Incidences of Involuntary Psychiatric Detentions in 25 U.S. States

OBJECTIVE

Characterizing commitment as an involuntary psychiatric emergency detention that possibly extends into a longer-term detention, the authors aimed to calculate population rates of detentions and chart interstate differences since 2011 by means of publicly available state counts.

METHODS

Searches of state health and court websites yielded counts from 38 U.S. states. Usable counts from 25 states were classified as emergency or longer-term detentions and converted to crude rates per 100,000 people by using Census Bureau figures.

RESULTS

All-ages rates (per 100,000 people) of emergency detentions ranged from 29 in Connecticut to 966 in Florida. In 22 states with continuous 2012-2016 data, the average rate increased from 273 to 309. In four of five states with separate counts for adults and minors, rates over time for both were nearly parallel. In eight states that provided relevant data, the mean longer-term detention rate was 42% of a state's average emergency detention rate. Only one state provided length-of-stay data, and one counted both detentions and persons detained. In 24 states-accounting for 51.9% of the U.S. population-591,402 emergency involuntary detentions were recorded in 2014, the most recent year with most states reporting, a crude rate of 357 per 100,000.

CONCLUSIONS

Incidences of involuntary psychiatric detentions between 2011 and 2018 varied 33-fold across 25 states, and the mean state rate increased by three times the mean state population increase. Omissions in most states' counts clouded interpretation. More valid incidences obtained from standardized national data would improve analysis of the controversial yet opaque procedure of involuntary inpatient civil commitment.

Centromeric cohesion failure invokes a conserved choreography of chromosomal mis-segregations in pancreatic neuroendocrine tumor

BACKGROUND

Pancreatic neuroendocrine tumors (PANETs) are rare, slow growing cancers that often present with local and distant metastasis upon detection. PANETS contain distinct karyotypes, epigenetic dysregulation, and recurrent mutations in MEN1, ATRX, and DAXX (MAD+); however, the molecular basis of disease progression remains uncharacterized.

METHODS

We evaluated associations between aneuploidy and the MAD+ mutational state of 532 PANETs from 11 published genomic studies and 19 new cases using a combination of exome, targeted panel, shallow WGS, or RNA-seq. We mapped the molecular timing of MAD+ PANET progression using cellular fractions corrected for inferred tumor content.

RESULTS

In 287 PANETs with mutational data, MAD+ tumors always exhibited a highly recurrent signature of loss of heterozygosity (LOH) and copy-number alterations affecting 11 chromosomes, typically followed by genome doubling upon metastasis. These LOH chromosomes substantially overlap with those that undergo non-random mis-segregation due to ectopic CENP-A localization to flanking centromeric regions in DAXX-depleted cell lines. Using expression data from 122 PANETs, we found decreased gene expression in the regions immediately adjacent to the centromere in MAD+ PANETs. Using 43 PANETs from AACR GENIE, we inferred this signature to be preceded by mutations in MEN1, ATRX, and DAXX. We conducted a meta-analysis on 226 PANETs from 8 CGH studies to show an association of this signature with metastatic incidence. Our study shows that MAD+ tumors are a genetically diverse and aggressive subtype of PANETs that display extensive chromosomal loss after MAD+ mutation, which is followed by genome doubling.

CONCLUSIONS

We propose an evolutionary model for a subset of aggressive PANETs that is initiated by mutation of MEN1, ATRX, and DAXX, resulting in defects in centromere cohesion from ectopic CENP-A deposition that leads to selective loss of chromosomes and the LOH phenotype seen in late-stage metastatic PANETs. These insights aid in disease risk stratification and nominate potential therapeutic vulnerabilities to treat this disease.

Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response

Publicly available data can potentially examine the relationship between environmental exposure and public health, however, it has not yet been widely applied. Arsenic is of environmental concern, and previous studies mathematically parameterized exposure duration to create a link between duration of exposure and increase in risk. However, since the dose metric emerging from exposure duration is not a linear or explicit variable, it is difficult to address the effects of exposure duration simply by using mathematical functions. To relate cumulative dose metric to public health requires a lifetime physiologically-based pharmacokinetic (PBPK) model, yet this model is not available at a population level. In this study, the data from the U.S. total diet study (TDS, 2006-2011) was employed to assess exposure: daily dietary intakes for total arsenic (tAs) and inorganic arsenic (iAs) were estimated to be 0.15 and 0.028μg/kg/day, respectively. Meanwhile, using National Health and Nutrition Examination Survey (NHANES, 2011-2012) data, the fraction of urinary As(III) levels (geometric mean: 0.31μg/L) in tAs (geometric mean: 7.75μg/L) was firstly reported to be approximately 4%. Together with Bayesian technique, the assessed exposure and urinary As(III) concentration were input to successfully optimize a lifetime population PBPK model. Finally, this optimized PBPK model was used to derive an oral reference dose (Rfd) of 0.8μg/kg/day for iAs exposure. Our study also suggests the previous approach (by using mathematical functions to account for exposure duration) may result in a conservative Rfd estimation.