Biology subjects

Job, M. O.

Publications and source records attributed to Job, M. O..

8 recordsLinked to original sources

bioRxiv2026

Cocaine and caffeine elicit different dopamine receptor-mediated locomotor activity profiles: insights from a new model.

BackgroundThe locomotor activity elicited by cocaine and caffeine can be distinguished via their underlying mechanisms and via differential responses to neuropharmacological manipulations. However, both cocaine- and caffeine-induced locomotor activity can be blocked by non-selective dopamine receptor antagonists, implying that we may not be able to distinguish their locomotor activity at the level of the dopamine receptor-mediated mechanism. With the rationale that this limitation may be due to a lack of sensitivity of current methods, we have developed a new Quantitative Structure of Curve Analytical (QSCAn) model. We hypothesized that QSCAn will be more effective, relative to the current model, in differentiating the dopamine receptor-mediated mechanism of cocaine versus caffeine-induced locomotor activity. MethodsWe assessed locomotor activity (quantified as distance traveled in cm over time) due to injections of saline (n = 6), cocaine (10 mg/kg i.p, n = 8) and caffeine (20 mg/kg i.p, n = 6) in male Sprague Dawley rats with and without pretreatment with vehicle and cis-flupenthixol (0.2 mg/kg i.p, non-selective dopamine receptor blocker)(current model). Because distance traveled over time follows an inverted u-shaped time-response curve, we employed gaussian fit of this structure to obtain several behavioral variables (QSCAn model). We compared both models. ResultsThe current model could not distinguish the locomotor activity profile of cocaine versus caffeine following vehicle and cis-flupenthixol pretreatments. QSCAn model could distinguish cocaine versus caffeine in the presence and absence of non-selective dopamine receptor blockade. ConclusionsThe new QSCAn model may be a promising tool to distinguish/characterize different psychostimulant-related effects.

neuroscience↗

bioRxiv2025

A Challenge To The Assumption That Short- versus Long-Access Groups of Opioid Users Represent Distinct Phenotypes

RationaleOne of the current models for drug (opioid) user typology employs differential access conditions to categorize takers into short-access and long-access groups (ShA, LgA) with the rationale that these groups represent distinct opioid user phenotypes. However, with the idea that differential vulnerabilities to opioid effects are already present prior to experimenter assignment into these groups, it is unclear that these groups represent distinct opioid user types. To clarify this, we have developed a method that includes principal component analysis-gaussian mixtures model clustering of variables derived from a new CENTERED (Cumulative Experience-Normalized Time-Effect on Response as an Exponential Decay structure) model. The goal of this study was to utilize CENTERED clustering to test the hypothesis that ShA and LgA groups defined by the experimenter via random assignment are composed of mixtures of individuals that belong to distinct opioid user types. MethodsWe reanalyzed data from a previous study in which the experimenter assigned male Sprague Dawley rats (n = 30) self-administering 0.1 mg/kg/infusion oxycodone for 20 days into ShA (3h-access) and LgA (9h-access). We conducted CENTERED clustering on all takers, irrespective of assigned group(s) to determine if the experimenter-assigned groups included mixtures of individuals from groups (opioid user types) identified via CENTERED clustering. ResultsCENTERED clustering revealed that ShA and LgA groups consisted of mixtures of different opioid user types. ConclusionsCENTERED clustering revealed that experimenter-imposed grouping via differential access conditions limits our ability to identify distinct opioid user types that already exist naturally in the population.

neuroscience↗

bioRxiv2024

Employing biological sex as a primary variable can restrict our understanding of behavioral diversity (and sex differences) in psychostimulant activity.

BackgroundIn addition to representing distinct biological sex groups, males and females are also individuals expressing behavioral diversity. Our MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model suggests that, with respect to behavior, grouping according to the individual reveals groups with differences that exceed biological sex-related differences, but this needs further clarification. We hypothesized that, compared to the current model (grouping by biological sex), the MISSING model (grouping by individual attributes) was the more effective grouping strategy to identify behavioral diversity. MethodsWe conducted experiments in rats to determine the locomotor activity (in 90 min) following intraperitoneal injections of saline (n = 12 males, n = 11 females) and cocaine (n = 8 males, n = 11 females). For the current model, we compared males versus females using unpaired t-tests. For the MISSING model, we identified clusters of individuals (males and females) using normal mixtures clustering analysis of several behavioral variables and employed unpaired t-tests to compare clusters and Two-way ANOVA to determine if there were any SEX by cluster interactions. For both models, we employed linear regression analysis to compare relationships between variables and Two-way repeated measures ANOVA to analyze locomotor activity time course. ResultsFor both the saline and cocaine groups, the MISSING model identified two behavioral clusters with differences that exceeded any differences due to biological sex. ConclusionsThe MISSING model suggests that employing biological sex as a primary variable can obscure our understanding of sex and individual differences in psychostimulant activity.

neuroscience↗

bioRxiv2024

The most significant differences between male and female rats regarding psychostimulant self-administration behavior are unrelated to biological sex

BackgroundThe goals of this study were to 1) validate the MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model for psychostimulant self-administration (SA), and 2) utilize it to explain the inconsistencies in the observation of sex differences in psychostimulant SA. MethodsWe allowed male and female Long Evans rats (n = 40) to self-administer methamphetamine METH dose 0.1 mg/kg (male n = 9, female n = 18) and saline (male n = 3, female n = 10) via the intravenous route, FR1 schedule, 6 h per day, 5 days per week for 4 weeks. For the MISSING model, we identified behavioral clusters of males and females using normal mixtures clustering analysis of baseline intake, total intake and total intake normalized-to-baseline intake (NBI), followed by unpaired t-tests to compare clusters and Two-way ANOVA to determine if there were any SEX by cluster interactions. For the current model, we grouped our subjects according to biological sex and compared the above variables using unpaired t-tests. For both models, we employed Two-way repeated measures ANOVA and linear regression analysis to analyze SA time course. ResultsFor saline and METH SA, there were no sex differences when we compared males and females generally, with sex differences evident only when we compared sexes from distinct clusters. The current model could not explain the inconsistencies in the observability of sex differences in METH SA. ConclusionsWe validated the MISSING model -it can explain the inconsistencies around sex differences in METH SA.

neuroscience↗

bioRxiv2024

Limitations of grouping subjects based on biological sex (males versus females) and a new approach: insights from intra-nucleus accumbens core dopamine-induced psychostimulant activity.

BackgroundIn the field of substance use disorder research, sex-as-a-biological-variable (SABV) is employed to determine the mechanisms governing sex differences. Based on our recently developed MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model, we hypothesized that grouping subjects by biological sex does not represent the most effective way to group behavioral data objectively. To test our hypothesis, we conducted experiments to compare the psychostimulant effect of intra-nucleus accumbens (NAc) dopamine on groups based on 1) biological sex (current model) and 2) behavioral clustering (MISSING model) for effectiveness in identifying groups of subjects that a) are distinct with regards to behavioral variables, and b) confirm NAc dopamine neurochemical expression/activity topography (NEAT). MethodsFor the current model, we separated subjects (n = 37 Sprague Dawley rats, male n = 20, female n = 17) by biological sex prior to all assessments. For the MISSING model, we conducted normal mixtures clustering of baseline activity, dopamine activity (as distance traveled in cm over 60 min) and dopamine activity normalized-to-baseline activity (NBA) of all subjects to identify behavioral clusters. ResultsSeparating groups by biological sex revealed groups (males and females) that were not clearly distinct with regards to behavioral variables and do not confirm NAc dopamine NEAT. Separating groups using the MISSING model revealed groups (behavioral clusters) that were clearly distinct with regards to behavior and confirm NAc dopamine NEAT. ConclusionsOur results reveal the limitations of grouping subjects based on biological sex. We discuss a new approach.

neuroscience↗

bioRxiv2024

Overestimation of sex differences in psychostimulant activity via comparisons of males and females from different behavioral groups.

BackgroundThere are inconsistencies in the observation of sex differences in baseline activity and psychostimulant activity. To address this, we have developed the MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model. MISSING model proposes that sex similarities are observed when we compare similar behavioral groups of males and females, with sex differences occurring when we compare distinct groups of sexes, but this model has not been tested. MethodsTo test this model, we identified within-sex groups of Sprague Dawley rats (male n = 22, female n = 23) by conducted normal mixtures clustering of baseline activity, cocaine activity (as distance traveled in cm over 90 min) and cocaine activity normalized-to-baseline activity (NBA) of all subjects. We employed 2-way ANOVA to determine the impact of within-sex heterogeneity on sex differences. We compared our cluster-based method to current median-split approaches. ResultsOur new cluster-based method revealed three distinct clusters, each consisting of both males and females. We determined there were no sex differences in any of the variables when males and females from the same clusters were compared. The within-sex clusters for females were not defined by estrous phase. Median split analysis was ineffective in accurately identifying within-sex groups. ConclusionsOur results validate the MISSING model: there are no sex differences in psychostimulant activity except when we compare males and females from different behavioral groups. This has significant implications for how we proceed with research towards understanding the mechanism governing sex differences in psychostimulant activity.

neuroscience↗

bioRxiv2024

A novel baseline-effect shift tracking model for more sensitive detection of differences in the effects of closely related dopamine transporter inhibitor/ sigma receptor antagonist drug combinations on psychostimulant use.

BackgroundFor the purpose of improving the ability to distinguish the activity of closely related drugs on psychostimulant use to enable more specific drug effect characterization, we have developed a new model termed the baseline-effect shift tracking (BEST) model. BEST compares/contrasts the baseline-drug activity relationship(s). AimTo compare the current model to our BEST model to determine which was more effective in distinguishing the effects of combinations of a dopamine transporter inhibitor (methylphenidate, MPD) and selective sigma1 (BD1063) and non-selective sigma (BD1008) receptor antagonists on cocaine consumption. MethodsMale Sprague Dawley rats were trained to self-administer cocaine (n = 9, 0.32 mg/kg/infusion) or sucrose pellets (n = 6, 20 mg pellets/delivery). We determined the effects for cocaine/sucrose of combinations of MPD (1 mg/kg i.p) and 1) BD1063 (0, 3.2, 10 mg/kg i.p), and 2) BD1008 (0, 3.2, 10 mg/kg i.p) on a) consumption at zero price (Q0), and b) essential value (eValue, demand elasticity) estimated using behavioral economic analysis of within-session demand curves, and c) the total intake under the price response curve (TIPR). We compared the models using ANOVA/ regression analysis. ResultsThe current model did not detect any differences in the effects of these drug combinations on cocaine/ sucrose taking behavior. For cocaine, but not for sucrose, the BEST model detected differences in the effects of these drug combinations on TIPR in subjects with higher baseline activity. ConclusionBEST model (with TIPR analysis) is more sensitive than the current models in differentiating drug effects on cocaine consumption.

neuroscience↗

bioRxiv2024

Experience-dependent sex differences in the role of dorsal striatal dopamine D1 receptor activity in methamphetamine self-administration revealed by a novel TREND model.

BACKGROUNDThe role of dorsal striatal dopamine D1 receptor systems in the mechanism of methamphetamine self-administration (METH SA), and sex differences in this role, are unclear. We hypothesized that this role would be sex and METH experience-dependent. Because prior experience regulates subsequent effects of drugs, we developed a novel model to account for this interaction, termed the TREND model (Time-Related-Experience-Normalized-Dynamics) for drug SA analysis. We tested our hypothesis by comparing results from the new TREND model and the current model. METHODSFor model validation, we reanalyzed previous data (Job et al., 2020) with the aim of determining which model (current or TREND) was more effective as an analytical tool. We compared variables from each model with the effect of Clozapine-N-Oxide (CNO, chemogenetic ligand) on METH SA. We employed regression analysis, median split, ANOVA to see which could reveal sex and experience dependency of dorsal striatal dopamine D1 receptor system. RESULTSThe current model variables were unrelated to CNO effect, with no sex differences in these relationships. TREND model revealed new variables that were unrelated to current variables but related to CNO effect on METH in males and females, with sex differences in these relationships. TREND, but not the current model, detected sex differences when comparing males and females with prior high, but not low, behavioral response variables. CONCLUSIONSTREND model is more sensitive than the current model for detecting experience-dependent sex differences in the role of the dorsal striatal dopamine D1 receptor systems in the mechanism of METH SA.

neuroscience↗