Search

Objectives People with schizophrenia (SCZ) present serious and generalised deficits in social cognition (SC), which affect negatively patients' functioning and treatment outcomes. The genetic background of SC has been investigated in disorders other than SCZ providing weak and sparse results. Thus, our aim was to explore possible genetic correlates of SC dysfunctions in SCZ patients with a genome-wide study (GWAS) approach. Methods We performed a GWAS meta-analysis of data coming from two cohorts made of 242 and 160 SCZ patients, respectively. SC was assessed with different tools in order to cover its different domains. Results We found GWAS significant association between the TMEM74 gene and the patients' ability in social inference as assessed by The Awareness of Social Inference Test; this association was confirmed by both SNP-based analysis (lead SNP rs3019332 p-value = 5.24 × 10-9) and gene-based analysis (p-value = 1.09 × 10-7). Moreover, suggestive associations of other genes with different dimensions of SC were also found. Conclusions Our study shows for the first time GWAS significant or suggestive associations of some gene variants with SC domains in people with SCZ. These findings should stimulate further studies to characterise the genetic underpinning of SC dysfunctions in SCZ.

Compared with the general population, people with severe mental disorders have significantly worse physical health and a higher mortality rate, which is partially due to the adoption of unhealthy lifestyle behaviors, such as heavy smoking, use of alcohol or illicit drugs, unbalanced diet, and physical inactivity. These unhealthy behaviors may also play a significant role in the personal and functional recovery of patients with severe mental disorders, although this relationship has been rarely investigated in methodologically robust studies. In this paper, we aim to: a) describe the levels of physical activity and recovery style in a sample of patients with severe mental disorders; b) identify the clinical, social, and illness-related factors that predict the likelihood of patients performing physical activity. The global sample consists of 401 patients, with a main psychiatric diagnosis of bipolar disorder (43.4%, N = 174), psychosis spectrum disorder (29.7%; N = 119), or major depression (26.9%; N = 118). 29.4% (N = 119) of patients reported performing physical activity regularly, most frequently walking (52.1%, N = 62), going to the gym (21.8%, N = 26), and running (10.9%, N = 13). Only 15 patients (3.7%) performed at least 75 min of vigorous physical activity per week. 46.8% of patients adopted sealing over as a recovery style and 37.9% used a mixed style toward integration. Recovery style is influenced by gender (p < 0.05) and age (p < 0.05). The probability to practice regular physical activity is higher in patients with metabolic syndrome (Odds Ratio - OR: 2.1; Confidence Interval - CI 95%: 1.2-3.5; p < 0.050), and significantly lower in those with higher levels of anxiety/depressive symptoms (OR: 0.877; CI 95%: 0.771-0.998; p < 0.01). Globally, patients with severe mental disorders report low levels of physical activities, which are associated with poor recovery styles. Psychoeducational interventions aimed at increasing patients' motivation to adopt healthy lifestyle behaviors and modifying recovery styles may improve the physical health of people with severe mental disorders thus reducing the mortality rates.

Background People with severe mental illnesses (SMI) have a mortality rate two times higher compared to the general population, with a decade of years of life lost. In this randomized controlled trial (RCT), we assessed in a sample of people with bipolar disorder, major depressive disorder, and schizophrenia spectrum disorder, the efficacy of an innovative psychosocial group intervention compared to a brief psychoeducational group intervention on patients’ body mass index (BMI), body weight, waist circumference, Framingham and HOMA-IR indexes. Methods This is a multicentric RCT with blinded outcome assessments carried out in six Italian university centers. After recruitment patients were randomized to receive a 6-month psychosocial intervention to improve patients’ physical health or a brief psychoeducational intervention. All recruited patients were assessed with standardized assessment instruments at baseline and after 6 months. Anthropometric parameters and blood samples have also been collected. Results Four-hundred and two patients with a diagnosis of bipolar disorder (43.3%), schizophrenia or other psychotic disorder (29.9%), or major depression (26.9%) were randomly allocated to the experimental (N = 206) or the control group (N = 195). After 6 months, patients from the experimental group reported a significant reduction in BMI (odds ratio [OR]: 1.93, 95% confidence intervals [CI]: 1.31–2.84; p p p Conclusions The experimental group intervention was effective in improving the physical health in SMI patients. Further studies are needed to evaluate the feasibility of this intervention in real-world settings.

First generation antipsychotics (FGAs) are more likely to induce extrapyramidal side-effects (EPS) than second generation antipsychotics (SGAs), and EPS have been shown associated to cognitive deficits in schizophrenia. So far, no study has explored the relationships between EPS and social cognition (SC) in people with schizophrenia. Therefore, we assessed the prevalence of EPS in a large sample of drug-treated community-dwelling persons with schizophrenia and explored their relationships with patients' neurocognitive and SC abilities. 875 patients underwent EPS, psychopathological, neurocognitive and SC assessments by means of standardized measures. Relationships between EPS, psychopathology and neurocognitive and SC measures were investigated by correlation tests. Moreover, a partial correlation network was computed by means of a network analysis. 256 patients were treated with FGAs alone or in combination with SGA and 619 with SGAs. EPS were significantly more frequent in FGA-treated group than in the SGA-treated one. Patients with EPS disclosed a more severe psychopathology and were more impaired in neurocognitive and SC measures compared to those without EPS. Disorganization, expressive deficit, and duration of illness were significantly associated to both neurocognitive and SC measures while EPS were associated to neurocognitive measures only. The network analysis showed that parkinsonism was the sole EPS directly connected to both psychopathological and neurocognitive indices whereas no direct connection emerged between EPS and SC measures. Present findings confirm that EPS are still present in the era of SGAs and contribute, together with other clinical variables, to the neurocognitive but not to the SC impairment of patients with schizophrenia.

Suicide risk and resilience strategies during the different phases of the COVID-19 pandemic are of great interest to researchers. At the pandemic onset, a dramatic suicides exacerbation was feared. Some authoritative authors warned the scientific and clinical community about this risk by pointing out that especially psychiatric, psychological, and social factors could interact with each other to create a vicious cycle. While worldwide case-reports and studies conducted at emergency departments did indeed find an increase in suicidal behavior, recent systematic reviews, meta-analyses, and time-series analyses could not confirm this for the first COVID-19 wave. Instead, it appears that the increased suicide risk outlasted the acute phase of the pandemic and thus affected people more during the pandemic following phases. One possible reason for this phenomenon may be a persistent state of insecurity regarding the economic crisis evolution with serious financial stressors in terms of income decrease, unemployment, repaying debts difficulty, home loss, one's social status derive, social hierarchy drop, and poverty. During the COVID-19 first wave, with particular regard to vulnerable populations, one of the postulated theories unifying different risk factors under a single frame was the "Interpersonal Theory of Suicide". Conversely, the "Interpersonal Trust" theory emerged as a protective factor even during an economic crisis. In a possible mirroring of the two theories, it seems to be feasible to find common themes between them and, above all, to gain relevant insights to devise effective prevention and supportive strategies for dealing with suicide risk challenges that COVID-19 will continue to pose in the foreseeable future. (www.actabiomedica.it).

In October 2020, BepiColombo performed a flyby maneuver at the Moon. The Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) was among the few instruments that could observe the Moon. We report on first preliminary results.

Our manuscript aims to: 1) assess physical health in a sample of patients with severe mental disorders; and 2) identify the psychopathological and psychosocial characteristics associated with an increased likelihood of having a poor physical health. The study, funded by the Italian Ministry of Education, has been carried out in psychiatric outpatient units of six Italian University sites. All recruited patients have been assessed through standardized assessment instruments. Moreover, anthropometric parameters have been obtained at recruitment and a blood samples have been collected to assess cardiometabolic parameters. Four-hundred and two patients with a primary diagnosis of bipolar disorder (43.3%), schizophrenia or other psychotic disorder (29.9%), or major depression (26.9%) were recruited. Internalized stigma, psychosocial functioning, quality of life, psychiatric hospitalizations, depressive/anxiety and manic symptoms and cognition were those domains more strongly associated with poor metabolic parameters, including high body mass index, HOMA and Framingham indexes and waist circumference. There were no statistically significant differences among the three diagnostic groups. Our findings highlight the importance of perceived stigma and quality of life on patients’ physical health. This should be taken into account when developing plans for reducing the mortality rate in patients with severe mental disorders.

Not required.

Background Autism spectrum disorders (ASDs) and schizophrenia spectrum disorders (SSDs), although conceptualized as separate entities, may share some clinical and neurobiological features. ASD symptoms may have a relevant role in determining a more severe clinical presentation of schizophrenic disorder but their relationships with cognitive aspects and functional outcomes of the disease remain to be addressed in large samples of individuals. Aims To investigate the clinical, cognitive, and functional correlates of ASD symptoms in a large sample of people diagnosed with schizophrenia. Methods The severity of ASD symptoms was measured with the PANSS Autism Severity Scale (PAUSS) in 921 individuals recruited for the Italian Network for Research on Psychoses multicenter study. Based on the PAUSS scores, three groups of subjects were compared on a wide array of cognitive and functional measures. Results Subjects with more severe ASD symptoms showed a poorer performance in the processing speed (p = 0.010), attention (p = 0.011), verbal memory (p = 0.035), and social cognition (p = 0.001) domains, and an overall lower global cognitive composite score (p = 0.010). Subjects with more severe ASD symptoms also showed poorer functional capacity (p = 0.004), real-world interpersonal relationships (p p Conclusions These findings strengthen the notion that ASD symptoms may have a relevant impact on different aspects of the disease, crucial to the life of people with schizophrenia. Prominent ASD symptoms may characterize a specific subpopulation of individuals with SSD.

Not required.

Background. Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions. Methods. Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression. Results. After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms. Conclusions. In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem., Highlights Better insight seems associated with depressive symptoms in schizophrenia.Network analyses were used to explore this association in a large sample.Insight was associated with self-depreciation, guilt, and suicidal ideation.Although cross-sectional, data suggest causal direction from insight to depression.

The aim of this paper is to critically ascertain the effectiveness of lamotrigine (LTG) as a key strategy for the treatment of bipolar I disorder.PubMed and Cochrane Library databases were searched using the following keywords: "lamotrigine" AND "bipolar disorder", "psychotic" or "mood disorder".Lamotrigine, has shown significant efficacy in preventing or delaying the onset of depressive episodes in bipolar disease. The standard final dose is 200 mg/day to be achieved with slow titration. The concomitant use of LTG and valproic acid requires a reduction of the standard final dosage of LTG to 100 mg/day in order to prevent the occurrence of adverse reactions, while an increase in the dosage of LTG (up to a maximum of 400 mg/day) is required in the case of concomitant use of enzyme inducers, such as carbamazepine. Lamotrigine is well tolerated and has a relatively low risk of side effects. Slow titration and accurate monitoring in the first weeks of treatment are necessary in order to reduce the risk of adverse events, such as severe skin rash, whose onset is however rare in the adult population (0.1%). It is possible to use LTG during pregnancy, breastfeeding or in subjects with liver or kidney disorders, following a preliminary assessment of the risk-benefit ratio.Lamotrigine is suitable for preventing or delaying the onset of depressive episodes in patients with bipolar I disorder, and has a high level of tolerability. Prevention of depression determines stabilization of bipolar disease and may contribute to a better overall outcome in patients with predominantly depressive episodes. In patients with a clinical history characterized by severe and repeated manic episodes, it is advisable to combine LTG with an antimanic agent (e.g. lithium or second generation antipsychotic) even in the maintenance phase. Lamotrigine is a valid therapeutic option in the long-term prevention and stabilization of the depressive phases in patients with bipolar I disorder.

The 27th of June 2018 the Japanese Haybusa-2 spacecraft approached the C-type Near Earth asteroid 162173 Ryugu [1]. Haybusa2 is equipped with three remote sensing instruments such i.e. as the Thermal Infrared Imager TIR [2], the NIRS 3 spectrometer [3] and the Optical Navigation Camera-Telescopic (ONC-T) with a wideband and seven narrow band filters [4]. A Lidar instrument [5] allowed to reconstruct the shape model of the asteroid and to measure the altimetry, in order to perform a precise touchdown in sampling the asteroidal regolith. Additionally, by using the robotic landers Minerva-II and Mascot [6], Hayabusa 2 has conducted in situ surface experiments. Ryugu is a top-shaped Cb type asteroid and is covered by a large number of boulders [7,8]. It is one of the darkest object in our Solar System with a quite homogenous composition, including OH-rich materials [7,9]. We found that the NIRS3 data contains sensible variations, possibly linked to geomorphological structures, even though Ryugu surface varies only of few percent in reflectance. Our approach is to exploit the whole spectrometer dataset, to find correlation that could not be foreseen with traditional methods relying on fewer spectral points. Past experience on Mercury data shows that this is a sensible approach, in case of homogeneous featureless targets. We collect NIRS3 data from 20180711_l3a and 20180719_l3a counting around 20k useful spectra, covering almost the whole surface. The data were windowed between 1.8 and 3.1 um to avoid residual thermal effects at higher wavelength, obtaining a data matrix of 20k row x 75 feature or bands. Then we applied a PCA transformation step to retain 10 component or 98% of the total variance, effectively compressing the data from 75 to 10 components. Even though the PCA components per se doesn’t normally have a clear physical meaning, because they mix spectral feature in an unpredictable way, it is interesting to look at the results. The first PCA component has redder slope between 1.8 and 2.5 um, where the second has an inverted redder slope in the same range. The third is spectrally flatter, with an hint of absorption between 2.4 and 2.5 um. The concentration distribution of those three components is also worth investigating: the PCA.0 is anti-correlated with the equatorial bulge and higher in craters, PCA.1 is also higher in crater but not strongly anti-correlated with the equatorial bulge like PCA.0. PCA.3 this is clearly showing a north-south asymmetry. The PCA component order indicate also the importance in explaining total data variance. After that, we apply T-distributed Stochastic Neighbour Embedding (t-SNE)[10]: this converts similarities between data to joint probabilities, minimize the divergence between the joint probabilities of the low-dimensional embedding and the high-dimensional data, typically 2 or 3 dimensions. Essentially, we can feed high dimensional data and get a lower dimension 2D map representation were closer point are also close in the original data space that is easy to visualize. On top of that we partitioned the data point using an Agglomerative Clustering algorithm: starting from all separated data point it clusters the closest together, where closeness is calculated with complete linkage, i.e. the maximum distances between all observations in each pair of classes. Hierarchical algorithm has the nice advantage to show which partition is more stable via a dendrogram plot. In our case, a 6 classes parti tion show as the most suitable one. Results: The surface of Ryugu could be separated in 6 spectral classes, which have a similar spectral trend and are spatially coherent Classes (0,1,5,3) have same trend, but different albedo (from lower to higher reflectance). Class 0 and 1 (C0/C1) are inter-craters terrains, the former mostly in the north , the latter in the south, with minor outcrops in the other hemisphere. C0 is up to -2% darker than Global Mean Reflectance (GMR) and C1 up to +4% brighter. Class 2 (C2) is the darkest class (-5% GMR), and it is found mostly in craters interiors. machine learningClass 3 (C3) is the brightest (+5% GMR) and it is found on the the equatorial bulge, but interrupted by Urashima, Momotaro, Kintaro and Kolobock craters. Class 4 and 5 (C4/C5) are two different trend of intermediate terrains. Those are the closest to GMR with a 2% variation around GMR. C4 is mostly found in the north, where C5 in the south, with substantial outcrops in the other hemisphere. The most interesting difference is that C5 follows the global trend of being slightly bluer than GMR between 1.9 um and 2.5 um, but C4 shows an inverted trend, being redder then GMR. In conclusion, we find an automated approach to extract spatially coherent region on Ryugu surface based only on spectral data using almost the whole NIRS3 spectral range. Those classes show a significant spatial correlation with geomorphological feature and different spectral trends.

Launched onboard the BepiColombo Mercury Planetary Orbiter (MPO) in October 2018, the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) is on its way to planet Mercury. MERTIS consists of a push-broom IR-spectrometer (TIS) and a radiometer (TIR), which operate in the wavelength regions of 7-14 μm and 7-40 μm, respectively. This wavelength region is characterized by several diagnostic spectral signatures: the Christiansen feature (CF), Reststrahlen bands (RB), and the Transparency feature (TF), which will allow us to identify and map rock-forming silicates, sulfides as well as other minerals. Thus, the instrument is particularly well-suited to study the mineralogy and composition of the hermean surface at a spatial resolution of about 500 m globally and better than 500 m for approximately 5-10% of the surface. The instrument is fully functional onboard the BepiColombo spacecraft and exceeds all requirements (e.g., mass, power, performance). To prepare for the science phase at Mercury, the team developed an innovative operations plan to maximize the scientific output while at the same time saving spacecraft resources (e.g., data downlink). The upcoming fly-bys will be excellent opportunities to further test and adapt our software and operational procedures. In summary, the team is undertaking action at multiple levels, including performing a comprehensive suite of spectroscopic measurements in our laboratories on relevant analog materials, performing extensive spectral modeling, examining space weathering effects, and modeling the thermal behavior of the hermean surface.

The Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) is part of the ESA BepiColombo Mercury Planetary Orbiter (MPO) payload and consists of a push-broom IR-spectrometer (-TIS) and a radiometer (-TIR) [1]. MERTIS-TIS and -TIR make use of the same optics, electronics, and inflight calibration components [2, 3]. MERTIS-TIS operates at wavelengths of 7-14 µm, has 78 spectral channels, and a spectral resolution of λ/∆λ=78-156. The radiometer operates between 7 and 40 µm with 2 spectral channels. Depending on surface characteristics, MERTIS spectral resolution is adapted to optimize the S/R ratio. Thus, the instrument is capable of resolving weak spectral bands with less than 1% contrast. During the long cruise to Mercury, and before its arrival on December 5th 2025, BepiColombo will perform 9 flybys: among them, the Earth/Moon flyby on April 10 th 2020. Due to the flight configuration, not all the instruments onboard BepiColombo are able to operate during cruise and flybys. Among the instruments that can operate is MERTIS. The MERTIS imaging spectrometer will provide the first hyperspectral observation of the Moon in the thermal infrared (TIR) wavelength range from space. At the Planetary Spectroscopy Laboratory (PSL) of DLR in Berlin, a spectral library for lunar analog rocks in the TIR spectral range, measured under simulated Moon surface conditions, has been built to help the interpretation of MERTIS’ Moon spectra.

The project aims to a prototypical system for structured storage and visualization of planetary data compiled and developed within planetary institutions.

We studied the effect of graphite on reflectance and emissivity spectra of pure minerals, chosen among a list of mercury analogues, when mixed with 5% graphite.