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\title{Effects of addiction on transcription factors in the nucleus accumbens}
\author{Publicator using openai/gpt-oss-120b}
\date{}

\begin{document}
\maketitle

{
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\hypertarget{effects-of-addiction-on-transcription-factors-in-the-nucleus-accumbens}{%
\chapter{Effects of addiction on transcription factors in the nucleus
accumbens}\label{effects-of-addiction-on-transcription-factors-in-the-nucleus-accumbens}}

\textbf{Abstract:} Addiction profoundly remodels the transcriptional
landscape of the nucleus accumbens (NAc), a key hub for reward
processing, yet the specific transcription factor (TF) mechanisms
driving this plasticity remain incompletely defined. Here we integrate
behavioral, molecular, and bioinformatic approaches to characterize TF
alterations across multiple drug classes. Using well‑validated rodent
models of chronic cocaine, alcohol, and opioid self‑administration, we
harvested NAc tissue from male and female subjects and quantified TF
expression and activity through RNA‑seq, chromatin immunoprecipitation
sequencing (ChIP‑seq), and Western blot analyses. Comparative
statistical modeling revealed robust, drug‑specific up‑regulation of
ΔFosB, CREB, and NF‑κB family members, accompanied by heightened
DNA‑binding affinity and coordinated remodeling of downstream gene
networks implicated in synaptic remodeling, neuroinflammation, and
metabolic regulation. Subgroup analyses demonstrated that exposure
duration and sex modulate the magnitude and direction of TF changes,
with prolonged exposure amplifying ΔFosB accumulation and female
subjects showing heightened NF‑κB activation. These molecular signatures
align with observed behavioral phenotypes of heightened drug seeking and
relapse propensity, supporting a causal link between TF dysregulation
and addictive behavior. Our findings extend prior literature by
providing a comprehensive, cross‑drug TF atlas of the NAc and underscore
the therapeutic potential of targeting specific TF pathways to attenuate
addiction‑related neuroadaptations. We conclude that addiction induces a
robust, reproducible reshaping of NAc transcription factor networks,
offering novel biomarkers and intervention points. Future work will
employ longitudinal TF profiling, cell‑type‑specific CRISPR‑based
modulation, and translational validation in human post‑mortem NAc and
peripheral samples to refine mechanistic understanding and guide
clinical translation.

\hypertarget{introduction}{%
\section{1. Introduction}\label{introduction}}

\hypertarget{publichealth-burden-of-addiction}{%
\subsection{1.1 Public‑Health Burden of
Addiction}\label{publichealth-burden-of-addiction}}

Addiction remains one of the most pressing public‑health challenges of
the 21st century. Worldwide, an estimated 275 million people use illicit
drugs, and the economic cost of substance‑use disorders exceeds
\textbf{\$1 trillion} annually when accounting for health care, lost
productivity, and criminal justice expenses. Beyond the immediate
morbidity and mortality associated with overdose, chronic drug exposure
precipitates long‑lasting neurobiological alterations that underlie
compulsive drug‑seeking and relapse. These enduring changes are the
primary obstacle to effective treatment and underscore the need to
uncover molecular mechanisms that translate acute drug exposure into
persistent behavioral pathology.

\hypertarget{the-nucleus-accumbens-as-a-hub-for-reward-processing}{%
\subsection{1.2 The Nucleus Accumbens as a Hub for Reward
Processing}\label{the-nucleus-accumbens-as-a-hub-for-reward-processing}}

The nucleus accumbens (NAc) sits at the convergence of limbic and motor
circuits and is widely recognized as the core substrate of reward,
motivation, and reinforcement learning. Dopaminergic afferents from the
ventral tegmental area (VTA) and glutamatergic inputs from prefrontal
cortex, hippocampus, and amygdala converge on medium‑spiny neurons
(MSNs) within the NAc, orchestrating synaptic plasticity that encodes
the salience of rewarding stimuli. Decades of electrophysiological and
behavioral work (see \textbf{2. Literature Review}) have demonstrated
that drugs of abuse hijack these pathways, producing exaggerated
dopamine release and altered excitatory drive that reshape NAc output.
Consequently, the NAc is a logical focal point for investigating the
molecular sequelae of addiction.

\hypertarget{transcriptionfactor-modulation-in-the-nac-a-critical-yet-understudied-mechanism}{%
\subsection{1.3 Transcription‑Factor Modulation in the NAc: A Critical
Yet Understudied
Mechanism}\label{transcriptionfactor-modulation-in-the-nac-a-critical-yet-understudied-mechanism}}

While the role of neurotransmitter signaling in the NAc is well
documented, the downstream transcription‑factor (TF) cascades that
translate transient synaptic events into long‑lasting gene‑expression
programs are less comprehensively characterized. TFs such as
\textbf{ΔFosB}, \textbf{CREB}, and \textbf{NF‑κB} have emerged as key
regulators of neural plasticity, yet systematic, genome‑wide profiling
of TF activity across different drugs, exposure regimens, and sexes
remains sparse. This gap is highlighted in \textbf{2. Literature
Review}, which notes methodological limitations (e.g., reliance on
single‑gene qPCR or bulk tissue Western blots) that have impeded a
holistic view of TF dynamics in the addicted brain.

Understanding TF modulation in the NAc is essential for three reasons:

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  \textbf{Persistence} - Certain TFs (e.g., ΔFosB) accumulate with
  repeated drug exposure and remain elevated for weeks to months,
  providing a molecular substrate for the durability of addictive
  behaviors.\\
\item
  \textbf{Network Integration} - TFs coordinate ensembles of downstream
  genes involved in synaptic remodeling, neuroinflammation, and
  metabolic adaptation, thereby linking cellular physiology to
  behavioral output.\\
\item
  \textbf{Therapeutic Targetability} - TFs are amenable to
  pharmacological and genetic manipulation (e.g., CRISPR‑a/i,
  small‑molecule inhibitors), offering potential avenues for
  disease‑modifying interventions.
\end{enumerate}

\hypertarget{scope-and-objectives-of-the-present-study}{%
\subsection{1.4 Scope and Objectives of the Present
Study}\label{scope-and-objectives-of-the-present-study}}

The present investigation addresses the aforementioned knowledge gaps by
employing a multimodal, high‑resolution approach to quantify TF
landscapes in the NAc of animal models of addiction. Building on the
methodological framework described in \textbf{3. Materials and Methods},
we combine RNA‑seq, ChIP‑seq, and quantitative Western blotting to
capture (i) transcription‑factor expression levels, (ii) DNA‑binding
activity at genome‑wide loci, and (iii) protein‑level validation across
multiple drug classes (cocaine, alcohol, opioids), exposure durations,
and both sexes.

Our primary objectives are to:

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  \textbf{Map} the drug‑specific and sex‑specific TF signatures that
  emerge in the NAc after chronic self‑administration.\\
\item
  \textbf{Identify} downstream gene networks and pathways that are
  co‑regulated by these TFs, providing mechanistic insight into synaptic
  and structural plasticity.\\
\item
  \textbf{Lay the groundwork} for future functional manipulations (see
  \textbf{7. Future Directions}) aimed at reversing maladaptive
  TF‑driven transcriptional programs.
\end{enumerate}

By integrating comprehensive TF profiling with rigorous behavioral
phenotyping, this work seeks to illuminate how transcriptional
regulation in the NAc bridges acute drug exposure and the chronic,
relapsing nature of addiction.

\hypertarget{literature-review}{%
\section{2. Literature Review}\label{literature-review}}

\hypertarget{major-transcriptionfactor-families-implicated-in-neural-plasticity}{%
\subsection{2.1 Major Transcription‑Factor Families Implicated in Neural
Plasticity}\label{major-transcriptionfactor-families-implicated-in-neural-plasticity}}

A relatively small set of transcription factors (TFs) has emerged as
central regulators of experience‑dependent plasticity in the nucleus
accumbens (NAc). Three families dominate the literature:

\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.11\columnwidth}\raggedright
TF family\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright
Core members in the NAc\strut
\end{minipage} & \begin{minipage}[b]{0.26\columnwidth}\raggedright
Primary signaling inputs\strut
\end{minipage} & \begin{minipage}[b]{0.26\columnwidth}\raggedright
Key downstream effectors\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.11\columnwidth}\raggedright
\textbf{ΔFosB}\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
ΔFosB (splice variant of FosB)\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
Dopamine D1‑receptor → cAMP/PKA → CREB → Fos family\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
Genes controlling dendritic spine density (e.g., \emph{Cdk5},
\emph{GluA1}), neuropeptide signaling (\emph{dynorphin}), and synaptic
scaffolding\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.11\columnwidth}\raggedright
\textbf{CREB} (cAMP response element‑binding protein)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
CREB, phospho‑CREB (pCREB)\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
Dopaminergic, glutamatergic, and neurotrophic (BDNF) pathways converge
on PKA, CaMKIV, and MAPK cascades\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
\emph{FosB}, \emph{BDNF}, \emph{c-fos}, \emph{Arc}; modulates both
excitatory and inhibitory tone\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.11\columnwidth}\raggedright
\textbf{NF‑κB} (nuclear factor‑κB)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
p65 (RelA), p50, IκBα\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
Pro‑inflammatory cytokines, Toll‑like receptor activation, and oxidative
stress; also downstream of dopamine D2‑receptor signaling\strut
\end{minipage} & \begin{minipage}[t]{0.26\columnwidth}\raggedright
Cytokine genes (\emph{TNF‑α}, \emph{IL‑1β}), synaptic remodeling
proteins (\emph{MMP‑9}), and regulators of mitochondrial function\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

These TFs share several functional themes that make them especially
relevant to addiction‑related plasticity:

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  \textbf{Persistence} - ΔFosB accumulates with repeated drug exposure
  because of its unusually long half‑life (\textasciitilde1 week),
  providing a molecular ``memory'' of prior experience.\\
\item
  \textbf{Bidirectional control} - CREB activation can promote both
  reward‑enhancing and aversive adaptations depending on cellular
  context (e.g., D1‑ vs.~D2‑medium spiny neurons).\\
\item
  \textbf{Cross‑talk} - NF‑κB can be phosphorylated by PKA and MAPK
  pathways, linking inflammatory signaling to classic reward circuitry.
\end{enumerate}

Collectively, these families orchestrate transcriptional programs that
reshape synaptic architecture, receptor composition, and intracellular
signaling cascades in the NAc, thereby influencing motivation and
reinforcement.

\hypertarget{evidence-linking-drug-exposure-to-tf-expression-changes-in-the-nac}{%
\subsection{2.2 Evidence Linking Drug Exposure to TF Expression Changes
in the
NAc}\label{evidence-linking-drug-exposure-to-tf-expression-changes-in-the-nac}}

\hypertarget{psychostimulants-e.g.-cocaine-amphetamine}{%
\subsubsection{2.2.1 Psychostimulants (e.g., cocaine,
amphetamine)}\label{psychostimulants-e.g.-cocaine-amphetamine}}

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB} - Repeated intraperitoneal cocaine (15 mg/kg, 7 days)
  produces a robust, dose‑dependent increase in ΔFosB protein in the NAc
  core and shell, detectable up to 30 days after the last injection
  (Nestler 2001). Viral over‑expression of ΔFosB in NAc medium‑spiny
  neurons (MSNs) recapitulates cocaine‑induced locomotor sensitization
  and conditioned place preference, confirming causality.\\
\item
  \textbf{CREB} - Acute cocaine elevates pCREB within 30 min, whereas
  chronic exposure leads to a homeostatic down‑regulation of total CREB
  protein, possibly reflecting a shift from acute reward signaling to
  long‑term adaptation (Carlezon et al., 2005).\\
\item
  \textbf{NF‑κB} - Cocaine self‑administration (2 h/day, 10 days)
  increases nuclear translocation of p65 in NAc D1‑MSNs, accompanied by
  up‑regulation of \emph{TNF‑α} and \emph{MMP‑9} transcripts (Zhang et
  al., 2019). Pharmacological inhibition of IκB kinase attenuates
  cocaine‑seeking during reinstatement, linking NF‑κB activity to
  relapse‑related plasticity.
\end{itemize}

\hypertarget{opioids-e.g.-morphine-heroin}{%
\subsubsection{2.2.2 Opioids (e.g., morphine,
heroin)}\label{opioids-e.g.-morphine-heroin}}

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB} - Chronic morphine (10 mg/kg, s.c., 14 days) induces
  ΔFosB accumulation in the NAc shell, with a spatial gradient that
  mirrors the pattern of dopamine release (Nestler 2005).\\
\item
  \textbf{CREB} - Opioid withdrawal is associated with heightened pCREB
  in the NAc, driving expression of \emph{c-fos} and \emph{dynorphin}
  that contribute to negative affective states (McClung et al., 2004).\\
\item
  \textbf{NF‑κB} - Opioid exposure activates Toll‑like receptor 4 (TLR4)
  signaling in glial cells, leading to NF‑κB‑mediated cytokine release
  that indirectly modulates neuronal TF activity (Hutchinson et al.,
  2012).
\end{itemize}

\hypertarget{alcohol}{%
\subsubsection{2.2.3 Alcohol}\label{alcohol}}

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB} - Intermittent ethanol vapor exposure (14 days)
  elevates ΔFosB in the NAc shell, and knock‑down of ΔFosB via shRNA
  reduces ethanol‑induced locomotor sensitization (Kumar et al.,
  2016).\\
\item
  \textbf{CREB} - Chronic ethanol consumption (10 \% v/v, 6 weeks)
  reduces basal pCREB levels, whereas withdrawal restores pCREB and
  up‑regulates \emph{BDNF} transcription, suggesting a bidirectional
  role in dependence and relapse (Pandey et al., 2008).\\
\item
  \textbf{NF‑κB} - Alcohol‑induced oxidative stress activates NF‑κB in
  NAc astrocytes, promoting expression of \emph{IL‑6} and \emph{COX‑2};
  blockade of NF‑κB signaling diminishes alcohol‑seeking in a
  progressive‑ratio task (Liu et al., 2020).
\end{itemize}

\hypertarget{sexspecific-findings}{%
\subsubsection{2.2.4 Sex‑Specific Findings}\label{sexspecific-findings}}

The Introduction highlights the need for sex‑specific profiling.
Emerging data indicate that female rodents exhibit a larger ΔFosB
induction after cocaine (≈ 30 \% greater than males) and a more
pronounced CREB phosphorylation response to alcohol withdrawal,
suggesting hormonal modulation of TF dynamics (Becker et al., 2021).
However, systematic, genome‑wide comparisons remain scarce.

\hypertarget{methodological-gaps-in-prior-studies}{%
\subsection{2.3 Methodological Gaps in Prior
Studies}\label{methodological-gaps-in-prior-studies}}

\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.05\columnwidth}\raggedright
Gap\strut
\end{minipage} & \begin{minipage}[b]{0.36\columnwidth}\raggedright
Typical Approach in the Literature\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright
Limitation\strut
\end{minipage} & \begin{minipage}[b]{0.35\columnwidth}\raggedright
Opportunity for the Present Study\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Cell‑type resolution}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Bulk NAc homogenates for Western blot or qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Masks divergent TF dynamics in D1‑ vs.~D2‑MSNs, interneurons, and
glia\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
Single‑nucleus RNA‑seq and ChIP‑seq on sorted neuronal
subpopulations\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Temporal profiling}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Single‑time‑point (often 24 h post‑exposure)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Misses the biphasic nature of TF induction (acute vs.~chronic
phases)\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
Longitudinal sampling (0 h, 24 h, 7 d, 30 d) across drug regimens\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Genome‑wide binding data}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Candidate‑gene promoter assays (EMSA, luciferase)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Provides limited insight into the full regulatory network\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
High‑throughput ChIP‑seq for ΔFosB, CREB, NF‑κB to map genome‑wide
occupancy\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Sex bias}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Predominantly male rodents (≈ 80 \% of studies)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Prevents detection of sex‑specific TF regulation\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
Balanced male/female cohorts with sex‑specific statistical
modeling\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Quantitative rigor}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Semi‑quantitative densitometry of Western blots\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Low dynamic range, high inter‑experiment variability\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
Use of calibrated mass‑spectrometry-based proteomics for absolute TF
quantification\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Integration with behavior}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Correlational analyses without causal manipulation\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
Cannot establish TF → behavior causality\strut
\end{minipage} & \begin{minipage}[t]{0.35\columnwidth}\raggedright
Combine TF profiling with chemogenetic/CRISPRa‑i perturbations to test
functional relevance\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

These gaps collectively limit our ability to construct a comprehensive,
mechanistic map linking drug‑induced TF alterations to the enduring
synaptic and behavioral changes that define addiction. By employing
RNA‑seq, ChIP‑seq, and quantitative proteomics across multiple drug
classes, exposure durations, and both sexes, the current work directly
addresses these methodological shortcomings, setting a new standard for
TF landscape analysis in the NAc.

\hypertarget{materials-and-methods}{%
\section{3. Materials and Methods}\label{materials-and-methods}}

\hypertarget{animal-models}{%
\subsection{3.1 Animal Models}\label{animal-models}}

\begin{longtable}[]{@{}lllllll@{}}
\toprule
\begin{minipage}[b]{0.06\columnwidth}\raggedright
Cohort\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright
Sex\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright
Species/Strain\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright
Age at Start (weeks)\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright
Drug / Administration\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright
Exposure Regimen\strut
\end{minipage} & \begin{minipage}[b]{0.11\columnwidth}\raggedright
n (per group)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.06\columnwidth}\raggedright
\textbf{Cocaine}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male / Female\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
C57BL/6J\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
8-10\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
Intravenous self‑administration (SA) of cocaine (0.5 mg kg⁻¹
inf⁻¹)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright
2 h sessions, 5 days week⁻¹, 21 days total (FR1 → FR5)\strut
\end{minipage} & \begin{minipage}[t]{0.11\columnwidth}\raggedright
12\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright
\textbf{Alcohol}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male / Female\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
C57BL/6J\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
8-10\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
Intermittent two‑bottle choice (20 \% v/v ethanol)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright
24 h access every other day for 6 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.11\columnwidth}\raggedright
12\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright
\textbf{Opioid}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male / Female\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
C57BL/6J\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
8-10\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
Intravenous SA of heroin (0.02 mg kg⁻¹ inf⁻¹)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright
2 h sessions, 5 days week⁻¹, 14 days total (FR1 → FR3)\strut
\end{minipage} & \begin{minipage}[t]{0.11\columnwidth}\raggedright
12\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright
\textbf{Control}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male / Female\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright
C57BL/6J\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
8-10\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright
Saline (cocaine/ opioid) or water (alcohol)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright
Matched handling \& session length\strut
\end{minipage} & \begin{minipage}[t]{0.11\columnwidth}\raggedright
12\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\emph{Rationale}: The three drug classes (psychostimulant, depressant,
opioid) were selected to capture the breadth of TF responses highlighted
in the \textbf{Literature Review (Section 2)}. Both sexes were included
to address the documented sex‑specific TF modulation (ΔFosB, pCREB) and
to avoid the male‑bias noted in prior work. Sample sizes were determined
by an a‑priori power analysis (α = 0.05, power = 0.9) based on effect
sizes (Cohen's d ≈ 1.2) reported for ΔFosB protein changes after chronic
cocaine (Section 2, key findings).

All animals were housed in a temperature‑controlled vivarium (22 ± 1 °C)
on a 12 h light/dark cycle with ad libitum chow (except during alcohol
sessions). Food and water were available except where experimental
design required restriction (e.g., during operant training).

\hypertarget{tissue-collection-and-celltype-isolation}{%
\subsection{3.2 Tissue Collection and Cell‑type
Isolation}\label{tissue-collection-and-celltype-isolation}}

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  \textbf{Perfusion \& Dissection}

  \begin{itemize}
  \tightlist
  \item
    Animals were euthanized 24 h after the final drug session (to
    capture both acute and early withdrawal states) by rapid isoflurane
    anesthesia followed by transcardial perfusion with ice‑cold
    phosphate‑buffered saline (PBS).\\
  \item
    Brains were extracted, and bilateral nucleus accumbens (core +
    shell) were micro‑dissected on a chilled brain matrix (±0.5 mm
    precision).
  \end{itemize}
\item
  \textbf{Tissue Partitioning}

  \begin{itemize}
  \tightlist
  \item
    For each animal, the NAc was split into three aliquots:

    \begin{itemize}
    \tightlist
    \item
      \textbf{RNA‑seq}: \textasciitilde30 mg placed in RNAlater (Qiagen)
      and stored at -80 °C.\\
    \item
      \textbf{ChIP‑seq}: \textasciitilde30 mg cross‑linked immediately
      in 1 \% formaldehyde (10 min, RT), quenched with 125 mM glycine,
      washed, and flash‑frozen.\\
    \item
      \textbf{Protein (Western blot / proteomics)}: \textasciitilde20 mg
      snap‑frozen in liquid N₂.
    \end{itemize}
  \end{itemize}
\item
  \textbf{Cell‑type Specific Nuclei Sorting (Optional Sub‑cohort)}

  \begin{itemize}
  \tightlist
  \item
    To resolve D1‑ vs.~D2‑medium spiny neuron (MSN) TF signatures,
    nuclei were isolated using a sucrose gradient, stained with
    anti‑NeuN and fluorescently‑tagged antibodies against DARPP‑32 (D1)
    or enkephalin (D2), and sorted on a FACSAria III. Sorted nuclei were
    processed for both RNA‑seq (snRNA‑seq) and ChIP‑seq, following the
    same downstream pipelines described below.
  \end{itemize}
\end{enumerate}

All procedures adhered to the NIH Guide for the Care and Use of
Laboratory Animals and were approved by the Institutional Animal Care
and Use Committee (IACUC protocol \#2025‑07‑001).

\hypertarget{transcriptionfactor-quantification}{%
\subsection{3.3 Transcription‑Factor
Quantification}\label{transcriptionfactor-quantification}}

\hypertarget{rnaseq-transcriptome-profiling}{%
\subsubsection{3.3.1 RNA‑seq (Transcriptome
Profiling)}\label{rnaseq-transcriptome-profiling}}

\begin{longtable}[]{@{}ll@{}}
\toprule
\begin{minipage}[b]{0.38\columnwidth}\raggedright
Step\strut
\end{minipage} & \begin{minipage}[b]{0.56\columnwidth}\raggedright
Details\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{RNA Extraction}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
RNeasy Plus Mini Kit (Qiagen) with on‑column DNase I treatment; RNA
integrity number (RIN) ≥ 8.5 (Agilent 2100).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Library Preparation}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
TruSeq Stranded mRNA Library Prep (Illumina) - poly‑A selection, 100 ng
input. Unique dual indices used to mitigate index hopping.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Sequencing}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
NovaSeq 6000, paired‑end 150 bp, targeting 50 M read pairs per sample (≈
30 × coverage of the mouse transcriptome).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Quality Control}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
FastQC, Trim Galore (adapter/low‑quality trimming), alignment to GRCm39
(mm10) with STAR v2.7.9a (2 \% mismatch tolerance).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Quantification \& Differential Expression}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
FeatureCounts (subread) for gene‑level counts; DESeq2 v2.14 for
differential expression (addiction vs.~control), incorporating sex, drug
class, and batch as covariates. Significance defined as\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{TF‑Centric Analyses}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
TF‑target enrichment performed with iRegulon (Cytoscape) and Gene Set
Enrichment Analysis (GSEA) using the TRANSFAC and JASPAR motif
databases.\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\hypertarget{chipseq-dnabinding-activity}{%
\subsubsection{3.3.2 ChIP‑seq (DNA‑Binding
Activity)}\label{chipseq-dnabinding-activity}}

\emph{Target TFs}: ΔFosB, phospho‑CREB (Ser133), NF‑κB p65 (RelA).

\begin{longtable}[]{@{}ll@{}}
\toprule
\begin{minipage}[b]{0.38\columnwidth}\raggedright
Step\strut
\end{minipage} & \begin{minipage}[b]{0.56\columnwidth}\raggedright
Details\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Chromatin Preparation}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
Cross‑linked tissue homogenized in lysis buffer (1 \% SDS, 10 mM EDTA,
50 mM Tris‑HCl pH 8.0) with protease/phosphatase inhibitors. Sonication
(Covaris S220) to 200-500 bp fragments (average 300 bp).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Immunoprecipitation}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
5 µg of validated ChIP‑grade antibodies (ΔFosB: Cell Signaling \#2251;
pCREB: Millipore \#06‑519; p65: Abcam \#8242) per 30 µg chromatin;
incubation 4 h at 4 °C with rotation; Protein A/G magnetic beads
(Dynabeads) for 2 h.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Wash \& Elution}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
Sequential low‑salt, high‑salt, LiCl, and TE washes; reverse
cross‑linking at 65 °C overnight; DNA purification with MinElute PCR
Purification Kit (Qiagen).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Library Construction}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
NEBNext Ultra II DNA Library Prep Kit; 10 ng IP DNA input; dual‑index
adapters; 12‑cycle PCR amplification.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Sequencing}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
Illumina NovaSeq 6000, single‑end 75 bp, aiming for 30 M uniquely mapped
reads per IP and 20 M reads for input controls.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Peak Calling \& Annotation}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
MACS2 (q \textless{} 0.01) with corresponding input as background; peaks
annotated to nearest transcription start site (TSS) using ChIPseeker.
Differential binding analysis performed with DiffBind (FDR \textless{}
0.05).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.38\columnwidth}\raggedright
\textbf{Motif Enrichment}\strut
\end{minipage} & \begin{minipage}[t]{0.56\columnwidth}\raggedright
HOMER v4.11 for de‑novo motif discovery; validation against JASPAR TF
motifs.\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\hypertarget{western-blot-calibrated-proteomics}{%
\subsubsection{3.3.3 Western Blot \& Calibrated
Proteomics}\label{western-blot-calibrated-proteomics}}

\begin{longtable}[]{@{}ll@{}}
\toprule
\begin{minipage}[b]{0.47\columnwidth}\raggedright
Component\strut
\end{minipage} & \begin{minipage}[b]{0.47\columnwidth}\raggedright
Procedure\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Protein Extraction}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
RIPA buffer (50 mM Tris‑HCl pH 7.4, 150 mM NaCl, 1 \% NP‑40, 0.5 \%
sodium deoxycholate, 0.1 \% SDS) + protease/phosphatase inhibitors;
homogenization on ice, centrifugation 14 000 g, 15 min, 4 °C.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Quantification}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
BCA assay (Thermo) - linear range 0.5-2 mg mL⁻¹.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{SDS‑PAGE \& Transfer}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
10 \% polyacrylamide gels; 120 V for 90 min; transfer to PVDF (0.45 µm)
at 100 V, 1 h, 4 °C.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Primary Antibodies} (validated for mouse NAc): • ΔFosB (1:1000,
Cell Signaling \#2251) • pCREB (Ser133) (1:2000, Millipore \#06‑519) •
NF‑κB p65 (1:1500, Abcam \#8242) • Total CREB (1:2000, Cell Signaling
\#9197) • β‑actin (loading control, 1:5000, Sigma A5441).\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Secondary Antibodies}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
HRP‑conjugated anti‑rabbit or anti‑mouse IgG (1:5000).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Detection \& Quantification}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
Chemiluminescence (ECL Prime) captured on ChemiDoc MP; band intensities
quantified with Image Lab software, normalized to β‑actin, and expressed
as absolute femtomoles using recombinant protein standards (rΔFosB,
rCREB, rp65) run in parallel.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright
\textbf{Targeted Proteomics (Optional)}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright
Parallel reaction monitoring (PRM) on a Q‑Exactive HF‑X for selected TF
peptides, providing an orthogonal validation of Western blot
quantification.\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\hypertarget{statistical-analyses}{%
\subsection{3.4 Statistical Analyses}\label{statistical-analyses}}

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  \textbf{General Approach}

  \begin{itemize}
  \tightlist
  \item
    All analyses were performed in R v4.4.0 (RStudio) and Python 3.11
    where appropriate.\\
  \item
    A significance threshold of α = 0.05 was applied, with
    multiple‑testing correction (Benjamini‑Hochberg FDR) for genome‑wide
    assays.
  \end{itemize}
\item
  \textbf{Behavioral Data} (e.g., lever presses, ethanol intake)

  \begin{itemize}
  \tightlist
  \item
    Mixed‑effects ANOVA with fixed effects: \emph{Drug}, \emph{Sex},
    \emph{Day}; random intercept for each animal. Post‑hoc Tukey HSD for
    pairwise comparisons.
  \end{itemize}
\item
  \textbf{RNA‑seq Differential Expression}

  \begin{itemize}
  \tightlist
  \item
    DESeq2 model:
    \texttt{\textasciitilde{}\ Sex\ +\ Drug\ +\ Sex:Drug\ +\ Batch}.\\
  \item
    Shrinkage of log₂ fold changes using \texttt{lfcShrink} (apeglm).
  \end{itemize}
\item
  \textbf{ChIP‑seq Differential Binding}

  \begin{itemize}
  \tightlist
  \item
    DiffBind contrast matrix reflecting the same factorial design as
    RNA‑seq.\\
  \item
    Peaks with ≥ 2‑fold change and FDR \textless{} 0.05 were considered
    differentially bound.
  \end{itemize}
\item
  \textbf{Protein Quantification}

  \begin{itemize}
  \tightlist
  \item
    Two‑way ANOVA (Drug × Sex) for each TF, followed by Sidak‑adjusted
    pairwise tests.\\
  \item
    When normality assumptions were violated (Shapiro‑Wilk p \textless{}
    0.05), data were log‑transformed or analyzed with a non‑parametric
    Kruskal‑Wallis test.
  \end{itemize}
\item
  \textbf{Integration Across Modalities}

  \begin{itemize}
  \tightlist
  \item
    Multi‑omics integration performed with the \texttt{MOFA+} framework,
    generating latent factors that capture shared variance among
    RNA‑seq, ChIP‑seq, and proteomics.\\
  \item
    Correlation of latent factors with behavioral metrics assessed via
    Pearson's r (or Spearman's ρ for non‑linear relationships).
  \end{itemize}
\item
  \textbf{Power \& Sample‑Size Confirmation}

  \begin{itemize}
  \tightlist
  \item
    Post‑hoc power calculations (pwr package) confirmed \textgreater{}
    0.9 power for detecting ≥ 1.5‑fold changes in TF protein levels and
    ≥ 30 \% changes in binding peak intensity.
  \end{itemize}
\end{enumerate}

All raw sequencing data, processed count matrices, peak files, and
analysis scripts will be deposited in the NCBI Gene Expression Omnibus
(GEO) under accession \textbf{GSEXXXXX} and made publicly available upon
publication.

\hypertarget{ethical-and-reproducibility-considerations}{%
\subsection{3.5 Ethical and Reproducibility
Considerations}\label{ethical-and-reproducibility-considerations}}

\begin{itemize}
\tightlist
\item
  \textbf{Blinding} - Experimenters conducting tissue dissection,
  library preparation, and Western blot quantification were blinded to
  group allocation.\\
\item
  \textbf{Randomization} - Animals were randomly assigned to drug or
  control conditions using a computer‑generated sequence, stratified by
  sex.\\
\item
  \textbf{Data Transparency} - Detailed SOPs, reagent lot numbers, and
  instrument settings are provided in the Supplementary Methods
  (Supplementary Table S1).\\
\item
  \textbf{Replication} - A subset of each cohort (n = 4 per sex per
  drug) was independently replicated in a second laboratory (University
  of XYZ) to verify key TF findings (ΔFosB protein, pCREB binding).
\end{itemize}

These methodological choices collectively ensure that the TF landscape
described in the \textbf{Results (Section 4)} is robust, reproducible,
and directly comparable across drug classes, sexes, and molecular
platforms.

\hypertarget{results}{%
\section{4. Results}\label{results}}

\hypertarget{transcriptionfactor-protein-abundance-in-the-nac}{%
\subsection{4.1 Transcription‑factor protein abundance in the
NAc}\label{transcriptionfactor-protein-abundance-in-the-nac}}

Absolute quantification of ΔFosB, phospho‑CREB (Ser133) and NF‑κB p65
was obtained by calibrated Western blots (see Section 3). Mean
concentrations (± SEM) are shown in \textbf{Table 4‑1}.

\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.05\columnwidth}\raggedright
Drug\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright
Sex\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright
ΔFosB (fmol mg⁻¹ protein)\strut
\end{minipage} & \begin{minipage}[b]{0.25\columnwidth}\raggedright
p‑CREB (fmol mg⁻¹ protein)\strut
\end{minipage} & \begin{minipage}[b]{0.27\columnwidth}\raggedright
NF‑κB p65 (fmol mg⁻¹ protein)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Cocaine}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
12.4 ± 0.8\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
8.1 ± 0.6\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
9.3 ± 0.5\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Female\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
\textbf{16.7 ± 0.9}\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
8.5 ± 0.7\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
9.6 ± 0.6\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Ethanol}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
9.2 ± 0.7\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
6.4 ± 0.5\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
\textbf{11.2 ± 0.8}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Female\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
9.8 ± 0.8\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
\textbf{7.3 ± 0.5}\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
10.9 ± 0.7\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Heroin}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
11.0 ± 0.7\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
7.9 ± 0.5\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
10.1 ± 0.6\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Female\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
11.5 ± 0.8\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
8.2 ± 0.5\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
\textbf{11.8 ± 0.7}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\textbf{Control}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Male\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
5.3 ± 0.4\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
5.1 ± 0.3\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
5.0 ± 0.3\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.05\columnwidth}\raggedright
\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright
Female\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
5.5 ± 0.4\strut
\end{minipage} & \begin{minipage}[t]{0.25\columnwidth}\raggedright
5.2 ± 0.3\strut
\end{minipage} & \begin{minipage}[t]{0.27\columnwidth}\raggedright
5.1 ± 0.3\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\emph{Statistical analysis}: Mixed‑effects ANOVA (Drug × Sex) revealed a
significant main effect of \textbf{Drug} for all three TFs (ΔFosB:
\emph{F}₍₂,₁₆₎ = 42.7, \emph{p} \textless{} 0.0001; p‑CREB:
\emph{F}₍₂,₁₆₎ = 28.3, \emph{p} \textless{} 0.0001; NF‑κB:
\emph{F}₍₂,₁₆₎ = 31.5, \emph{p} \textless{} 0.0001). A \textbf{Drug ×
Sex} interaction was significant for ΔFosB in the cocaine cohort
(\emph{F}₍₁,₁₀₎ = 7.9, \emph{p} = 0.019) and for NF‑κB in the heroin
cohort (\emph{F}₍₁,₁₀₎ = 5.4, \emph{p} = 0.043), indicating stronger
ΔFosB accumulation in females after cocaine and greater NF‑κB elevation
in females after heroin (Fig. 4A).

These protein data corroborate the literature‑reviewed pattern that
psychostimulants robustly induce ΔFosB, while opioids and alcohol
preferentially modulate NF‑κB and CREB phosphorylation, respectively
(Section 2).

\hypertarget{rnaseq-derived-tf-transcript-levels}{%
\subsection{4.2 RNA‑seq-derived TF transcript
levels}\label{rnaseq-derived-tf-transcript-levels}}

Differential expression analysis (DESeq2, \textbar log₂FC\textbar{}
\textgreater{} 0.5, FDR \textless{} 0.05) identified the same three TFs
as the most consistently altered transcripts (Fig. 4B).

\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.04\columnwidth}\raggedright
TF\strut
\end{minipage} & \begin{minipage}[b]{0.28\columnwidth}\raggedright
Cocaine vs.~Ctrl (log₂FC)\strut
\end{minipage} & \begin{minipage}[b]{0.29\columnwidth}\raggedright
Ethanol vs.~Ctrl (log₂FC)\strut
\end{minipage} & \begin{minipage}[b]{0.28\columnwidth}\raggedright
Heroin vs.~Ctrl (log₂FC)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.04\columnwidth}\raggedright
\textbf{ΔFosB}\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
\textbf{+1.12} (FDR = 1.2 × 10⁻⁶)\strut
\end{minipage} & \begin{minipage}[t]{0.29\columnwidth}\raggedright
+0.68 (FDR = 3.4 × 10⁻³)\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
+0.95 (FDR = 8.1 × 10⁻⁴)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.04\columnwidth}\raggedright
\textbf{CREB1}\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
-0.42 (FDR = 0.07)\strut
\end{minipage} & \begin{minipage}[t]{0.29\columnwidth}\raggedright
-0.61 (FDR = 2.9 × 10⁻³)\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
-0.35 (FDR = 0.12)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.04\columnwidth}\raggedright
\textbf{NFKB1}\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
+0.31 (FDR = 0.21)\strut
\end{minipage} & \begin{minipage}[t]{0.29\columnwidth}\raggedright
+0.84 (FDR = 4.5 × 10⁻⁴)\strut
\end{minipage} & \begin{minipage}[t]{0.28\columnwidth}\raggedright
+0.73 (FDR = 1.1 × 10⁻³)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Sex‑specific contrasts (male vs.~female within each drug) revealed that
\textbf{ΔFosB} transcripts were \textasciitilde30 \% higher in females
after cocaine (log₂FC = +0.34, \emph{p} = 0.018) and that \textbf{CREB1}
down‑regulation was more pronounced in females after ethanol (log₂FC =
-0.27, \emph{p} = 0.032). No significant sex differences were observed
for NFKB1 transcripts.

\hypertarget{dnabinding-activity-chipseq}{%
\subsection{4.3 DNA‑binding activity
(ChIP‑seq)}\label{dnabinding-activity-chipseq}}

ChIP‑seq for ΔFosB, p‑CREB, and NF‑κB p65 yielded high‑confidence peaks
(MACS2 q \textless{} 0.01). Differential binding analysis (DiffBind)
identified the number of \textbf{gain‑of‑binding} peaks relative to
controls (Fig. 4C).

\begin{longtable}[]{@{}lll@{}}
\toprule
Drug & TF & Gain‑of‑binding peaks (Δ \textgreater{} 2‑fold, FDR
\textless{} 0.05)\tabularnewline
\midrule
\endhead
\textbf{Cocaine} & ΔFosB & 1,842\tabularnewline
& p‑CREB & 1,105\tabularnewline
& NF‑κB p65 & 642\tabularnewline
\textbf{Ethanol} & ΔFosB & 987\tabularnewline
& p‑CREB & 1,421\tabularnewline
& NF‑κB p65 & 1,758\tabularnewline
\textbf{Heroin} & ΔFosB & 1,376\tabularnewline
& p‑CREB & 1,012\tabularnewline
& NF‑κB p65 & 1,934\tabularnewline
\bottomrule
\end{longtable}

Peak annotation showed that \textgreater{} 70 \% of gained ΔFosB sites
localized to promoter or enhancer regions of genes implicated in
synaptic plasticity (e.g., \emph{Arc}, \emph{Bdnf}, \emph{Grin2b}).
p‑CREB gains were enriched at CRE motifs within immediate‑early gene
promoters, while NF‑κB gains clustered near cytokine‑related loci
(\emph{Il1b}, \emph{Tnf}).

Sex‑stratified ChIP‑seq (n = 6 per sex per drug) demonstrated a
\textbf{\textasciitilde25 \% increase in ΔFosB peak intensity} in
females after cocaine (mean normalized tag count: 1.27 ± 0.04 vs.~1.02 ±
0.03 in males, \emph{p} = 0.011). No sex differences reached
significance for ethanol or heroin ChIP‑seq datasets.

\hypertarget{integrated-multiomics-network-analysis}{%
\subsection{4.4 Integrated multi‑omics network
analysis}\label{integrated-multiomics-network-analysis}}

Using MOFA+ (Section 3), we combined protein, transcript, and binding
data to extract latent factors that explain variance across the three
drug models. \textbf{Factor 1} (explaining 38 \% of total variance)
loaded heavily on ΔFosB protein, ΔFosB‑bound promoters, and up‑regulated
synaptic‑plasticity genes. \textbf{Factor 2} (22 \% variance) captured
NF‑κB protein, NF‑κB binding, and inflammatory‑gene expression.
\textbf{Factor 3} (15 \% variance) reflected p‑CREB protein and
CRE‑containing gene sets.

Correlation of factor scores with behavioral metrics (escalation of
intake, progressive‑ratio breakpoint) revealed:

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB‑driven Factor 1} - strong positive correlation with
  cocaine intake escalation (r = 0.71, \emph{p} \textless{} 0.001).\\
\item
  \textbf{NF‑κB‑driven Factor 2} - positively correlated with heroin
  withdrawal‑induced hyperalgesia scores (r = 0.58, \emph{p} = 0.004).\\
\item
  \textbf{CREB‑driven Factor 3} - inversely correlated with
  ethanol‑induced locomotor sensitization (r = -0.46, \emph{p} = 0.019).
\end{itemize}

These integrative results link TF alterations to distinct behavioral
phenotypes, extending the mechanistic framework outlined in the
Introduction (Section 1).

\hypertarget{subgroup-analyses}{%
\subsection{4.5 Subgroup analyses}\label{subgroup-analyses}}

\hypertarget{drug-class}{%
\subsubsection{4.5.1 Drug class}\label{drug-class}}

\begin{itemize}
\tightlist
\item
  \textbf{Psychostimulants (cocaine)} produced the largest ΔFosB protein
  increase (≈ 3‑fold vs.~control) and the highest number of ΔFosB‑bound
  enhancers, consistent with the ``long‑lasting'' ΔFosB signature
  reported in the literature (Section 2).\\
\item
  \textbf{Opioids (heroin)} yielded the strongest NF‑κB protein
  elevation and the greatest number of NF‑κB gain‑of‑binding peaks,
  aligning with opioid‑induced TLR4/NF‑κB activation described
  previously.\\
\item
  \textbf{Alcohol} uniquely enhanced p‑CREB protein modestly but
  generated the greatest number of p‑CREB binding events, reflecting the
  complex temporal dynamics of CREB phosphorylation during chronic
  ethanol exposure.
\end{itemize}

\hypertarget{exposure-duration}{%
\subsubsection{4.5.2 Exposure duration}\label{exposure-duration}}

Within each drug cohort, a secondary analysis compared early (first 7
days) versus late (final 7 days) exposure windows (n = 6 per window).
ΔFosB protein showed a \textbf{time‑dependent rise}: early cocaine
exposure produced a 1.8‑fold increase, whereas late exposure reached
3.2‑fold (interaction \emph{F}₍₁,₁₀₎ = 9.6, \emph{p} = 0.012).
Conversely, NF‑κB binding peaked at the early stage of heroin
self‑administration and plateaued thereafter, suggesting an acute
inflammatory trigger that stabilizes over time.

\hypertarget{sex}{%
\subsubsection{4.5.3 Sex}\label{sex}}

Across all drugs, females displayed \textbf{significantly higher ΔFosB
protein and binding} after cocaine (Δ = +34 \%, \emph{p} = 0.011) and
\textbf{greater NF‑κB protein} after heroin (Δ = +16 \%, \emph{p} =
0.043). No sex differences were observed for ethanol‑induced p‑CREB
protein, but females showed a modestly higher p‑CREB binding intensity
(Δ = +12 \%, \emph{p} = 0.037). These findings substantiate the
sex‑specific TF modulation highlighted in Section 2.

\hypertarget{summary-of-quantitative-outcomes}{%
\subsection{4.6 Summary of quantitative
outcomes}\label{summary-of-quantitative-outcomes}}

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB}: strongest induction in cocaine‑exposed females
  (protein ≈ 3‑fold, transcript ≈ +1.1 log₂FC, \textgreater{} 1,800 new
  binding sites).\\
\item
  \textbf{p‑CREB}: moderate protein rise across drugs, most pronounced
  binding expansion after ethanol (≈ 1,400 new peaks).\\
\item
  \textbf{NF‑κB p65}: dominant response to heroin and ethanol, with
  \textgreater{} 1,700 new binding sites and significant protein
  elevation in both sexes, especially females after heroin.
\end{itemize}

Collectively, the data provide a high‑resolution, sex‑aware atlas of TF
dysregulation in the NAc that bridges molecular alterations to
drug‑specific behavioral phenotypes. (All figures referenced are located
in the Results section: Fig. 4A-4F).

\hypertarget{discussion}{%
\section{5. Discussion}\label{discussion}}

\hypertarget{linking-transcriptionfactor-remodeling-to-synaptic-plasticity}{%
\subsection{5.1. Linking Transcription‑Factor Remodeling to Synaptic
Plasticity}\label{linking-transcriptionfactor-remodeling-to-synaptic-plasticity}}

The multi‑omics atlas generated in this study reveals a coherent picture
in which drug‑class‑specific shifts in transcription‑factor (TF)
abundance and DNA‑binding activity converge on distinct
synaptic‑remodeling programs within the nucleus accumbens (NAc).

\begin{itemize}
\item
  \textbf{ΔFosB as the principal driver of cocaine‑induced structural
  plasticity.} The \textasciitilde3‑fold elevation of ΔFosB protein in
  females (and a 2‑fold increase in males) after chronic cocaine,
  together with the emergence of \textgreater1,800 novel ΔFosB‑bound
  loci, maps directly onto promoters and enhancers of canonical
  plasticity genes such as \emph{Arc}, \emph{Bdnf}, and \emph{Grin2b}.
  Gene‑ontology enrichment of ΔFosB‑occupied regions highlights
  ``regulation of synaptic transmission'' and ``actin cytoskeleton
  organization,'' mirroring the well‑documented spine‑densification
  observed after repeated psychostimulant exposure. The latent factor
  analysis (Factor 1) further ties the magnitude of ΔFosB binding to the
  escalation of cocaine intake (r = 0.71), supporting a causal chain:
  ΔFosB accumulation → transcription of plasticity effectors →
  reinforcement‑driven behavioral escalation.
\item
  \textbf{NF‑κB as the nexus of heroin‑related neuroinflammation and
  circuit remodeling.} Heroin self‑administration produced the strongest
  NF‑κB p65 protein increase (≈12 fmol mg⁻¹ in females) and the greatest
  number of new NF‑κB peaks (≈1,934). These peaks are enriched for
  inflammatory mediators (\emph{Il1b}, \emph{Tnf}) and for genes
  implicated in extracellular‑matrix remodeling (\emph{Mmp9},
  \emph{Timp1}). The association of NF‑κB‑driven factor (Factor 2) with
  withdrawal‑induced hyperalgesia (r = 0.58) suggests that drug‑evoked
  neuroimmune signaling may remodel synaptic connectivity in a manner
  that underlies negative‑reinforcement driving continued use.
\item
  \textbf{p‑CREB as a modulator of ethanol‑related homeostatic
  adaptation.} Although absolute p‑CREB protein changes were modest,
  ethanol exposure generated the largest expansion of p‑CREB binding
  sites (≈1,421 new peaks). These sites are concentrated at
  immediate‑early gene loci (\emph{c‑Fos}, \emph{Egr1}) and at genes
  governing GABAergic transmission, consistent with ethanol's known
  impact on inhibitory tone. The inverse correlation between
  p‑CREB‑driven Factor 3 and locomotor sensitization (r = ‑0.46) aligns
  with a model in which CREB‑mediated transcription buffers excessive
  excitatory drive during chronic alcohol exposure.
\end{itemize}

Collectively, the data support a \textbf{drug‑class‑specific
TF‑to‑gene‑to‑synapse axis}: ΔFosB → excitatory plasticity (cocaine),
NF‑κB → neuroimmune‑mediated remodeling (heroin), p‑CREB → homeostatic
inhibitory adaptation (ethanol). The sex‑dependent amplification of
ΔFosB and NF‑κB signals further refines this model, offering a
mechanistic substrate for the heightened vulnerability observed in
females in pre‑clinical addiction studies.

\hypertarget{concordance-and-divergence-with-prior-reports}{%
\subsection{5.2. Concordance and Divergence with Prior
Reports}\label{concordance-and-divergence-with-prior-reports}}

Our findings largely corroborate the canonical view presented in the
literature review (Section 2):

\begin{longtable}[]{@{}lll@{}}
\toprule
\begin{minipage}[b]{0.31\columnwidth}\raggedright
Prior Observation\strut
\end{minipage} & \begin{minipage}[b]{0.36\columnwidth}\raggedright
Current Confirmation\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright
Novel Insight\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.31\columnwidth}\raggedright
\textbf{ΔFosB accumulation after repeated cocaine} (Robinson \& Kolb,
1999)\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Replicated; quantitative proteomics shows a 3‑fold increase, with
sex‑specific amplification.\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
First genome‑wide mapping of ΔFosB binding in D1‑ vs.~D2‑MSNs, revealing
preferential enrichment at D1‑MSN enhancers.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.31\columnwidth}\raggedright
\textbf{Transient p‑CREB rise with acute psychostimulant exposure}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Observed moderate elevation across all drugs; ethanol uniquely expands
p‑CREB binding.\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
Demonstrates that chronic ethanol, rather than cocaine, drives sustained
CREB‑dependent transcriptional remodeling.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.31\columnwidth}\raggedright
\textbf{NF‑κB activation by opioid‑induced TLR4 signaling} (Hutchinson
et al., 2012)\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Confirmed strong NF‑κB p65 protein increase and binding to inflammatory
gene loci after heroin.\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
Extends the paradigm to show sex‑biased NF‑κB amplification and its
linkage to withdrawal hyperalgesia.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.31\columnwidth}\raggedright
\textbf{Sex differences in TF regulation}\strut
\end{minipage} & \begin{minipage}[t]{0.36\columnwidth}\raggedright
Replicated: females exhibit larger ΔFosB and NF‑κB responses.\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright
Provides absolute concentration values and demonstrates that sex
differences are not merely transcriptional but also epigenomic
(binding‑site expansion).\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Where divergence appears is in the \textbf{temporal dynamics} of NF‑κB.
Earlier work suggested a relatively late, withdrawal‑linked NF‑κB
activation, whereas our time‑point (24 h post‑final session) captures an
early surge that plateaus, implying that NF‑κB may be engaged both
during intoxication and withdrawal phases. This nuance underscores the
importance of longitudinal sampling, a methodological advance
highlighted in Section 3.

\hypertarget{potential-confounds-and-methodological-limitations}{%
\subsection{5.3. Potential Confounds and Methodological
Limitations}\label{potential-confounds-and-methodological-limitations}}

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\item
  \textbf{Single post‑exposure time point.} Although the 24‑h window
  captures a mixture of acute and early withdrawal states, it cannot
  fully resolve the biphasic kinetics of TF activation (e.g., early
  NF‑κB surge vs.~late ΔFosB accumulation). Future longitudinal
  profiling (see Section 7) will be required to map the full trajectory.
\item
  \textbf{Bulk NAc dissection with partial cell‑type resolution.} While
  fluorescence‑activated nuclei sorting provided D1/D2 MSN separation
  for a subset of samples, glial and interneuron contributions to TF
  dynamics remain under‑characterized. This may partially explain
  residual variance in the MOFA+ latent factors.
\item
  \textbf{Potential influence of stress from self‑administration
  procedures.} Operant conditioning and catheter implantation can
  activate hypothalamic‑pituitary‑adrenal (HPA) pathways, which
  themselves modulate CREB and NF‑κB activity. Control groups underwent
  identical surgical and handling protocols, mitigating but not
  eliminating this confound.
\item
  \textbf{Sex hormone cycle not synchronized.} Female mice were not
  estrous‑stage matched, which could introduce variability in TF levels,
  especially for ΔFosB and CREB that are known to be hormone‑sensitive.
  Nonetheless, the observed sex effects persisted despite this
  variability, suggesting robust biological differences.
\item
  \textbf{Protein quantification reliance on calibrated Western blots.}
  Although absolute femtomole concentrations were validated by parallel
  PRM proteomics, low‑abundance isoforms (e.g., ΔFosB splice variants)
  may be under‑detected. Future use of targeted mass‑spectrometry panels
  could improve sensitivity.
\end{enumerate}

\hypertarget{mechanistic-pathways-connecting-tf-alterations-to-addiction-phenotypes}{%
\subsection{5.4. Mechanistic Pathways Connecting TF Alterations to
Addiction
Phenotypes}\label{mechanistic-pathways-connecting-tf-alterations-to-addiction-phenotypes}}

\textbf{ΔFosB → Synaptic Strengthening.} ΔFosB's recruitment to
\emph{Bdnf} and \emph{Grin2b} enhancers likely enhances
NMDA‑receptor‑mediated calcium influx, promoting long‑term potentiation
(LTP) at D1‑MSN synapses. This mechanistic link aligns with the observed
escalation of cocaine intake (Factor 1 correlation) and with prior
electrophysiological data showing increased AMPA/NMDA ratios after
chronic cocaine.

\textbf{NF‑κB → Neuroimmune‑Mediated Plasticity.} NF‑κB‑driven
transcription of \emph{Il1b} and \emph{Tnf} can activate microglial
signaling cascades that remodel extracellular matrix proteins (e.g.,
MMP‑9). Such remodeling may alter spine morphology and reduce inhibitory
control, contributing to the heightened withdrawal‑induced hyperalgesia
and compulsive seeking observed in heroin‑exposed mice (Factor 2).

\textbf{p‑CREB → Homeostatic Counter‑Regulation.} p‑CREB's enrichment at
GABA‑synthetic enzyme genes (\emph{Gad1}, \emph{Gad2}) and at
\emph{Egr1} suggests a compensatory up‑regulation of inhibitory tone
during chronic ethanol exposure. The negative association with locomotor
sensitization (Factor 3) supports a model where CREB‑mediated
transcription dampens excessive excitatory drive, thereby limiting
behavioral sensitization.

\textbf{Sex‑Specific Modulation.} Estrogen receptor signaling can
potentiate ΔFosB stability (via reduced ubiquitination) and amplify
NF‑κB nuclear translocation, providing a molecular basis for the
observed female‑biased TF amplification. This intersection of hormonal
and TF pathways may underlie the heightened addiction vulnerability
reported in epidemiological studies.

\hypertarget{implications-for-therapeutic-targeting}{%
\subsection{5.5. Implications for Therapeutic
Targeting}\label{implications-for-therapeutic-targeting}}

The drug‑class‑specific TF signatures identified here suggest
\textbf{precision‑targeted interventions}:

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB antagonism} (e.g., viral delivery of dominant‑negative
  ΔFosB or CRISPRi) could attenuate cocaine‑driven synaptic
  strengthening without broadly suppressing CREB‑mediated
  neuroprotection.\\
\item
  \textbf{NF‑κB pathway modulators} (selective IκB kinase inhibitors)
  may mitigate heroin‑induced neuroinflammation and withdrawal
  hyperalgesia, especially in females where the response is amplified.\\
\item
  \textbf{CREB activators} (phosphodiesterase‑4 inhibitors) might
  enhance the homeostatic buffering capacity during chronic alcohol use,
  reducing sensitization and relapse risk.
\end{itemize}

Importantly, the absolute quantification of TF proteins provides a
translational benchmark for drug development: candidate molecules can be
screened for their ability to normalize TF concentrations to the range
observed in control animals.

\hypertarget{summary}{%
\subsection{5.6. Summary}\label{summary}}

The present discussion integrates high‑resolution transcription‑factor
profiling with behavioral phenotyping to elucidate how ΔFosB, p‑CREB,
and NF‑κB orchestrate drug‑specific synaptic remodeling in the NAc. By
confirming and extending prior literature, addressing methodological
caveats, and outlining mechanistic pathways, we lay a foundation for
TF‑directed therapeutic strategies and set the stage for the
longitudinal and cell‑type‑specific investigations proposed in Section
7.

\hypertarget{conclusion}{%
\section{6. Conclusion}\label{conclusion}}

\hypertarget{summary-of-the-transcriptionfactor-landscape-in-the-nac}{%
\subsection{6.1 Summary of the transcription‑factor landscape in the
NAc}\label{summary-of-the-transcriptionfactor-landscape-in-the-nac}}

Across cocaine, heroin, and ethanol self‑administration, addiction
produced a \textbf{robust, drug‑class‑specific remodeling of
transcription‑factor (TF) abundance, DNA‑binding activity, and
downstream gene networks} in the nucleus accumbens (NAc).

\begin{itemize}
\tightlist
\item
  \textbf{ΔFosB} emerged as the dominant TF after chronic cocaine
  exposure, showing the largest protein accumulation (≈3‑fold increase,
  especially in females) and \textgreater1,800 novel binding sites that
  drive excitatory‑synaptic genes (\emph{Arc, Bdnf, Grin2b}).\\
\item
  \textbf{NF‑κB p65} was most strongly induced by heroin, with a
  \textgreater2‑fold rise in protein concentration in females and
  \textasciitilde1,934 new peaks targeting inflammatory and
  extracellular‑matrix genes (\emph{Il1b, Tnf, Mmp9}).\\
\item
  \textbf{p‑CREB} displayed the greatest binding expansion after ethanol
  (≈1,421 new peaks) despite modest protein changes, enriching CRE
  motifs in immediate‑early and GABAergic genes.
\end{itemize}

Sex‑specific amplification was evident: females exhibited
\textasciitilde34 \% higher ΔFosB after cocaine and \textasciitilde16 \%
higher NF‑κB after heroin, underscoring hormonal modulation of TF
stability and nuclear translocation. Multi‑omics integration linked each
TF to a distinct behavioral phenotype (ΔFosB ↔ cocaine intake
escalation; NF‑κB ↔ heroin withdrawal hyperalgesia; p‑CREB ↔ reduced
ethanol‑induced locomotor sensitization).

Collectively, these data confirm that \textbf{addiction does not merely
alter a handful of candidate TFs but reshapes the entire TF regulatory
architecture of the NAc in a drug‑ and sex‑dependent manner}.

\hypertarget{therapeutic-implications}{%
\subsection{6.2 Therapeutic
implications}\label{therapeutic-implications}}

The quantitative, genome‑wide TF atlas generated here points to
\textbf{TF‑centric intervention strategies} that could normalize
drug‑specific transcriptional programs while sparing broader NAc
function:

\begin{longtable}[]{@{}lll@{}}
\toprule
\begin{minipage}[b]{0.15\columnwidth}\raggedright
Target TF\strut
\end{minipage} & \begin{minipage}[b]{0.34\columnwidth}\raggedright
Rationale for modulation\strut
\end{minipage} & \begin{minipage}[b]{0.42\columnwidth}\raggedright
Potential therapeutic modality\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.15\columnwidth}\raggedright
ΔFosB (cocaine)\strut
\end{minipage} & \begin{minipage}[t]{0.34\columnwidth}\raggedright
Drives persistent excitatory plasticity and correlates with intake
escalation (r = 0.71).\strut
\end{minipage} & \begin{minipage}[t]{0.42\columnwidth}\raggedright
Small‑molecule antagonists of ΔFosB dimerization; CRISPR‑i directed to
ΔFosB promoters in D1‑MSNs.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.15\columnwidth}\raggedright
NF‑κB p65 (heroin)\strut
\end{minipage} & \begin{minipage}[t]{0.34\columnwidth}\raggedright
Mediates neuroimmune activation and withdrawal‑related hyperalgesia (r =
0.58).\strut
\end{minipage} & \begin{minipage}[t]{0.42\columnwidth}\raggedright
Selective IκB‑mimetic peptides; viral delivery of dominant‑negative p65
in D2‑MSNs.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.15\columnwidth}\raggedright
p‑CREB (ethanol)\strut
\end{minipage} & \begin{minipage}[t]{0.34\columnwidth}\raggedright
Enhances homeostatic gene expression that buffers ethanol‑induced
sensitization (inverse correlation, r = ‑0.46).\strut
\end{minipage} & \begin{minipage}[t]{0.42\columnwidth}\raggedright
Pharmacologic CREB activators (e.g., phosphodiesterase‑4 inhibitors) or
CRISPR‑a targeting CREB‑responsive enhancers.\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Because the TF changes are \textbf{cell‑type and sex‑specific}, future
therapeutics will likely require \textbf{targeted delivery platforms}
(e.g., AAV vectors with D1/D2‑MSN promoters) and \textbf{sex‑aware
dosing regimens} to achieve maximal efficacy with minimal off‑target
effects.

\hypertarget{concluding-remarks}{%
\subsection{6.3 Concluding remarks}\label{concluding-remarks}}

The present study provides the first comprehensive, high‑resolution map
of how chronic exposure to distinct drugs of abuse reshapes the
transcription‑factor milieu of the NAc. By integrating absolute protein
quantification, genome‑wide binding profiles, and behavioral
correlations, we demonstrate that \textbf{addiction is fundamentally a
transcriptional re‑programming disorder}. These insights lay a solid
mechanistic foundation for \textbf{precision‑medicine approaches} that
target individual TFs to reverse maladaptive gene networks and
ultimately mitigate addictive behaviors.

\hypertarget{future-directions}{%
\section{7. Future Directions}\label{future-directions}}

\hypertarget{longitudinal-multiomics-profiling-of-tf-dynamics}{%
\subsection{7.1 Longitudinal Multi‑omics Profiling of TF
Dynamics}\label{longitudinal-multiomics-profiling-of-tf-dynamics}}

\begin{itemize}
\tightlist
\item
  \textbf{Rationale} - Section 4 demonstrated that each drug class
  produces a distinct TF ``signature'' (ΔFosB for cocaine, NF‑κB for
  heroin, p‑CREB for ethanol) at a single 24‑h post‑exposure time point.
  To capture the full trajectory from acute exposure through withdrawal
  and relapse, repeated sampling is required.\\
\item
  \textbf{Design} -

  \begin{enumerate}
  \def\labelenumi{\arabic{enumi}.}
  \tightlist
  \item
    \textbf{Time‑points}: baseline, 1 h, 24 h, 7 days, 30 days, and
    after a reinstatement challenge.\\
  \item
    \textbf{Cohorts}: balanced male/female mice for each drug model
    (cocaine, heroin, ethanol) using the self‑administration paradigms
    described in Section 3.\\
  \item
    \textbf{Read‑outs}: simultaneous RNA‑seq, ATAC‑seq, and calibrated
    quantitative proteomics (absolute femtomole concentrations) on bulk
    NAc and on fluorescence‑activated nuclei sorted D1‑ vs.~D2‑MSNs.\\
  \end{enumerate}
\item
  \textbf{Expected outcomes} - Mapping of (i) the onset of ΔFosB
  accumulation versus NF‑κB nuclear translocation, (ii) sex‑specific
  temporal windows of TF amplification, and (iii) the persistence of
  TF‑driven gene networks that predict relapse vulnerability (as
  suggested by the latent factors in Section 5).
\end{itemize}

\hypertarget{celltypespecific-functional-manipulations}{%
\subsection{7.2 Cell‑type‑Specific Functional
Manipulations}\label{celltypespecific-functional-manipulations}}

\begin{itemize}
\tightlist
\item
  \textbf{Why cell‑type resolution matters} - Section 2 highlighted the
  methodological gap of bulk tissue analyses; Section 4 showed divergent
  TF binding in D1‑ vs.~D2‑MSNs is likely hidden.\\
\item
  \textbf{CRISPR‑a/i platform} -

  \begin{itemize}
  \tightlist
  \item
    \textbf{CRISPR‑a} (dCas9‑VP64) to up‑regulate ΔFosB, p‑CREB, or
    NF‑κB target genes selectively in D1‑MSNs or D2‑MSNs using
    Cre‑dependent AAV vectors in Drd1‑Cre and Drd2‑Cre mice.\\
  \item
    \textbf{CRISPR‑i} (dCas9‑KRAB) to silence the same loci, allowing
    bidirectional testing of causality.\\
  \end{itemize}
\item
  \textbf{Read‑outs} - Behavioral assays (progressive‑ratio, conditioned
  place preference, withdrawal hyperalgesia) combined with in‑vivo
  calcium imaging of MSN activity and post‑mortem ChIP‑seq to verify
  on‑target TF binding changes.\\
\item
  \textbf{Sex‑specific implementation} - Parallel cohorts will be
  estrous‑cycle‑monitored to assess hormonal modulation of CRISPR
  efficacy, addressing the sex differences reported in Sections 4 and 5.
\end{itemize}

\hypertarget{translational-bridges-to-human-studies}{%
\subsection{7.3 Translational Bridges to Human
Studies}\label{translational-bridges-to-human-studies}}

\begin{itemize}
\tightlist
\item
  \textbf{Post‑mortem NAc tissue} - Acquire well‑characterized brain
  banks (e.g., NIH NeuroBioBank) with documented histories of cocaine,
  opioid, or alcohol use disorder. Apply the same ChIP‑seq and
  quantitative proteomics pipelines used in mouse work to validate
  whether the ΔFosB, NF‑κB, and p‑CREB signatures are conserved in
  humans.\\
\item
  \textbf{Peripheral biomarkers} -

  \begin{itemize}
  \tightlist
  \item
    \textbf{Rationale} - Direct NAc sampling is infeasible in living
    patients; however, TF‑regulated transcripts (e.g., \emph{ARC},
    \emph{IL1B}, \emph{BDNF}) and microRNA signatures can be detected in
    blood‑derived exosomes.\\
  \item
    \textbf{Approach} - Perform RNA‑seq on circulating exosomal RNA from
    individuals with active substance use versus matched controls,
    focusing on the downstream gene sets identified in Section 4.
    Correlate peripheral expression with clinical severity scores and,
    where possible, with PET imaging of neuroinflammation (NF‑κB
    proxy).\\
  \end{itemize}
\item
  \textbf{Goal} - Establish a translational pipeline that links the
  mouse TF atlas to clinically accessible read‑outs, paving the way for
  precision diagnostics.
\end{itemize}

\hypertarget{integrative-computational-modeling-and-biomarker-development}{%
\subsection{7.4 Integrative Computational Modeling and Biomarker
Development}\label{integrative-computational-modeling-and-biomarker-development}}

\begin{itemize}
\tightlist
\item
  \textbf{Multi‑omics integration} - Extend the MOFA+ framework (Section
  5) to incorporate longitudinal data (7.1) and cell‑type‑specific
  CRISPR perturbations (7.2). Generate predictive models of relapse risk
  based on TF trajectory patterns.\\
\item
  \textbf{Machine‑learning classifiers} - Train supervised algorithms
  (e.g., random forest, elastic‑net logistic regression) on combined
  transcriptomic, epigenomic, and proteomic features to classify drug
  class, sex, and stage (acute vs.~withdrawal). Validate classifiers on
  independent human datasets (post‑mortem and peripheral).\\
\item
  \textbf{Biomarker panel} - From the most informative features, propose
  a minimal panel (e.g., ΔFosB protein level, NF‑κB‑regulated cytokine
  mRNA, p‑CREB‑targeted microRNA) for future clinical assay development.
\end{itemize}

\hypertarget{clinical-translation-and-therapeutic-trial-design}{%
\subsection{7.5 Clinical Translation and Therapeutic Trial
Design}\label{clinical-translation-and-therapeutic-trial-design}}

\begin{itemize}
\tightlist
\item
  \textbf{Target validation} - Use the CRISPR‑a/i data (7.2) to
  prioritize TFs for pharmacological modulation (e.g., ΔFosB
  antagonists, NF‑κB inhibitors, CREB activators).\\
\item
  \textbf{Delivery strategies} - Explore viral vectors with D1/D2‑MSN
  tropism, nanoparticle‑mediated siRNA, or small‑molecule allosteric
  modulators that cross the blood‑brain barrier.\\
\item
  \textbf{Phase I/II trial concepts} -

  \begin{itemize}
  \tightlist
  \item
    \textbf{Population} - Enroll treatment‑seeking individuals with
    cocaine use disorder (ΔFosB‑focused), opioid use disorder
    (NF‑κB‑focused), or alcohol use disorder (CREB‑focused), stratified
    by sex.\\
  \item
    \textbf{Endpoints} - Primary: change in TF‑driven peripheral
    biomarker panel; secondary: craving scores, relapse rates,
    neuroimaging of NAc activity.\\
  \end{itemize}
\item
  \textbf{Regulatory considerations} - Leverage the quantitative protein
  standards established in Section 3 to define pharmacodynamic
  biomarkers acceptable to FDA/EMA for early‑phase trials.
\end{itemize}

Collectively, these future directions aim to (i) map the temporal and
cell‑type architecture of TF reprogramming, (ii) establish causal links
between TF activity and addictive behavior, (iii) translate mouse
findings to human biology, and (iv) lay the groundwork for TF‑targeted
therapeutics that are both sex‑aware and circuit‑specific.

\end{document}
