Publications by authors named "Maria G Bianco"

Essential Tremor (ET) is characterized by action tremor often associated with resting tremor (rET). Although previous studies have identified widespread brain white matter (WM) alterations in ET patients, differences between ET and rET have been less explored. In this study we employed differential tractography to investigate WM microstructural alterations in these tremor disorders.

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During the time-course of cognitive decline, Behavioral and Psychological Symptoms of Dementia (BPSD) may arise, negatively impacting the outcomes. The aim of this single center, longitudinal study was to evaluate the correlation between frailty and BPSD in a population of older patients with dementia. BPSD were classified into three clusters: "mood/apathy" (depression, apathy, sleep disturbances, appetite disturbances), "psychosis" (delusions, hallucinations, and anxiety), and "hyperactivity" (agitation, elation, motor aberrant behavior, irritability, disinhibition).

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Article Synopsis
  • Differentiating between progressive supranuclear palsy (PSP) and Parkinson's disease (PD) is difficult due to similar symptoms, prompting a search for reliable biomarkers.
  • Researchers analyzed serum samples from patients and healthy controls using a proximity elongation assay (PEA) and machine learning techniques to identify key protein differences, leading to the discovery of five promising proteins.
  • Notably, levels of TFF3, CPB1, and OPG varied between the two conditions, but ELISA tests revealed no differences in the three most significant biomarkers, raising concerns about the reliability of translating proteomic data into clinical applications.
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Introduction: Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data.

Methods: We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC).

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Introduction: Differentiating Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) may be clinically challenging. In this study, we explored the performance of machine learning models based on MR imaging and blood molecular biomarkers in distinguishing between these two neurodegenerative diseases.

Methods: Twenty-eight PSP patients, 46 PD patients and 60 control subjects (HC) were consecutively enrolled in the study.

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Objective: To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET.

Methods: We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec).

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Background: Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis.

Objective: In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches.

Methods: We consecutively enrolled 142 PD patients and 45 control subjects.

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Background And Aims: The management of complications of arteriovenous fistula (AVF) for hemodialysis, principally stenosis, remains a major challenge for clinicians with a substantial impact on health resources. Stenosis not infrequently preludes to thrombotic events with the loss of AVF functionality. A functioning AVF, when listened by a stethoscope, has a continuous systolic-diastolic low-frequency murmur, while with stenosis, the frequency of the murmur increases and the duration of diastolic component decreases, disappearing in severe stenosis.

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The decompensation trajectory check is a basic step to assess the clinical course and to plan future therapy in hospitalized patients with acute decompensated heart failure (ADHF). Due to the atypical presentation and clinical complexity, trajectory checks can be challenging in older patients with acute HF. Point-of-care ultrasound (POCUS) has proved to be helpful in the clinical decision-making of patients with dyspnea; however, to date, no study has attempted to verify its role in predicting determinants of ADHF in-hospital worsening.

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Random Survival Forests (RSF) has recently showed better performance than statistical survival methods as Cox proportional hazard (CPH) in predicting conversion risk from mild cognitive impairment (MCI) to Alzheimer's disease (AD). However, RSF application in real-world clinical setting is still limited due to its black-box nature.For this reason, we aimed at providing a comprehensive study of RSF explainability with SHapley Additive exPlanations (SHAP) on biomarkers of stable and progressive patients (sMCI and pMCI) from Alzheimer's Disease Neuroimaging Initiative.

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This paper reports the proceedings of a meeting convened by the Research Group on Thoracic Ultrasound in Older People of the Italian Society of Gerontology and Geriatrics, to discuss the current state-of-the-art of clinical research in the field of geriatric thoracic ultrasound and identify unmet research needs and potential areas of development. In the last decade, point-of-care thoracic ultrasound has entered clinical practice for diagnosis and management of several respiratory illnesses, such as bacterial and viral pneumonia, pleural effusion, acute heart failure, and pneumothorax, especially in the emergency-urgency setting. Very few studies, however, have been specifically focused on older patients with frailty and multi-morbidity, who frequently exhibit complex clinical pictures needing multidimensional evaluation.

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Article Synopsis
  • Machine-learning techniques were used to predict poor outcomes in elderly heart failure patients by including factors like frailty and comorbidity, which previous studies hadn’t considered.
  • The study analyzed data from 571 older patients discharged for acute heart failure, using random forest analysis and clustering methods to identify distinct groups based on their frailty and comorbidity levels.
  • Four phenogroups were identified, with patients in certain clusters showing a significantly higher risk of death or readmission within six months, indicating the need for personalized care strategies in this population.
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Background: Differentiating Progressive supranuclear palsy-Richardson's syndrome (PSP-RS) from PSP-Parkinsonism (PSP-P) may be extremely challenging. In this study, we aimed to distinguish these two PSP phenotypes using MRI structural data.

Methods: Sixty-two PSP-RS, 40 PSP-P patients and 33 control subjects were enrolled.

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Objective: We aimed to identify the brain structures associated with postural instability (PI) in Progressive Supranuclear Palsy (PSP).

Methods: Forty-seven PSP patients and 45 control subjects were enrolled in this study. PI was assessed using the items 27 and 28 of the PSP rating scale (postural instability score, PIS).

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Introduction: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes.

Methods: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled.

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Introduction: The functional connectivity patterns in the brain are highly heritable; however, it is unclear how genetic factors influence the directionality of such "information flows." Studying the "directionality" of the brain functional connectivity and assessing how heritability modulates it can improve our understanding of the human connectome.

Methods: Here, we investigated the heritability of "directed" functional connections using a state-space formulation of Granger causality (GC), in conjunction with blind deconvolution methods accounting for local variability in the hemodynamic response function.

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High-intensity, low-frequency magnetic fields (MFs) have been widely used in the treatment of diseases and in drug delivery, even though they could induce structural changes in pharmacological molecules. Morphological changes in ketoprofen and KiOil were investigated through Fourier-transform infrared spectroscopy (FT-IR). Unsupervised principal component analysis was carried out for data clustering.

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Since sunlight is one of the most easily available and clean energy supplies, solar cell development and the improvement of its conversion efficiency represent a highly interesting topic. Superficial light reflection is one of the limiting factors of the photovoltaic cells (PV) efficiency. To this end, interfacial layer with anti-reflective properties reduces this phenomenon, improving the energy potentially available for transduction.

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Article Synopsis
  • This study looked at two brain diseases: Progressive Supranuclear Palsy (PSP) and Idiopathic Normal Pressure Hydrocephalus (iNPH), which can be hard to tell apart because they have similar symptoms.
  • Researchers used machine learning to analyze brain scans from patients with these diseases and compare them with healthy people.
  • They found that iNPH patients had more noticeable brain changes (like thinning in certain areas) than PSP patients, and the machine learning model was really good at telling the differences between the two diseases, which could help doctors make better decisions for treatment.
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The clinical differential diagnosis between Parkinson's disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field.

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Background: Imaging studies investigating cerebellar gray matter (GM) in essential tremor (ET) showed conflicting results. Moreover, no large study explored the cerebellum in ET patients with resting tremor (rET), a syndrome showing enhanced blink reflex recovery cycle (BRrc).

Objective: To investigate cerebellar GM in ET and rET patients using voxel-based morphometry (VBM) analysis.

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Article Synopsis
  • About 10% of patients diagnosed with Parkinson's disease have a condition called SWEDD, which shows no signs of dopamine deficits on imaging, challenging the PD diagnosis.
  • The study aimed to compare brain connectivity in patients with SWEDD to healthy controls using advanced imaging techniques like MRI and DAT-SPECT to better understand their brain networks.
  • Results indicated that SWEDD patients had altered connectivity patterns, showing increased and decreased connection strengths in specific brain pathways, highlighting the complexity of this syndrome and its relationship to various tremor disorders.*
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Background: Differentiating progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) is clinically challenging.

Objective: This study aimed to develop an automated Magnetic Resonance Parkinsonism Index 2.0 (MRPI 2.

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The demand of glucose monitoring devices and even of updated guidelines for the management of diabetic patients is dramatically increasing due to the progressive rise in the prevalence of diabetes mellitus and the need to prevent its complications. Even though the introduction of the first glucose sensor occurred decades ago, important advances both from the technological and clinical point of view have contributed to a substantial improvement in quality healthcare. This review aims to bring together purely technological and clinical aspects of interest in the field of glucose devices by proposing a roadmap in glucose monitoring and management of patients with diabetes.

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