Search

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.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Therapeutic options for PDAC are primarily restricted to surgery in the early stages of the disease or chemotherapy in advanced disease. Only a subset of patients with germline defects in BRCA1/2 genes can potentially benefit from personalized therapy, with the PARP inhibitor olaparib serving as a maintenance treatment for metastatic disease. Although the role of radiotherapy in PDAC remains controversial, the use of radiosensitizers offers hope for improving cancer management. Previously, we have shown that damage-specific DNA binding protein 2 (DDB2) is a potential prognostic and predictive biomarker for chemotherapy response in PDAC. In this study, we investigated the function of DDB2 in radiotherapy response, with and without radiosensitization by olaparib in PDAC cells. Our findings demonstrated DDB2 resistance to radiation effects, thereby improving cell survival and enhancing the repair of ionizing radiation-induced DNA double-strand breaks. We observed that DDB2 expression enhances the cell cycle arrest in the G2 phase by phosphorylating Chk1 and Chk2 cell cycle checkpoints. Additionally, we identified a novel link between DDB2 and PARP1 in the context of radiotherapy, which enhances the expression and activity of PARP1. Our findings highlight the potential of low-DDB2 expression to potentiate the radiosensitization effect of olaparib in PDAC cells. Collectively, this study provides novel insights into the impacts of DDB2 in the radiotherapy response in PDAC, enabling its employment as a potential biomarker to predict resistance to radiation. Furthermore, DDB2 represents a significant step forward in precision radiotherapy by widening the scope of patients who can be benefiting from olaparib as a radiosensitizer. Hence, this research has the potential to enrich the limited use of radiotherapy in the care of patients with PDAC.

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.

Anhedonia, a reduced ability to experience positive affect and seek rewards, is present across many psychiatric disorders, notably among individuals who experienced trauma. Within the social domain, anhedonia manifests as an altered sense of belonging and social isolation and is associated with poorer clinical outcomes. Yet, mechanistic operationalizations of social anhedonia are lacking, limiting our understanding of the relationship between these mechanisms and affective symptoms. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. Higher social connectedness (β = 0.51; 95 % CI=[0.11,0.94]) and anxiety (β = 0.57; 95 % CI=[0.13,1.00]) were independently associated with more model-based choices of the partner they anticipated to be most complimenting. In the dorsal anterior cingulate cortex (ACC; z = 3.89, p .001) and left inferior parietal lobule (z = 3.96, p .001), neural responses to reward prediction errors (RPE) were more positive in response to compliment relative to non-compliment outcomes. Greater positive RPE ACC activation was associated with lower anxiety (β = −0.51; 95 % CI=[−0.99,−0.10]. Computational approaches to social reinforcement learning can help identify important neurocognitive differences in social reward sensitivity among individuals with complex affective profiles, such as trauma-exposed individuals. Understanding these differences may help develop new prediction and treatment tools for social anhedonia.

BackgroundPosttraumatic 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.MethodsIn 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.ResultsWe 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.ConclusionsData-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.

Frustration is common in adolescence and often interferes with executive functioning, particularly reward-based decision-making, and yet very little is known about how incidental frustrating events (independent of task-based feedback) disrupt the neural circuitry of reward processing in this important age group. While undergoing functional magnetic resonance imaging (fMRI), 45 healthy adolescents played a card game in which they had to guess between two options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby increasing frustration potential. Neural deactivation of the precuneus, a Default Mode Network region, was observed during obstructed action blocks across stake conditions, but less so on high- relative to low-stake trials. Moreover, less deactivation in goal-directed reward processing regions (i.e., caudate), frontoparietal "task control" regions, and interoceptive processing regions (i.e., somatosensory cortex, thalamus) were observed on high-stake relative to low-stake trials. These findings are consistent with less disruption of goal-directed reward seeking during blocked action efficacy in high-stake conditions among healthy adolescents. These results provide a roadmap of neural systems critical to the processing of frustrating events during reward-based decision-making in youths and could help to characterize how frustration regulation is altered in a range of pediatric psychopathologies.

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.

Abstract Pancreatic cancer is one of the most aggressive diseases with a very poor outcome. Olaparib, a PARP inhibitor, as maintenance therapy showed benefits in patients with metastatic pancreatic adenocarcinoma bearing germline BRCA1/2 mutations. However, germline BRCA mutation has been described in only 4–7% of patients with pancreatic adenocarcinoma. A CRISPR/Cas9-mediated system was used to knock-in the c.763G > T p.(Glu255*) and c.2133C > A p.(Cys711*) mutations in cell lines to obtain truncated BRCA1 and BRCA2 proteins, respectively. A CRISPR/Cas9 ribonucleoprotein complex was assembled for each mutation and transfected into two pancreatic cell lines (T3M4 and Capan-2) and into a breast cancer cell lines (MCF7) as control. BRCA protein levels were significantly decreased in all BRCA-depleted cells (P

This article explores the transformative potential of fermentation in elevating the quality of plant-based matrices to match the desirable attributes of traditional dairy and meat products. As the demand for sustainable products without animal welfare issues increases, fermentation has emerged as a key process to enhance the organoleptic properties and nutritional content of plant-based analogs. This study explores the effect of fermentation when applied to legume matrices, focusing on the resulting texture, flavor, and nutritional value. A selection of Bacillus subtilis, lactic acid bacteria (LAB) strains, and combinations thereof showed potential for improving the aforementioned organoleptic and nutritional characteristics of fermented plant bases. In four different legume-derived matrices, fermentation improved texture, degraded undesirable plant carbohydrates, and removed off-flavor compounds, while producing desirable dairy-associated compounds. The degradation of the undesirable beany off-flavor-causing compound hexanal appears to be a universal phenomenon, as every tested strain as well as their combinations exhibited the capability to decrease the hexanal content, albeit with varying efficiency. Some LAB strains were found to be capable of producing carotenoids and might hence have the potential for tailoring fermented plant-based matrices for specific applications, such as yellow cheese or red meat analogs.

Abstract Gene fusions and MET exon skipping drive oncogenesis in 8–9% and 3% of non-small cell lung cancers (NSCLC) respectively. Their detection are essential for the management of patients since they confer sensitivity to specific targeted therapies with significant clinical benefit over conventional chemotherapy. Immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH) account for historical reference techniques however molecular-based technologies (RNA-based sequencing and RT-PCR) are emerging as alternative or complementary methods. Here, we evaluated the analytical performance of the fully-automated RT-PCR Idylla GeneFusion assay compared to reference methods using 35 fixed NSCLC samples. Idylla demonstrated overall agreement, sensitivity and specificity of 100% compared to RNASeq. Interestingly, it succeeded in retrieving 10 out of 11 samples with inconclusive results due to insufficient RNA quality for sequencing. Idylla showed an overall agreement, sensitivity and specificity of 90.32%, 91.67% and 89.47% compared to IHC/FISH respectively. Using commercial standards, the limit of detection of the Idylla system for the most frequent fusions and exon skipping ranges between 5 and 10 ng RNA input. These results support that the Idylla assay is a reliable and rapid option for the detection of these alterations, however a particular attention is needed for the interpretation of the expression imbalance.

Abstract Background Alcohol use disorder (AUD) is highly prevalent and commonly co-occurs with other psychiatric disorders among Veterans. Provisional evidence supports the use of Approach Avoidance Training (AAT) - a form of computer-delivered cognitive bias modification designed to target implicit approach bias for alcohol-related cues - as an adjunctive program to treat AUD. However, the extent to which AAT is effective for improving AUD recovery outcomes in outpatient Veteran samples and those with psychiatric comorbidities has been understudied to date. Here we describe a double-blind randomized controlled trial of AAT versus a comparison condition (Sham) being conducted in Veterans with comorbid psychiatric conditions completing outpatient standard care. Methods One hundred thirty-six Veterans currently receiving outpatient treatment for AUD will be recruited for this randomized controlled trial with parallel group assignment. Participants will be randomized to either 6 weeks of AAT (n = 68) or Sham (n = 68) training in conjunction with usual care. Assessments will occur at baseline and 6 weeks, 3 months, and 6 months post-baseline. Primary outcome variables will include functional consequences of drinking. Secondary outcome variables will include alcohol consumption, and behavioral indicators of alcohol approach bias. A subset of participants (n = 51) will also complete functional magnetic resonance imaging (fMRI) to assess neural response during an alcohol approach bias assessment. Discussion This study is the first randomized controlled trial of AAT administered as an adjunctive treatment to standard care in Veterans with AUD and comorbid psychiatric disorders. Additionally, behavioral and neuroimaging data will be used to determine the extent to which AAT targets approach bias for alcohol cues. If effective, AAT may be a promising low-cost adjunctive treatment option for individuals with AUD. Registry name AAT for Alcohol Use Disorder in Veterans. Trial registration ClinicalTrials.gov: NCT05372029; Date of Registration: 5/9/2022.

Abstract Background With more than 15,000 new cases /year in France and 2,000 deaths, cutaneous melanoma represents approximately 4% of incidental cancers and 1.2% of cancer related deaths. In locally advanced (stage III) or resectable metastatic (stage IV) melanomas, medical adjuvant treatment is proposed and recent advances had shown the benefit of anti-PD1/PDL1 and anti-CTLA4 immunotherapy as well as anti-BRAF and anti-MEK targeted therapy in BRAF V600 mutated tumors. However, the recurence rate at one year is approximately 30% and justify extensive research of predictive biomarkers. If in metastatic disease, the follow-up of circulating tumor DNA (ctDNA) has been demonstrated, its interest in adjuvant setting remains to be precised, especially because of a lower detection rate. Further, the definition of a molecular response could prove useful to personalized treatment. Methods PERCIMEL is an open prospective multicentric study executed through collaboration of the Institut de Cancérologie de Lorraine (non-profit comprehensive cancer center) and 6 French university and community hospitals. A total of 165 patients with resected stage III and IV melanoma, eligible to adjuvant imunotherapy or anti-BRAF/MEK kinase inhibitors will be included. The primary endpoint is the presence of ctDNA, 2 to 3 weeks after surgery, defined as mutated ctDNA copy number calculated as the allelic fraction of a clonal mutation relative to total ctDNA. Secondary endpoints are recurrence-free survival, distant metastasis-free survival and specific survival. We will follow ctDNA along treatment, quantitatively through ctDNA mutated copy number variation, qualitatively through the presence of cfDNA and its clonal evolution. Relative and absolute variations of ctDNA during follow-up will be also analyzed. PERCIMEL study aims at provide scientific evidence that ctDNA quantitative and qualitative variations can be used to predict the recurrence of patients with melanoma treated with adjuvant immunotherapy or kinase inhibitors, thus defining the notion of molecular recurrence.

Individuals exhibit a natural bias to approach positive social cues (e.g., smiling face) and to avoid negative ones, which may be altered in psychiatric conditions. Computerized approach/avoidance training to promote affectively congruent behavior has proven useful in modulating such biases. Here, we investigate how exposure to a higher rate of congruency impacts neural processing of social-affective cues. While undergoing functional magnetic resonance imaging (fMRI), twenty-four individuals completed two versions of the approach-avoidance task (AAT), in which they had to approach or avoid dynamic facial expressions of either happiness or disgust. In the high congruency condition, congruent responses (i.e. approaching happy faces, avoiding disgusted faces) were more frequent. The balanced condition had equal amounts of congruent and incongruent responses. Processing of congruent approach-avoidance actions towards social cues was associated with lower recruitment of the right anterior insula in the congruency-intensive relative to the balanced condition. Differential activation between the high congruency and balanced condition in the right hippocampus was negatively related to individuals' trait avoidance tendency. These findings are consistent with reduced affective neural processing of social cues when being exposed to congruent AAT contexts. These neural foci could be important targets when assessing the effectiveness of affective congruency training protocols.

Post-traumatic stress disorder (PTSD) is associated with neuro-physiological abnormalities reflecting increased anticipatory anxiety and reactivity to traumatic cues. It remains unclear whether neural mechanisms associated with PTSD treatment responsiveness, i.e. hyperactivation of the affective salience network in the brain, extend to a comorbid PTSD and substance use disorder population. Thirty-one Veterans with PTSD and co-occurring alcohol use disorder (AUD) were randomly assigned to either prolonged exposure or a non-exposure based treatment. They completed an affective anticipation task while undergoing fMRI, immediately prior and after completing treatment. After controlling for type and length of treatment, larger reduction of PTSD symptoms was associated with decreased anticipatory activation to negative trauma-related cues in the right pre-Supplementary Motor Area (pre-SMA), a region associated with emotion regulation. Smaller reduction in PTSD severity was associated with enhanced anticipatory activation to those cues within the right para-hippocampal region, an affective processing region. Our findings suggest that post-treatment reductions in anticipatory reactivity to trauma-related cues in the pre-SMA and para-hippocampal area are associated with larger PTSD symptom reduction in individuals with co-occurring PTSD and AUD. These results may offer neurofeedback training targets as an alternative to or enhancement of other PTSD treatment modalities in this population.

Implicit social-affective biases-reflected in a propensity to approach positive and avoid negative stimuli-have been documented in humans with paradigms, such as the Approach-Avoidance Task (AAT). However, the degree to which preemptively engaging cognitive control can help to down-regulate those behavioral tendencies remains poorly understood. While undergoing functional magnetic resonance imaging (fMRI), 24 healthy participants completed a cued version of the AAT, in which they responded to pictures of happy or angry faces by pulling a joystick toward themselves (approach) or pushing the joystick away (avoidance) based on the color of the stimulus frame. On some trials, they were cued to reverse the frame color/joystick action instructions. Before stimulus onset, a reverse cue was associated with deactivation of a visuo-spatial and motor planning network and subsequent slowing down in response to stimuli. During the stimulus phase, a reverse cue was associated with a) activation of cognitive control areas, including the right inferior frontal gyrus (IFG) and right inferior parietal lobule (IPL); and b) reduced right precentral gyrus activation when having to push (avoid) a happy face. Overall, these results suggest that proactively engaging cognitive control can help fine-tune behavioral and neural adjustment to emotionally incongruent behavioral conditions.

Posttraumatic stress disorder (PTSD) is associated with inhibitory control dysfunction that extends beyond difficulties inhibiting trauma-related intrusions. Inhibitory learning has been proposed as a potential mechanism of change underlying the effectiveness of extinction-based therapies such as prolonged exposure (PE), a first-line treatment for PTSD. To identify neurocognitive markers of change in inhibitory learning associated with PE, we applied a Bayesian learning model to the analysis of neuroimaging data collected during an inhibitory control task, both before and after PE treatment. Veterans (N = 20) with combat-related PTSD completed a stop-signal task (SST) while undergoing fMRI at time points immediately before and after PE treatment. Participants exhibited a small, significant improvement in performance on the SST, as demonstrated by longer reaction times and improved inhibition accuracy. Amplitude of neural activation associated with a signed prediction error (SPE; i.e., the discrepancy between actual outcome and model-based expectation of needing to stop) in the right caudate decreased from baseline to posttreatment assessment. Change in model-based activation was modulated by performance accuracy, with a decrease in positive SPE activation observed on successful trials, d = 0.79, and a reduction in negative SPE activation on error trials, d = 0.74. The decrease in SPE-related activation on successful stop trials was correlated with PTSD symptom reduction. These results are consistent with the notion that PE may help broadly strengthen inhibitory learning and the development of more accurate model-based predictions, which may thus facilitate change in cognitions in response to trauma-related cues and help reduce PTSD symptoms.

The considerable comorbidity of posttraumatic stress disorder (PTSD) and alcohol use disorders (AUD) poses a greater public health burden than either condition alone. Although there is a substantial body of evidence linking the direct neurotoxic effect of heavy drinking to gray matter (GM) deficits, as well as a growing body of literature supporting a strong association between PTSD and GM alterations, there is scant research interrogating the direct interaction of the two disorders. In order to generate data-driven, specific hypotheses regarding the overlapping neural substrates of PTSD and AUD, we conducted a meta-analysis of GM volumes in each disorder relative to healthy control subjects. We found shared GM deficits in the anterior cingulate cortex (ACC) across both disorders relative to healthy control participants. These findings suggest that reduced volumes of the ACC across PTSD and AUD may have implications for the development, expression, or treatment of symptoms linked to these frequently co-existing disorders. Recommendations are made for future work aimed at delineating the specific and shared effects of traumatic stress and alcoholism on neural integrity.

Methamphetamine use disorder is associated with a high likelihood of relapse. Identifying robust predictors of relapse that have explanatory power is critical to develop secondary prevention based on a mechanistic understanding of relapse. Computational approaches have the potential to identify such predictive markers of psychiatric illness, with the advantage of providing a finer mechanistic explanation of the cognitive processes underlying psychiatric vulnerability. In this study, sixty-two recently sober methamphetamine-dependent individuals were recruited from a 28-day inpatient treatment program, and completed a Stop Signal Task (SST) while undergoing functional magnetic resonance imaging (fMRI). These individuals were prospectively followed for 1 year and assessed for relapse to methamphetamine use. Thirty-three percent of followed participants reported relapse. We found that neural activity associated with two types of Bayesian prediction error, i.e. the difference between actual and expected need to stop on a given trial, significantly differentiated those individuals who remained abstinent and those who relapsed. Specifically, relapsed individuals exhibited smaller neural activations to such Bayesian prediction errors relative to those individuals who remained abstinent in the left temporoparietal junction (Cohens d = 0.91), the left inferior frontal gyrus (Cohens d = 0.57), and left anterior insula (Cohens d = 0.63). In contrast, abstinent and relapsed participants did not differ in neural activation to non-model based task contrasts or on various self-report clinical measures. In conclusion, Bayesian cognitive models may help identify predictive biomarkers of relapse, while providing a computational explanation of belief processing and updating deficits in individuals with methamphetamine use disorder.