Platelet-rich fibrin matrix was not shown to significantly improve perioperative morbidity, clinical outcomes, or structural integrity. While longer term follow-up or different platelet-rich plasma formulations may show differences, early follow-up does not show significant improvement in perioperative morbidity, structural integrity, or clinical outcome.

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According to recent WHO reports, alcohol remains the number one substance used and abused by adolescents, despite public health efforts to curb its use. Adolescence is a critical period of biological maturation where brain development, particularly the mesocorticolimbic dopamine system, undergoes substantial remodeling. These circuits are implicated in complex decision making, incentive learning and reinforcement during substance use and abuse. An appealing theoretical approach has been to suggest that alcohol alters the normal development of these processes to promote deficits in reinforcement learning and decision making, which together make individuals vulnerable to developing substance use disorders in adulthood. Previously we have used a preclinical model of voluntary alcohol intake in rats to show that use in adolescence promotes risky decision making in adulthood that is mirrored by selective perturbations in dopamine network dynamics. Further, we have demonstrated that incentive learning processes in adulthood are also altered by adolescent alcohol use, again mirrored by changes in cue-evoked dopamine signaling. Indeed, we have proposed that these two processes, risk-based decision making and incentive learning, are fundamentally linked through dysfunction of midbrain circuitry where inputs to the dopamine system are disrupted by adolescent alcohol use. Here, we test the behavioral predictions of this model in rats and present the findings in the context of the prevailing literature with reference to the long-term consequences of early-life substance use on the vulnerability to develop substance use disorders. We utilize an impulsive choice task to assess the selectivity of alcohol’s effect on decision-making profiles and conditioned reinforcement to parse out the effect of incentive value attribution, one mechanism of incentive learning. Finally, we use the differential reinforcement of low rates of responding (DRL) task to examine the degree to which behavioral disinhibition may contribute to an overall decision-making profile. The findings presented here support the proposition that early life alcohol use selectively alters risk-based choice behavior through modulation of incentive learning processes, both of which may be inexorably linked through perturbations in mesolimbic circuitry and may serve as fundamental vulnerabilities to the development of substance use disorders.

In abstinent drug addicts, cues formerly associated with drug-taking experiences gain relapse-inducing potency (‘incubate’) over time. Animal models of incubation may help develop treatments to prevent relapse, but these models have ubiquitously focused on the role of conditioned stimuli (CSs) signaling drug delivery. Discriminative stimuli (DSs) are unique in that they exert stimulus-control over both drug taking and drug seeking behavior and are difficult to extinguish. For this reason, incubation of the excitatory effects of DSs that signal drug availability, not yet examined in preclinical studies, could be relevant to relapse prevention. We trained rats to self-administer cocaine (or palatable food) under DS control, then investigated DS-controlled incubation of craving, in the absence of drug-paired CSs. DS-controlled cocaine (but not palatable food) seeking incubated over 60 days of abstinence and persisted up to 300 days. Understanding the neural mechanisms of this DS-controlled incubation holds promise for drug relapse treatments.

Biological Structure (SAG).Author contributions: MJ, RM, and SAG conceived of the pipeline and contributed intellectually to its development. MJ programmed, packaged, and created SMART and its supporting webpage. RM and CAMA developed the modified tissue clearing protocol. RM, CAMA and SAG conducted all imaging. MJ, SJW and JDN analyzed the dataset. JDN developed the Shiny applet used to display the example dataset. MJ, RM, and SAG wrote the manuscript with input from the other authors. members for their help with this project. We would like to thank Lauren E. Komer and Vadim Kashtelyan for their technical assistance. We also thank the NIDA Histology Core and staff for their support. AbstractMapping immediate early gene (IEG) expression across intact brains is becoming a popular approach for identifying the brain-wide activity patterns underlying behavior. Registering whole brains to an anatomical atlas presents a technical challenge that has predominantly been tackled using automated voxel-based registration methods; however, these methods may fail when brains are damaged or only partially imaged, can be challenging to correct, and require substantial computational power. Here we present an open source package in R called SMART (semi-manual alignment to reference templates) as an extension to the WholeBrain framework for automated segmentation and semi-automated registration of experimental images to vectorized atlas plates from the Allen Brain Institute Mouse Common Coordinate Framework (CCF).The SMART package was created with the novice programmer in mind and introduces a streamlined pipeline for aligning, registering, and segmenting large LSFM volumetric datasets with the CCF across the anterior-posterior axis, using a simple 'choice game' and interactive user-friendly menus.SMART further provides the flexibility to register partial brains or discrete user-chosen experimental images across the CCF, making it compatible with analysis of traditionally sectioned coronal brain slices.In addition to SMART, we introduce a modified tissue clearing protocol based on the iDISCO+ procedure that is optimized for uniform Fos antibody labeling and tissue clearing across whole intact mouse brains.Here we demonstrate the utility of the SMART-WholeBrain pipeline, in conjunction with the modified iDISCO+ Fos procedure, by providing example datasets alongside a full user tutorial. Finally, we present a subset of these data online in an interactive web applet. The complete SMART package is available for download on GitHub.

Mapping immediate early gene (IEG) expression across intact mouse brains allows for unbiased identification of brainwide activity patterns underlying complex behaviors. Accurate registration of sample brains to a common anatomic reference is critical for precise assignment of IEG-positive ("active") neurons to known brain regions of interest (ROIs). While existing automated voxel-based registration methods provide a high-throughput solution, they require substantial computing power, can be difficult to implement and fail when brains are damaged or only partially imaged. Additionally, it is challenging to cross-validate these approaches or compare them to any preexisting literature based on serial coronal sectioning. Here, we present the open-source R package SMART (Semi-Manual Alignment to Reference Templates) that extends the WholeBrain R package framework to automated segmentation and semi-automated registration of intact mouse brain light-sheet fluorescence microscopy (LSFM) datasets. The SMART package was created for novice programmers and introduces a streamlined pipeline for aligning, registering, and segmenting LSFM volumetric datasets across the anterior-posterior (AP) axis, using a simple "choice game" and interactive menus. SMART provides the flexibility to register whole brains, partial brains or discrete user-chosen images, and is fully compatible with traditional sectioned coronal slice-based analyses. We demonstrate SMART's core functions using example datasets and provide step-by-step video tutorials for installation and implementation of the package. We also present a modified iDISCO1 tissue clearing procedure for uniform immunohistochemical labeling of the activity marker Fos across intact mouse brains. The SMART pipeline, in conjunction with the modified iDISCO1 Fos procedure, is ideally suited for examination and orthogonal cross-validation of brain-wide neuronal activation datasets.

Studies using rodent models have shown that relapse to drug or food seeking increases progressively during abstinence, a behavioral phenomenon termed “incubation of craving.” Mechanistic studies of incubation of craving have focused on specific neurobiological targets within preselected brain areas. Recent methodological advances in whole-brain immunohistochemistry, clearing, and imaging now allow unbiased brain-wide cellular resolution mapping of regions and circuits engaged during learned behaviors. However, these whole-brain imaging approaches were developed for mouse brains, while incubation of drug craving has primarily been studied in rats, and incubation of food craving has not been demonstrated in mice. Here, we established a mouse model of incubation of palatable food craving and examined food reward seeking after 1, 15, and 60 abstinence days. We then used the neuronal activity marker Fos with intact-brain mapping procedures to identify corresponding patterns of brain-wide activation. Relapse to food seeking was significantly higher after 60 abstinence days than after 1 or 15 days. Using unbiased ClearMap analysis, we identified increased activation of multiple brain regions, particularly corticostriatal structures, following 60 but not 1 or 15 abstinence days. We used orthogonal SMART2 analysis to confirm these findings within corticostriatal and thalamocortical subvolumes and applied expert-guided registration to investigate subdivision and layer-specific activation patterns. Overall, we 1) identified brain-wide activity patterns during incubation of food seeking using complementary analytical approaches and 2) provide a single-cell resolution whole-brain atlas that can be used to identify functional networks and global architecture underlying the incubation of food craving.

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