from 0.15% to 5.00% (weight basis) to encompass the 0.3% legal distinction between hemp and marijuana. Validation was performed assessing imprecision/bias, calibration model, recovery, interferences, limit of detection, matrix matching, carryover, accuracy, and an assessment of CBD conversion to delta‐9‐THC. The calibration curves were quadratic weighted 1/x with r2 > 0.990. The method had a detection limit of 0.075% in plant material for each analyte. Analyte recovery was greater than 70% in plant material. Carryover was not observed up to concentrations equivalent to 100% analyte, and no forensically significant conversion of CBD to delta‐9‐THC was observed. One cannabinoid isomer, 9(R)‐delta‐7‐tetrahydrocannabinol (9(R)‐delta‐7‐THC), was determined to interfere with the quantitation of delta‐9‐THC, but could be differentiated based on mass spectrum. The method was determined to be suitable for quantitation of delta‐9‐THC, delta‐8‐THC, delta‐9‐THCA, and CBD and was able to differentiate hemp samples from marijuana samples. [ABSTRACT FROM AUTHOR]

Synthetic cannabinoid receptor agonists (SCRAs) are a diverse class of new psychoactive substances (NPS) and new structural scaffolds have emerged on the recreational drug market since the enactment of Chinese SCRA analog controls in 2021. This study reports the first SCRAs to be detected with a bromide at the 5 position (5′Br) on the phenyl ring of the indazole core and without a tail moiety. ADB‐5′Br‐INACA (ADMB‐5′Br‐INACA) and MDMB‐5′Br‐INACA were detected in seized samples from Scottish prisons, Belgian customs, and US forensic casework. The brominated analog with a tail moiety, ADB‐5′Br‐BUTINACA (ADMB‐5′Br‐BUTINACA), was also detected in Scottish prisons and US forensic casework. The metabolites of these compounds and the predicted compound MDMB‐5′Br‐BUTINACA were identified through incubation with primary human hepatocytes to aid in their toxicological identification. The bromide on the indazole remains intact on metabolites, allowing these compounds to be easily distinguished in toxicological samples from their non‐brominated analogs. Glucuronidation was more common for tail‐less analogs than their butyl tail‐containing counterparts. Forensic toxicologists are advised to update their analytical methods with the characteristic ions for these compounds, as well as their anticipated urinary markers: amide hydrolysis and monoOH at tert‐butyl metabolites (after β‐glucuronidase treatment) for ADB‐5′Br‐INACA; monoOH at tert‐butyl and amide hydrolysis metabolites for ADB‐5′Br‐BUTINACA; and ester hydrolysis metabolites with additional metabolites for MDMB‐5′Br‐INACA and MDMB‐5′Br‐BUTINACA. Toxicologists should remain vigilant to the emergence of new SCRAs with halogenation of the indazole core and tail‐less analogs, which have already started to emerge. [ABSTRACT FROM AUTHOR]

Due to the increase in the use of novel psychoactive substances (NPS) and their overall prevalence, it is important to have effective and reliable screening technologies to detect NPS in biological matrices. Enzyme-linked immunosorbent assays (ELISA) are among the most popular screening methods. To evaluate the effectiveness of ELISA for NPS detection, five subclasses of NPS (novel synthetic opioids, fentanyl analogs, stimulants, benzodiazepines and hallucinogens) were evaluated in whole blood for their cross-reactivity on commercially available ELISA kits. A variety of novel synthetic opioids were tested at concentrations of 1–80 ng/mL and 50–2000 ng/mL and demonstrated no cross-reactivity to a morphine ELISA plate at either concentration range. Fentanyl analogs were tested at concentrations ranging from 0.01 to 1 ng/mL and had cross-reactivities ranging from 8% to 178% on the fentanyl ELISA kit used. Both para-chloro fentanyl (178%) and acryl fentanyl (164%) showed cross-reactivities well above that of fentanyl. Novel stimulants were tested at concentrations of 0.5–40 ng/mL and 20–2,000 ng/mL. 4-Fluoroamphetamine was the only novel stimulant with cross-reactivity (3,354%) to the amphetamine ELISA plate. Novel benzodiazepines were tested at concentrations of 1–40 ng/mL on a benzodiazepine plate. Cross-reactivities ranged from 36.1% to 263%, with desalkylflurazepam having the highest cross-reactivity. Finally, novel hallucinogens were tested at concentrations of 0.5–10 ng/mL on a phencyclidine (PCP) ELISA plate, which produced no cross-reactivity and then with 10–1,000 ng/mL, which gave results from 56.6% to 151%. Both hydroxy-PCP (151%) and chloro-PCP (137%) showed cross-reactivities above that of PCP. This research has demonstrated the utility of using ELISA-based screening for novel benzodiazepines, hallucinogens and for fentanyl analogs; however, there is limited application and risk of false-negative results for the other drug classes due to low or non-existent cross-reactivities. [ABSTRACT FROM AUTHOR]