Almost 150 papers about brain lymphatics have been published in the last 150 years. Recently, the information in these papers has been synthesized into a picture of central nervous system (CNS) “glymphatics,” but the fine structure of lymphatic elements in the human brain based on imaging specific markers of lymphatic endothelium has not been described. We used LYVE1 and PDPN antibodies to visualize lymphatic marker-positive cells (LMPCs) in postmortem human brain samples, meninges, cavernous sinus (cavum trigeminale), and cranial nerves and bolstered our findings with a VEGFR3 antibody. LMPCs were present in the perivascular space, the walls of small and large arteries and veins, the media of large vessels along smooth muscle cell membranes, and the vascular adventitia. Lymphatic marker staining was detected in the pia mater, in the arachnoid, in venous sinuses, and among the layers of the dura mater. There were many LMPCs in the perineurium and endoneurium of cranial nerves. Soluble waste may move from the brain parenchyma via perivascular and paravascular routes to the closest subarachnoid space and then travel along the dura mater and/or cranial nerves. Particulate waste products travel along the laminae of the dura mater toward the jugular fossa, lamina cribrosa, and perineurium of the cranial nerves to enter the cervical lymphatics. CD3-positive T cells appear to be in close proximity to LMPCs in perivascular/perineural spaces throughout the brain. Both immunostaining and qPCR confirmed the presence of adhesion molecules in the CNS known to be involved in T cell migration.

Background Nephrolithiasis in allograft kidneys is rare but this diagnosis may lead to allograft complications and patient morbidity. Previous studies that have evaluated nephrolithiasis post-transplant focused on surgical stone management with limited data on urine metabolic risk factors and presence of stones after follow-up. Methods We retrospectively evaluated kidney transplant recipients who were diagnosed with transplant nephrolithiasis between 2009–2019. Computed tomography and ultrasound imaging were used to confirm stone presence. Results The incidence of allograft kidney stone formation was 0.86% of 6,548 kidney transplant recipients. Of the 56 cases identified, 17 (30%) had pre-transplant history of nephrolithiasis. Only 4 (7%) patients received a known kidney stone at the time of allograft implantation. Of the 56 cases, 34 had a 24-hour supersaturation study. The urine supersaturation study showed 32 patients (94%) had a urine citrate of less than 450mg excreted in 24 hours (median 124.5 mg/24hr, reference range > 500 mg/24hrs),  along with 22 patients (61%) having a urine oxalate excretion of greater or equal to 30 mg in 24 hours (median 34.4 mg/24 hr., reference range < 30 mg/24hrs). Calcium oxalate composition was the most common (91% with greater than 1 supersaturation for calcium oxalate crystals) with normal median urine calcium levels (median urine calcium 103.5mg/24hours,  reference range <200 mg/24hrs). After a four-year follow-up, 50% (28) required surgical intervention and 43 (77%) patients continued to have evidence of transplant nephrolithiasis on imaging. Conclusions This is the largest study of transplant nephrolithiasis confirming that hypocitraturia and hyperoxaluria were the most significant urine metabolic risk factors associated with allograft nephrolithiasis and that hyperoxaluria was the most prevalent driver for calcium oxalate stone composition. Our study is first to show low stone free rates at last follow-up and a significant proportion requiring surgical intervention.

RATIONALE: A timely asthma diagnosis for preschool children is often difficult as lung function tests are not always feasible. To address this challenge, we assessed feasibility of natural language processing (NLP) algorithm-based asthma ascertainment for children prior to 4 years of age. METHODS: Asthma status of the 1997-2007 Olmsted County Birth Cohort was defined by the NLP algorithm for Predetermined Asthma Criteria (NLP-PAC) during the first 4 years of life (Yes/No). We assessed concurrent validity by using Asthma Predictive Index (API) and predictive validity by assessing subsequent physician diagnosis of asthma during the study period (1997-2015) and subsequent lung function measures for a random sample of the Birth cohort (n5221). We also assessed construct validity by assessing the association of NLP-PAC positivity with the known comorbidities (ie, other atopic conditions and pneumonia). RESULTS: Of the eligible 8,196 study subjects (51% male, 80% White), median age (IQR) was 12 (9-14) years. Children who meet NLP-PAC (n51,679, 20%), compared to those who do not, were more likely to meet API (68% vs. 9%), have a physician diagnosis of asthma (62% vs. 10%), have other atopic conditions (49% vs. 37%), have pneumonia (32% vs. 17%) (p<0.001 in all), and have lower FEV1/FVC% (median [IQR], 93 [87, 99] vs. 98 [92, 101], p5.003). CONCLUSIONS: Two thirds of children who meet the PAC prior to 4 th birthday had a subsequent physician diagnosis of asthma and lower lung function during school age. NLP-PAC can be a useful population management tool for early identification of asthma and treatment among preschool children.

Background: There is a paucity of evidence to inform the value of pharmacogenomic (PGx) results in patients after kidney transplant and how these results differ between Indigenous Americans and Whites. This study aims to identify the frequency of recommended medication changes based on PGx results and compare the pharmacogenomic (PGx) results and patients’ perceptions of the findings between a cohort of Indigenous American and White kidney transplant recipients. Methods: Thirty-one Indigenous Americans and fifty White kidney transplant recipients were studied prospectively. Genetic variants were identified using the OneOme RightMed PGx test of 27 genes. PGx pharmacist generated a report of the genetic variation and recommended changes. Pre- and post-qualitative patient surveys were obtained. Results: White and Indigenous American subjects had a similar mean number of medications at the time of PGx testing (mean 13 (SD 4.5)). In the entire cohort, 53% received beta blockers, 30% received antidepressants, 16% anticoagulation, 47% pain medication, and 25% statin therapy. Drug–gene interactions that warranted a clinical action were present in 21.5% of patients. In 12.7%, monitoring was recommended. Compared to the Whites, the Indigenous American patients had more normal CYP2C19 (p = 0.012) and CYP2D6 (p = 0.012) activities. The Indigenous American patients had more normal CYP4F2 (p = 0.004) and lower VKORC (p = 0.041) activities, phenotypes for warfarin drug dosing, and efficacy compared to the Whites. SLC6A4, which affects antidepressant metabolism, showed statistical differences between the two cohorts (p = 0.017); specifically, SLC6A4 had reduced expression in 45% of the Indigenous American patients compared to 20% of the White patients. There was no significant difference in patient perception before and after PGx. Conclusions: Kidney transplant recipients had several drug–gene interactions that were clinically actionable; over one-third of patients were likely to benefit from changes in medications or drug doses based on the PGx results. The Indigenous American patients differed in the expression of drug-metabolizing enzymes and drug transporters from the White patients.