A variety of LSD analogs have emerged in recent years with dual purposes of avoiding prosecution from possession while providing new options for those willing to experiment with hallucinogenic drugs. In this study, a previously published automated sample preparation method for LSD and its primary metabolite (OH-LSD) was utilized to extract LSD, OH-LSD, and nine LSD analogs from urine. The liquid chromatography tandem mass spectrometry (LC-MS/MS) method was modified from the previously published LC conditions to utilize a different analytical column and gradient elution program. Mobile phases of 10 mM ammonium formate with 0.1% formic acid in deionized water (mobile phase A) and 0.1% formic acid in methanol (mobile phase B) were employed. The method was validated to ANSI/ASB Standard 036 with a 0.1 ng/mL limit of detection for all analytes and was utilized for the analysis of 325 urine specimens. Although no LSD analogs were observed in the samples analyzed, this validated method was demonstrated to be suitable for the analysis of these compounds in laboratories seeking to expand their testing scope. Automated sample preparation allows for the efficient analysis of these analytically challenging compounds with minimal manual handling. Additionally, there was no increased analytical time burden when the LC column and gradient were modified to target nine additional analytes. Detection may improve as new reference standards are developed to allow laboratories to focus on the metabolic products of these analogs. For now, this validated procedure can assist with the routine analysis and surveillance of these emerging substances.

PM2.5 was sampled over a seven-year period (2013-2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015-2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen\'s) were used to assess statistically significant changes in the factor contributions to PM2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (-0.03 μg/m³/yr or -4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (-0.27 μg/m³/yr or -12.6%/yr), biomass burning (-0.05 μg/m³/yr or -9.02%/yr), crustal matter (-0.03 μg/m³/yr or -5.28%/yr). These factors mainly accounted for the significant decline in PM2.5 over the study period (-0.35 μg/m³/yr or -4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations.

Recently, lysergic acid diethylamide (LSD) has become a resurgent drug of abuse. The detection of LSD is problematic because of the low dosage taken by users, light and heat sensitivity of the analyte and the lack of efficient analytical methods. Presented here is the validation of an automated sample preparation method for the analysis of LSD and its primary urinary metabolite, 2-oxo-3-hydroxy-LSD (OHLSD), in urine samples by liquid chromatography-tandem mass spectrometry. Analytes were extracted from urine using an automated Dispersive Pipette XTRaction method on Hamilton STAR and STARlet liquid handling systems. The limit of detection for both analytes was administratively defined at the lowest calibrator used in the experiments, and the limit of quantitation was 0.05 ng/mL for both analytes. All validation criteria were acceptable per Department of Defense Instruction 1010.16 requirements. This method offers an efficient, sensitive analytical solution to routinely evaluate large numbers of urine specimens for LSD in workplace drug deterrence programs.

Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available clinical trial datasets are often not representative for heterogeneous patient groups. The aim of this study was constructing a natural language processing (NLP) pipeline that extracts variables for building predictive models from EHRs. We specifically tailor the pipeline for extracting information on outcomes of psychiatry treatment trajectories, applicable throughout the entire spectrum of mental health disorders (\"transdiagnostic\").
A qualitative study into beliefs of clinical staff on measuring treatment outcomes was conducted to construct a candidate list of variables to extract from the EHR. To investigate if the proposed variables are suitable for measuring treatment effects, resulting themes were compared to transdiagnostic outcome measures currently used in psychiatry research and compared to the HDRS (as a gold standard) through systematic review, resulting in an ideal set of variables. To extract these from EHR data, a semi-rule based NLP pipeline was constructed and tailored to the candidate variables using Prodigy. Classification accuracy and F1-scores were calculated and pipeline output was compared to HDRS scores using clinical notes from patients admitted in 2019 and 2020.
Analysis of 34 questionnaires answered by clinical staff resulted in four themes defining treatment outcomes: symptom reduction, general well-being, social functioning and personalization. Systematic review revealed 242 different transdiagnostic outcome measures, with the 36-item Short-Form Survey for quality of life (SF36) being used most consistently, showing substantial overlap with the themes from the qualitative study. Comparing SF36 to HDRS scores in 26 studies revealed moderate to good correlations (0.62-0.79) and good positive predictive values (0.75-0.88). The NLP pipeline developed with notes from 22,170 patients reached an accuracy of 95 to 99 percent (F1 scores: 0.38 - 0.86) on detecting these themes, evaluated on data from 361 patients.
The NLP pipeline developed in this study extracts outcome measures from the EHR that cater specifically to the needs of clinical staff and align with outcome measures used to detect treatment effects in clinical trials.

According to a classic result in evolutionary biodemography, selection on age-specific survival invariably declines with reproductive age. The result assumes proportional changes in survival and a constant environment. Here, we look at selection on age-specific survival when changes are still proportional but the environment fluctuates. We find that selection may or may not decline with reproductive age depending on how exactly survival is proportionally altered by mutations. However, interpreted in neutral terms, the mathematics behind the classic result capture a general property that the genetics of populations with age structure possess both in a constant and in a fluctuating environment.

UNASSIGNED: The sex ratio of human birth cohorts predicts the health and longevity of their members. Most literature invokes natural selection in support of the argument that heritable tendencies to produce male or female offspring induce oscillation in the sex ratio and its sequelae. Tests of the argument remain exceedingly rare because they require vital statistics describing many generations of a population both unaffected by migration and exposed to an exogenous stressor virulent enough to change the sex ratio at birth. We contribute to the literature by using time-series modeling to detect oscillation in the best data currently available for such a test.
UNASSIGNED: We apply rigorous time-series methods to data describing Sweden from 1751 through 1830, a period when the population not only aged in place without migration, but also exhibited the effects of an Icelandic volcanic eruption including a historically low secondary sex ratio. That very low sex ratio should have induced oscillation if heritable mechanisms appear in humans.
UNASSIGNED: We detected oscillation in the ratio but not that predicted by heritable tendencies to produce males or females. We found peak-to-trough oscillation at 14 rather than the approximately 32 years expected from the heritable tendencies argument.
UNASSIGNED: Our findings suggest that mechanisms other than perturbation of heritable tendencies to produce males or females induce oscillation in the human secondary sex ratio. These other mechanisms may include reproductive suppression and selection in utero.
UNASSIGNED: The male to female ratio in human birth cohorts predicts longevity but its variation over time remains unexplained. We test the long-held theory that the ratio oscillates due to heritable tendencies to produce males or females. We find oscillation, but it appears due to social processes rather than heritable mechanisms.

The musical Hamilton, written by Lin-Manuel Miranda, creatively depicts the life and career of founding father Alexander Hamilton. While Hamilton is the primary focus, highlights of the career and personal journeys of other leaders, such as George Washington, Thomas Jefferson, and Aaron Burr, are interjected throughout the production. Often the musical numbers in Hamilton focus on aspects of leadership and career development that Hamilton and his contemporaries were learning or needed to learn. These lessons are applicable to the challenges that faculty members in academic pharmacy face today at different stages of a career. These include the importance of maximizing opportunities, listening, self-reflection, compromise, patience, empathy, prioritizing, tending relationships, making difficult decisions, knowing when to say goodbye, and managing a legacy.

UNASSIGNED: Stroke has been shown to cause cardiac autonomic dysfunction. Depression is common complication after acute ischemic stroke (AIS). The purpose of this study was to investigate whether decreased heart rate variability (HRV) was related to poststroke depression (PSD) in patients with mild-moderate AIS.
UNASSIGNED: In this study, we assessed autonomic function of ischemic stroke patients within 72 h from symptom onset by fractal dimension (FD). 503 patients (mean age 65.93 ± 10.19) with mild-moderate AIS underwent FD test after admission. Depressive symptoms were assessed using 17-item Hamilton Depression Rating Scale (HDRS) at baseline (within 7 days) and 3 months. Depression were defined if HDRS >6 points. According to the data of FD, we investigated association with early-onset PSD status and 3-month PSD.
UNASSIGNED: 59.24% (293/503) of patients had early-onset PSD status at baseline, and 38.66% (184/476) of patients had PSD at 3 months. ROC curve analysis shown that the optimal cut point of FD for early-onset PSD status and 3-month PSD were FD ≤ 1.27 and FD ≤ 1.19, respectively. In fully adjusted models, higher NIHSS [adjusted odd ratios (OR), 1.15; 95% confidence interval (CI), 1.05-1.27; P=0.005], younger age (adjusted OR, 1.18; 95% CI, 1.01-1.13; P=0.046), and FD ≤ 1.27 (adjusted OR, 3.31; 95% CI, 2.23-4.92; P<0.001) were associated with increased risk of early-onset PSD status. Higher NIHSS (adjusted OR, 1.21; 95% CI, 1.09-1.43; P<0.001) and FD ≤ 1.19 (adjusted OR, 2.68; 95% CI, 1.79-4.03; P=0.000) were associated with increased risk of 3-month PSD.
UNASSIGNED: PSD is common after mild-moderate AIS and is highly correlated with decreased HRV, FD could serve as an objective tool to help in prediction of PSD.

To address the risks associated with polypharmacy, health care providers are investigating the feasibility of deprescribing programs as part of routine medical care to reduce medication burden to older adults. As older adults are enrolled in these programs, they are confronted with two dominant and legitimate accounts of medications, labeled the medication paradox: medications keep you healthy but they might be making you sick. We investigated how the medication paradox operates in the lives of older adults. In-depth qualitative interviews were conducted and analyzed with older adults aged 70+ to identify the various paradoxes that seniors live through regarding their medications and the narratives that they engage to negotiate these contradictions. Older adults were found to have established interpretative repertoires to make sense of the incongruent narratives of the medication paradox. In this article, we demonstrate older adults\' efforts to carve out their unique place in the dichotomized institution of medicine.