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Nephrotoxicity is a significant concern during the development of new drugs or when assessing the safety of chemicals in consumer products. Traditional methods for testing nephrotoxicity involve animal models or 2D in vitro cell cultures, the latter of which lack the complexity and functionality of the human kidney. 3D in vitro models are created by culturing human primary kidney cells derived from urine in a 3D microenvironment that mimics the fluid shear stresses of the kidney. Thus, 3D in vitro models provide more accurate and reliable predictions of human nephrotoxicity compared to existing 2D models. In this review, we focus on precision nephrotoxicity testing using 3D in vitro models with human autologous urine-derived kidney cells as a promising approach for evaluating drug safety.

Research surrounding tumor boards has focused on patient outcomes and care coordination. Little is known about the patient experience with tumor boards. This survey examined aspects of the patient experience for patients presented at our multidisciplinary endocrine tumor board (ETB). A 15-item survey was distributed via the online patient portal to patients over the age of 18 whose case had been discussed at our ETB over an 18-month period. Descriptive statistics were reported, and a Fisher's exact test was used to examine relationships between variables. A total of 47 patients completed the survey (46%). A majority (72%) report their provider explained what the ETB is, and 77% report being informed their case would be discussed. Most patients were satisfied their case was being discussed (72%). A number of patients did report moderate or severe anxiety knowing their case was being discussed (15%). Sixty-four percent of patients report the ETB recommendations were clearly explained; however, satisfaction with the recommendations was slightly lower (53%). Despite the somewhat low satisfaction with the recommendations, 75% of patients felt more confident in their treatment plan knowing their case was discussed. Finally, if given the chance, 66% responded that they would have been interested in participating in their own ETB discussion. This study provides some insight into the patient experience surrounding tumor board discussions. Overall, patients are satisfied when their case is discussed at ETB. Patients can also experience anxiety about these discussions, and many patients desire to be present for their own discussions.

Literature suggests patients with thyroid cancer have unmet informational needs in many aspects of care. Patients often turn to online resources for their health-related information, and generative artificial intelligence programs such as ChatGPT are an emerging and attractive resource for patients. To assess the quality of ChatGPT's responses to thyroid cancer-related questions. Four endocrinologists and 4 endocrine surgeons, all with expertise in thyroid cancer, evaluated the responses to 20 thyroid cancer-related questions. Responses were scored on a 7-point Likert scale in areas of accuracy, completeness, and overall satisfaction. Comments from the evaluators were aggregated and a qualitative analysis was performed. Overall, only 57%, 56%, and 52% of the responses \"agreed\" or \"strongly agreed\" that ChatGPT's answers were accurate, complete, and satisfactory, respectively. One hundred ninety-eight free-text comments were included in the qualitative analysis. The majority of comments were critical in nature. Several themes emerged, which included overemphasis of diet and iodine intake and its role in thyroid cancer, and incomplete or inaccurate information on risks of both thyroid surgery and radioactive iodine therapy. Our study suggests that ChatGPT is not accurate or reliable enough at this time for unsupervised use as a patient information tool for thyroid cancer.

ABSTRACT Hirschprung’s disease co-occurs with multiple endocrine neoplasia type 2A infrequently but at a higher rate with certain RET mutations. We present a case of a patient evaluated for an adrenal incidentaloma with a history of familial Hirschprung’s. Our patient was found to have synchronous pheochromocytoma and medullary thyroid carcinoma illustrating the importance of genetic testing in these patients to determine appropriate screening for endocrine tumors.

Background: A mild increase in prolactin has been previously reported in patients with pathological conditions, such as ESRD, as well as with several medications. Typically this is a mild elevation (<100 ng/mL), though certain medications have been shown to increase prolactin up to 200 ng/mL. However, we report a case of severe hyperprolactinemia in a patient with ESRD and on medications known to cause mild prolactin elevations. Clinical Case: Our patient is a 35-year-old female presenting for hyperprolactinemia. She has a history of uncontrolled diabetes with complications of ESRD on iHD, gastroparesis, and neuropathy. Further history revealed galactorrhea for 15 years following the birth of her second child as well as amenorrhea for the last 1.5 years. At the time of evaluation, she was not breastfeeding and did not have any reported life stressors. Medications were unchanged and included metoclopramide 10 mg daily and promethazine 25 mg PRN. Initial prolactin level one year prior to visit was 618 ng/mL. TSH 1.33. Brain MRI at that time did not reveal a pituitary mass, though pituitary protocol was not performed. Prolactin repeated on our initial visit had increased to 1352 ng/mL. Pituitary MRI was without evidence of pituitary mass. Despite discussing the importance of estrogen replacement, the patient was not interested in OCP therapy due to prior intolerance. Clinical Lesson(s): Hyperprolactinemia can be seen in patients on hemodialysis as a result of increased secretion in the uremic state and decreased clearance. Dialysis does not significantly improve the prolactin level. A recent study revealed a median prolactin of 65.2 ng/mL in dialysis patients. Our case emphasizes that the degree of hyperprolactinemia as a result of ESRD and medications can vary widely. It remains important to continue to consider the diagnosis of pituitary pathology in patients with a prolactin level that is higher than expected. However, if imaging is unrevealing, as in our patient, hyperprolactinemia may be attributed to medications and pathological disease states. Elevated serum prolactin has been shown to increase cardiovascular and all-cause mortality in a level-dependent effect. Hyperprolactinemia has also been associated with insulin resistance and worsened diabetes control. As we continue to learn more regarding the negative side effects of prolactin, it may become increasingly important to monitor and reduce prolactin levels in our patients, especially those on dialysis already with an elevated risk of cardiovascular disease.

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.