Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form.

Background And Objective: Detecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decision-making processes in the treatment of this malignancy. Though several machine learning models analyzing both clinical and histopathological information have been developed in literature to address this task, these approaches turned out to be unsuitable for describing this problem.

Methods: In this study, we designed a novel artificial intelligence-based approach which converts clinical information into an image-form to be analyzed through Convolutional Neural Networks.

Efficacy of a Food Supplement Containing LA14, Peptides, and a Multivitamin Complex in Improving Gastroesophageal Reflux Disease-Related Outcomes and Quality of Life of Subjects Showing Mild-to-Moderate Gastroesophageal Reflux Disease.

Dietary interventions represent an interesting alternative to pharmacological treatments for improving the quality of life (QoL) of subjects suffering from gastroesophageal reflux disease (GERD). This randomized, double-blind, placebo-controlled study aimed to evaluate the efficacy of a food supplement (FS) containing a probiotic strain, bioactive peptides, and vitamins in relieving heartburn/dyspeptic symptoms in subjects with mild-to-moderate GERD. Fifty-six adult participants were randomly assigned to receive the placebo or the active FS for 28 days.

A Novel Metric for Alzheimer's Disease Detection Based on Brain Complexity Analysis via Multiscale Fuzzy Entropy.

Alzheimer's disease (AD) is a neurodegenerative brain disorder that affects cognitive functioning and memory. Current diagnostic tools, including neuroimaging techniques and cognitive questionnaires, present limitations such as invasiveness, high costs, and subjectivity. In recent years, interest has grown in using electroencephalography (EEG) for AD detection due to its non-invasiveness, low cost, and high temporal resolution.

Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI.

Type 1 diabetes mellitus (T1DM) is characterized by insulin deficiency and blood sugar control issues. The state-of-the-art solution is the artificial pancreas (AP), which integrates basal insulin delivery and glucose monitoring. However, APs are unable to manage postprandial glucose response (PGR) due to limited knowledge of its determinants, requiring additional information for accurate bolus delivery, such as estimated carbohydrate intake.

Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence.

Non-Small cell lung cancer (NSCLC) is one of the most dangerous cancers, with 85% of all new lung cancer diagnoses and a 30-55% of recurrence rate after surgery. Thus, an accurate prediction of recurrence risk in NSCLC patients during diagnosis could be essential to drive targeted therapies preventing either overtreatment or undertreatment of cancer patients. The radiomic analysis of CT images has already shown great potential in solving this task; specifically, Convolutional Neural Networks (CNNs) have already been proposed providing good performances.

Prognostic power assessment of clinical parameters to predict neoadjuvant response therapy in HER2-positive breast cancer patients: A machine learning approach.

Background: About 15%-20% of breast cancer (BC) cases is classified as Human Epidermal growth factor Receptor type 2 (HER2) positive. The Neoadjuvant chemotherapy (NAC) was initially introduced for locally advanced and inflammatory BC patients to allow a less extensive surgical resection, whereas now it represents the current standard for early-stage and operable BC. However, only 20%-40% of patients achieve pathologic complete response (pCR).

Infrared Thermography for Real-Time Assessment of the Effectiveness of Scoliosis Braces.

This work proposes an innovative method, based on the use of low-cost infrared thermography (IRT) instrumentation, to assess in real time the effectiveness of scoliosis braces. Establishing the effectiveness of scoliosis braces means deciding whether the pressure exerted by the brace on the patient's back is adequate for the intended therapeutic purpose. Traditionally, the evaluation of brace effectiveness relies on empirical, qualitative assessments carried out by orthopedists during routine follow-up examinations.

Co-Expression of Podoplanin and CD44 in Proliferative Vitreoretinopathy Epiretinal Membranes.

Epiretinal membranes (ERMs) are sheets of tissue that pathologically develop in the vitreoretinal interface leading to progressive vision loss. They are formed by different cell types and by an exuberant deposition of extracellular matrix proteins. Recently, we reviewed ERMs' extracellular matrix components to better understand molecular dysfunctions that trigger and fuel the onset and development of this disease.

Uncovering the Correlation between COVID-19 and Neurodegenerative Processes: Toward a New Approach Based on EEG Entropic Analysis.

COVID-19 is an ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although it primarily attacks the respiratory tract, inflammation can also affect the central nervous system (CNS), leading to chemo-sensory deficits such as anosmia and serious cognitive problems. Recent studies have shown a connection between COVID-19 and neurodegenerative diseases, particularly Alzheimer's disease (AD).

Assessment of small intestinal bacterial overgrowth and methane production in patients on chronic proton-pump inhibitor treatment: prevalence and role of rifaximin in its management in primary care.

Background: Although proton pump inhibitor (PPI) drugs have considered able to induce small intestinal bacterial overgrowth (SIBO), no data are so far available from primary care (PC). We assessed the prevalence of SIBO and methane (CH4) production consequent to chronic PPI therapy using Lactulose Breath Test (LBT). Secondary aim was to explore the possible role of rifaximin in treating PPI-induced SIBO patients.

Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning.

An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon's subjective assessment. As such, this leads to assessments that are strongly experience-dependent.

Untangling the Extracellular Matrix of Idiopathic Epiretinal Membrane: A Path Winding among Structure, Interactomics and Translational Medicine.

Idiopathic epiretinal membranes (iERMs) are fibrocellular sheets of tissue that develop at the vitreoretinal interface. The iERMs consist of cells and an extracellular matrix (ECM) formed by a complex array of structural proteins and a large number of proteins that regulate cell-matrix interaction, matrix deposition and remodelling. Many components of the ECM tend to produce a layered pattern that can influence the tractional properties of the membranes.

Translational Gap between Guidelines and Clinical Medicine: The Viewpoint of Italian General Practitioners in the Management of IBS.

Irritable bowel syndrome (IBS) guidelines are generally developed by experts, with the possibility of a translational gap in clinical medicine. The aim of our study was to assess an Italian group of general practitioners (GPs) for their awareness and use of criteria for the diagnosis and management of IBS. For this purpose, a survey was carried out involving 235 GPs, divided into two groups according to their years of activity: 65 “junior general practitioners” (JGPs) (≤10 years) and 170 “senior general practitioners” (SGPs) (>10 years).

Assessment and Scientific Progresses in the Analysis of Olfactory Evoked Potentials.

The human sense of smell is important for many vital functions, but with the current state of the art, there is a lack of objective and non-invasive methods for smell disorder diagnostics. In recent years, increasing attention is being paid to olfactory event-related potentials (OERPs) of the brain, as a viable tool for the objective assessment of olfactory dysfunctions. The aim of this review is to describe the main features of OERPs signals, the most widely used recording and processing techniques, and the scientific progress and relevance in the use of OERPs in many important application fields.

Performance and Usability Evaluation of an Extended Reality Platform to Monitor Patient's Health during Surgical Procedures.

An extended-reality (XR) platform for real-time monitoring of patients' health during surgical procedures is proposed. The proposed system provides real-time access to a comprehensive set of patients' information, which are made promptly available to the surgical team in the operating room (OR). In particular, the XR platform supports the medical staff by automatically acquiring the patient's vitals from the operating room instrumentation and displaying them in real-time directly on an XR headset.

Treatment of Paget's disease of the bone: long-term effect of neridronate in a real-life setting.

Background: Bisphosphonates represent the gold standard treatment for Paget's disease of bone. Neridronate is a potent bisphosphonate, licensed in Italy for this use, but only few clinical trials have investigated the outcomes of this treatment. The aim of our study was to report our long-term experience with intravenous Neridronate.

Soft Transducer for Patient's Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection.

This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In particular, first, the soft transducer measures hypertension-related vitals (heart rate, oxygen saturation and systolic/diastolic pressure) and sends the data to a remote database (which can be easily consulted both by the patient and the physician).

Craniopharyngioma, Chronotypes and Metabolic Risk Profile.

Aim: To investigate the potential association among Craniopharyngioma (CP), chronotypes and metabolic risk profile.

Subjects And Methods: The study population included 28 patients (46.4% males; 42.

Responding to COVID-19 through an integrated primary care/behavioral health program.

Background and Implementation: Novel coronavirus disease 2019 (COVID-19) has presented unique challenges for patients and health care systems, including a surge in behavioral health (BH) needs. A community teaching public hospital system in Massachusetts (MA) whose 13 primary care (PC) clinics serve a diverse patient population, has developed a model for Primary Care Behavioral Health Integration (PCBHI) to provide brief, evidence-based interventions to patients in PC. In response to COVID-19, the system developed an intensive community management strategy to care for patients with COVID-19 outside of the hospital, and its PCBHI program adapted alongside this strategy to provide rapid support to patients in emotional distress.

LRG1 Expression Is Elevated in the Eyes of Patients with Neovascular Age-Related Macular Degeneration.

Leucine-rich a-2-glycoprotein 1 (LRG1) is a candidate therapeutic target for treating the neovascular form of age-related macular degeneration (nvAMD). In this study we examined the expression of LRG1 in eyes of nvAMD patients. Choroidal neovascular membranes (CNVMs) from patients who underwent submacular surgery for retinal pigment epithelium-choroid graft transplantation were collected from 5 nvAMD patients without any prior intravitreal anti-VEGF injection, and from six patients who received intravitreal anti-VEGF injections before surgery.

Combined Punctual and Diffused Monitoring of Concrete Structures Based on Dielectric Measurements.

This work presents a microwave reflectometry-based system for monitoring large concrete structures (during the curing process and also while the structure is in use), through the combined use of punctual and diffused sensing elements. In particular, the adoption of punctual probes on a reference concrete specimen allows the development of an innovative and accurate calibration procedure, useful to obtain the value of the water content on a larger structure made of the same material. Additionally, a wire-like diffused sensing element can be permanently embedded in buildings and used to monitor the structure along the entire length of the sensing element.

Real-world performance and accuracy of stress echocardiography: the EVAREST observational multi-centre study.

Aims: Stress echocardiography is widely used to identify obstructive coronary artery disease (CAD). High accuracy is reported in expert hands but is dependent on operator training and image quality. The EVAREST study provides UK-wide data to evaluate real-world performance and accuracy of stress echocardiography.

The extracellular matrix complexity of idiopathic epiretinal membranes and the bilaminar arrangement of the associated internal limiting membrane in the posterior retina.

Purpose: To study the composition of the internal limiting membrane (ILM) of the retina, the extracellular matrix (ECM) of idiopathic epiretinal membranes (iERMs), and the relationships occurring between the two membranes.

Methods: Forty-six iERMs, 24 of them associated with the ILM, were collected and included in this study. The investigation has been carried out by immunofluorescence and confocal microscopy on glutaraldehyde- and osmium-fixed epon-embedded samples and on frozen samples.