Healthy Control

The iCaRe2 is a multi-institutional resource created and maintained by the Fred \& Pamela Buffett Cancer Center to collect and manage standardized, multi-dimensional, longitudinal data and biospecimens on consented adult cancer patients, high-risk individuals, and normal controls. The distinct characteristic of the iCaRe2 is its geographical coverage, with a significant percentage of small and rural hospitals and cancer centers. The iCaRe2 advances comprehensive studies of risk factors of cancer development and progression and enables the design of novel strategies for prevention, screening, early detection and personalized treatment of cancer. Centers with expertise in cancer epidemiology, genetics, biology, early detection, and patient care can collaborate by using the iCaRe2 as a platform for cohort and population studies.

Bipolar disorder (BD) has become a significant public health problem with complex clinical manifestations, difficult treatment, and poor prognosis. However, there is still a lack of effective biological markers for diagnosing and predicting recurrence. Sentiment analysis computing usually refers to using machine equipment to classify, identify, interpret, and imitate human emotions. However, current multi-modal emotion analysis research is mainly based on one or two modalities. Due to the diversity and complexity of patients' emotional expressions, this single- and dual-modal information analysis is far from enough for accurate discrimination of emotional symptoms. Only emotion analysis technology based on multi-modal feature fusion can make more precise and effective judgments. The current project is based on our previous research on cognitive neuroimaging and big data analysis of bipolar disorder. The investigators plan to enroll 200 BD patients who meet DSM-5 diagnostic criteria and 200 healthy controls. The investigators will use sentiment analysis technology with multi-modal feature fusion (text data, audio and visual modalities, eye movements, and electrophysiology) to identify BD recurrence. Biological markers for risk prediction and an algorithm model for joint judgment of multi-source information will be established to analyze the characterization data. The effectiveness of this recurrence prediction model will be further verified and optimized through a large-sample, prospective cohort study design. It is hoped that it can provide a new method for predicting the recurrence risk of BD patients. In the near future, clinical decision-making aids based on this auxiliary method can be developed, and the translational application value of clinical diagnosis and treatment can be explored.

The goal of this research study is to examine the endocannabinoid (eCB) function in vivo in individuals with opioid use disorder (OUD) by measuring cannabinoid receptor 1 (CB1R) availability.

The aim of the present study is to assess the availability of cannabinoid receptors (CB1R) in the human brain. CB1R are present in everyone's brain, regardless of whether or not someone has used cannabis. The investigators will image brain cannabinoid receptors using Positron Emission Tomography (PET) imaging and the radioligand OMAR, in healthy individuals and several conditions including 1) cannabis use disorders, 2) psychotic disorders, 3) prodrome of psychotic illness and 4) individuals with a family history of alcoholism, 5) Post-Traumatic Stress Disorder 6) Opioid Use Disorder using the PET imaging agent or radiotracer, \[11C\]OMAR. This will allow us to characterize the number and distribution of CB1R in these conditions. It is likely that the list of conditions will be expanded after the collection of pilot data and as new data on cannabinoids receptor function and psychiatric disorders becomes available. Those in the cannabis us disorder arm of the study will have a PET scan on at least three occasions: once while smoking as usual, once after 48-hours of abstinence from cannabis, and a final time after 4 weeks of abstinence. Additional scans may be conducted within the 4 weeks and the last scan may be conducted well beyond 4 weeks. Similarly, while most schizophrenia patients may get scanned just once, a subgroup of patients may get scanned more than once. For example to tease out the effects of medications, unmedicated patients may get scanned while unmedicated and again after treatment with antipsychotic medications. Similarly prodromes may get scanned while in the prodromal stage off medications, on medications and after conversion to schizophrenia.

Prematurity affects around 7% of births in France. Necrotizing enterocolitis (NEC) is a dreaded digestive complication. It is responsible for a mortality rate ranging from 15 to 40%, a rate that has remained stable in recent years, and for medium- and long-term digestive and neurodevelopmental morbidity. Its onset is unpredictable and sudden, usually between 10 and 20 days of life, and requires immediate, aggressive management: hemodynamic support, fasting, systemic antibiotic therapy or even surgery. Prevention is therefore essential, but systematic measures with proven efficacy (breastfeeding, early enteral feeding, multiple probiotics) are few and far between. What's more, these preventive measures cannot be modulated and adapted individually, since it is not possible to finely predict the risk of developing enterocolitis. Thus, the use of a predictive diagnostic test for NEC would make it possible to identify high-risk premature babies and develop personalized preventive measures. Changes in the digestive microbiota precede the onset of NEC, but it has not been possible to identify a reproducible and reliable microbial signature. As a result, the limited power of microbiota analysis and interpretation means that it cannot be used in practice to predict ECUN. Our partner team (MEDiS) has developed a bioinformatics chain (RiboTaxa) to obtain the precise structure of complex microbial communities from direct metagenomic sequencing data. Stool samples from international cohorts (1562 samples, 208 preterm infants) were then mined to train a deep neural network and generate a predictive diagnostic test for NEC. In a local study (10 cases and 10 controls), the predictive diagnostic performance of this test was 90%, with the 1ère stool identified as "at risk" preceding NEC by 8 days (extremes 4 - 17 days), and the 2nde by 2 days (extremes 0-7 days). We would now like to test our predictive diagnostic technique on a larger number of premature babies in the AURA region. 1000 children included, 200 children tested (50 NEC - 150 controls)

This study focuses on the structure and function of the brain and gene expression in peripheral blood of patients with schizophrenia, to explore the interaction and influence between the three. Patients with mental disorders who have been recruited will take their medication regularly for 1 year and participate in baseline and follow-up assessments.

The goal of this clinical trial is to examine the neural mechanisms underlying transcranial magnetic stimulation (TMS) using concurrent functional magnetic resonance imaging (fMRI) in both healthy controls (HCs) and patients with high negative affect symptoms, such as depression. Approximately half male and half female participants aged 18-65 will be recruited. The main questions it aims to answer are: 1. Is the acute/transient effect induced by single-pulse TMS related to the long-term modulatory effect induced by repetitive TMS (rTMS)? 2. Do any of these effects predict negative affect symptoms, such as depression? Participants will: 1. Complete several tests to assess their cognitive abilities and emotional states 2. Undergo several brain scans, including resting-state fMRI, structural MRI, diffusion tensor imaging (DTI), and task fMRI 3. Have two different types of TMS sequences, single-pulse and repetitive pulses, administered to specific brain regions while undergoing fMRI

Given the limited evidence in the literature regarding the effect of perceived social support on life satisfaction and social participation in adults with stroke, this study aimed to investigate the effect of perceived social support on these outcomes.

This research employs AI to analyze facial expressions and speech patterns, aiming to develop new digital tools for diagnosing and differentiating Parkinson's disease and similar disorders.

The goal of this observational study is to evaluate the role of IgE proteoforms in healthy volunteers and in patients with type I allergy, patients with chronic spontaneous urticaria, patients with a recent history of anaphylaxis, patients with mastocytosis, patients with hereditary alpha tryptasemia, patients with X-linked agammaglobulinemia (XLA), and patients undergoing desensitization for venom or medication allergy.

The study will evaluate the feasibility of using smartphone speakers and microphones to evaluate the caliber of the airways, detect airway obstruction, aid in airway disease diagnosis, and identify disease exacerbations.

The aim of the study is to investigate test-retest reliability and agreement of trunk muscle activation during functional tasks and clinical sensorimotor control tests in pain-free persons.

The comprehensive analysis of health records, TCM constitution, biomarker, and whole-genome sequencing among dry eye syndrome, healthy control, Sjögren's syndrome and other inflammation disease in Taiwan: an integrated analysis between Taiwan Biobank and Sjögren's syndrome Database