Can Machine Learning predict therapeutic outcomes in affective and not affective psychosis? A systematic review and meta-analysis.

Machine learning (ML) could be useful in identifying reliable predictors of treatment response in affective and not affective psychoses, potentially helping to propose personalized interventions. In this systematic review and meta-analysis, we evaluated studies exploiting ML algorithms to predict the improvement of psychotic symptoms, cognition and quality of life in psychoses related to different treatments. We searched MEDLINE (PubMed), Web of Science, and PsycINFO databases updated until February 2024, identifying 64 articles published in English in peer-reviewed journals.

Spontaneous neural activity mediates the effect of adverse childhood experiences on negative cognitive styles in mood disorders: a multivariate approach.

Negative cognitive styles and spontaneous neural activity can reveal cognitive and neurobiological underpinnings of depression, related to poor clinical outcomes and worsened by Adverse Childhood Experiences (ACEs). This study examined the associations between ACEs, fractional Amplitude of Low Frequency Fluctuations (fALFF), and negative cognitive styles in Major Depressive Disorder (MDD) and Bipolar Disorder (BD). In a sample of 94 patients (48 MDD; 46 BD) and 35 matched HC, Canonical Correlation Analysis was used to assess the multivariate association between fALFF and ACEs, rated with the Childhood Trauma Questionnaire.

Differences in resting-state functional connectivity between depressed bipolar and major depressive disorder patients: A machine learning study.

Nearly 60 % of individuals with bipolar disorder (BD) are initially classified as major depressive disorder (MDD) patients, resulting in inappropriate drug treatment. Identifying reliable biomarkers for the differential diagnosis between MDD and BD patients may allow to define the best treatment option since the early phases. In this study, we deployed machine learning predictive models to classify 62 MDD and 63 BD patients with a current depressive episode from resting functional neuroimaging feature (rs-fMRI), including fractional amplitude of low-frequency fluctuations, regional homogeneity, atlas-based connectivity across 434 regions of interest, seed-based connectivity maps for 44 seeds, and 14 dual regression components.

Long term effect of COVID-19 on brain metabolism and connectivity.

Aims: After 3 years from the beginning of SARS-CoV-2 pandemic, a substantial proportion of affected patients still present at least one symptom after infection. Given that: magnetic resonance imaging studies up to two years after COVID-19 reported changes in white matter (WM) microstructure and in functional connectivity; WM associates with glutamate and N-acetyl-aspartate levels in BD; the link between cognitive impairment and WM integrity, the aim of the study was to investigate metabolites associations with alterations in structural and functional brain connectivity and cognition in 64 COVID-19 survivors and 33 healthy controls (HC).

Methods: We compared WM microstructure and metabolites levels between individuals recovering from COVID-19 and HCs.

In vitro models of the crosstalk between multiple myeloma and stromal cells recapitulate the mild NF-κB activation observed in vivo.

Multiple myeloma (MM) is linked to chronic NF-κB activity in myeloma cells, but this activity is generally considered a cell-autonomous property of the cancer cells. The precise extent of NF-κB activation and the contributions of the physical microenvironment and of cell-to-cell communications remain largely unknown. By quantitative immunofluorescence, we found that NF-κB is mildly and heterogeneously activated in a fraction of MM cells in human BMs, while only a minority of MM cells shows a strong activation.

Has climate change over the last ten years caused a banalisation of diatom communities in Cypriot streams?

To unveil possible changes in diatom communities in Cypriot streams over the last ten years or so, we selected samples from the years 2020, 2021, and 2022 for the "recent" dataset (N = 119) and samples from the years 2010 and 2011 for the "historical" dataset (N = 108). Biotic homogenization has become a truly global phenomenon. Here we show that, over the last ten years, in response to increased water temperature, conductivity, and discharge variability due to climate-change, Cypriot stream diatom communities include a higher number of trivial (= widespread, tolerant, and opportunistic), aerial, and thermophilic species, have reduced β-diversity and increased nestedness.

Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance.

An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy.

A machine learning pipeline for efficient differentiation between bipolar and major depressive disorder based on multimodal structural neuroimaging.

Due to the overlapping depressive symptomatology with major depressive disorder (MDD), 60% of patients with bipolar disorder (BD) are initially misdiagnosed, calling for the definition of reliable biomarkers that can support the diagnostic process. Here, we optimized a machine learning pipeline for the differentiation between depressed BD and MDD patients based on multimodal structural neuroimaging features. Diffusion tensor imaging (DTI) and T1-weighted magnetic resonance imaging (MRI) data were acquired for 282 depressed BD (n = 180) and MDD (n = 102) patients.

Evaluating the performance of large language models in haematopoietic stem cell transplantation decision-making.

In a first-of-its-kind study, we assessed the capabilities of large language models (LLMs) in making complex decisions in haematopoietic stem cell transplantation. The evaluation was conducted not only for Generative Pre-trained Transformer 4 (GPT-4) but also conducted on other artificial intelligence models: PaLm 2 and Llama-2. Using detailed haematological histories that include both clinical, molecular and donor data, we conducted a triple-blind survey to compare LLMs to haematology residents.

Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: A multimodal neuroimaging study.

Background: For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings.

Aims: To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample.

Brain correlates of subjective cognitive complaints in COVID-19 survivors: A multimodal magnetic resonance imaging study.

Cognitive impairment represents a leading residual symptom of COVID-19 infection, which lasts for months after the virus clearance. Up-to-date scientific reports documented a wide spectrum of brain changes in COVID-19 survivors following the illness's resolution, mainly related to neurological and neuropsychiatric consequences. Preliminary insights suggest abnormal brain metabolism, microstructure, and functionality as neural under-layer of post-acute cognitive dysfunction.

Cognitive remediation therapy for post-acute persistent cognitive deficits in COVID-19 survivors: A proof-of-concept study.

Cognitive impairments figure prominently in COVID-19 survivors. Cognitive remediation therapy (CRT) improves functional outcomes reducing long-term cognitive deficits in several neurological and psychiatric conditions. Our case-control study investigates the efficacy of a CRT programme administered to COVID-19 survivors in the post-acute phase of the illness.

Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysis.

Applying machine learning (ML) to objective markers may overcome prognosis uncertainty due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA-compliant meta-analysis provides new systematic evidence of the BD classification accuracy reached by different markers and ML algorithms. We focused on neuroimaging, electrophysiological techniques, peripheral biomarkers, genetic data, neuropsychological or clinical measures, and multimodal approaches.

CXCR4 engagement triggers CD47 internalization and antitumor immunization in a mouse model of mesothelioma.

Boosting antitumor immunity has emerged as a powerful strategy in cancer treatment. While releasing T-cell brakes has received most attention, tumor recognition by T cells is a pre-requisite. Radiotherapy and certain cytotoxic drugs induce the release of damage-associated molecular patterns, which promote tumor antigen cross-presentation and T-cell priming.

First Responders Shape a Prompt and Sharp NF-κB-Mediated Transcriptional Response to TNF-α.

Nuclear factor (NF)-κB controls the transcriptional response to inflammatory signals by translocating into the nucleus, but we lack a single-cell characterization of the resulting transcription dynamics. Here we show that upon tumor necrosis factor (TNF)-α transcription of NF-κB target genes is heterogeneous in individual cells but results in an average nascent transcription profile that is prompt (i.e.

Smoothed Particle Hydrodynamics multiphase modelling of an experimental microfluidic device for conformal coating of pancreatic islets.

The paper discusses a Smoothed Particle Hydrodynamics (SPH) model for the analysis of the multiphase flow occurring in an experimental microfluidic device for conformal coating of pancreatic islets with a biocompatible and permeable polymer. The proposed numerical model, based on a weakly-compressible SPH approach, accurately mimics the encapsulation process while assuring phase conservation, thus overcoming potential limitations of grid-based models. The proposed SPH model is a triphasic multi-phase model that allows one: (i) to reproduce the physics of islet conformal coating, including the effects of surface tension at the interface of the involved fluids and of the islet diameter; and (ii) to evaluate how modulation of process parameters influences the fluid dynamics within the microfluidic device and the resulting coating characteristics.

Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion.

Nuclear positioning within cells is important for multiple cellular processes in development and regeneration. The most intriguing example of nuclear positioning occurs during skeletal muscle differentiation. Muscle fibers (myofibers) are multinucleated cells formed by the fusion of muscle precursor cells (myoblasts) derived from muscle stem cells (satellite cells) that undergo proliferation and differentiation.

NF-κB, the Importance of Being Dynamic: Role and Insights in Cancer.

In this review, we aim at describing the results obtained in the past years on dynamics features defining NF-κB regulatory functions, as we believe that these developments might have a transformative effect on the way in which NF-κB involvement in cancer is studied. We will also describe technical aspects of the studies performed in this context, including the use of different cellular models, culture conditions, microscopy approaches and quantification of the imaging data, balancing their strengths and limitations and pointing out to common features and to some open questions. Our emphasis in the methodology will allow a critical overview of literature and will show how these cutting-edge approaches can contribute to shed light on the involvement of NF-κB deregulation in tumour onset and progression.

Development of a microfluidic platform for high-throughput screening of non-viral gene delivery vectors.

The grail of gene delivery is the development of delivery vectors as effective and non-cytotoxic as possible. In this regard, there is an urgent need of new tools for the straightforward and quantitative assessment of transfection efficiency and cytotoxicity simultaneously. We herein reported the development and validation of an easy-to-use lab-on-chip platform to perform cell transfection assays for unbiased, high-throughput selection of more and more effective gene delivery vectors by using two commercially sourced lipids, Lipofectamine 2000 and FuGene 6.

Regenerative medicine: Clinical applications and future perspectives.

After many years of basic research, regenerative medicine (RM) is now beginning to represent a valuable tool to cure several clinical conditions in both acute injuries and chronic diseases. The aim of this study is to update readers on current clinical applications of some selected organs and pathologies which may benefit from RM. An extensive literature research was performed using PubMed, Google and specialized journals.

Distribution and diversity of soil microfauna from East Antarctica: assessing the link between biotic and abiotic factors.

Terrestrial life in Antarctica has been described as some of the simplest on the planet, and mainly confined to soil microfaunal communities. Studies have suggested that the lack of diversity is due to extreme environmental conditions and thought to be driven by abiotic factors. In this study we investigated soil microfauna composition, abundance, and distribution in East Antarctica, and assessed correlations with soil geochemistry and environmental variables.

Ostreopsis cf. ovata bloom in the northern Adriatic Sea during summer 2009: ecology, molecular characterization and toxin profile.

Intense blooms of the benthic dinoflagellate Ostreopsis cf. ovata have occurred in the northern Adriatic Sea since 2006. These blooms are associated with noxious effects on human health and with the mortality of benthic organisms because of the production of palytoxin-like compounds.

Phenotype-genotype correlation: challenge of intestinal-type adenocarcinoma of the nasal cavity and paranasal sinuses.

Background: Intestinal-type adenocarcinoma (ITAC) of the nasal cavity and paranasal sinuses shows microscopic features indistinguishable from colorectal cancer. Our aim was to verify whether the morphologic resemblances mirror genetic profile similarities.

Methods: Twenty consecutive surgically treated ITAC cases, previously investigated for p16(INK4a) and TP53, were investigated for hMLH1, hMSH2, and beta-catenin immunoreactivity, and for adenomatous polyposis coli (APC), K-ras, and BRAF gene mutations.