Norgan, Andrew P

Abstract Objectives Recent work has demonstrated that automated fluorescence flow cytometry (FLC) is a potential alternative for the detection and quantification of Plasmodium parasites. The objective of this study was to apply this novel FLC method to detect and quantify Babesia parasites in venous blood and compare results to light microscopy and polymerase chain reaction methods. Methods An automated hematology/malaria analyzer (XN-31; Sysmex) was used to detect and quantify B microti–infected red blood cells from residual venous blood samples (n = 250: Babesia positive, n = 170; Babesia negative, n = 80). As no instrument software currently exists for Babesia, qualitative and quantitative machine learning (ML) algorithms were developed to facilitate analysis. Results Performance of the ML models was verified against the XN-31 software using P falciparum–infected samples. When applied to Babesia-infected samples, the qualitative ML model demonstrated an area under the curve (AUC) of 0.956 (sensitivity, 95.9%; specificity, 83.3%) relative to polymerase chain reaction. For valid scattergrams, the qualitive model achieved an AUC of 1.0 (sensitivity and specificity, 100%), while the quantitative model demonstrated an AUC of 0.986 (sensitivity, 94.4%; specificity, 100%). Conclusions This investigation demonstrates that Babesia parasites can be detected and quantified directly from venous blood using FLC. Although promising, opportunities remain to improve the general applicability of the method.

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020 and 2022 and used Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest calculated introduction into Minnesota was to Hennepin County from a domestic source around 22 January 2020; 6 weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota and, eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International Airport) totaling 45 (out of 107) over the 2-year period. Southern Minnesota counties were most common for domestic introductions, with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois, which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations ( n = 772) over the 2-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases nor the major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have an impact on virus diversity across each individual county. IMPORTANCE We analyzed over 22,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes of patient samples tested at Mayo Clinic Laboratories during a 2-year period in the COVID-19 pandemic, which included Alpha, Delta, and Omicron variants of concern to examine the roles and relationships of Minnesota virus transmission. We found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after an initial predicted introduction with the virus in early 2020 from an international source, while other counties acted as transmission “sinks.” In addition, major policies, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.

Sequencing is increasingly used for infective endocarditis (IE) diagnosis. Here, the performance of 16S rRNA gene PCR/sequencing of heart valves utilized in routine clinical practice was compared with conventional IE diagnostics.

AbstractObjectiveFetal surgery has improved neonatal outcomes; however, it is unknown if the intervention contributes to the developmental of inflammatory pathologies in the placenta. Here, an association between fetal surgery and placental pathology was examined.MethodThis case‐control study compared pregnancies with fetal surgery (n = 22), pregnancies with an indication for fetal surgery but without an intervention being done (n = 13), and gestational‐age and fetus‐number matched controls (n = 36). Data on maternal, infant, and placental outcomes were abstracted. Additionally, immunohistochemistry identified expression of lymphoid and myeloid cells in the placenta on a subset of cases. Comparisons were performed using Kruskal‐Wallis or Pearson's chi‐squared tests.ResultsMaternal characteristics were comparable between groups. Most fetal interventions were for diaphragmatic hernia, spina bifida, or twin‐to‐twin transfusion syndrome. Fetuses who were operated on before birth were more likely to be born preterm (p = 0.02). There was no increase in the rate of observed placental pathologies or immune cell infiltration in fetal surgery cases compared to controls.ConclusionThe data suggest that fetal surgery is not associated with increased inflammatory or morphologic pathology in the placenta. This observation supports the growing field of fetal surgery.

Newborn screening for congenital hypothyroidism remains challenging decades after broad implementation worldwide. Testing protocols are not uniform in terms of targets (TSH and/or T4) and protocols (parallel vs. sequential testing; one or two specimen collection times), and specificity (with or without collection of a second specimen) is overall poor. The purpose of this retrospective study is to investigate the potential impact of multivariate pattern recognition software (CLIR) to improve the post-analytical interpretation of screening results. Seven programs contributed reference data (N = 1,970,536) and two sets of true (TP, N = 1369 combined) and false (FP, N = 15,201) positive cases for validation and verification purposes, respectively. Data were adjusted for age at collection, birth weight, and location using polynomial regression models of the fifth degree to create three-dimensional regression surfaces. Customized Single Condition Tools and Dual Scatter Plots were created using CLIR to optimize the differential diagnosis between TP and FP cases in the validation set. Verification testing correctly identified 446/454 (98%) of the TP cases, and could have prevented 1931/5447 (35%) of the FP cases, with variable impact among locations (range 4% to 50%). CLIR tools either as made here or preferably standardized to the recommended uniform screening panel could improve performance of newborn screening for congenital hypothyroidism.

Context.— Small case series have evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in formalin-fixed, paraffin-embedded tissue using reverse transcription–polymerase chain reaction, immunohistochemistry (IHC), and/or RNA in situ hybridization (RNAish). Objective.— To compare droplet digital polymerase chain reaction, IHC, and RNAish to detect SARS-CoV-2 in formalin-fixed, paraffin-embedded tissue in a large series of lung specimens from coronavirus disease 2019 (COVID-19) patients. Design.— Droplet digital polymerase chain reaction and RNAish used commercially available probes; IHC used clone 1A9. Twenty-six autopsies of COVID-19 patients with formalin-fixed, paraffin-embedded tissue blocks of 62 lung specimens, 22 heart specimens, 2 brain specimens, and 1 liver, and 1 umbilical cord were included. Control cases included 9 autopsy lungs from patients with other infections/inflammation and virus-infected tissue or cell lines. Results.— Droplet digital polymerase chain reaction had the highest sensitivity for SARS-CoV-2 (96%) when compared with IHC (31%) and RNAish (36%). All 3 tests had a specificity of 100%. Agreement between droplet digital polymerase chain reaction and IHC or RNAish was fair (κ = 0.23 and κ = 0.35, respectively). Agreement between IHC and in situ hybridization was substantial (κ = 0.75). Interobserver reliability was almost perfect for IHC (κ = 0.91) and fair to moderate for RNAish (κ = 0.38–0.59). Lung tissues from patients who died earlier after onset of symptoms revealed higher copy numbers by droplet digital polymerase chain reaction (P = .03, Pearson correlation = −0.65) and were more likely to be positive by RNAish (P = .02) than lungs from patients who died later. We identified SARS-CoV-2 in hyaline membranes, in pneumocytes, and rarely in respiratory epithelium. Droplet digital polymerase chain reaction showed low copy numbers in 7 autopsy hearts from ProteoGenex Inc. All other extrapulmonary tissues were negative. Conclusions.— Droplet digital polymerase chain reaction was the most sensitive and highly specific test to identify SARS-CoV-2 in lung specimens from COVID-19 patients.