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Filter by:BACKGROUND: Binge eating disorder (BED) is the worldwide most-prevalent eating disorder. It is associated with psychiatric comorbidities and obesity, a high impact in life functioning, and high morbidity and mortality. First symptoms appear frequently in youths, who most commonly present incomplete (subthreshold) criteria for BED (precursor forms, PREC-BED). While some subjects will evolve from PREC-BED to BED, there is no gold standard to identify the clinical evolution. Information from prior studies suggest early alterations in reward and inhibitory brain circuits in PREC-BED may predict increased vulnerability or resilience to develop BED. Tools based on MRI brain connectivity analyses (MRI-BC), built on robust and interpretable connectivity whole-brain models, have proven successful in diagnostic classification and predicting certain clinical outcomes. OBJECTIVES: To study MRI-BC diagnostic markers of PREC-BED and to explore prognosis at 1 year of follow-up in a sample of adolescents with obesity (12-17 years old). METHODS: A) Transversal analytical design: 3-group (n=34 per group) comparison of neuroimaging (MRI-BC), neurocognitive and clinical markers in adolescents with obesity and i) BED, ii) PREC-BED, iii) no BED nor PREC-BED (Healthy group, HC). B) Longitudinal analytical design, pilot, exploratory: adolescents with PREC-BED will be evaluated in clinical and neurocognitive variables at 1 year. Baseline brain neuroimaging variables (alone and in combination with clinical and neurocognitive variables) will be analyzed as predictors of clinical prognosis, including conversion to BED.
To evaluate the efficacy and safety of LM108 plus toripalimab plusnab-paclitaxel or eribulin as first-line or post-line treatment in patients with metastatic triple-negative breast cancer.
The goal of this randomized, crossover, clinical trial is to link: 1) gastrointestinal motility patterns induced by acute consumption of whole and refined grains, 2) enteric microbial production of bioactive metabolites, and 3) circulating postprandial appearance of metabolites important to cardiometabolic health including glucose, triglycerides, and cholesterol. Participants will be asked to consume a Smartpill monitoring device that records metrics of gastrointestinal motility in response to whole or refined grains, monitor cardiometabolic metabolties over an 8 hour postprandial window, and provide a fecal sample for microbiome-related analyses.
The goal of this observational study is to learn about the risk factors of lifestyle, medication and sexual habits in adult chronic prostatitis / chronic pelvic pain syndrome patients. The main questions it aims to answer are: - Is lifestyle, medication, and sexual habits related to chronic prostatitis / chronic pelvic pain syndrome - Is there any medication available to protect men from chronic prostatitis / chronic pelvic pain syndrome. Participants will: - Independently receive a survey questionnaire on lifestyle, medication, and sexual habits. - Symptomatic individuals will undergo additional prostate fluid examination for diagnosis. Researchers will compare healthy adult males to see if there are differences on lifestyle, medication and sexual habits between the two groups.
The goal of this observational study is to find out if artificial intelligence (AI) can accurately predict acute coronary syndrome (ACS) using data on white blood cells in adults. The main question it aims to answer is: - Can AI algorithms based on white blood cell data predict ACS with accuracy comparable to that of high-sensitivity cardiac troponin (hs-cTn)? Researchers will look at how the AI model's predictions stack up against the standard hs-cTn blood tests to see which is more accurate in diagnosing ACS. Participants in this study will have already had blood tests as part of their usual care. Their previously collected health information and blood test results will be used to help train and test the AI algorithms. Participants will not undergo any new procedures for the study itself.
This is a real world data collection observational study at a single site. There are both prospective and retrospective cohorts. The study will examine the safety and effectiveness of the Synergy cervical disc system in patients with degenerative cervical disc disease.
Congenital heart disease (CHD) is the most common congenital disease in children. The early detection, diagnosis and treatment of CHD in children is of great significance to improve the prognosis and reduce the mortality of children, but the current screening methods have limitations. Electrocardiogram (ECG), as an economical and rapid means of heart disease detection, has a very important value in the auxiliary diagnosis of CHD.Big data and deep learning technologies in artificial intelligence (AI) have shown great potential in the medical field. The advent of the big data era provides rich data resources for the in-depth study of CHD ECG signals in children. The development of deep learning technology, especially the breakthrough in the field of image recognition, provides a strong technical support for the intelligent analysis of electrocardiogram. The particularity of children electrocardiogram requires the development of a special algorithm model. At present, the research on the application of deep learning models to identify children's electrocardiograms is limited, and the training and verification from large data sets are lacking. Based on the Chinese Congenital Heart Disease Collaborative Research Network, this project aims to integrate data and deep learning technology to develop a set of intelligent electrocardiogram assisted diagnosis system (CHD-ECG AI system) suitable for children with CHD, so as to improve the early detection rate of CHD and improve the efficiency of congenital heart disease screening.
The investigators plan to establish a dedicated network of Italian Hematologic Departments interconnected with the Amyloidosis Research and Treatment Center in Pavia to: 1. Implement a biomarker-based screening strategy to promote early diagnosis of AL amyloidosis among at-risk patients, including patients with monoclonal gammopathy of undetermined significance, MGUS, and altered free light chain ratio (aFLCR), and patients with smoldering multiple myeloma (SMM) 2. Expedite and facilitate patients' referral and their enrollment in ongoing pre-clinical/clinical studies, also to reflect a broader spectrum of the real-world population of patients with AL amyloidosis in Italy; 3. Investigate the clinical utility of novel diagnostic technologies, including light chain sequencing and N-glycosylation analysis
177Lu-NYM032 injection is a radioligand therapeutic agent that targets prostate specific membrane antigen (PSMA)-expressing prostate tumors. NYM032 is a small molecular with strong affinity for PSMA.
Anterior cruciate ligament (ACL) reconstruction surgery is a common procedure performed by orthopedic surgeons. Postoperatively, patients often experience pain, muscle tension, and concerns about their ability to return to sports. These factors influence the recovery and return to sports capabilities of ACL patients. According to research, only 64% of patients are able to recover to their pre-injury level after surgery, and the success rate for returning to competitive sports is only 56%. Psychological factors during the recovery process may explain this disparity. ACL injury is associated with anxiety, pain reaction, and emotional disorders, with fear of re-injury being the most common obstacle to returning to sports, accounting for 19%. A study by Lentz et al. (2015) also found no significant differences in pain assessments between individuals who were afraid of re-injury and those who were able to return to sports at six months and one year after surgery. This suggests that fear of pain may limit activity and increase the risk of unsuccessful return to sports. Mindfulness intervention is a psychological approach that involves non-judgmental awareness and focus on moment to moment. Mindfulness practice is known to reduce stress in athletes, promote recovery, enhance athletic performance, and improve sleep quality. Good sleep quality contributes to emotional stability and physical recovery. Even short daytime naps can be beneficial for athletes. A review of 37 studies of moderate quality found that daytime napping can improve physical and cognitive performance, psychological state, and nighttime sleep. Therefore, investigators hypothesize that integrating mindfulness practice into daytime napping may lead to improved spirit upon waking, reduce sleep inertia, and over time, potentially increase the rate of return to sports after ACL reconstruction.