United States

### Background &amp; Objectives
The 2025 ACC/AHA hypertension guidelines incorporate the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations to guide the initiation of antihypertensive medications for primary prevention of cardiovascular disease (CVD). This study aimed to compare population sizes recommended for antihypertensive treatment according to primary prevention criteria from the 2017 versus 2025 guidelines.

### Methods 
Using NHANES data (2011–2020), we identified participants aged 30–79 years who had systolic blood pressure (SBP) of 130–140 mmHg or diastolic blood pressure (DBP) of 80–90 mmHg, and who had no prior diagnosis of hypertension, CVD, diabetes, or chronic kidney disease, and were not pregnant nor taking antihypertensive medication. We estimated the 10-year risk for each participant using the Pooled Cohort Equations (PCE; stroke and myocardial infarction for those aged 40–75 years) and the PREVENT base model for total CVD (stroke, MI, and heart failure for those aged 30–79 years). High risk was defined as a 10-year ASCVD risk ≥10% with PCE and total CVD risk ≥7.5% with PREVENT. Analyses incorporated NHANES sampling weights to generate nationally representative estimates.

### Results
The initial population for both analyses included 29.6 million U.S. adults with SBP 130–140 mmHg or DBP 80–90 mmHg, not on antihypertensive medication, not pregnant and without CVD, diabetes, or chronic kidney disease. Of these, 18.4 million were aged 40–75 years and thus eligible for risk assessment with PCE; among these, 3.3 million had a 10-year ASCVD risk ≥10%. In contrast, 24.0 million were aged 30–79 years and thus eligible for total CVD risk assessment using the PREVENT model; of these, 3.5 million had a 10-year PREVENT base total CVD risk ≥7.5%.

### Conclusion
Under the updated thresholds, PREVENT identified nearly 200,000 more high-risk U.S. adults with untreated stage 1 hypertension than PCE, despite differences in model inputs and age range.



AMA Research Challenge 2025 

Comparison of the 2017 Pooled Cohort Equations and 2025 PREVENT Risk Prediction Models in U.S. Adults with Untreated Stage 1 Hypertension and Without CVD, Diabetes, or CKD: NHANES 2011 to March 2020

As AI transforms healthcare, ensuring reliability is critical. However, systems learning from existing data often reflect gaps or inconsistencies, leading to false inferences, diagnostic errors, and unequal performance across patient groups.

Open Data is pivotal for transparency and accountability. Biases emerging from unrepresentative datasets or flawed assumptions can perpetuate health disparities.

Leveraging public data on genomics, clinical trials, and social determinants allows researchers to audit and mitigate these risks effectively.

We task undergraduate and graduate students to harness data science to:

* Detect, reduce, and prevent bias in diagnostics and drug discovery;

* Develop data-driven tools that increase fairness and inclusivity;

* Innovate bias-aware model evaluation techniques to build trustworthy AI systems.

Equitable Health Technologies: Overcoming Biases and False Inferences in AI Diagnostics and Drug Discovery

As AI transforms healthcare, ensuring reliability is critical. However, systems learning from existing data often reflect gaps or inconsistencies, leading to false inferences, diagnostic errors, and unequal performance across patient groups.

### Background & Objectives
The 2025 ACC/AHA hypertension guidelines incorporate the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations to guide the initiation of antihypertensive medications for primary prevention of cardiovascular disease (CVD). This study aimed to compare population sizes recommended for antihypertensive treatment according to primary prevention criteria from the 2017 versus 2025 guidelines.

### Methods 
Using NHANES data (2011–2020), we identified participants aged 30–79 years who had systolic blood pressure (SBP) of 130–140 mmHg or diastolic blood pressure (DBP) of 80–90 mmHg, and who had no prior diagnosis of hypertension, CVD, diabetes, or chronic kidney disease, and were not pregnant nor taking antihypertensive medication. We estimated the 10-year risk for each participant using the Pooled Cohort Equations (PCE; stroke and myocardial infarction for those aged 40–75 years) and the PREVENT base model for total CVD (stroke, MI, and heart failure for those aged 30–79 years). High risk was defined as a 10-year ASCVD risk ≥10% with PCE and total CVD risk ≥7.5% with PREVENT. Analyses incorporated NHANES sampling weights to generate nationally representative estimates.

### Results
The initial population for both analyses included 29.6 million U.S. adults with SBP 130–140 mmHg or DBP 80–90 mmHg, not on antihypertensive medication, not pregnant and without CVD, diabetes, or chronic kidney disease. Of these, 18.4 million were aged 40–75 years and thus eligible for risk assessment with PCE; among these, 3.3 million had a 10-year ASCVD risk ≥10%. In contrast, 24.0 million were aged 30–79 years and thus eligible for total CVD risk assessment using the PREVENT model; of these, 3.5 million had a 10-year PREVENT base total CVD risk ≥7.5%.

### Conclusion
Under the updated thresholds, PREVENT identified nearly 200,000 more high-risk U.S. adults with untreated stage 1 hypertension than PCE, despite differences in model inputs and age range.



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### Background
Progesterone receptor membrane component 2 (PGRMC2) is critical for ciliogenesis and the biogenesis of ciliary extracellular vesicles (ciEVs), which play an essential role in maintaining cardiac function. Extracellular vesicles (EVs) are currently being evaluated in eight clinical trials as therapeutic agents for cardiac remodeling. While these studies highlight the therapeutic promise of EVs, the role of ciEVs and their regulation via PGRMC2 remains largely unexplored. This study investigates the impact of cardiac-specific PGRMC2 knockout on heart structure and function and proposes ciEV supplementation as a novel strategy to target cardiac dysfunction, expanding the therapeutic potential of EV-based cardiac therapies.

### Methods 
A cardiac-specific PGRMC2 knockout (KO) mouse model was generated using the Cre-LoxP system to investigate the role of PGRMC2 in cardiac structure and function. Mice were randomized into four groups (n=24 total; equal sex ratio): (1) wild-type with saline, (2) wild-type with EV treatment, (3) KO with saline, and (4) KO with EV treatment. Starting at two weeks of age and continuing through 17 weeks, mice received weekly intravenous injections of either 200 µL saline or 1.6 million EVs.
Assessments were conducted weekly and included treadmill exercise testing and blood pressure measurements. At 18 weeks, cardiac tissue was collected for histological evaluation using Masson’s trichrome staining to assess fibrosis, and left ventricular wall thickness. Statistical significance was defined as P < 0.05.

### Results
Survival analysis demonstrated a high mortality rate (50%) in knockout mice and treadmill exercise-stress tests revealed a marked reduction in exercise capacity (p<0.00001) in KO mice. Blood pressure analysis showed a greater decline in diastolic (p<0.0001 before exercise; p<0.00001 after exercise) and systolic (p<0.0001 after exercise) blood-pressure in male KO mice compared to females.
Pressure-volume (PV) loop analysis assessed cardiac performance under baseline (saline), increased workload (epinephrine), and reduced workload (diltiazem) conditions. KO mice exhibited reduced stroke-volume, indicating impaired cardiac output and efficiency.
Histological analysis revealed left ventricular hypertrophy (p<0.0001 female; p<0.001 male) and a significant increase in cardiac fibrosis (p<0.001 female; p < 0.00001 male) in knockout mice. EV treatment significantly improved survival rate (75%), blood-pressure regulation, ventricular thickness, and cardiac fibrosis.

### Conclusion
Loss of PGRMC2 disrupts ciEVs release, leading to structural and functional cardiac deterioration. Extracellular vesicle injections rescue these deficits, highlighting the essential role of ciEVs and PGRMC2 in maintaining cardiac homeostasis, further reinforcing their therapeutic potential.

PGRMC2 Knockout Disrupts Ciliary Extracellular Vesicle Biogenesis and Cardiac Functions

### Background
One in five adults will develop skin cancer in their lives. Medicare insured adults ages ≥65 account for nearly half of all skin cancers, with a disproportionately higher incidence in rural communities where patients face significant barriers in access to dermatologists. This study aims to fill a gap in the research for this vulnerable patient population by quantifying the relationships between skin cancer prevalence, beneficiary‑service volume of preventative and treatment services, and health care costs for Medicare beneficiaries across the rural-urban continuum from 2019 to 2023.

### Methods
Retrospective analysis of the publicly available 2019-2023 Medicare claims data files and the 2019-2023 National Health Interview Survey. Healthcare Common Procedure Coding System (HCPCS) codes were categorized as skin cancer prevention and treatment services based on the American Medical Association’s CPT Consumer Friendly Descriptors.

Zip codes were cross-walked to four levels of the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme: large central metro (LCM), large fringe metro (LFM), medium and small metro (MSM), and non-metropolitan areas (non-metro).

### Results
4,314 Medicare beneficiaries reported a skin cancer diagnosis in their lifetime (8.8%), with a greater incidence of each type of skin cancer in rural areas than urban areas (p<0.03). 

Non‑metropolitan areas had a greater share of dermatology beneficiary‑service volume for preventive services (LCM 23.4%; LFM 23.6%; MSM 25.7%; non‑metro 26.7%; P < 0.001) and services were 2-fold more likely to be any skin cancer treatment and 3.5-fold more likely to be radiation‑related treatment (OR 2.00 [1.99–2.01]; 3.52 [3.48–3.57]) than in LCM areas. 

After standardization for geographic differences in service payment rates, the average Medicare payment for surgical skin cancer treatment services was greater than for preventative care services, and both were greater in rural areas than urban areas (Overall, $118.54 vs. $48.22; LCM, $118.32 vs. $46.85; LFM, $121.7 vs. $48.41; MSM, $117.34 vs. $48.99; non-metro, $116.36 vs. $53.05; p<0.001 for each). Interestingly, no rural-urban difference was observed in radiation-related or chemotherapy treatment services (p=0.230, p=0.260).

### Conclusion
Rural-urban differences in dermatologists’ skin cancer prevention and treatment beneficiary‑service volume reflect a greater need for preventative services in rural areas of the country and provide more recent, service-level evidence for this vulnerable population.

These findings suggest preventative services for skin cancer may significantly lower health care costs in both the short-term and long-term for Medicare patients and CMS, and these calculations may be useful when evaluating new policy for expanding skin cancer prevention efforts nationwide.

Rural-Urban Skin Cancer Prevention and Treatment Differences for Medicare Beneficiaries, 2019–2023

### Background
Bankart lesions (anteroinferior glenoid labrum tears) can cause significant shoulder pain and dysfunction but are often difficult to detect on standard non-contrast MRI. To improve diagnostic sensitivity, MRI arthrography (MRA) is frequently used, although it is more invasive, costly, and uncomfortable for patients. Deep learning (DL), a subset of machine learning, identifies complex patterns in large datasets without the need for manual input. DL has improved diagnostic accuracy across several areas of medical imaging and is particularly well suited for detecting subtle abnormalities. This study developed a DL model to detect Bankart lesions on both MRI and MRA and evaluated its clinical utility through a clinician user study.

### Methods
A dataset of 586 shoulder MRIs/MRAs from 546 patients who underwent shoulder arthroscopy within one year of imaging was retrospectively analyzed. Arthroscopic findings served as the reference standard. A custom neural network ensemble was trained on 410 scans (224 MRI, 186 MRA), tuned on 59 (40 MRI, 19 MRA), and tested on 117 (71 MRI, 46 MRA). Gradient-weighted class activation maps (Grad-CAM) were used to assess the anatomical focus of model predictions. To evaluate clinical impact, a user study was conducted with two shoulder/elbow fellowship-trained orthopaedic surgeons and two orthopaedic residents. Each clinician reviewed all 117 test MRIs/MRAs in two phases: once without model predictions (unaided), and again after a 60-day washout period with DL predictions shown (aided).

### Results
For standard MRI, the model achieved 90.1% accuracy, 83.3% sensitivity, and 90.8% specificity—substantially outperforming radiology reports from the same scans (80.3% accuracy, 16.7% sensitivity, 86.2% specificity). On MRA, the model achieved 89.1% accuracy, 94.1% sensitivity, and 86.2% specificity, compared to radiology reports at 84.8% accuracy, 82.4% sensitivity, and 86.2% specificity. Grad-CAM showed consistent model attention on the anterior labrum. In the user study, mean clinician sensitivity improved from 38.0% to 78.3% with model assistance. Specificity slightly decreased (86.7% to 85.4%), while accuracy increased (77.1% to 84.0%). Clinician confidence increased by 0.65 points on a 10-point scale (p < 0.001).

### Conclusion
The model performed comparably on standard MRI to radiologists on MRA, with Grad-CAM confirming that predictions were based on appropriate anatomic regions. The user study demonstrated that clinicians achieved greater sensitivity and confidence when aided by the model. These results highlight the potential for DL tools to close the gap between non-contrast and contrast-enhanced imaging—avoiding the added cost, discomfort, and invasiveness of MRA.

AI-Assisted MRI Interpretation Improves Surgeon Performance in Diagnosing Bankart Lesions

### Background:
Central blood pressure (BP) more accurately reflects the loading conditions of the heart compared to brachial BP. Brachial BP is routinely used as a surrogate for central BP due to its ease of access, lower cost, and the efficiency of measurement. However, using brachial BP as a surrogate for central BP when calculating carotid arterial stiffness (CAS) has not been studied in older adults.

### Methods:
Veterans (n=180) age 65+ were recruited from Madison VA Hospital. Resting supine brachial BP and central BP (estimated from radial artery waveforms, Atcor Medical) were obtained. CAS (Peterson’s elastic modulus [PEM], Young’s elastic modulus [YEM]) and distensibility coefficient (DC) were calculated using brachial and central BP. Differences in CAS were compared using paired Wilcoxon tests. Linear regression models evaluated associations with cardiovascular risk factors (age, sex, hypertension status, diabetes, sleep apnea, alcohol intake, active smoking, and lifetime smoking status).

### Results:
Participants were 70.4 (7.7) years old and 27.8% were female. Average brachial systolic BP and pulse pressure were significantly higher than central (132.3 [18.6] mmHg vs 123.8 [17.7] mmHg, p<0.001) and pulse pressure (53mmHg [16.4] vs 43.8mmHg [15.3], p<0.001). Compared to brachial BP, using central BP to calculate stiffness measures resulted in significantly lower YEM and PEM and significantly higher DC (PEM: 480.6 [209.5] mmHg vs 378.3 [178.4] mmHg; YEM: 2220.2 [926.6] mmHg vs 1746.9 [785.4] mmHg; DC: 2.4 [1.0] x10-3 mmHg-1 vs 3.1 [1.1]
x10-3 mmHg-1; all p<0.001). Absence of hypertension was associated with smaller differences in PEM and DC (PEM: 𝛽=-29.1, SE=12.1, p=0.02; DC: 𝛽=-123.8, SE=55.3, p=0.027), while older age was associated with greater differences in YEM when calculated using brachial vs central BP (𝛽=1.9x10-5, SE=0.69x10-5, p=0.006).

### Conclusion:
Brachial and central BP significantly differ in older adults and result in significant differences in calculated CAS and distensibility. Brachial BP tends to significantly overestimate CAS, especially in those with hypertension. Our study highlights the importance of considering central BP when evaluating CAS to predict cardiovascular health and better understand vascular aging, especially in older adults with hypertension. Relying solely on peripheral BP may lead to an overestimation of vascular risk in these populations. Future studies should prioritize using central
BP measurements or CAS indices that are independent of BP to more accurately assess arterial health and improve CVD risk stratification. This can help better guide antihypertensive therapy, potentially improving outcomes and reducing the risk of over- or under-treatment.

Central and Brachial Pressures: Effects on Arterial Stiffness in Older Adults

### Background
As large language models (LLMs) gain multimodal capabilities to interpret both images and text, their potential to assist in clinical decision-making continues to grow. While prior research has shown LLMs can match and even outperform individual physicians on standardized exams, little is known about their performance relative to collective human reasoning where varied perspectives contribute to more accurate conclusions. This study evaluates the performance of state-of-the-art multimodal LLMs in solving complex medical challenges compared to both individual and aggregate responses from a large pool of medically literate readers.

### Methods
We compiled 100 ophthalmology-related cases from the New England Journal of Medicine (NEJM) Image Challenge archive (2006–2024), each containing a clinical vignette, image, and multiple-choice question. Six multimodal LLMs (GPT-4 Turbo, GPT-4o, GPT-4o mini, Gemini 1.5 Flash, Gemini 1.5 Pro, and Claude 3.5 Haiku) were prompted to answer each case and self-report confidence (1–4 scale). Human performance was assessed using (1) the average accuracy of NEJM respondents and (2) the accuracy of the most commonly selected (modal) answer per case, representing collective judgment. LLM accuracy and confidence were compared using Kruskal-Wallis and post hoc Dunn’s tests (p < 0.05 considered significant).

### Results
All LLMs except Claude 3.5 Haiku outperformed the average individual respondent (mean human accuracy: 50.4%, 95% CI: 40.8–60.0%), with GPT-4o achieving the highest model accuracy at 72.0% (95% CI: 66.7–76.8%). However, the collective human response—the most frequently selected answer—was correct in 93.0% of cases (95% CI: 86.3–96.6%), significantly outperforming every LLM. The most popular response across LLMs (i.e., the answer most frequently selected by the models) was correct in 65.3% of cases (95% CI: 56.0–74.7), significantly lower than the collective human accuracy. Correct answers were associated with higher confidence scores for all LLMs except Gemini Flash, suggesting self-rated confidence may be a useful proxy for model reliability.

### Conclusion
Multimodal LLMs can outperform individual human respondents on image-based diagnostic tasks but fall short of the accuracy achieved by collective human reasoning. This underscores a key strength of human cognition: the diversity of thought across individuals produces more accurate outcomes than any single decision-maker, human or machine. In contrast, LLMs often rely on a uniform reasoning process that can propagate the same errors consistently. While LLMs hold promise as diagnostic aids, further refinement may be required for them to match the collective intelligence of human experts in interpreting clinical vignettes.

Accuracy of Multimodal Large Language Models vs. Human Consensus in Interpreting Clinical Vignettes

### Background
Infertility is a rising health concern that affects approximately 13% of reproductive age women, but advancements in treatment are limited by our understanding of endometrial function. Decidualization is the process of endometrial stromal cell (eSC) differentiation from a fibroblastic state to a secretory state that occurs during the mid-secretory phase of the menstrual cycle and is associated with a dramatic influx of uterine natural killer (uNK) cells to the endometrium. Defects in decidualization and uNK cell function are associated with infertility, implantation failure, and pregnancy loss, but mechanisms of eSC-uNK cell interaction are not well defined. In this study, we developed and validated uNK cell isolation and expansion techniques using menstrual effluent (ME) as a source of endometrial tissue, then used these ME-derived uNK cells to investigate interactions between uNK cells and decidualizing eSCs to further understand cellular processes occurring prior to embryo implantation.

### Methods
ME samples were collected from participants of the Research OutSmarts Endometriosis (ROSE) study at the Feinstein Institutes for Medical Research. uNK cells were purified by sequential magnetic isolations and expanded in vitro using IL-15 and IL-2. These ME-derived uNK cells were transcriptionally verified by scRNAseq and compared to reference datasets. For co-culture experiments, eSC decidualization was induced by cAMP + MPA. Interactions between uNK cells and decidualizing eSCs were characterized by live-imaging microscopy, eSC staining, and scRNAseq. Functional mechanisms of uNK-eSC interaction were described by protein and gene expression using ELISA and qPCR analyses.

### Results
This novel uNK cell isolation method achieved a purity of up to 92% CD56bright CD16- uNK cells. Cultured ME-derived uNK cells exhibited up to 30-fold expansion, maintained viability for approximately 30 days, and retained phenotypes of reference decidua-derived uNK cells as assessed by flow cytometry and single cell RNA sequencing. In an ME-derived model of uNK-eSC interaction, uNK cells mediated contact-dependent eSC remodeling during decidualization as determined by live-imaging microscopy and cell density analysis. uNK cells concurrently stimulated a pro-inflammatory eSC response in part via IFN release as determined by transcriptomic and proteomic analysis.

### Conclusion
These results indicate that ME is a viable, non-invasive source of uNK cells that can be used for downstream analyses and suggest that uNK cells mediate both eSC remodeling and inflammation during decidualization. Interactions between uNK cells and eSCs are critical for endometrial receptivity, and this novel ME-derived system greatly expands the available tools to investigate mechanisms contributing to endometrial homeostasis and female fertility.

Waste to Wonder: Understanding endometrial interactions using a menstrual-effluent derived model

### Background
Veterans of the armed forces are the embodiment of our nation's security and freedom. The health challenges they face are often exacerbated by service-related issues including psychological trauma, excess repetitive noise, radiation exposure, and subjection to dangerous chemicals from Agent Orange, burn pit smoke, water contamination, asbestos, and more. [ref PMID: 34070145] Veterans experience a higher prevalence of complex health conditions, including increased risk of heart and lung diseases, diabetes mellitus, and various cancers. [ref PMID: 39696828] Providing high-quality equitable care to veterans requires targeted healthcare strategies that address their specific needs.

### Methods
To enhance the quality of care provided to our veteran population at Geisinger, we integrated inquiries about military service and health requirements into an 8-question “About Me” questionnaire. This initiative aimed to establish a clearer connection between veterans and the medical services they require. Utilizing the SlicerDicer® tool in the Epic electronic health record system, we analyzed our veteran population to identify prevalent health risks with the goal of using these data to develop targeted care programs.

### Results
Veterans (n=35,648) had higher overall risk scores for various health conditions compared to the non-veteran population (n=507,773). Specifically, the risk ratios for chronic obstructive pulmonary disease (COPD) were 2.09, for hypertension 1.60, for heart failure 2.47, for diabetes 1.74, and for other cancers 2.19. Among Vietnam veterans (n=5,441), the risk ratios for certain conditions indicated increased vulnerabilities: hypertension at 1.79, type 2 diabetes at 1.99, prostate cancer at 2.89, skin cancer at 2.44, and atherosclerosis at 2.18. Gulf War veterans (1990-present, n=7,586) showed significantly higher relative risks for post-traumatic stress disorder (PTSD) at 7.00, COPD at 3.55, hypertension at 2.84, asthma at 1.58, and lung cancer at 2.14.

### Conclusion
Our findings highlight the critical need for tailored healthcare initiatives for Vietnam and Gulf War veterans, who are the most at-risk populations among veterans. These findings support the development of specialized screening, prevention, and treatment protocols that recognize both the physical and psychological effects of military service as seen in previous studies. This information will be used to create a value-based care guide aimed at optimizing care for our veteran population, as many utilize community healthcare facilities outside of the VA, and this fills an urgent gap in educating healthcare teams about veteran health needs.

Leveraging Patient-Provided Data in the Electronic Health Record to Improve Care for Veterans

### Background
The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides essential nutritional, health, and educational support to low-income pregnant women; however, little is known about trends in program participation and associated maternal characteristics this past decade. We aim to investigate temporal trends and maternal predictors of WIC participation during pregnancy in California from 2010-2021, focusing on sociodemographic, geographic, and behaviors. Understanding these predictors is critical for informing equitable access and targeted policy interventions.

### Methods
We conducted a retrospective cohort analysis of 5,529,722 singleton births among California residents using population-based birth cohort data from 2010 to 2021. Descriptive statistics, linear trend analyses, and multivariate logistic regression models were used to assess prevalence and predictors of WIC utilization during pregnancy. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values were reported in quantified associations. Statistical significance was defined as p < 0.05.

### Results
WIC participation declined significantly over the study period, from 54.1% in 2010 to 35.0% in 2021 (β=–1.83, p<.0001, R²=0.98). Multivariate analysis identified several independent predictors of WIC utilization. Compared to mothers aged 40–54 years, those under 20 had the highest odds of WIC use (OR = 3.12; 95% CI: 3.06–3.19). African American (OR = 3.126), Hispanic (OR = 2.96), and American Indian mothers (OR = 1.53) were significantly more likely to participate than White mothers. A strong inverse gradient was observed; mothers with less than high school education had nearly sixfold higher odds (OR = 5.84) than those with a bachelor’s degree or higher. Utilization was higher among foreign born mothers (OR = 1.53) and in regions such as San Joaquin Valley (OR = 2.72) and Los Angeles County (OR = 2.55) compared to Greater Bay Area. Mothers with Medi-Cal (OR=8.09), first-trimester prenatal care (OR = 1.07), higher prepregnancy BMI (e.g., OR = 1.91 for Obese III), vaginal deliveries (OR = 1.02), and maternal smoking during both trimesters (OR = 1.17) were significantly more likely to participate.

### Conclusion
WIC utilization during pregnancy has declined markedly in California, despite persistent disparities by age, race/ethnicity, education, nativity, geographic region, and healthcare access. Addressing structural barriers and improving outreach is essential to enhance equitable WIC engagement and improve maternal-child health.

Trends and Determinants of WIC Participation Among Pregnant Women in California: A Decade-Long Population Study

Levodopa, co-administered with the dopa decarboxylase inhibitor carbidopa, remains the gold standard for treating Parkinson's Disease; however, due to rapid degradation, only about 1% of orally administered levodopa crosses the blood-brain barrier.
This study developed and validated a robust high-performance liquid chromatography method to quantify levodopa, achieving reliable linearity across multiple replicates. Various buffer systems and pH conditions were tested, with phosphate buffered saline (PBS) at pH 6 and supplemented with glutamic acid hydrochloride offering the most stable environment. With stability confirmed, levodopa was successfully incorporated into a hydrogel matrix using poly(vinyl alcohol) (PVA), and hydrogel-forming microneedles using poly(methyl vinyl
ether/maleic acid), polyethylene glycol, and sodium bicarbonate. These microneedles
demonstrated sufficient mechanical strength to penetrate Parafilm “M” skin simulants, suggesting potential for effective skin permeation.
This work represents a significant step toward creating an alternative levodopa delivery system that could reduce gastrointestinal side effects, improve patient adherence, and offer more consistent plasma drug levels, thereby alleviating the motor fluctuations common with oral levodopa therapy. Although not curative, the finding supports further investigation into in vitro permeation studies and eventual clinical translation of microneedle-based patch system for Parkinson’s disease management.

Development and Characterization of Levodopa Microneedle Patches for Parkinson's Disease

### Background
Despite current treatment strategies for atherosclerotic vascular disease focusing on lifestyle modification and lowering cholesterol, a significant residual risk of major atherosclerotic complication remains, prompting investigation into lipoprotein(a) [Lp(a)] as a potential predictive biomarker. The objective of this study was to determine the utility of Lp(a) in identifying patients at high risk of incident extracoronary atherosclerotic vascular disease and complications. 

### Methods
Data from 460,544 participants in the UK Biobank with prospectively measured Lp(a) concentrations were included in this analysis. Cox proportional hazards regressions modeled the associations of Lp(a) concentrations with incident peripheral arterial disease (PAD) and incident carotid artery stenosis, and progression to the first major adverse limb event (MALE) and the first stroke, respectively.

### Results
Of the study participants, the median [IQR] age at study enrollment was 58 [51 – 64] years, 54.2% were male, 94.4% European, 5.5% had diabetes, and 10.5% were smokers. Over a median follow-up time of 13.6 [12.9 – 14.4] years, 6,347 (1.4%) and 1,972 (0.43%) developed the first incidence of PAD and carotid stenosis, respectively. Among participants with prevalent PAD and carotid stenosis at enrollment, 196 (2.7%) and 67 (1.9%) progressed to the first incidence of MALE and stroke, respectively. Median Lp(a) concentrations were significantly different in those without atherosclerotic vascular disease at 19.5 nmol/L [7.6-73.5] compared to incident PAD at 25.3 nmol/L [8.3-107.3], progression to MALE at 33.3 nmol/L [8.7-158.2], incident carotid stenosis at 29.5 nmol/L [8.5-116.3], and carotid stenosis progression to stroke at 37.8 nmol/L [11.1-158.3]. The risk estimate per 75 nmol/L Lp(a) for incident PAD (HR 1.18, 95% CI 1.15-1.20, p-value<0.0001) was similar to incident carotid stenosis (HR 1.17, 95% CI 1.13-1.20, p-value<0.0001). Among participants with PAD, those with high Lp(a) concentrations were at 1.57 times the risk of developing MALE than participants with normal Lp(a) concentrations (95% CI 1.14-2.16, p-value=0.006). Among participants with carotid stenosis, participants had 1.40 times the risk of developing an ischemic stroke with high Lp(a) concentrations, although this was not significant (95% CI 0.81-2.40, p-value=0.228).

### Conclusion
High concentrations of Lp(a) are associated with both incident extracoronary atherosclerotic vascular disease and progression to major complications.


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