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Abstract Introduction Visual assessment and imaging of the donor liver are inaccurate in predicting fibrosis and remain surrogates for histopathology. We demonstrate that 3‐s scans using a handheld near‐infrared‐spectroscopy (NIRS) instrument can identify and quantify fibrosis in fresh human liver samples. Methods We undertook NIRS scans on 107 samples from 27 patients, 88 from 23 patients with liver disease, and 19 from four organ donors. Results Liver disease patients had a median immature fibrosis of 40% (interquartile range [IQR] 20–60) and mature fibrosis of 30% (10%–50%) on histopathology. The organ donor livers had a median fibrosis (both mature and immature) of 10% (IQR 5%–15%). Using machine learning, this study detected presence of cirrhosis and METAVIR grade of fibrosis with a classification accuracy of 96.3% and 97.2%, precision of 96.3% and 97.0%, recall of 96.3% and 97.2%, specificity of 95.4% and 98.0% and area under receiver operator curve of 0.977 and 0.999, respectively. Using partial‐least square regression machine learning, this study predicted the percentage of both immature (R2 = 0.842) and mature (R2 = 0.837) with a low margin of error (root mean square of error of 9.76% and 7.96%, respectively). Conclusion This study demonstrates that a point‐of‐care NIRS instrument can accurately detect, quantify and classify liver fibrosis using machine learning.

Background. We aimed to facilitate the donation of tissue samples for research by establishing a centralized system integrated in the organ donation program for collection, storage, and distribution of samples (the Australian Donation and Transplantation Biobank [ADTB]). Methods. Feasibility of a research biobank integrated within the deceased organ and tissue donation program was assessed. DonateLife Victoria sought consent for ADTB donation after consent was received for organ donation for transplantation from the donor’s senior available next of kin. ADTB samples were collected during donation surgery and distributed fresh to researchers or stored for future research. The main outcome measures were ADTB donation rates, ADTB sample collection, ADTB sample use, and to identify ethical considerations. Results. Over 2 y, samples were collected for the ADTB from 69 donors (28% of 249 donors). Samples were obtained from the spleen (n = 59, 86%), colon (n = 57, 83%), ileum (n = 56, 82%), duodenum (n = 55, 80%), blood (n = 55, 80%), bone marrow (n = 55, 80%), skin (n = 54, 78%), mesenteric lymph nodes (n = 56, 81%), liver (n = 21, 30%), lung (n = 29, 42%), and lung-draining lymph node (n = 29, 42%). Heart (n = 20), breast (n = 1), and lower urinary tract (n = 1) samples were obtained in the second year. Five hundred fifty-six samples were used in 19 ethics-approved research projects spanning the fields of immunology, microbiology, oncology, anatomy, physiology, and surgery. Conclusions. The integration of routine deceased donation and transplantation activities with a coordinated system for retrieval and allocation of donor samples for use in a range of research projects is feasible and valuable.

Abstract Objectives Endemic human coronaviruses (hCoVs) circulate worldwide but cause minimal mortality. Although seroconversion to hCoV is near ubiquitous during childhood, little is known about hCoV‐specific T‐cell memory in adults. Methods We quantified CD4 T‐cell and antibody responses to hCoV spike antigens in 42 SARS‐CoV‐2‐uninfected individuals. Antigen‐specific memory T cells and circulating T follicular helper (cTFH) cells were identified using an activation‐induced marker assay and characterised for memory phenotype and chemokine receptor expression. Results T‐cell responses were widespread within conventional memory and cTFH compartments but did not correlate with IgG titres. SARS‐CoV‐2 cross‐reactive T cells were observed in 48% of participants and correlated with HKU1 memory. hCoV‐specific T cells exhibited a CCR6+ central memory phenotype in the blood, but were enriched for frequency and CXCR3 expression in human lung‐draining lymph nodes. Conclusion Overall, hCoV‐specific humoral and cellular memory are independently maintained, with a shared phenotype existing among coronavirus‐specific CD4 T cells. This understanding of endemic coronavirus immunity provides insight into the homeostatic maintenance of immune responses that are likely to be critical components of protection against SARS‐CoV‐2.