Hessellundparrish3131

The clinical course of SARS-CoV-2 in the pediatric kidney transplant population is not well described.

We performed a retrospective cohort study of a pediatric kidney transplant population at a New York transplant center. Baseline characteristics and clinical course of patients with SARS-CoV-2 positivity (Ab or PCR) were described, and comparison between COVID-positive and COVID-negative transplant patients was performed.

Twenty-two patients had COVID-19 IgG testing performed, eight of whom also had PCR testing. 23% of our cohort had evidence of COVID-19 infection. Four patients had positive IgG only, and one patient had a positive PCR. All five patients with a positive COVID test were female. Two patients had COVID-19 symptoms, which were mild. Of the symptomatic patients, one had a positive PCR at time of symptoms, while the other had a negative PCR during symptoms but subsequently had positive IgG. As compared to patients with COVID-19 negative results, those with COVID-19 positivity were significantly more likely to have a known COVID-19 exposure, and were also more likely to be female. There was no significant difference in time from transplant between the groups. Those in the COVID-positive group had higher baseline antimetabolite dose and CNI troughs, although these did not reach statistical significance.

Pediatric kidney transplant recipients are at risk for development of COVID-19 infection. While this population may be more at risk for SARS-CoV-2 infection due to their immunosuppressed status, their clinical course appears mild and similar to a healthy pediatric population.

Pediatric kidney transplant recipients are at risk for development of COVID-19 infection. While this population may be more at risk for SARS-CoV-2 infection due to their immunosuppressed status, their clinical course appears mild and similar to a healthy pediatric population.Extracellular adenosine plays important roles in modulating the immune responses. We have previously demonstrated that infection of dendritic cells (DC) by Leishmania amazonensis leads to increased expression of CD39 and CD73 and to the selective activation of the low affinity A2B receptors (A2B R), which contributes to DC inhibition, without involvement of the high affinity A2A R. To understand this apparent paradox, we now characterized the alterations of both adenosine receptors in infected cells. With this aim, bone marrow-derived DC from C57BL/6J mice were infected with metacyclic promastigotes of L. amazonensis. Fluorescence microscopy revealed that L. amazonensis infection stimulates the recruitment of A2B R, but not of A2A R, to the surface of infected DC, without altering the amount of mRNA or the total A2B R density, an effect dependent on lipophosphoglycan (LPG). Log-phase promastigotes or axenic amastigotes of L. amazonensis do not stimulate A2B R recruitment. Retatrutide mouse A2B R clusters are localized in caveolin-rich lipid rafts and the disruption of these membrane domains impairs A2B R recruitment and activation. More importantly, our results show that A2B R co-localize with CD39 and CD73 forming a "purinergic cluster" that allows for the production of extracellular adenosine in close proximity with these receptors. We conclude that A2B R activation by locally produced adenosine constitutes an elegant and powerful evasion mechanism used by L. amazonensis to down-modulate the DC activation.

Machine learning in digital pathology can improve efficiency and accuracy via prescreening with automated feature identification. Studies using uniform histologic material have shown promise. Generalized application requires validation on slides from multiple institutions. We used machine learning to identify glomeruli on renal biopsies and compared performance between single and multiple institutions.

Randomly selected, adequately sampled renal core biopsy cases (71) consisting of 4 stains each (H&E, trichrome, silver, PAS)from 3 institutions were digitizedat 40x. Glomeruli were manually annotated by 3 renal pathologists using a digitaltool. Cases were divided into training/validation (n=52) and evaluation (n=19) cohorts. An algorithm was trained to develop 3 convolutional neural network (CNN) models which tested case cohorts intra- and inter-institutionally. Raw CNN search data from each of the 4 slides per case were merged into composite regions of interest (ROI) containing putative glomeruli. The ely account for algorithm performance contrasts. Our data highlight the need for diverse training sets for the development of generalizable machine learning histology algorithms.To identify hepatitis B virus (HBV)-related lncRNA(s), we previously examined the transcription profiles of the HBV-transgenic cell line HepG2-4D14 and parental HepG2 cells by RNA deep sequencing and identified 38 upregulated long noncoding RNAs (lncRNAs). In the present study, the lncRNA MAFG-AS1 is investigated in detail because its gene is located adjacent to the MAFG gene, which is an important transcription factor involved in cell proliferation. The level of MAFG-AS1 is significantly higher in HCC tissue than in nontumor tissues. TCGA data show that the expression level of MAFG-AS1 is negatively correlated with survival of HCC patients. GEO cohort data show that compared with healthy tissues, the expression level of MAFG-AS1 is significantly higher in HBV-infected liver tissues. Real-time PCR and luciferase reporter assay data show that HBx can enhance the transcription of MAFG-AS1. Gain-of-function and loss-of-function experiments indicate that MAFG-AS1 promotes proliferation, migration, and invasion of HCC cells. Tumor formation assay results demonstrate that knockdown of MAFG-AS1 significantly inhibits cell proliferation in nude mice. Furthermore, MAFG-AS1 enhances the transcription of adjacent MAFG via E2F1. Additionally, MAFG-AS1 interacts with three subunits (MYH9, MYL12B, and MYL6) of nonmuscle myosin IIA (NM IIA). Knockdown of MAFG-AS1 inhibits ATPase activity of MYH9, interaction of NM IIA subunits, and cell cycle progression. Thus, the lncRNA MAFG-AS1 is upregulated by HBV and promotes proliferation and migration of HCC cells. Our findings suggest that MAFG-AS1 is a potential oncogene that may contribute to HBV-related HCC development.