High prevalence of extended-spectrum beta-lactamase organisms and the COVID-19 pandemic impact on donor recruitment for fecal microbiota transplantation in Hong Kong. | LitMetric
Background: With increasing number of clinical trials relating to fecal microbiota transplantation (FMT), it is crucial to identify and recruit long-term, healthy, and regular fecal donors.
Objective: We aimed to report the outcomes of screening and recruitment of fecal donors for FMT.
Methods: Potential donors were recruited via advertisement through internal mass emails at a university. They were required to undergo a pre-screening telephone interview, a detailed questionnaire, followed by blood and stool investigations.
Results: From January 2017 to December 2020, 119 potential donors were assessed with 75 failed pre-screening. Reasons for failure included: inability to come back for regular and long-term donation (n = 19), high body mass index (n = 17), underlying chronic illness or on long-term medications (n = 11), being healthcare professionals (n = 10), use of antibiotics within 3 months (n = 5) and others (n = 13). Forty-four donors completed questionnaires and 11 did not fulfill the clinical criteria. Of the remaining 33 potential donors who had stool and blood tests, 21 failed stool investigations (19 extended-spectrum beta-lactamase [ESBL] organisms, one Clostridioides difficile, one C. difficile plus Methicillin Resistant Staphylococcus aureus), one failed blood tests (high serum alkaline phosphatase level), one required long-term medication and nine withdrew consent and/or lost to follow-up. In total, only one out of 119 (0.8%) potential donors was successfully recruited as a regular donor.
Conclusion: There was a high failure rate in donor screening for FMT. Main reasons for screening failure included high prevalence of positive ESBL organisms in stool and failed commitment to regular stool donation.
Department of Emergency Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.
Aortic dissection (AD) represents a critical condition characterised by a tear in the inner lining of the aorta, leading to the leakage of blood into the layers of the aortic wall, posing a significant risk to life. However, the pathogenesis is unclear. In this study, scRNA-seq was applied to cells derived from aortas of both AD and non-AD donors (control) to unveil the cellular landscape.
Photochromic films have attracted increasing attention for their potential in information storage and photoswitchable devices. Developing novel photochromic materials is still a highly challenging topic. In this work, we successfully obtained an unprecedented mixed-heteroatom-templated Er-incorporated polyoxometalate [HN(CH)]NaKH{Er(HO)WO[SeTeWO][B-α-TeWO]}·117HO () by concurrently introducing the [TeO] and [SeO] heteroanion templates into the Er/WO system.
Objectives: To evaluate the manufacturability, efficacy and safety of allogeneic CD19 chimeric antigen receptor double-negative T cells (CD19-CAR-DNTs) as an off-the-shelf therapeutic cell product.
Methods: A membrane proteome array was used to assess the off-target binding of CD19-CAR. DNTs derived from healthy donors were transduced with lentiviral vectors encoding the CD19-CAR.
Applying artificial intelligence (AI) to image-based morphological profiling cells offers significant potential for identifying disease states and drug responses in high-content imaging (HCI) screens. When differences between populations (e.g.
Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, Intelligent Critical Care Center, College of Pharmacy, University of Florida, Orlando, FL, USA.
Human islets display a high degree of heterogeneity in terms of size, number, architecture, and endocrine cell-type compositions. An ever-increasing number of immunohistochemistry-stained whole slide images (WSIs) are available through the online pathology database of the Network for Pancreatic Organ donors with Diabetes (nPOD) program at the University of Florida (UF). We aimed to develop an enhanced machine learning-assisted WSI analysis workflow to utilize the nPOD resource for analysis of endocrine cell heterogeneity in the natural history of type 1 diabetes (T1D) in comparison to donors without diabetes.
