To investigate a potential role for galectins as biomarkers that enable diagnosis or prognostication of breast or non-small cell lung cancer, the serum levels of galectins -1, -3, -7, -8, and -9 of cancer patients determined by ELISA assays were compared to the mutation status of 50 known cancer-critical genes, which were determined using multiplex PCR in tumors of the same patients. Mutations in the KIT proto-oncogene, which codes for the c-Kit protein, a receptor tyrosine kinase, correlated with higher levels of galectins -1, -3, -8, and -9 in breast cancer patients and galectin-1 in non-small cell lung cancer patients. Mutations in the KIT gene were more likely found in brain metastases from both of these primary cancers. The most common KIT mutation in our panel was p.M541L, a missense mutation in the transmembrane domain of the c-Kit protein. These results demonstrate an association between KIT oncogenic signaling and elevated serum galectins in patients with metastatic disease. Changes in protein trafficking and the glycocalyx composition of cancer cells may explain the observed alterations in galectin expression. This study can be useful for the targeted selection of receptor tyrosine kinase and galectin inhibitor anti-cancer treatments.

Hypertension (HTN) is a chronic condition that requires careful monitoring and management. Blood pressure readings in the clinic and self-reported blood pressure readings are often too intermittent to allow for careful management. Remote patient monitoring is a solution that may have positive impacts on HTN management. Individuals at cardiac and primary care clinics were prescribed a remote patient-monitoring (RPM) program. Patients were sent blood pressure monitors that were enabled to transmit data over cellular networks. We reviewed trends in HTN management retrospectively in patients who had previously been on conventional therapy for a year and participated in RPM for a minimum of 90 days. There were 6595 patients enrolled, and the mean duration on RPM was 289 days. A total of 4370 participants (66.3%) had uncontrolled HTN, and 2476 (37.5%) had stage 2 HTN. After at least 90 days on the RPM program, the number of patients with uncontrolled HTN reduced to 2648 (40.2%, p < 0.01), and the number of patients with stage 2 HTN reduced to 1261 (19.1%, p < 0.01). Systolic blood pressure improved by 7.3 mmHg for all patients and 16.7 mmHg for stage 2 HTN. There was improvement in mean arterial pressure (MAP) in all patients with uncontrolled HTN by 8.5 mmHg (p < 0.0001). RPM is associated with improved HTN control and provides further evidence supporting telehealth programs which can aid in chronic disease management.

• EIMG® may offer healthcare providers a pathway to improve patient health outcomes. • The current EIMG® clinic-to-community model is well received by patients. • Adding EIMG® to patients’ usual care may reduce blood pressure and body weight.

La Crosse virus (LACV) is a rare cause of pediatric encephalitis, yet identifying and mitigating transmission foci is critical to detecting additional cases. Neurologic disease disproportionately occurs among children, and survivors often experience substantial, life-altering chronic disability. Despite its severe clinical impact, public health resources to detect and mitigate transmission are lacking. This study aimed to design a Bayesian modelling approach to effectively identify and predict LACV incidence for geospatially informed public health interventions. A Bayesian negative binomial spatio-temporal regression model best fit the data and demonstrated high accuracy. Nine variables were statistically significant in predicting LACV incidence for the Appalachian Mountain Region. Proportion of children, proportion of developed open space, and proportion of barren land were positively associated with LACV incidence, while vapor pressure deficit index, year, and proportions of developed high intensity land, evergreen forest, hay pasture, and woody wetland were negatively associated with LACV incidence. Model prediction error was low, less than 2%, indicating high accuracy in predicting annual LACV human incidence at the county level. In summary, this study demonstrates the utility of Bayesian negative binomial spatio-temporal regression models for predicting rare but medically important LACV human cases. Future studies could examine more granular models for predicting LACV cases from localized variables such as mosquito control efforts, local reservoir host density and local weather fluctuations.

To examine food insecurity resource navigation program costs and how navigation intensity relates to clinical outcomes, healthcare costs, and quality of life (QOL) for diabetes and/or hypertension patients. This retrospective study included patients receiving resource navigation (July 12, 2021-December 31, 2022 with twelve-month follow-up) across three primary care practices in South Carolina's largest health system. Participants were 18+ years old (from electronic medical records/Epic), had food insecurity (from Hunger Vital Sign™), and diabetes and/or hypertension (from Epic registries). Matched controls came from food insecurity screening-only practices. Patients in each group (n = 219) had diabetes (9.13%), hypertension (50.23%), or both (40.64%). Navigation, fixed resources, and training costs were estimated using micro-costing from a US hospital system perspective (2025 USD). Multivariable models examined associations between outcomes (HbA1c, blood pressure, body mass index, primary, emergency, and inpatient charges, QOL), and navigation frequency, and duration, controlling for age, gender, race/ethnicity, payer, and comorbidities. Program costs (total = $29,752.91) primarily included case reviews ($19,809.25), navigation ($5,068.67), and training ($1,975.84), averaging $135.86 per patient. Navigation intensity was associated with twelve-month changes in HbA1c, BMI, QOL, primary, and inpatient charges. Navigation programs incur significant personnel time costs. Individuals with great healthcare needs may require intensive navigation.