Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review.

Background: Schizophrenia spectrum disorders (SSD) can be associated with an increased risk of violent behavior (VB), which can harm patients, others, and properties. Prediction of VB could help reduce the SSD burden on patients and healthcare systems. Some recent studies have used machine learning (ML) algorithms to identify SSD patients at risk of VB. In this article, we aimed to review studies that used ML to predict VB in SSD patients and discuss the most successful ML methods and predictors of VB. Methods: We performed a systematic search in PubMed, Web of Sciences, Embase, and PsycINFO on September 30, 2023, to identify studies on the application of ML in predicting VB in SSD patients. Results: We included 18 studies with data from 11,733 patients diagnosed with SSD. Different ML models demonstrated mixed performance with an area under the receiver operating characteristic curve of 0.56-0.95 and an accuracy of 50.27-90.67% in predicting violence among SSD patients. Our comparative analysis demonstrated a superior performance for the gradient boosting model, compared to other ML models in predicting VB among SSD patients. Various sociodemographic, clinical, metabolic, and neuroimaging features were associated with VB, with age and olanzapine equivalent dose at the time of discharge being the most frequently identified factors. Conclusion: ML models demonstrated varied VB prediction performance in SSD patients, with gradient boosting outperforming. Further research is warranted for clinical applications of ML methods in this field.

Machine learning and the prediction of suicide in psychiatric populations: a systematic review.

Machine learning (ML) has emerged as a promising tool to enhance suicidal prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric populations, a formal psychiatric diagnosis emerged as a strong predictor of suicidal risk, overshadowing more subtle risk factors specific to distinct populations. To overcome this limitation, we conducted a systematic review of ML studies evaluating suicidal behaviors exclusively in psychiatric clinical populations. A systematic literature search was performed from inception through November 17, 2022 on PubMed, EMBASE, and Scopus following the PRISMA guidelines. Original research using ML techniques to assess the risk of suicide or predict suicide attempts in the psychiatric population were included. An assessment for bias risk was performed using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. About 1032 studies were retrieved, and 81 satisfied the inclusion criteria and were included for qualitative synthesis. Clinical and demographic features were the most frequently employed and random forest, support vector machine, and convolutional neural network performed better in terms of accuracy than other algorithms when directly compared. Despite heterogeneity in procedures, most studies reported an accuracy of 70% or greater based on features such as previous attempts, severity of the disorder, and pharmacological treatments. Although the evidence reported is promising, ML algorithms for suicidal prediction still present limitations, including the lack of neurobiological and imaging data and the lack of external validation samples. Overcoming these issues may lead to the development of models to adopt in clinical practice. Further research is warranted to boost a field that holds the potential to critically impact suicide mortality.

Right frontal cingulate cortex mediates the effect of prenatal complications on youth internalizing behaviors.

Prenatal and perinatal complications represent well-known risk factors for the future development of psychiatric disorders. Such influence might become manifested during childhood and adolescence, as key periods for brain and behavioral changes. Internalizing and externalizing behaviors in adolescence have been associated with the risk of psychiatric onset later in life. Both brain morphology and behavior seem to be affected by obstetric complications, but a clear link among these three aspects is missing. Here, we aimed at analyzing the association between prenatal and perinatal complications, behavioral issues, and brain volumes in a group of children and adolescents. Eighty-two children and adolescents with emotional-behavioral problems underwent clinical and 3 T brain magnetic resonance imaging (MRI) assessments. The former included information on behavior, through the Child Behavior Checklist/6-18 (CBCL/6-18), and on the occurrence of obstetric complications. The relationships between clinical and gray matter volume (GMV) measures were investigated through multiple generalized linear models and mediation models. We found a mutual link between prenatal complications, GMV alterations in the frontal gyrus, and withdrawn problems. Specifically, complications during pregnancy were associated with higher CBCL/6-18 withdrawn scores and GMV reductions in the right superior frontal gyrus and anterior cingulate cortex. Finally, a mediation effect of these GMV measures on the association between prenatal complications and the withdrawn dimension was identified. Our findings suggest a key role of obstetric complications in affecting brain structure and behavior. For the first time, a mediator role of frontal GMV in the relationship between prenatal complications and internalizing symptoms was suggested. Once replicated on independent cohorts, this evidence will have relevant implications for planning preventive interventions.

Case report and systematic review of cerebellar vermis alterations in psychosis.

INTRODUCTION: Cerebellar alterations, including both volumetric changes in the cerebellar vermis and dysfunctions of the corticocerebellar connections, have been documented in psychotic disorders. Starting from the clinical observation of a bipolar patient with cerebellar hypoplasia, the purpose of this review is to summarize the data in the literature about the association between hypoplasia of the cerebellar vermis and psychotic disorders [schizophrenia (SCZ) and bipolar disorder (BD)]. METHODS: A bibliographic search on PubMed has been conducted, and 18 articles were finally included in the review: five used patients with BD, 12 patients with SCZ and one subject at psychotic risk. RESULTS: For SCZ patients and subjects at psychotic risk, the results of most of the reviewed studies seem to suggest a gray matter volume reduction coupled with an increase in white matter volumes in the cerebellar vermis, compared to healthy controls. Instead, the results of the studies on BD patients are more heterogeneous with evidence showing a reduction, no difference or even an increase in cerebellar vermis volume compared to healthy controls. CONCLUSIONS: From the results of the reviewed studies, a possible correlation emerged between cerebellar vermis hypoplasia and psychotic disorders, especially SCZ, ultimately supporting the hypothesis of psychotic disorders as neurodevelopmental disorders.

Microstructural white matter alterations associated with social anxiety disorders: A systematic review.

BACKGROUND: Social anxiety disorder (SAD) is a psychiatric condition characterized by impaired social functioning that negatively impacts individuals' quality of life. Previous neuroimaging studies have revealed morphological and functional changes in various brain regions associated with SAD. Recent advances in diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) have enabled the investigation of microstructural white matter (WM) alterations in SAD. This study aims to provide an overview of DTI/DWI studies exploring WM microstructure changes in SAD. METHODS: A systematic search on PubMed, Scopus, Web of Science, and PsycINFO was conducted for relevant records on July 8, 2023. An exploratory meta-analysis was also performed. RESULTS: Eight studies were reviewed. Consistent findings indicated reduced fractional anisotropy and increased diffusivity measures in different WM tracts in SAD patients compared to healthy controls. These alterations were mostly observed within regions of the fronto-limbic network, like uncinate fasciculus (UF) and superior and inferior longitudinal fasciculi (SLF and ILF). Finally, our exploratory meta-analysis on four studies utilizing a voxel-wise analytic approach yielded no significant differences between SAD patients and controls. LIMITATIONS: Limited number of studies, small sample sizes, and heterogeneity in analysis methods. CONCLUSIONS: Patients with SAD exhibited altered WM integrity, particularly in the UF, SLF, and ILF, compared to healthy controls. However, due to the limited number of included studies, our meta-analysis yielded no significant differences between SAD patients and controls. Therefore, future research is crucial to unravel the link between altered WM structure and the involvement of other limbic and cortical structures in SAD pathogenesis.

SARS-CoV-2 Infections, Re-Infections and Clinical Characteristics: A Two-Year Retrospective Study in a Large University Hospital Cohort of Vaccinated Healthcare Workers.

At the University Hospital of Bari, during the first year after the start of the mandatory vaccination campaign with BNT162b2 mRNA COVID-19 vaccine, the preliminary results of an observational study showed a significant prevalence of SARS-CoV-2 breakthrough infections (BIs) among healthcare workers (HCWs), but no hospitalization or deaths. In the present study, we extended the observation period (January 2021-January 2023) with the aim of determining the incidence, characteristics and clinical course of SARS-CoV-2 BIs among 6213 HCWs. All HCWs were regularly monitored and screened. To allow return to work after BI, the protocol required one negative nasopharyngeal swab test followed by a medical examination certifying complete clinical recovery. We observed an overall incidence rate of SARS-CoV-2 BIs of 20.2%. Females were most affected, especially in the nurse group compared with doctors and other HCWs (p < 0.0001). Cardiovascular diseases were the most frequent comorbidity (n = 140; 11.4%). The source of infection was non-occupational in 52.4% of cases. Most cases (96.9%) showed minor symptoms and only two cases of hospitalization (one in intensive care unit), 13 cases of re-infection and no deaths were recorded. Our results confirm that SARS-CoV-2 infection can break vaccination protection but the clinical course is favorable.

Mesothelioma Risk Among Maritime Workers According to Job Title: Data From the Italian Mesothelioma Register (ReNaM).

The study describes the 466 cases of malignant mesotheliomas (MM) collected by the National Mesothelioma Register (ReNaM) in Italy in the period 1993-2018 relating to subjects with exclusive asbestos exposure in merchant or military navy. The cases among maritime workers represent 1.8% of the total cases with defined exposure registred in the ReNaM, of which 212 cases (45.4%) among merchant maritime workers and 254 cases (54.5%) among navy. The distribution by site of mesothelioma showed 453 (97.2%) MM cases of the pleura, 11 (2.3%) of the peritoneum and 2 (0.4%) of the tunica vaginalis of the testis. With regard to occupational exposure, it was classified as certain in 318 (68.2%) cases, probable in 69 (14.8%) cases and possible in 79 (16.9%) cases. Among the 23 classified jobs, the highest percentages of certain exposures are among naval engineers, motor mechanics, machine captains and sailors. Machine crew accounted for 49.3% of the cases, deck crew for 27.6%. All cases began exposure on board between 1926 and 1988. Seamen were exposed to asbestos while at sea by virtue of living onboard ships and from continual release of asbestos fibers due to the motion of a vessel. Epidemiological surveillance through the ReNaM has allowed us to verify among cases in the maritime, navy and merchant marine sectors, that in the past, subjects were exposed regardless of the ship's department where have provided service therefore all these cases must be considered as occupational diseases.

Association between cannabis use and symptom dimensions in schizophrenia spectrum disorders: an individual participant data meta-analysis on 3053 individuals.

Background: The association between cannabis use and positive symptoms in schizophrenia spectrum disorders is well documented, especially via meta-analyses. Yet, findings are inconsistent regarding negative symptoms, while other dimensions such as disorganization, depression, and excitement, have not been investigated. In addition, meta-analyses use aggregated data discarding important confounding variables which is a source of bias. Methods: PubMed, ScienceDirect and PsycINFO were used to search for publications from inception to September 27, 2022. We contacted the authors of relevant studies to extract raw datasets and perform an Individual Participant Data meta-analysis (IPDMA). Inclusion criteria were: psychopathology of individuals with schizophrenia spectrum disorders assessed by the Positive and Negative Syndrome Scale (PANSS); cannabis-users had to either have a diagnosis of cannabis use disorder or use cannabis at least twice a week. The main outcomes were the PANSS subscores extracted via the 3-factor (positive, negative and general) and 5-factor (positive, negative, disorganization, depression, excitement) structures. Preregistration is accessible via Prospero: ID CRD42022329172. Findings: Among the 1149 identified studies, 65 were eligible and 21 datasets were shared, totaling 3677 IPD and 3053 complete cases. The adjusted multivariate analysis revealed that relative to non-use, cannabis use was associated with higher severity of positive dimension (3-factor: Adjusted Mean Difference, aMD = 0.34, 95% Confidence Interval, CI = [0.03; 0.66]; 5-factor: aMD = 0.38, 95% CI = [0.08; 0.63]), lower severity of negative dimension (3-factor: aMD = -0.49, 95% CI [-0.90; -0.09]; 5-factor: aMD = -0.50, 95% CI = [-0.91; -0.08]), higher severity of excitement dimension (aMD = 0.16, 95% CI = [0.03; 0.28]). No association was found between cannabis use and disorganization (aMD = -0.13, 95% CI = [-0.42; 0.17]) or depression (aMD = -0.14, 95% CI = [-0.34; 0.06]). Interpretation: No causal relationship can be inferred from the current results. The findings could be in favor of both a detrimental and beneficial effect of cannabis on positive and negative symptoms, respectively. Longitudinal designs are needed to understand the role of cannabis is this association. The reported effect sizes are small and CIs are wide, the interpretation of findings should be taken with caution. Funding: This research did not receive any specific grant or funding. Primary financial support for authors was provided by Le Vinatier Psychiatric Hospital.

Resting-state functional magnetic resonance imaging alterations in borderline personality disorder: A systematic review.

BACKGROUND: Borderline personality disorder (BPD) is a severe psychiatric disorder characterized by emotion dysregulation, impulsivity, and interpersonal disturbances. Several structural and functional neuroimaging abnormalities have been described in BPD. In particular, resting-state functional magnetic resonance imaging (rs-fMRI) studies have recently suggested various connectivity alterations within and between large-scale brain networks in BPD. This review aimed at providing an updated summary of the evidence reported by the available rs-fMRI studies in BPD individuals. METHODS: A search on PubMed, Scopus, and Web of Science was performed to identify rs-fMRI alterations in BPD. A total of 15 studies met our inclusion criteria. RESULTS: Overall, aberrant resting-state functional connectivity (rs-FC) within and between default mode network (DMN), salience network (SN), and central executive network (CEN) were observed in BPD compared to healthy controls, as well as selective functional impairments in bilateral amygdala, anterior and posterior cingulate cortex, hippocampus, and prefrontal cortex. LIMITATIONS: The observational design, small sample size, prevalence of females, high rates of concurrent comorbidities and medications, and heterogeneity across imaging methodologies limit the generalizability of the results. CONCLUSIONS: The identification of altered patterns of rs-FC within and between selective brain networks, including DMN, SN, and CEN, could further our knowledge of the clinical symptoms of BPD, and therefore, future studies with multimodal methodologies and longitudinal designs are warranted to further explore the neural correlates of this disorder.

Machine learning applied to functional magnetic resonance imaging in anxiety disorders.

BACKGROUND: Brain functional abnormalities have been commonly reported in anxiety disorders, including generalized anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, and specific phobias. The role of functional abnormalities in the discrimination of these disorders can be tested with machine learning (ML) techniques. Here, we aim to provide a comprehensive overview of ML studies exploring the potential discriminating role of functional brain alterations identified by functional magnetic resonance imaging (fMRI) in anxiety disorders. METHODS: We conducted a search on PubMed, Web of Science, and Scopus of ML investigations using fMRI as features in patients with anxiety disorders. A total of 12 studies (resting-state fMRI n = 5, task-based fMRI n = 6, resting-state and task-based fMRI n=1) met our inclusion criteria. RESULTS: Overall, the studies showed that, regardless of the classifiers, alterations in functional connectivity and aberrant neural activation involving the amygdala, anterior cingulate cortex, hippocampus, insula, orbitofrontal cortex, temporal pole, cerebellum, default mode network, dorsal attention network, sensory network, and affective network were able to discriminate patients with anxiety from controls, with accuracies spanning from 36 % to 94 %. LIMITATIONS: The small sample size, different ML approaches and heterogeneity in the selection of regions included in the multivariate pattern analyses limit the conclusions of the present review. CONCLUSIONS: ML methods using fMRI as features can distinguish patients with anxiety disorders from healthy controls, indicating that these techniques could be used as a helpful tool for the diagnosis and the development of more targeted treatments for these disorders.

Classification of suicidality by training supervised machine learning models with brain MRI findings: A systematic review.

BACKGROUND: Suicide is a global public health issue causing around 700,000 deaths worldwide each year. Therefore, identifying suicidal thoughts and behaviors in patients can help lower the suicide-related mortality rate. This review aimed to investigate the feasibility of suicidality identification by applying supervised Machine Learning (ML) methods to Magnetic Resonance Imaging (MRI) data. METHODS: We conducted a systematic search on PubMed, Scopus, and Web of Science to identify studies examining suicidality by applying ML methods to MRI features. Also, the Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed for the quality assessment. RESULTS: 23 studies met the inclusion criteria. Of these, 20 developed prediction models without external validation and 3 developed prediction models with external validation. The performance of ML models varied among the reviewed studies, with the highest reported values of accuracies and Area Under the Curve (AUC) ranging from 51.7 % to 100 % and 0.52 to 1, respectively. Over half of the studies that reported accuracy (12/21) or AUC (13/16) achieved values of ≥0.8. Our comparative analysis indicated that deep learning exhibited the highest predictive performance compared to other ML models. The most commonly identified discriminative imaging features were resting-state functional connectivity and grey matter volume within prefrontal-limbic structures. LIMITATIONS: Small sample sizes, lack of external validation, heterogeneous study designs, and ML model development. CONCLUSIONS: Most of the studies developed ML models capable of ML-based suicide identification, although ML models' predictive performance varied across the reviewed studies. Thus, further well-designed is necessary to uncover the true potential of different ML models in this field.

How does feeling pain look like in depression: A review of functional neuroimaging studies.

INTRODUCTION: Major Depression Disorder (MDD) and pain appear to be reciprocal risk factors and sharing common neuroanatomical pathways and biological substrates. However, the role of MDD on pain processing remains still unclear. Therefore, this review aims to focus on the effect of depression on pain anticipation, and perception, before and after treatment, through functional magnetic resonance imaging (fMRI). METHODS: A bibliographic search was conducted on PubMed, Scopus and Web of Science, looking for fMRI studies exploring pain processing in MDD patients. RESULTS: Amongst the 602 studies retrieved, 12 met the inclusion criteria. In terms of pain perception, studies evidenced that MDD patients generally presented increased activation in brain regions within the prefrontal cortex, insula and in the limbic system (such as amygdala, hippocampus) and occipital cortex. The studies investigating the effect of antidepressant treatment evidenced a reduced activation in areas such as insula, anterior cingulate, and prefrontal cortices. In terms of pain anticipation, contrasting results were evidenced in MDD patients, which presented both increased and decreased activity in the prefrontal cortex, the insula and the temporal lobe, alongside with increased activity in the anterior cingulate cortex, the frontal gyrus and occipital lobes. LIMITATIONS: The small number of included studies, the heterogeneous approaches of the studies might limit the conclusions of this review. CONCLUSIONS: Acute pain processing in MDD patients seems to involve numerous and different brain areas. However, more specific fMRI studies with a more homogeneous population and rigorous approach should be conducted to better highlight the effect of depression on pain processing.

Neuroimaging alterations associated with medication use in early-onset bipolar disorder: An updated review.

BACKGROUND: Pediatric bipolar disorder (PBD) is a severe disorder characterized by mood fluctuations starting at a young age. Several neuroimaging studies revealed a specific biological signature of PBD involving alterations in the amygdala and prefrontal regions. Considering the growing concerns regarding the effects of PBD treatments on developing brains, this review aims to provide an overview of the studies investigating the effect of mood stabilizers, antipsychotics, and anticonvulsants on neuroimaging findings in PBD. METHODS: We searched PubMed, Scopus, and Web of Science to identify all structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI) studies exploring the effects of medications on neuroimaging findings in PBD. A total of 18 studies met our inclusion criteria (fMRI n = 11, sMRI n = 6, DTI n = 1). RESULTS: Although the findings varied highly across the studies, some investigations consistently indicated that medications primarily affect the prefrontal cortex and the amygdala. Moreover, despite some exceptions, the reported medication effects predominantly lean towards structural and functional normalization. LIMITATIONS: The reviewed studies differ in methods, medications, and fMRI paradigms. Furthermore, most studies used observational approaches with small sample sizes, minimizing the statistical power. CONCLUSIONS: Evidence suggests the potential of antipsychotics and mood stabilizers to modulate the neuroimaging findings in PBD patients, mostly normalizing brain structure and function in key mood-regulating regions.

Infection Control among Healthcare Workers and Management of a Scabies Outbreak in a Large Italian University Hospital.

This retrospective observational study describes the results of an ad-hoc designated prevention protocol aimed at containing the spread of the scabies infestation among healthcare workers (HCWs) of a large University Hospital in Italy. The outbreak started on October 2022 and a preventive protocol was set up thanks to a multidisciplinary approach. HCWs at high scabies risk were defined as subjects working in Operative Units with a scabies prevalence higher than 2%, close contacts of a confirmed case of scabies, or HCWs with signs and symptoms of the disease. All cases at high scabies risk underwent a dermatological examination, and the infested HCWs were suspended from work until definitive healing. Mass drug administration was established for all HCWs working in Operative Units with a scabies prevalence higher than 2%. Until March 2023, out of 183 screening dermatological examinations, 21 (11.5%) were diagnostic for scabies. Between 11 October 2022 (date of the first diagnosed scabies case) and 6 March 2023 (the end of incubation period related to the last case detected), the frequency of scabies was 0.35% (21 scabies cases/6000 HCWs). The duration of the outbreak in our hospital was 14.7 weeks. Statistical analysis shows a significant association between scabies and being a nurse and having an allergy to dust mites. We obtained a low frequency of scabies infection, limiting the duration of the outbreak and the related economic burden.

White matter modifications of corpus callosum in bipolar disorder: A DTI tractography review.

BACKGROUND: The recent widespread use of diffusion tensor imaging (DTI) tractography allowed researchers to investigate the diffusivity modifications and neuroanatomical changes of white matter (WM) fascicles in major psychiatric disorders, including bipolar disorder (BD). In BD, corpus callosum (CC) seems to have a crucial role in explaining the pathophysiology and cognitive impairment of this psychiatric disorder. This review aims to provide an overview on the latest results emerging from studies that investigated neuroanatomical changes of CC in BD using DTI tractography. METHODS: Bibliographic research was conducted on PubMed, Scopus and Web of Science datasets until March 2022. Ten studies fulfilled our inclusion criteria. RESULTS: From the reviewed DTI tractography studies a significant decrease of fractional anisotropy emerged in the genu, body and splenium of CC of BD patients compared to controls. This finding is coupled with reduction of fiber density and modification in fiber tract length. Finally, an increase of radial and mean diffusivity in forceps minor and in the entire CC was also reported. LIMITATIONS: Small sample size, heterogeneity in terms of methodological (diffusion gradient) and clinical (lifetime comorbidity, BD status, pharmacological treatments) characteristics. CONCLUSIONS: Overall, these findings suggest the presence of structural modifications in CC in BD patients, which may in turn explain the cognitive impairments often observed in this psychiatric disorder, especially in executive processing, motor control and visual memory. Finally, structural modifications may suggest an impairment in the amount of functional information and a morphological impact within those brain regions connected by CC.

Mesothelioma Risk among Construction Workers According to Job Title: Data from the Italian Mesothelioma Register.

BACKGROUND: An increased risk of mesothelioma has been reported in various countries for construction workers. The Italian National Mesothelioma Registry, from 1993 to 2018, reported exposure exclusively in the construction sector in 2310 cases. We describe the characteristics of these cases according to job title. METHODS: We converted into 18 groups the original jobs (N=338) as reported by ISTAT codes ('ATECO 91'). The exposure level was attributed at certain, probable and possible in accordance with the qualitative classification of exposure as reported in the Registry guidelines. Descriptive analysis by jobs highlights the total number of subjects for each single job and certain exposure, in descending order, insulator, plumbing, carpenter, mechanic, bricklayer, electrician, machine operator, plasterer, building contractor, painter and labourer. RESULTS: The cases grow for plumbing in the incidence periods 1993-2018, while, as expected, it decreases for insulator. Within each period considered the most numerous cases are always among bricklayers and labourers, these data confirm the prevalence of non-specialised "interchangeable" jobs in Italian construction sector in the past. CONCLUSIONS: Despite the 1992 ban, the construction sector still presents an occupational health prevention challenge, circumstances of exposure to asbestos may still occur due to incomplete compliance with prevention and protection measures.

The association between anger rumination and emotional dysregulation in borderline personality disorder: A review.

INTRODUCTION: Borderline Personality Disorder (BPD) is characterized by impulsiveness, interpersonal difficulties, emotional instability and dysfunctional cognitive processes. In addition to these symptoms, anger rumination is a cognitive mechanism often prominent in BPD patients and it has been found to be associated with maladaptive outcomes, such as increasing anger feelings, aggressive and impulsive behaviors. In this context, the aim of our review is to synthesize results on the relationship between emotional dysregulation and anger rumination in BPD with the final goal to get more information about possible psychotherapeutic methods in the treatment of BPD. METHODS: A comprehensive search on BPD and anger rumination was performed on PubMed, Embase and Scopus. The search identified 8 articles meeting our inclusion criteria. RESULTS: Most of the studies reported a correlation between BPD emotional instability and dyscontrolled behaviors, anger and depressive rumination. Specifically, from the reviewed studies, it emerged that the tendency to use dysfunctional cognitive strategies, such as anger rumination, predicted aggressive behavior above and beyond emotion dysregulation, ultimately suggesting that anger rumination mediates the relationship between emotional dysregulation and aggression proneness. LIMITATIONS: The cross-sectional design and the inclusion of subjects without a definite diagnosis of BPD (e.g., university students), may have decreased the generalizability of the results to the clinical populations and limited the possibility to explore the effect of anger rumination over time in BPD. CONCLUSIONS: From the reviewed studies emerged that the identification of anger rumination as a proximal process with respect to BPD may have the potential to expand and support psychotherapeutic treatment.

Neuroimaging Correlates of Treatment Response to Transcranial Magnetic Stimulation in Bipolar Depression: A Systematic Review.

Transcranial magnetic stimulation (TMS) has become a promising strategy for bipolar disorder (BD). This study reviews neuroimaging findings, indicating functional, structural, and metabolic brain changes associated with TMS in BD. Web of Science, Embase, Medline, and Google Scholar were searched without any restrictions for studies investigating neuroimaging biomarkers, through structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and single photon emission computed tomography (SPECT), in association with response to TMS in patients with BD. Eleven studies were included (fMRI = 4, MRI = 1, PET = 3, SPECT = 2, and MRS = 1). Important fMRI predictors of response to repetitive TMS (rTMS) included higher connectivity of emotion regulation and executive control regions. Prominent MRI predictors included lower ventromedial prefrontal cortex connectivity and lower superior frontal and caudal middle frontal volumes. SPECT studies found hypoconnectivity of the uncus/parahippocampal cortex and right thalamus in non-responders. The post-rTMS changes using fMRI mostly showed increased connectivity among the areas neighboring the coil. Increased blood perfusion was reported post-rTMS in PET and SPECT studies. Treatment response comparison between unipolar depression and BD revealed almost equal responses. Neuroimaging evidence suggests various correlates of response to rTMS in BD, which needs to be further replicated in future studies.

Effects of COVID-19 pandemic on depression in patients with schizophrenia: A mini-review of the current evidence.

BACKGROUND: Since the emergence of COVID-19, there have been concerns about the psychological effects of the pandemic on people's mental health around the world. Individuals with psychotic disorders like schizophrenia (SCZ) may be more prone to develop mood disorders during the lockdowns due to their limited access to healthcare, reduced social support, and probable cognitive impairment. METHODS: We conducted a systematic search on PubMed and Scopus to explore the effects of the pandemic on depressive symptoms in individuals with SCZ. A total of 12 studies were included. RESULTS: Overall, studies suggested higher depression rates in patients with SCZ compared to healthy controls. Isolation due to the COVID-19 infection emerged as a risk factor for the development of depressive symptoms. However, results regarding the longitudinal changes of depression in SCZ patients during the lockdowns were inconsistent. LIMITATIONS: The small sample sizes of studies, different depression scales and stages of the lockdowns, as well as the different government policies and restriction levels across the countries limit the conclusions of the present review. CONCLUSIONS: Our review suggests an increased probability of depression in patients with SCZ during the pandemic. Identifying the risk factors for developing depression in this population helps find new, suitable approaches to address patients' needs and lower the adverse psychological effects of the pandemic.

A review of resting-state fMRI correlations with executive functions and social cognition in bipolar disorder.

BACKGROUND: Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains. METHODS: A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria. RESULTS: Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients. LIMITATIONS: The heterogeneity of the reviewed studies, in terms of the cognitive domains explored and the neuroimaging acquisitions employed, limited the comparability of the findings. CONCLUSIONS: rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.