Derek Gordon

Background: Researchers screen candidate anti-cancer drugs for their ability to inhibit tumor growth in patient-derived xenografts (PDXs). Typically, a single laboratory will use a single measure of tumor growth. Purpose: An effective drug-screening test as one that correctly identifies whether a drug treatment inhibits or does not inhibit tumor growth. We document improvements in the experimental design and statistical analysis of drug-screening tests based on the criteria of sensitivity and specificity. Methods: We analyzed two published datasets. The response of each PDX model was known in advance. This information provided for statistical ground-truth classification. One dataset analyzed growth inhibition in the presence of one specific drug treatment for two PDX tumor models for numerous labs. A second dataset reported tumor growth of many PDX models in the presence of many drugs. A PDX model for which the treatment showed no tumor growth inhibition is referred to as Progressive Disease (PD). A PDX model for which the treatment showed complete tumor growth inhibition is referred to as Completely Responsive (CR). We created and analyzed four drug-screening tests, based on p-values for either a single-measure and single-lab, or p-values from meta-analysis and multiple-test correction. The outcome of each screening test was that either the drug treatment was effective or it was not. For both datasets, we computed median sensitivities and specificities by applying bootstrap resampling, and specification of a significance level. Results: Our results showed that drug screening tests utilizing p-values from meta-analysis of numerous labs, or multiple test correction, produced median sensitivities and specificities that were always at least as high as those for the Single-Measure, Single-Lab test. This result was true for all significance levels. The 95% confidence intervals were usually greater in length for the Single-Measure, Single-Lab screening test.

Background: Alcohol use disorders (AUDs) pose a significant public health challenge, with adolescence representing a critical period of vulnerability for the initiation of alcohol consumption. Variability in drinking behaviors among individuals complicates efforts to characterize developmental trajectories, limiting our understanding of underlying biological mechanisms. Objective: This study aimed to identify and characterize distinct patterns of voluntary alcohol consumption in adolescent mice, using advanced statistical methods to model behavioral heterogeneity. Methods: Thirty-five male CD-1 outbred mice were monitored for alcohol consumption using a two-bottle free-choice paradigm from early adolescence to young adulthood (4–11 weeks of age). Finite mixture modeling, using the method implemented in the software SAS Proc Traj, was applied to categorize individual drinking behaviors into trajectory groups based on Bayesian Information Criterion (BIC) and Bayesian Posterior Probabilities (BPP). Results: Three distinct drinking trajectory groups were identified: non-drinkers, late drinkers, and early drinkers. Non-drinkers exhibited consistently low alcohol consumption throughout the study, late drinkers showed a significant increase in alcohol intake during adolescence-to-adulthood transition, and early drinkers maintained high levels of consumption from the start. Notably, the late and early drinkers converged on similarly high consumption levels by the end of the observation period. These findings highlight the heterogeneity of drinking behaviors during adolescence and its developmental implications. Conclusions: This study demonstrates the utility of finite mixture modeling in characterizing developmental trajectories of voluntary alcohol consumption in adolescent mice. The identification of distinct behavioral trajectory patterns provides a foundation for future investigations into the genetic, molecular, and neural mechanisms underpinning susceptibility to alcohol use disorders.

Tourette disorder (TD) is poorly understood, despite affecting 1/160 children. A lack of animal models possessing construct, face, and predictive validity hinders progress in the field. We used CRISPR/Cas9 genome editing to generate mice with mutations orthologous to human de novo variants in two high-confidence Tourette genes, CELSR3 and WWC1 . Mice with human mutations in Celsr3 and Wwc1 exhibit cognitive and/or sensorimotor behavioral phenotypes consistent with TD. Sensorimotor gating deficits, as measured by acoustic prepulse inhibition, occur in both male and female Celsr3 TD models. Wwc1 mice show reduced prepulse inhibition only in females. Repetitive motor behaviors, common to Celsr3 mice and more pronounced in females, include vertical rearing and grooming. Sensorimotor gating deficits and rearing are attenuated by aripiprazole, a partial agonist at dopamine type II receptors. Unsupervised machine learning reveals numerous changes to spontaneous motor behavior and less predictable patterns of movement. Continuous fixed-ratio reinforcement shows that Celsr3 TD mice have enhanced motor responding and reward learning. Electrically evoked striatal dopamine release, tested in one model, is greater. Brain development is otherwise grossly normal without signs of striatal interneuron loss. Altogether, mice expressing human mutations in high-confidence TD genes exhibit face and predictive validity. Reduced prepulse inhibition and repetitive motor behaviors are core behavioral phenotypes and are responsive to aripiprazole. Enhanced reward learning and motor responding occur alongside greater evoked dopamine release. Phenotypes can also vary by sex and show stronger affection in females, an unexpected finding considering males are more frequently affected in TD.

Major depressive disorder (MDD) and type 2 diabetes (T2D) are complex disorders whose comorbidity can be due to hypercortisolism and may be explained by dysfunction of the corticotropin-releasing hormone receptor 1 (CRHR1) and cortisol feedback within the hypothalamic–pituitary–adrenal axis (HPA axis). To investigate the role of the CRHR1 gene in familial T2D, MDD, and MDD-T2D comorbidity, we tested 152 CRHR1 single-nucleotide-polymorphisms (SNPs), via 2-point parametric linkage and linkage disequilibrium (LD; i.e., association) analyses using 4 models, in 212 peninsular families with T2D and MDD. We detected linkage/LD/association to/with MDD and T2D with 122 (116 novel) SNPs. MDD and T2D had 4 and 3 disorder-specific novel risk LD blocks, respectively, whose risk variants reciprocally confirm one another. Comorbidity was conferred by 3 novel independent SNPs. In silico analyses reported novel functional changes, including the binding site of glucocorticoid receptor-alpha [GR-α] on CRHR1 for transcription regulation. This is the first report of CRHR1 pleiotropic linkage/LD/association with peninsular familial MDD and T2D. CRHR1 contribution to MDD is stronger than to T2D and may antecede T2D onset. Our findings suggest a new molecular-based clinical entity of MDD-T2D and should be replicated in other ethnic groups.

The corticotropin-releasing hormone receptor 2 (CRHR2) gene encodes CRHR2, contributing to the hypothalamic–pituitary–adrenal stress response and to hyperglycemia and insulin resistance. CRHR2−/− mice are hypersensitive to stress, and the CRHR2 locus has been linked to type 2 diabetes and depression. While CRHR2 variants confer risk for mood disorders, MDD, and type 2 diabetes, they have not been investigated in familial T2D and MDD. In 212 Italian families with type 2 diabetes and depression, we tested 17 CRHR2 single nucleotide polymorphisms (SNPs), using two-point parametric-linkage and linkage-disequilibrium (i.e., association) analysis (models: dominant-complete-penetrance-D1, dominant-incomplete-penetrance-D2, recessive-complete-penetrance-R1, recessive-incomplete-penetrance-R2). We detected novel linkage/linkage-disequilibrium/association to/with depression (3 SNPs/D1, 2 SNPs/D2, 3 SNPs/R1, 3 SNPs/R2) and type 2 diabetes (3 SNPs/D1, 2 SNPs/D2, 2 SNPs/R1, 1 SNP/R2). All detected risk variants are novel. Two depression-risk variants within one linkage-disequilibrium block replicate each other. Two independent novel SNPs were comorbid while the most significant conferred either depression- or type 2 diabetes-risk. Although the families were primarily ascertained for type 2 diabetes, depression-risk variants showed higher significance than type 2 diabetes-risk variants, implying CRHR2 has a stronger role in depression-risk than type 2 diabetes-risk. In silico analysis predicted variants’ dysfunction. CRHR2 is for the first time linked to/in linkage-disequilibrium/association with depression-type 2 diabetes comorbidity and may underlie the shared genetic pathogenesis via pleiotropy.

The organization's leaders are bestowed with the ability to plan their workforce and are supported in that endeavor by various supporting leaders such as human resource professionals. The attitudes of C-level leaders, high and mid-level leaders, as well as front line leaders directly influence the organization's culture. Probationary periods are an effective and legal means used to fill openings with the most qualified candidates based upon observed merit via demonstrating essential skills, knowledge, and abilities. A robust probationary period is a critical practice that increases a good fit between newcomers and the organization increasing efficiency and producing greater return on investment. Those organizations who leaders forego entry-point training programs are likely to experience a disconnect between worker and role resulting in sustained mediocrity and eventually cease to exist. This chapter walks the reader through the development of the probationary period, case studies, and best practices. Request access from your librarian to read this chapter's full text.