Change in resting state functional connectivity following working memory training in individuals with repetitive negative thinking.

BACKGROUND: Repetitive negative thinking (RNT) symptoms, which are characterized by pervasive, uncontrollable negative thoughts, are common in individuals with mood, anxiety, and traumatic stress disorders. Inability to regulate the contents of working memory is a hypothesized etiological factor in RNT, suggesting that training to improve working memory may be beneficial. This study examined the effects of working memory training on resting state functional connectivity (rsFC) in individuals with elevated RNT and whether such changes would be associated with clinical improvement. METHODS: We conducted a secondary analysis of pre-post resting state data collected as part of a randomized controlled trial [NCT04912089] of working memory training interventions (n=42) compared to a waitlist control group (n=23). We hypothesized that individuals completing training would show increased rsFC between the two key intrinsic connectivity networks - default mode network (posterior cingulate cortex; PCC) and frontoparietal network (dorsolateral prefrontal cortex; dlPFC). We explored whether magnitude of rsFC change was associated with change in RNT symptom severity. RESULTS: rsFC increased between the PCC and regions including frontal and parietal cortex in the training group relative to waitlist. Increased connectivity between the PCC and superior frontal cortex was associated with RNT symptom reduction. CONCLUSIONS: These data provide evidence that working memory training can modulate neural circuitry at rest in individuals with RNT. Results align with accounts of working memory training effects on large-scale neurocircuitry changes and suggest that these changes may contribute to clinical promise of this type of intervention on transdiagnostic RNT symptoms.

Motivational context and neurocomputation of stop expectation moderate early attention responses supporting proactive inhibitory control.

Alterations in attention to cues signaling the need for inhibitory control play a significant role in a wide range of psychopathology. However, the degree to which motivational and attentional factors shape the neurocomputations of proactive inhibitory control remains poorly understood. The present study investigated how variation in monetary incentive valence and stake modulate the neurocomputational signatures of proactive inhibitory control. Adults (N = 46) completed a Stop-Signal Task (SST) with concurrent EEG recording under four conditions associated with stop performance feedback: low and high punishment (following unsuccessful stops) and low and high reward (following successful stops). A Bayesian learning model was used to infer individual's probabilistic expectations of the need to stop on each trial: P(stop). Linear mixed effects models were used to examine whether interactions between motivational valence, stake, and P(stop) parameters predicted P1 and N1 attention-related event-related potentials (ERPs) time-locked to the go-onset stimulus. We found that P1 amplitudes increased at higher levels of P(stop) in punished but not rewarded conditions, although P1 amplitude differences between punished and rewarded blocks were maximal on trials when the need to inhibit was least expected. N1 amplitudes were positively related to P(stop) in the high punishment condition (low N1 amplitude), but negatively related to P(stop) in the high reward condition (high N1 amplitude). Critically, high P(stop)-related N1 amplitude to the go-stimulus predicted behavioral stop success during the high reward block, providing evidence for the role of motivationally relevant context and inhibitory control expectations in modulating the proactive allocation of attentional resources that affect inhibitory control. These findings provide novel insights into the neurocomputational mechanisms underlying proactive inhibitory control under valence-dependent motivational contexts, setting the stage for developing motivation-based interventions that boost inhibitory control.

Exploring the effects of fitbit incentive on treatment outcomes in veterans undergoing intensive pain rehabilitation program.

OBJECTIVE: This study compares clinical pain outcomes between patients in a pain treatment program that received a Fitbit, to patients that did not. We also explored: (1) cognitive, emotional, and psychological factors that may have impacted the decision to opt in to receiving a Fitbit; and (2) whether the choice to receive a Fitbit impacted changes in cognitive, emotional, and psychological factors following treatment. METHODS: Among 58 patients in a multidisciplinary pain treatment program at a Veterans Affairs Healthcare System hospital, 31 patients opted to receive a Fitbit as adjunct treatment, while 27 did not. This study utilized patient-reported and practitioner-collected data from the pain treatment program. RESULTS: Compared to the non-Fitbit group, the Fitbit group displayed a significant decrease in average pain intensity, however showed no correlation between Fitbit activity and average pain intensity. Additionally, treatment satisfaction was the only predictor of treatment group, when modeling pre- and post-treatment outcomes changes. CONCLUSION: The implementation of a Fitbit may lead to improved pain intensity. Initial evidence suggests that opting to receive a Fitbit during a pain treatment program indicates treatment engagement leading to greater treatment satisfaction. Future work is needed to verify and expand upon this potential mechanism.

Identification of group differences in predictive anticipatory biasing of pain during uncertainty: preparing for the worst but hoping for the best.

ABSTRACT: Pain anticipation during conditions of uncertainty can unveil intrinsic biases, and understanding these biases can guide pain treatment interventions. This study used machine learning and functional magnetic resonance imaging to predict anticipatory responses in a pain anticipation experiment. One hundred forty-seven participants that included healthy controls (n = 57) and individuals with current and/or past mental health diagnosis (n = 90) received cues indicating upcoming pain stimuli: 2 cues predicted high and low temperatures, while a third cue introduced uncertainty. Accurate differentiation of neural patterns associated with specific anticipatory conditions was observed, involving activation in the anterior short gyrus of the insula and the nucleus accumbens. Three distinct response profiles emerged: subjects with a negative bias towards high pain anticipation, those with a positive bias towards low pain anticipation, and individuals whose predictions during uncertainty were unbiased. These profiles remained stable over one year, were consistent across diagnosed psychopathologies, and correlated with cognitive coping styles and underlying insula anatomy. The findings suggest that individualized and stable pain anticipation occurs in uncertain conditions.

Endocrine islet ß-cell subtypes with differential function are derived from biochemically distinct embryonic endocrine islet progenitors that are regulated by maternal nutrients.

Endocrine islet b cells comprise heterogenous cell subsets. Yet when/how these subsets are produced and how stable they are remain unknown. Addressing these questions is important for preventing/curing diabetes, because lower numbers of b cells with better secretory function is a high risk of this disease. Using combinatorial cell lineage tracing, scRNA-seq, and DNA methylation analysis, we show here that embryonic islet progenitors with distinct gene expression and DNA methylation produce b-cell subtypes of different function and viability in adult mice. The subtype with better function is enriched for genes involved in vesicular production/trafficking, stress response, and Ca2+-secretion coupling, which further correspond to differential DNA methylation in putative enhancers of these genes. Maternal overnutrition, a major diabetes risk factor, reduces the proportion of endocrine progenitors of the b-cell subtype with better-function via deregulating DNA methyl transferase 3a. Intriguingly, the gene signature that defines mouse b-cell subtypes can reliably divide human cells into two sub-populations while the proportion of b cells with better-function is reduced in diabetic donors. The implication of these results is that modulating DNA methylation in islet progenitors using maternal food supplements can be explored to improve b-cell function in the prevention and therapy of diabetes.

Amplification of Positivity Treatment for Anxiety and Depression: A Randomized Experimental Therapeutics Trial Targeting Social Reward Sensitivity to Enhance Social Connectedness.

BACKGROUND: Social disconnection is common and causes significant impairment in anxiety and depressive disorders, and it does not respond sufficiently to available treatments. The positive valence system supports social bond formation and maintenance but is often hyporesponsive in people with anxiety or depression. We conducted an experimental therapeutics trial to test the hypothesis that targeting positive valence processes through cognitive and behavioral strategies would enhance responsivity to social rewards, a core mechanism underlying social connectedness. METHODS: Sixty-eight adults who endorsed clinically elevated anxiety and/or depression with social impairment were randomized 1:1:1 to 5 (n = 23) or 10 (n = 22) sessions of amplification of positivity (AMP) treatment or waitlist (n = 23). Pre- to posttreatment change in striatal activity (primary outcome) during social reward anticipation was measured using functional magnetic resonance imaging, and reactivity to a social affiliation task (secondary) and self-reported social connectedness (exploratory) were examined. Primary analyses compared AMP (doses combined) versus waitlist. A second aim was to compare the effects of different doses. RESULTS: AMP engaged the hypothesized treatment target, leading to greater striatal activation during anticipation of social rewards versus waitlist (d = 1.01 [95% CI = 0.42-1.61]; largest striatal volume). AMP yielded larger improvements in positive affect and approach behavior during the affiliation task (but not other outcomes) and social connectedness. Larger striatal and social connectedness increases were observed for 5-session versus 10-session AMP (d range = 0.08-1.03). CONCLUSIONS: Teaching people with anxiety or depression strategies to increase positive thoughts, behaviors, and emotions enhances activity in brain regions that govern social reward processing and promotes social connectedness. Social reward sensitivity may be a transdiagnostic target for remediating social disconnection.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

A Specialized Epithelial Cell Type Regulating Mucosal Immunity and Driving Human Crohn's Disease.

Crohn's disease (CD) is a complex chronic inflammatory disorder that may affect any part of gastrointestinal tract with extra-intestinal manifestations and associated immune dysregulation. To characterize heterogeneity in CD, we profiled single-cell transcriptomics of 170 samples from 65 CD patients and 18 non-inflammatory bowel disease (IBD) controls in both the terminal ileum (TI) and ascending colon (AC). Analysis of 202,359 cells identified a novel epithelial cell type in both TI and AC, featuring high expression of LCN2, NOS2, and DUOX2, and thus is named LND. LND cells, confirmed by high-resolution in-situ RNA imaging, were rarely found in non-IBD controls, but expanded significantly in active CD. Compared to other epithelial cells, genes defining LND cells were enriched in antimicrobial response and immunoregulation. Moreover, multiplexed protein imaging demonstrated that LND cell abundance was associated with immune infiltration. Cross-talk between LND and immune cells was explored by ligand-receptor interactions and further evidenced by their spatial colocalization. LND cells showed significant enrichment of expression specificity of IBD/CD susceptibility genes, revealing its role in immunopathogenesis of CD. Investigating lineage relationships of epithelial cells detected two LND cell subpopulations with different origins and developmental potential, early and late LND. The ratio of the late to early LND cells was related to anti-TNF response. These findings emphasize the pathogenic role of the specialized LND cell type in both Crohn's ileitis and Crohn's colitis and identify novel biomarkers associated with disease activity and treatment response.

A contamination focused approach for optimizing the single-cell RNA-seq experiment.

Droplet-based single-cell RNA-seq (scRNA-seq) data are plagued by ambient contaminations caused by nucleic acid material released by dead and dying cells. This material is mixed into the buffer and is co-encapsulated with cells, leading to a lower signal-to-noise ratio. Although there exist computational methods to remove ambient contaminations post-hoc, the reliability of algorithms in generating high-quality data from low-quality sources remains uncertain. Here, we assess data quality before data filtering by a set of quantitative, contamination-based metrics that assess data quality more effectively than standard metrics. Through a series of controlled experiments, we report improvements that can minimize ambient contamination outside of tissue dissociation, via cell fixation, improved cell loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide end-users with insights on factors that can guide their decision-making regarding optimizations that minimize ambient contamination, and metrics to assess data quality.

Unsupervised learning for prognostic validity in patients with chronic pain in transdisciplinary pain care.

Chronic pain is not a singular disorder and presents in various forms and phenotypes. Here we show data from a cohort of patients seeking treatment in a transdisciplinary pain clinic. Patients completed a multidimensional patient-reported battery as part of routine initial evaluation at baseline and at each of the four subsequent visits over 1-year follow-up (0, 1, 3, 6, 12 months). The goal of this work was to use unsupervised modeling approach to identify whether patients with chronic pain undergoing transdisciplinary intensive rehabilitation treatment: (1) can be derived based upon self-reported outcome measures at baseline (or before treatment initiation), (2) are clinically validated based on their clinical diagnosis and medication use, and (3) differ in treatment trajectories over 1 year of transdisciplinary treatment. We applied unsupervised clustering on baseline outcomes using nine patient-reported symptoms and examined treatment trajectories. The three-cluster solution was internally validated. Psychiatric diagnosis, chronic back pain-related disability and symptoms severity determined cluster assignment and treatment prognosis. Conversely, clinical pain severity had lesser effect. Furthermore, clusters showed stability over time despite symptoms improvement. The accurate and meaningful subgrouping of the underlying chronic pain phenotypes would greatly enhance treatment and provide personalized and effective pain management.

State-specific alterations in the neural computations underlying inhibitory control in women remitted from bulimia nervosa.

The neurocomputational processes underlying bulimia nervosa and its primary symptoms, out-of-control overeating and purging, are poorly understood. Research suggests that the brains of healthy individuals form a dynamic internal model to predict whether control is needed in each moment. This study tested the hypothesis that this computational process of inhibitory control is abnormally affected by metabolic state (being fasted or fed) in bulimia nervosa. A Bayesian ideal observer model was fit to behavioral data acquired from 22 women remitted from bulimia nervosa and 20 group-matched controls who completed a stop-signal task during two counterbalanced functional MRI sessions, one after a 16 h fast and one after a meal. This model estimates participants' trial-by-trial updating of the probability of a stop signal based on their experienced trial history. Neural analyses focused on control-related Bayesian prediction errors, which quantify the direction and degree of "surprise" an individual experiences on any given trial. Regardless of group, metabolic state did not affect behavioral performance on the task. However, metabolic state modulated group differences in neural activation. In the fed state, women remitted from bulimia nervosa had attenuated prediction-error-dependent activation in the left dorsal caudate. This fed-state activation was lower among women with more frequent past binge eating and self-induced vomiting. When they are in a fed state, individuals with bulimia nervosa may not effectively process unexpected information needed to engage inhibitory control. This may explain the difficulties these individuals have stopping eating after it begins.

How Obstructed Action Efficacy Impacts Reward-Based Decision Making in Adolescent Depression: An fMRI Study.

OBJECTIVE: Disruption of reward seeking behavior by unforeseen obstacles can promote negative affect, including frustration and irritability, in adolescents. Repeated experiences of obstructed reward may in fact contribute to the development of depression in adolescents. However, the neurocognitive mechanisms whereby goal disruption impacts reward processing in adolescent depression have not yet been characterized. The present study addresses this gap by using neuroimaging and a novel paradigm to assess how incidental action obstruction impacts reward-based decision making. METHOD: We assessed 62 unmedicated adolescents with major depressive disorder (MDD; mean age = 15.6 years, SD = 1.4 years, 67% female participants) and 68 matched healthy control participants (mean age = 15.3 years, SD = 1.4 years, 50% female participants) using functional magnetic resonance imaging (fMRI) while they played a card game in which they had to guess between 2 options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby blocking action efficacy. RESULTS: Participants with MDD made fewer button press repetitions in response to action efficacy obstruction, which was more apparent in the low-stake condition (rate ratio =0.85, p = .034). During response repetition across stake conditions, MDDs exhibited higher activation in regions in the ventromedial prefrontal cortex, caudate, and putamen (F1,125 = 16.4-25.6, df=1,125; p values <.001; Hedges g = 0.85-0.98). CONCLUSION: Adolescents with depression tend to exhibit less flexible behavioral orientation in the face of blocked action efficacy, and abnormalities in neural systems critical to regulating negative affect during reward-based decision making. This research highlights possible mechanisms relevant to understanding and treating affective dysregulation in adolescent depression.

Resting-state connectivity subtype of comorbid PTSD and alcohol use disorder moderates improvement from integrated prolonged exposure therapy in Veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and are associated with significant functional impairment and inconsistent treatment outcomes. Data-driven subtyping of this clinically heterogeneous patient population and the associated underlying neural mechanisms are highly needed to identify who will benefit from psychotherapy. METHODS: In 53 comorbid PTSD/AUD patients, resting-state functional magnetic resonance imaging was collected prior to undergoing individual psychotherapy. We used a data-driven approach to subgroup patients based on directed connectivity profiles. Connectivity subgroups were compared on clinical measures of PTSD severity and heavy alcohol use collected at pre- and post-treatment. RESULTS: We identified a subgroup of patients associated with improvement in PTSD symptoms from integrated-prolonged exposure therapy. This subgroup was characterized by lower insula to inferior parietal cortex (IPC) connectivity, higher pregenual anterior cingulate cortex (pgACC) to posterior midcingulate cortex connectivity and a unique pgACC to IPC path. We did not observe any connectivity subgroup that uniquely benefited from integrated-coping skills or subgroups associated with change in alcohol consumption. CONCLUSIONS: Data-driven approaches to characterize PTSD/AUD subtypes have the potential to identify brain network profiles that are implicated in the benefit from psychological interventions - setting the stage for future research that targets these brain circuit communication patterns to boost treatment efficacy.

Matrix stiffness enhances cancer-macrophage interactions and M2-like macrophage accumulation in the breast tumor microenvironment.

The role of intratumor heterogeneity is becoming increasingly apparent in part due to expansion in single cell technologies. Clinically, tumor heterogeneity poses several obstacles to effective cancer therapy dealing with biomarker variability and treatment responses. Matrix stiffening is known to occur during tumor progression and contribute to pathogenesis in several cancer hallmarks, including tumor angiogenesis and metastasis. However, the effects of matrix stiffening on intratumor heterogeneity have not been thoroughly studied. In this study, we applied single-cell RNA sequencing to investigate the differences in the transcriptional landscapes between stiff and compliant MMTV-PyMT mouse mammary tumors. We found similar compositions of cancer and stromal subpopulations in compliant and stiff tumors but differential intercellular communication and a significantly higher concentration of tumor-promoting, M2-like macrophages in the stiffer tumor microenvironments. Interestingly, we found that cancer cells seeded on stiffer substrates recruited more macrophages. Furthermore, elevated matrix stiffness increased Colony Stimulating Factor 1 (CSF-1) expression in breast cancer cells and reduction of CSF-1 expression on stiffer substrates reduced macrophage recruitment. Thus, our results demonstrate that tissue phenotypes were conserved between stiff and compliant tumors but matrix stiffening altered cell-cell interactions which may be responsible for shifting the phenotypic balance of macrophages residing in the tumor microenvironment towards a pro-tumor progression M2 phenotype. STATEMENT OF SIGNIFICANCE: Cells within tumors are highly heterogeneous, posing challenges with treatment and recurrence. While increased tissue stiffness can promote several hallmarks of cancer, its effects on tumor heterogeneity are unclear. We used single-cell RNA sequencing to investigate the differences in the transcriptional landscapes between stiff and compliant MMTV-PyMT mouse mammary tumors. We found similar compositions of cancer and stromal subpopulations in compliant and stiff tumors but differential intercellular communication and a significantly higher concentration of tumor-promoting, M2-like macrophages in the stiffer tumor microenvironments. Using a biomaterial-based platform, we found that cancer cells seeded on stiffer substrates recruited more macrophages, supporting our in vivo findings. Together, our results demonstrate a key role of matrix stiffness in affecting cell-cell communication and macrophage recruitment.

Temporal recording of mammalian development and precancer.

Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo , while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.

HIV peripheral neuropathy-related degeneration of white matter tracts to sensorimotor cortex.

Human immunodeficiency virus-associated distal sensory polyneuropathy (HIV-DSP) affects up to 50% of people with HIV and is associated with depression, unemployment, and generally worsened quality of life. Previous work on the cortical mechanism of HIV neuropathy found decreased gray matter volume in the bilateral midbrain, thalamus, and posterior cingulate cortex, but structural connectivity in this context remains under-studied. Here we examine alterations in white matter microstructure using diffusion imaging, hypothesizing that cortical white matter degeneration would be observed in continuation of the peripheral white matter atrophy previously observed in HIV-DSP. Male HIV seropositive patients (n = 57) experiencing varying degrees of HIV neuropathy underwent single-shell diffusion tensor imaging with 51 sampling directions. The scans were pooled using tractography and connectometry to create a quantitative map of white matter tract integrity, measured in generalized fractional anisotropy (GFA). The relationship between GFA and neuropathy severity was evaluated with linear regression. Correction for multiple comparisons was done using false discovery rate (FDR), a statistical method commonly used in genomics and imaging to minimize false positives when thousands of individual comparisons are made. Neuropathy severity was associated with decreased GFA along thalamocortical radiations leading along the lateral thalamus to sensorimotor cortex, with r = -0.405 (p < 0.001; FDR), as well as with the superior bilateral cingulum (r = -0.346 (p < 0.05; FDR)). Among a population of HIV neuropathy patients, greater neuropathy severity was correlated with lower white matter integrity running from midbrain to somatosensory cortex. This suggests ascending deafferentation extending from damaged peripheral nerves further downstream than seen previously, into the axons of third-order neurons. There is also evidence of cingulum degeneration, implying some more complex mechanism beyond the ascending atrophy observed here.

Distal neuropathic pain in HIV is associated with functional connectivity patterns in default mode and salience networks.

HIV-associated distal neuropathic pain (DNP) is one of the most prevalent, disabling, and treatment-resistant complications of HIV, but its biological underpinnings are incompletely understood. While data specific to mechanisms underlying HIV DNP are scarce, functional neuroimaging of chronic pain more broadly implicates the role of altered resting-state functional connectivity within and between salience network (SN) and default mode network (DMN) regions. However, it remains unclear the extent to which HIV DNP is associated with similar alterations in connectivity. The current study aimed to bridge this gap in the literature through examination of resting-state functional connectivity patterns within SN and DMN regions among people with HIV (PWH) with and without DNP. Resting state functional magnetic resonance imaging (rs-fMRI) scans were completed among 62 PWH with HIV-associated peripheral neuropathy, of whom 27 reported current DNP and 35 did not. Using subgrouping group iterative multiple estimation, we compared connectivity patterns in those with current DNP to those without. We observed weaker connectivity between the medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) and stronger connectivity between the anterior cingulate cortex (ACC) and thalamus among those reporting DNP. Overall, these findings implicate altered within DMN (i.e., MPFC-PCC) and within SN (i.e., ACC-thalamus) connectivity as potential manifestations of adaptation to pain from neuropathy and/or mechanisms underlying the development/maintenance of DNP. Findings are discussed in the context of differential brain response to pain (i.e., mind wandering, pain aversion, pain facilitation/inhibition) and therapeutic implications.