bluuebunny/crossref_metadata_2025_split huggingface dataset:
PREDICTING DEPRESSED AND ELEVATED MOOD SYMPTOMATOLOGY IN BIPOLAR DISORDER USING BRAIN FUNCTIONAL CONNECTOMES
Authors: Sankar *Anjali , Shen Xilin , Colic Lejla , Goldman Danielle A , Villa Luca M , Kim Jihoon A , Pittman Brian , Scheinost Dustin , Constable R Todd , Blumberg Hilary P 
Published: February 2025

Abstract

Background
Depressed and elevated mood symptom severity underlie the suffering associated with bipolar disorder and are among the strongest clinical predictors of functional impairment and disability in the disorder. Furthermore, mood symptoms contribute to the high risk for suicide in the disorder.
Elucidation of the brain functional disturbances that contribute to mood symptoms in individuals with bipolar disorder could advance our understanding of the pathophysiology of the disorder and enable the development of more targeted therapeutic approaches.

Aims and Objectives
The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder using the machine learning approach Connectome-based Predictive Modeling (CPM).

Methods
Functional magnetic resonance imaging data were obtained from 81 adults with bipolar disorder while they performed an emotion processing task. CPM with 5000 permutations of leave-one- out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with bipolar disorder.

Results
CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r = 0.45, p = 0.002).

Discussion and Conclusion
This study identified distributed functional connectomes predictive of depressed and elevated mood severity in bipolar disorder. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.
“IMMUNOSUPPRESSIVE” CANNABINOID CB2 RECEPTORS TAKE “IMMUNOACTIVE” ROLE IN HIGH-FAT DIET EVOKED SYSTEMIC INFLAMMATORY RESPONSE
Authors: Nozaki *Chihiro , Hosoki Haruka , Zimmer Andreas 
Published: February 2025

Abstract

Background
It is widely known that cannabinoid type 2 (CB2) receptor deficiency enhances inflammatory response and further symptoms in various animal models of inflammation, allergy, or cancer. As CB2 receptors are inhibitory Gi/Go G-protein coupled receptors and as major expression site of CB2 receptors are immune cells, it is no wonder that lack of CB2 receptor might lead the exacerbated inflammation.

Aims & Objectives
Number of study shows high fat diet (HFD) induce peripheral inflammation, however contribution of CB2 receptor has not been studied yet. We therefore exposed HFD to CB2 deficient mice (CB2-KOs), and evaluated the development of peripheral hypersensitivity and neuroinflammation as well as modification of splenic immune cell population.

Method
6-weeks-old male CB2-KOs and their wild-type (WT) controls are used. All animals are single housed, and exposed to either HFD (60kcal% fat, 5.24 kcal/g) or SFD (Standard fat diet, 10kcal% fat, 3.85kcal/g). At 5th week of exposure, animals are subjected to von-Frey test to evaluate the tactile sensitivity, then sacrificed to collect the sciatic nerve and dorsal root ganglia for further immunohistochemistry, and spleen for flow cytometric analysis.

Results
Surprisingly, CB2-KOs showed the significant resistance to the HFD-induced neuroinflammation. Namely, 5-week feeding of HFD induced substantial hypersensitivity in WT mice, while tactile sensitivity of HFD- fed CB2-KO remained intact. In the same animals, we further found the robust upregulation of infiltrated macrophages, chemokine receptor CXCR4 expression and modified differentiation of splenic myeloid-derived suppressor cells (MDSCs) in HFD-fed WT animals, but not in either HFD-fed CB2 knockout mice or SFD-fed CB2-KO animals (Fig 1).

Discussion & Conclusion
Based on these results, we will propose that CB2 receptors might have the bipolar regulatory role to chemokine receptor-mediated inflammatory response through the modulation of splenic MDSC differentiation, which in the end might enhance or inhibit the development of neuroinflammation depending on its cause. Present results also suggests that modulation of CB2 signaling might be able to modify the physiological change lead by metabolism change (e.g. HFD exposure), however further study using other models e.g. diabetic or inflammatory model animal is required to prove this upcoming hypothesis.
CHRONIC POST-COVID NEUROPSYCHIATRIC SYMPTOM CLUSTERS DO NOT SHARE THE SAME RISK FACTORS IN A COHORT INFECTED BY THE OMICRON VARIANT
Authors: Chau *Steven Wai Ho , Chue Timothy Mitchell , Lai Yee Lok , Tsui Ling , Lam Tsz Ching , Chan Rachel Ngai Yin 
Published: February 2025

Abstract

Background
It is suggested that post-COVID neuropsychiatric symptoms are not a unified syndrome, but a heterogeneous entity consisting of distinct symptom clusters (Chau et al., 2023). In a cohort infected by pre-Omicron strain, we showed that the symptoms could be clustered into a cognitive dysfunction- fatigue cluster and an anxiety-depression cluster, which do not share the same predictors.

Aims & Objectives
We aim to test whether we can discover the same symptom structure in a larger cohort infected by the Omicron variant of SARS-CoV-2 virus, and whether the symptom clusters have different risk factors as well. Method:We recruited 508 adult subjects who were infected by the Omicron variant, but not the pre-Omicron variants of SARS-CoV-2 for the first time more than one year ago from the community.
They completed a COVID symptom checklist, questionnaires on the demographics, socioeconomic status and health status and self-reported symptom scales on mood, anxiety, insomnia, and PTSD symptoms via a mobile app.

Results
The mean age of the subjects is 38.2 years. 68% of them are female and 5.1% had known psychiatric illness prior to COVID. 74% of them suffered from asymptomatic to mild acute COVID, and none of them required oxygen therapy. Partial correlation network analysis discovered two symptom clusters: one features cognitive complaints and another one features anxiety-depression (Figure 1). Multiple regression model showed that, while the number of pre-COVID medical conditions and existence of pre- COVID mental illness predicts the number of symptoms from either cluster, level of pre-COVID material deprivation only predicts number of symptoms from the anxiety depression cluster, and the severity of the index infection only predicts number of symptoms from the cognitive complaints cluster.

Discussion & Conclusion
Our result from the Omicron cohort replicated our previous findings from the pre-Omicron cohort by demonstrating that cognitive complaints and anxiety-depression symptoms are distinct sub-syndromes with overlapping yet distinct risk factors. This replication suggests that the characteristics of chronic post-COVID neuropsychiatric symptoms from the pre-Omicron and Omicron strains infection are similar. This replication also strengthens the argument that the two symptom clusters should not be considered a unified entity.

References
Chau, S.W.H, et al. 'Chronic post-COVID neuropsychiatric symptoms persisting beyond one year from infection: a case-control study and network analysis’. Under review.
STIMULATING THE PREFRONTAL CORTEX TO REDUCE HYPERREACTIVITY TO STRESS IN PEOPLE AT RISK OF SCHIZOPHRENIA
Authors: Brunelin *Jerome , Adam Ondine , Mondino Marine 
Published: February 2025

Abstract

Background
According to the vulnerability stress model of schizophrenia, an abnormal hyperreactivity to stress is incriminated in the transition from at risk stages to full-blown psychotic episodes.

Aims & Objectives
We proposed that stimulating the dorsolateral prefrontal cortex (DLPFC) with transcranial direct current stimulation (tDCS) during acute stress exposure would lead to modulation of hypothalamo-pituitary-adrenal (HPA) axis responsiveness in people at risk for schizophrenia.

Method
In a randomized sham-controlled 2-arm study (http://clinicaltrials.gov, NCT03217357, 05/07/2017), 30 unaffected siblings of patients with schizophrenia were randomly allocated to receive either active (n=15) or sham tDCS (n=15) while exposed to an acute stress situation combining physical and psychological stress (the Maastricht Acute Stress Test). The stress exposure started 5 minutes after the start of the tDCS session and lasted 10 minutes. Active stimulation consisted of delivering 2 mA of DC current for 30 min with the anode placed over the left DLPFC and the cathode over the right DLPFC. Sham stimulation consisted of 30 s of ramp up/down and 1 min of active stimulation followed by no stimulation for the remaining 30 min of the stimulation period. Our primary outcome was the concentration of salivary cortisol. A saliva sample was taken every 10 min (every 5 min during stress exposure) for a total of 10 samples. A general linear model with group (active, sham) and time (10 saliva samples) followed by FDR corrected contrasts was performed to examine the effect of tDCS on HPA axis reactivity.

Results
The two groups did not differ at baseline in any sociodemographic characteristics, nor in baseline cortisol concentration (4.69 nmol/L (± 2.53) in the sham group versus 3.54 nmol/L (± SD 1.99) in the active group; W = 78.00; p = 0.25). The GLM revealed a significant association between the group and the time (X2 = 41.16; p &lt;0.001), with the difference between groups being significant at 5 and 10 minutes after the end of the stress exposure. In the sham group, the mean increase in cortisol release was +291% from baseline, whereas the cortisol increase in the active group was +259%.

Discussion & Conclusion
Bifrontal tDCS can prevent stress-induced cortisol release in people at genetic risk of schizophrenia. These results are consistent with our previous studies in healthy participants and suggest that tDCS, which shows promise in treating patients with treatment-resistant symptoms of schizophrenia, may also be of interest in the early stages of the disease to reduce biological hyperreactivity to stress.
ERGOGENIC WORDS: HOW PLACEBOS CHANGE OUR BRAIN
Authors: Carlino *Elisa , Persiani Francesca , Campaci Francesco , Lanzo Gianluca , Volpino Valeria , Piedimonte Alessandro 
Published: February 2025

Abstract

Background
The placebo effect is an illustrative example of the mind-brain-body interaction whereby a positive physical outcome follows the administration of an inert treatment that is expected to be effective. The two main psychological determinants of the placebo effect are conscious expectations, induced through verbal suggestion, and learning, induced through classical conditioning. Accumulating behavioral data suggested that positive expectations of motor improvement result in better motor control for several motor functions in athletes, non-athletes, and patients with motor deficits. These effects have been related to changes in brain areas involved in motor planning and execution, although a deep understanding of the precise neural network underlying this complex psychobiological phenomenon is still missing.

Aims and Objectives
The aim of this study was to tackle the role of frontal cortical regions after placebo manipulations using, for the first time, fNIRS (functional near infrared spectroscopy). The fNIRS is a non-invasive technique used to investigate changes in the concentration of blood oxygen levels induced by brain activity, hence, oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR), at the level of cortical microcirculation blood vessels. Although not having the same spatial resolution as the fMRI, fNIRS has often been compared to fMRI due to both following the same kind of signal and recording the same activity from the cortex.

Methods
For this study, 30 healthy volunteers have been recruited from the student population of the University of Turin. Participants were asked to perform a force motor task and were randomly assigned to two different groups. Participants in the Placebo Group (P group) were informed that the application of 2 electrodes (actually sham) would have improved their motor performance. Participants in the Control Group (C group) performed the motor task without positive verbal information about the effectiveness of the sham electrodes.

Results
From a behavioral point of view, results showed that participants in the P group improved their motor performance compared with the C group (p&lt; 0.05). Moreover, differences in HbO have been observed in the P group in different brain regions, including the left dorsolateral prefrontal cortex (DLPFC).

Discussion
These findings bring new evidence on the neural underpinnings of the motor placebo effect, by showing that the left DLPFC may undermine the expectation-induced enhancement of motor performance in participants that expected a positive motor improvement.
CAUSAL RELATIONSHIPS BETWEEN STRUCTURAL BRAIN IMAGING MARKERS IN ADOLESCENCE AND PSYCHIATRIC DISORDERS IN ADULTHOOD
Authors: Lin *Yen-Feng , Lin Shu-Chin 
Published: February 2025

Abstract

Background
Adolescent brain imaging markers have been identified as potential predictors of adult psychiatric disorders, but it remains unclear whether brain development during childhood and adolescence causally results in psychiatric disorders.

Aims & Objectives
The goal of our research is to better understand the causal relationship between youth’ s cerebral cortex and three primary psychiatric disorders: bipolar disorder (BIP), major depressive disorder (MDD), and schizophrenia (SCZ).

Method
We implemented a two-sample Mendelian randomization (MR) approach to estimate the causal effects of adolescent cortical thickness (CT) and cortical surface area (SA) of 34 regions of interest (ROIs) on the three mental disorders. We integrated imaging and genotypic data from the Adolescent Brain Cognitive Development (ABCD) Study and the summary results of genome-wide association studies (GWAS) from the ENIGMA consortium (N=33,992) and the Psychiatric Genomics Consortium (BIP: 41,917 cases and 371,549 controls; MDD: 170,756 cases and 329,443 controls; SCZ:74,776 cases and 101,023 controls) to conduct the causal analysis. We computed the genetic correlations (rg) between the cortical measures and mental disorders. We employed MR to investigate the causal relationship between ROIs that are genetically associated with the mental disorders.

Results
The global measure of SA was positively correlated with BIP (rg: 0.068 and P-value: 0.037) and inversely correlated with MDD (rg: -0.080 and P-value: 0.009). We identified significant genetic correlations between SA of seven ROIs and BIP, and SA of twelve ROIs and MDD. We identified that SA of the superior frontal as a potential causal region for BIP (OR: 1.22 and 95% CI: 1.10-1.36) based on MR causal analysis. Other ROIs with nominally significant causal effects (P &lt;0.05) included SA of the caudal middle frontal on BIP, and the SA of the four regions (medial orbitofrontal, lateral orbitofrontal, inferior temporal and lateral occipital) on MDD.

Discussion & Conclusion
Our findings suggest that larger SA in early adolescence may causally increase the risk of BIP, with superior frontal being the potential causal ROI. Additionally, we identified potential ROIs such as medial and lateral orbitofrontal regions, which are negatively associated with MDD.
UTILIZING AI MODELS TO IDENTIFY AND PREDICT MOOD TRANSITION PATTERNS IN PATIENTS WITH BIPOLAR DISORDER
Authors: Feng *Xiaoyang , Ma Yantao , Guo Liangkun , Zhang Yuyanan , Sun Yaoyao , Lu Zhe , Liao Yundan , Kang Zhewei , Yu Xin , Yue Weihua 
Published: February 2025

Abstract
Bipolar disorder is characterized by recurrent episodes of depression and mania, making diagnosis and treatment challenging, often leading to poor prognosis. Predicting future episodes based on the assessment of current and past emotional phases in patients can offer valuable insights for clinicians, aiding in the prevention of misdiagnosis and relapse, and in intervention strategies. This study included 812 patients with bipolar disorder from 9 centers, who were assessed online or offline using BDCC, YMRS, and HAMD tools. We employed four AI methodologies to learn from the assessment results and time series, ultimately predicting future emotional phases of the patients. By learning from current assessment results to predict the next emotional phase, the AUCs of the four models were 0.81, 0.70, 0.84, and 0.81, respectively. External validation on 30-day and 90-day emotional phase follow-ups of patients showed prediction accuracies of 0.9, 0.65, 0.86, and 0.62 for each model. While predictive efficacy decreased over time, the average AUC remained above 0.75 at 180 days. Our findings suggest that utilizing big data and AI methods can effectively learn the characteristics of emotional phase transitions in bipolar patients, achieving high accuracy. This model holds significant value for clinical diagnosis and medication guidance for clinicians
SEX DIFFERENCES IN NEURAL PROJECTIONS OF FEAR MEMORY PROCESSING IN MICE AND HUMANS
Authors: Andero *Raul 
Published: February 2025

Abstract

Background
The Tac2 pathway is a pharmacological opportunity for brain disorders since Tac2 antagonists are safe and well tolerated in humans and modulate memory in rodents.

Aims & Objectives
It remains unexplored whether the connectivity between two brain areas is necessary for one sex, but not in the other one, for the formation of the same memory.

Method
In mice we used fear procedures, chemogenetics, clozapine N-oxide delivered intracerebrally and systemically, immunohistochemistry, electrophysiology and in vivo calcium imaging in freely moving mice. In humans we used fear procedures, neuroimaging and genetic analyses of post-mortem brain tissue.

Results
Here, the chemogenetic silencing of CeM-Tac2 fibers in the lateral posterior BNST (BNSTpl) decreases fear memory consolidation in male mice, but not females. Optogenetic excitation of CeM-Tac2 shows increased inhibitory post-synaptic currents in the BNSTpl of males compared to females. In vivo calcium imaging analysis reveals a sex-dimorphic fear memory engram in the BNSTpl. In humans, the single-nucleotide polymorphism (SNP) in the Tac2 receptor (rs2765) (TAC3R) decreases the CeM-BNST connectivity in a fear task, impairs fear memory consolidation and increases the expression of the TAC3R mRNA in AA-carrier men but not in women.

Discussion & Conclusion
These sex differences in necessary neuronal projections of fear memory formation may be relevant for mental disorders with memory alterations. Also, these data highlight the role of Tac2 antagonists in treating and preventing fear-based disorders.
A MACHINE LEARNING APPROACH TO PREDICT THE THERAPEUTIC EFFICACY OF MOBILE NEUROFEEDBACK IN CHILDREN WITH ADHD
Authors: Kim *Junwon , Yang Seungheon , Han Sooin 
Published: February 2025

Abstract

Background
Attention-Deficit/Hyperactivity Disorder (ADHD) is a type of neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity, associated with adverse long-term functional outcomes. Neurofeedback training as an add-on to medication therapy has been proposed.

Aims & Objectives
This study aimed to evaluate the effectiveness of machine learning (ML) models in predicting the therapeutic response to mobile neurofeedback (MNF) in children diagnosed with ADHD. Method: A total of 41 children with ADHD were allocated to one of two groups: ADHD MNF-medication (n=28) and ADHD MNF alone (n=13). Participants already receiving medication for ADHD maintained their medication dosages throughout the MNF treatment period. The MNF program was administered three days a week, twice daily, for 10-20 minutes over a span of 12 weeks. The assessment of the MNF's effectiveness was based on changes in the Clinical Global Impression-Severity scale (CGI-S). We quantified absolute and relative power across 19 channels and analyzed quantitative electroencephalography (qEEG) data within the following frequency ranges: delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–25 Hz), high beta (25–30 Hz), and gamma (30–80 Hz). We employed the XGBoost algorithm to determine the classification potential based on quantitative EEG characteristics and achieved optimal classification performance through hyperparameter optimization, utilizing Python- based XGBoost software.

Results
The highest classification performance obtained through hyperparameter optimization yielded an accuracy rate of 99.7%. To assess the contribution of individual features to the classification, we quantified the impact on classification performance for each group using SHAP (SHapley Additive exPlanations) values and identified the top 10 contributing features. Notably, in the classification based on EEG data obtained with eyes closed, the following features exhibited high importance: F7 (Delta), Fp1 (Delta), F8 (Low Beta), F8 (Beta), F7 (Relative Delta), F4 (Middle Beta), F4 (Beta), Fp1 (Gamma), F7 (Gamma), and O2 (Middle Beta / Theta).

Discussion & Conclusion
Our machine learning analysis demonstrated a high level of accuracy in predicting the therapeutic response to mobile neurofeedback. Notably, delta and beta waves in the frontal lobe were identified as having the highest impact on classification performance.