Telerehabilitation: A Solution for Patients After Hip Fracture?

- Hip fracture is the most common cause of hospitalization in frail geriatric subjects due to osteoporosis and recurrent falls. The clinical practice guidelines for rehabilitation after surgery in patients with hip fractures recommend to start treatment early. However, the outbreak of SARS-CoV-2 pandemic between December 2019 and January 2020 forced to lockdown. Thus, telerehabilitation seemed the best solution to remote assistance. In this scenario, the aim of our study is to assess the effects of telerehabilitation and to clarify and rearrange the knowledge about its usability and feasibility in patients after hip fracture in emergency conditions, such as the pandemic of SARS-CoV-2. Three databases were systematically searched from caption to December 2023, considering only articles published in peer-reviewed journals, with the use of three macro-areas: 'telerehabilitation', 'remote rehabilitation' and 'hip fracture'. In the present review, 26 articles were considered eligible and 10 were included. Heterogeneous results were found due to the different characteristics of the patients recruited in the studies, designs and type of the studies, and reporting/conducting of the research. Also, the typologies of telerehabilitation provided were various. In conclusion, this review demonstrated that telerehabilitation is safe, effective and well tolerated from patients and seems to be not inferior to the conventional physiotherapy. It also plays a positive role in psychological rehabilitation, in the prevention of complications and in the maintenance of achieved goals. However, further studies are needed to guide the clinical practice in providing the better posology and typology of telerehabilitation.

A Set of Possible Markers for Monitoring Heart Failure and Cognitive Impairment Associated: A Review of Literature from the Past 5 Years.

BACKGROUND: Heart failure is an epidemiologically relevant disease because of the aging population and widespread lifestyles that promote it. In addition to the acute event, it is possible for the disease to become chronic with periodic flare-ups. It is essential to study pathology from a diagnostic and prognostic point of view and to identify parameters for effective monitoring. In addition, heart failure is associated with multiple comorbidities, including cognitive impairment, which is monitored clinically but not through specific biomarkers in these patients. The purpose of this review is to gather the most recent scientific evidence on a few possible biomarkers previously identified for monitoring heart failure and associated cognitive impairment. METHODS: We surveyed studies inherent to a set of previously identified markers, evaluating English-language articles from the past five years conducted in adult heart failure patient populations. We used the databases PubMed, Web of Sciences, and Cochrane Library for search studies, and we considered articles published in journals with an impact factor greater than five in the publication year. RESULTS: Among the biomarkers evaluated, a concordant indication for serial measurements for heart failure monitoring emerged only for interleukin-6. For the other markers, there is still little evidence available, which is interesting but sometimes conflicting. Interesting studies have also emerged for biomarkers of cognitive decline assessed in patients with heart failure, confirming the hypotheses of the increasingly studied heart-brain correlation. CONCLUSION: Certainly, further studies in large populations are needed to identify effective biomarkers for monitoring heart failure and associated cognitive impairment.

Wearable Technologies and AI at the Far Edge for Chronic Heart Failure Prevention and Management: A Systematic Review and Prospects.

Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors.

Healthcare worker burnout during the first COVID-19 lockdown in Italy: experiences from an intensive neurological rehabilitation unit.

OBJECTIVE: The study aim was to investigate the prevalence of behavioral symptoms and burnout in healthcare workers in an intensive neurological rehabilitation unit in Messina, Italy, during the first COVID-19 lockdown in Italy. METHODS: Forty-seven healthcare workers (including neurologists, physiatrists, nurses and rehabilitation therapists) were enrolled in this cross-sectional study from February 2020 to June 2020. Participants were administered the following psychometric tests to investigate burnout and related symptoms: the Maslach Burnout Inventory, which measures emotional exhaustion, depersonalization and reduced personal accomplishment; the Zung Self-Rating Depression Scale (SDS); the Pre-Sleep Arousal Scale (PSAS); the Dyadic Adjustment Scale; and the Buss-Perry Aggression Questionnaire (BPAQ). RESULTS: We found several correlations between test scores and burnout subdimensions. Emotional exhaustion was correlated with SDS (r = 0.67), PSAS-Cognitive (r = 0.67) and PSAS-Somatic (r = 0.70) scores, and moderately correlated with all BPAQ dimensions (r = 0.42). Depersonalization was moderately correlated with SDS (r = 0.54), PSAS-Cognitive (r = 0.53) and PSAS-Somatic (r = 0.50) scores. CONCLUSION: During the first COVID-19 lockdown in Italy, healthcare workers were more exposed to physical and mental exhaustion and burnout. Research evaluating organizational and system-level interventions to promote psychological well-being at work for healthcare workers are needed.

Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve.

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the "black-box" nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients' risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

In vivo probabilistic atlas of white matter tracts of the human subthalamic area combining track density imaging and optimized diffusion tractography.

The human subthalamic area is a region of high anatomical complexity, tightly packed with tiny fiber bundles. Some of them, including the pallidothalamic, cerebello-thalamic, and mammillothalamic tracts, are relevant targets in functional neurosurgery for various brain diseases. Diffusion-weighted imaging-based tractography has been suggested as a useful tool to map white matter pathways in the human brain in vivo and non-invasively, though the reconstruction of these specific fiber bundles is challenging due to their small dimensions and complex anatomy. To the best of our knowledge, a population-based, in vivo probabilistic atlas of subthalamic white matter tracts is still missing. In the present work, we devised an optimized tractography protocol for reproducible reconstruction of the tracts of subthalamic area in a large data sample from the Human Connectome Project repository. First, we leveraged the super-resolution properties and high anatomical detail provided by short tracks track-density imaging (stTDI) to identify the white matter bundles of the subthalamic area on a group-level template. Tracts identification on the stTDI template was also aided by visualization of histological sections of human specimens. Then, we employed this anatomical information to drive tractography at the subject-level, optimizing tracking parameters to maximize between-subject and within-subject similarities as well as anatomical accuracy. Finally, we gathered subject level tracts reconstructed with optimized tractography into a large-scale, normative population atlas. We suggest that this atlas could be useful in both clinical anatomy and functional neurosurgery settings, to improve our understanding of the complex morphology of this important brain region.

Feasibility, Usability, and Customer Satisfaction of the Tele-COVID19 Project, Sicilian Model.

Background and Objectives: In March 2020, COVID-19 pandemic affected the world. All countries, to limit viral transmission, imposed quarantine. This emergency exerted personal, social, economic, and psychological impact on people. For health systems, was needed to create alternative care pathways. Telemedicine can be helpful to reduce isolation, provide health care services, and monitor virus infections. Italian regions, including Sicily, have activated telemedicine services for management of patients with COVID-19. Objective: The purpose of study is to describe a Sicilian telemedicine model for management of COVID-19 patients, showing results on feasibility, usability and quality of service and patient satisfaction. Materials and Methods: This is a descriptive exploratory study on a telemedicine service for residents in Messina infected by COVID-19. It included monitoring of vital signs and specialist consultations (i.e., doctor, psychologists, social workers, and nutritionist biologists). Results: More than twenty percent (23.8%) of participants used tele-monitoring and tele-counselling services; 14.3% were only telemonitored. Participants judged positively telemedicine service (30% were quiet and 50% were very satisfied), as well as tool (70% were quiet and 10% were very satisfied). Telemonitoring had a low agreement (10% were slightly satisfied and 50% were neutral); tele-counselling had a high rate of satisfaction (40% quiet and 60% were very satisfied). Conclusions: This study showed that telemedicine model for Sicilian population affected by COVID-19 was feasible, easy to use and appreciated by patients. Our promising results allow us to assume that if in Sicily there was a return of the emergency, we would be ready to manage it This system can be the solution to remote management of these patients, to reduce isolation, provide health services, and monitor virus infections. The use of this technology should encourage future research to change the health care system and provides opportunities to ensure health and care for oneself and others.

White matter substrates of functional connectivity dynamics in the human brain.

The contribution of structural connectivity to functional connectivity dynamics is still far from being elucidated. Herein, we applied track-weighted dynamic functional connectivity (tw-dFC), a model integrating structural, functional, and dynamic connectivity, on high quality diffusion weighted imaging and resting-state fMRI data from two independent repositories. The tw-dFC maps were analyzed using independent component analysis, aiming at identifying spatially independent white matter components which support dynamic changes in functional connectivity. Each component consisted of a spatial map of white matter bundles that show consistent fluctuations in functional connectivity at their endpoints, and a time course representative of such functional activity. These components show high intra-subject, inter-subject, and inter-cohort reproducibility. We provided also converging evidence that functional information about white matter activity derived by this method can capture biologically meaningful features of brain connectivity organization, as well as predict higher-order cognitive performance.

Care models for mental health in a population of patients affected by COVID-19.

OBJECTIVE: Emergency psychological interventions are needed in patients with COVID-19. During the pandemic, psychological counseling services have been provided using online platforms to address adverse psychological impacts and symptoms in patients and the general population. We investigated the effects of telepsychotherapy on emotional well-being and psychological distress in patients affected by COVID-19. METHODS: Forty-five Sicilian patients who had contracted COVID-19 joined "Telecovid Sicilia" from March to June 2020. Participants completed self-assessment questionnaires and psychological testing to measure levels of anxiety, presence of depressive symptoms, and altered circadian rhythm with consequent sleep disorders and psychological distress. Individual telepsychotherapy services were provided for 1 hour, twice a week, for 16 sessions in total. RESULTS: We enrolled 45 patients (42.2% women). We found significant changes between baseline and the end of follow-up in all outcome measures, especially depression (χ2 (1) = 30.1; effect size [ES] = 0.82), anxiety (χ2 (1) = 37.4; ES = 0.91), and paranoid ideation (χ2 (1) = 5.6; ES = 0.35). The proportion of participants with sleep disorders decreased to 84.1% after intervention (χ2 (1) = 58.6; ES = 1.14). CONCLUSION: A telepsychotherapeutic approach showed promising effects on psychological symptoms, with significantly reduced patient anxiety and depression.

Humanoid Robot Use in Cognitive Rehabilitation of Patients with Severe Brain Injury: A Pilot Study.

Severe acquired brain injury (SABI) is a major global public health problem and a source of disability. A major contributor to disability after SABI is limited access to multidisciplinary rehabilitation, despite evidence of sustained functional gains, improved quality of life, increased return to work, and reduced need for long-term care. Twelve patients with a diagnosis of SABI were enrolled and equally divided into two groups: experimental and control. Patients in both groups underwent intensive neurorehabilitation according to the severity of their disabilities (motor, psycho-cognitive, and sensory deficits). However, in the experimental group, the treatment was performed by using a humanoid robot. At baseline, the two groups differed significantly only in Severe Impairment Battery (SIB) scores. Results showed that the experimental treatment had a higher effect than the traditional one on quality of life and mood. In conclusion, this pilot study provides evidence of the possible effects of relational and cognitive stimulation in more severely brain-injured patients.

Effect of MAO-B Inhibitors on Neurometabolic Profile of Patients Affected by Parkinson Disease: A Proton Magnetic Resonance Spectroscopy Study.

Parkinson's Disease (PD) is the most common neurodegenerative movement disorder whose treatment is symptomatic. No suitable methods for assessing the effects of dopaminergic drugs on disease progression in clinical trials have yet been provided. The aim of this longitudinal study is to evaluate the influence of rasagiline and selegiline on neurometabolic profile in de novo PD patients by using Proton Magnetic Resonance Spectroscopy (1H-MRS). We enrolled de novo PD patients who were divided into two groups of 20 patients each, according to the dopaminergic treatment prescribed at the baseline visit (rasagiline or selegiline). At the baseline visit and after 12 months, all patients underwent neurological evaluation as well as 1H-MRS. Forty healthy controls (HC) underwent 1H-MRS at baseline and after 12 months. PD patients, compared to HC, showed significantly lower concentrations of NAA in the motor cortex, while the Cho levels showed a decreasing trend. After 12 months of therapy, the 1H-MRS study revealed that rasagiline and selegiline in a similar way were able to restore the NAA levels to values similar to those of HC. In addition, this neurometabolic change showed a correlation with UPDRS-III scores. This is the first longitudinal study that provides preliminary evidence that 1H-MRS may be a suitable method to evaluate objectively the influence of MAO-B inhibitors on the neurometabolic profile of PD patients. These results could open a new scenario on the hypothesis of a drug-induced slowing effect of PD progression.

Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation.

The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson's Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories. We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. All pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. On the other hand, higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

Does cybersickness affect virtual reality training using the Computer Assisted Rehabilitation Environment (CAREN)? Preliminary results from a case-control study in Parkinson's disease.

INTRODUCTION AND OBJECTIVE: This pilot study aimed to evaluate whether and to what extent cybersickness (CS) may affect a rehabilitation program using the Computer-assisted Rehabilitation Environment (CAREN), a virtual reality (VR) computer-assisted device for clinical rehabilitation. METHODS: The study was carried out on 30 subjects, 15 patients with Parkinson's Disease (PD) and 15 healthy controls (HC), which underwent a set of four exergames programmed by our team for PD rehabilitation training. RESULTS: All participants completed the Motion Sickness Susceptibility Questionnaire Short-form (MSSQ) before the training and the Motion Symptoms Assessment Questionnaire (MSAQ) immediately after a single CAREN session. Overall, mean MSAQ scores remained low after the session, suggesting that the users did not experience severe discomfort. We found no significant difference in MSAQ scores between the two groups, while there was a statistically significant difference for the subsection of MSAQ regarding the peripheral symptoms (i.e. sweating, cold sweating, feeling warm), which were higher in HC. Moreover, the results highlighted some correlation between MSSQ and MSAQ. Gastrointestinal symptoms in PD, as well as MSSQ and sopite-related symptoms in HC, were also correlated with susceptibility to CS. CONCLUSIONS: As CS is rarely reported after CAREN, this and similar devices may be considered comfortable and safe for patients' rehabilitation involving VR training, including PD persons.

Striatal topographical organization: Bridging the gap between molecules, connectivity and behavior.

The striatum represents the major hub of the basal ganglia, receiving projections from the entire cerebral cortex and it is assumed to play a key role in a wide array of complex behavioral tasks. Despite being extensively investigated during the last decades, the topographical organization of the striatum is not well understood yet. Ongoing efforts in neuroscience are focused on analyzing striatal anatomy at different spatial scales, to understand how structure relates to function and how derangements of this organization are involved in various neuropsychiatric diseases. While being subdivided at the macroscale level into dorsal and ventral divisions, at a mesoscale level the striatum represents an anatomical continuum sharing the same cellular makeup. At the same time, it is now increasingly ascertained that different striatal compartments show subtle histochemical differences, and their neurons exhibit peculiar patterns of gene expression, supporting functional diversity across the whole basal ganglia circuitry. Such diversity is further supported by afferent connections which are heterogenous both anatomically, as they originate from distributed cortical areas and subcortical structures, and biochemically, as they involve a variety of neurotransmitters. Specifically, the cortico-striatal projection system is topographically organized delineating a functional organization which is maintained throughout the basal ganglia, subserving motor, cognitive and affective behavioral functions. While such functional heterogeneity has been firstly conceptualized as a tripartite organization, with sharply defined limbic, associative and sensorimotor territories within the striatum, it has been proposed that such territories are more likely to fade into one another, delineating a gradient-like organization along medio-lateral and ventro-dorsal axes. However, the molecular and cellular underpinnings of such organization are less understood, and their relations to behavior remains an open question, especially in humans. In this review we aimed at summarizing the available knowledge on striatal organization, especially focusing on how it links structure to function and its alterations in neuropsychiatric diseases. We examined studies conducted on different species, covering a wide array of different methodologies: from tract-tracing and immunohistochemistry to neuroimaging and transcriptomic experiments, aimed at bridging the gap between macroscopic and molecular levels.

Transcriptomic Data Analysis Reveals a Down-Expression of Galectin-8 in Schizophrenia Hippocampus.

Schizophrenia (SCZ) is a severe psychiatric disorder with several clinical manifestations that include cognitive dysfunction, decline in motivation, and psychosis. Current standards of care treatment with antipsychotic agents are often ineffective in controlling the disease, as only one-third of SCZ patients respond to medications. The mechanisms underlying the pathogenesis of SCZ remain elusive. It is believed that inflammatory processes may play a role as contributing factors to the etiology of SCZ. Galectins are a family of ß-galactoside-binding lectins that contribute to the regulation of immune and inflammatory responses, and previous reports have shown their role in the maintenance of central nervous system (CNS) homeostasis and neuroinflammation. In the current study, we evaluated the expression levels of the galectin gene family in post-mortem samples of the hippocampus, associative striatum, and dorsolateral prefrontal cortex from SCZ patients. We found a significant downregulation of LGALS8 (Galectin-8) in the hippocampus of SCZ patients as compared to otherwise healthy donors. Interestingly, the reduction of LGALS8 was disease-specific, as no modulation was observed in the hippocampus from bipolar nor major depressive disorder (MDD) patients. Prediction analysis identified TBL1XR1, BRF2, and TAF7 as potential transcription factors controlling LGALS8 expression. In addition, MIR3681HG and MIR4296 were negatively correlated with LGALS8 expression, suggesting a role for epigenetics in the regulation of LGALS8 levels. On the other hand, no differences in the methylation levels of LGALS8 were observed between SCZ and matched control hippocampus. Finally, ontology analysis of the genes negatively correlated with LGALS8 expression identified an enrichment of the NGF-stimulated transcription pathway and of the oligodendrocyte differentiation pathway. Our study identified LGALS8 as a disease-specific gene, characterizing SCZ patients, that may in the future be exploited as a potential therapeutic target.

The Cerebellar Dopaminergic System.

In the central nervous system (CNS), dopamine (DA) is involved in motor and cognitive functions. Although the cerebellum is not been considered an elective dopaminergic region, studies attributed to it a critical role in dopamine deficit-related neurological and psychiatric disorders [e.g., Parkinson's disease (PD) and schizophrenia (SCZ)]. Data on the cerebellar dopaminergic neuronal system are still lacking. Nevertheless, biochemical studies detected in the mammalians cerebellum high dopamine levels, while chemical neuroanatomy studies revealed the presence of midbrain dopaminergic afferents to the cerebellum as well as wide distribution of the dopaminergic receptor subtypes (DRD1-DRD5). The present review summarizes the data on the cerebellar dopaminergic system including its involvement in associative and projective circuits. Furthermore, this study also briefly discusses the role of the cerebellar dopaminergic system in some neurologic and psychiatric disorders and suggests its potential involvement as a target in pharmacologic and non-pharmacologic treatments.

Ventral intermediate nucleus structural connectivity-derived segmentation: anatomical reliability and variability.

The Ventral intermediate nucleus (Vim) of thalamus is the most targeted structure for the treatment of drug-refractory tremors. Since methodological differences across existing studies are remarkable and no gold-standard pipeline is available, in this study, we tested different parcellation pipelines for tractography-derived putative Vim identification. Thalamic parcellation was performed on a high quality, multi-shell dataset and a downsampled, clinical-like dataset using two different diffusion signal modeling techniques and two different voxel classification criteria, thus implementing a total of four parcellation pipelines. The most reliable pipeline in terms of inter-subject variability has been picked and parcels putatively corresponding to motor thalamic nuclei have been selected by calculating similarity with a histology-based mask of Vim. Then, spatial relations with optimal stimulation points for the treatment of essential tremor have been quantified. Finally, effect of data quality and parcellation pipelines on a volumetric index of connectivity clusters has been assessed. We found that the pipeline characterized by higher-order signal modeling and threshold-based voxel classification criteria was the most reliable in terms of inter-subject variability regardless data quality. The maps putatively corresponding to Vim were those derived by precentral and dentate nucleus-thalamic connectivity. However, tractography-derived functional targets showed remarkable differences in shape and sizes when compared to a ground truth model based on histochemical staining on seriate sections of human brain. Thalamic voxels connected to contralateral dentate nucleus resulted to be the closest to literature-derived stimulation points for essential tremor but at the same time showing the most remarkable inter-subject variability. Finally, the volume of connectivity parcels resulted to be significantly influenced by data quality and parcellation pipelines. Hence, caution is warranted when performing thalamic connectivity-based segmentation for stereotactic targeting.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

In Vivo Super-Resolution Track-Density Imaging for Thalamic Nuclei Identification.

The development of novel techniques for the in vivo, non-invasive visualization and identification of thalamic nuclei has represented a major challenge for human neuroimaging research in the last decades. Thalamic nuclei have important implications in various key aspects of brain physiology and many of them show selective alterations in various neurologic and psychiatric disorders. In addition, both surgical stimulation and ablation of specific thalamic nuclei have been proven to be useful for the treatment of different neuropsychiatric diseases. The present work aimed at describing a novel protocol for histologically guided delineation of thalamic nuclei based on short-tracks track-density imaging (stTDI), which is an advanced imaging technique exploiting high angular resolution diffusion tractography to obtain super-resolved white matter maps. We demonstrated that this approach can identify up to 13 distinct thalamic nuclei bilaterally with very high inter-subject (ICC: 0.996, 95% CI: 0.993-0.998) and inter-rater (ICC:0.981; 95% CI:0.963-0.989) reliability, and that both subject-based and group-level thalamic parcellation show a fair share of similarity to a recent standard-space histological thalamic atlas. Finally, we showed that stTDI-derived thalamic maps can be successfully employed to study structural and functional connectivity of the thalamus and may have potential implications both for basic and translational research, as well as for presurgical planning purposes.