The CHA Somerville Campus is an outpatient medical center at 33 Tower Street in Somerville, Massachusetts - near Porter Square and Davis Square.It is operated by Cambridge Health Alliance.
Artificial intelligence (AI) tools can improve breast screening performance but different screening sites have varying needs. Here the GEMINI prospective evaluation of 10,889 women, within one UK region, used both live AI integration and simulations to model 17 different ways AI could be used in breast screening. All women received routine care. One AI tool was assessed. When the AI tool recommended recall but routine double reading did not, cases underwent additional human review, detecting 11 additional cancers. The primary AI workflow could improve cancer detection by 10.4% (1 per 1,000), maintain the recall rate (0.8% reduction) and reduce workload by up to 31%. Other workflow variations significantly improved all measured metrics (superiority in cancer detection rate, recall rate, positive predictive value (PPV), sensitivity and specificity) with up to 36% workload savings. Different AI integrations in breast screening could offer various clinical and operational gains, allowing for adaptation to local healthcare needs.
The production of lithium chemicals needs to increase to meet rising demand for lithium batteries. Spodumene [LiAl(SiO 3 ) 2 ] is an abundant mineral source of lithium, but its extraction is not cost-competitive with brine resources. Current spodumene-refining methods are energy- and waste-intensive, requiring high-temperature roasting (>1000°C) and chemical leaching. We demonstrate a low-temperature, near-zero-waste process that converts α-spodumene into battery-grade lithium carbonate (Li 2 CO 3 ), smelter-grade alumina (Al 2 O 3 ), and cementitious silica (SiO 2 ). Aqueous ammonium fluoride (NH 4 F) is used as the reagent to solubilize the mineral feedstock at <100°C in a closed-loop process that regenerates the reagent. Techno-economic analysis indicates that this approach may reduce the cost of producing lithium from α-spodumene by >40% and enable cost parity with brines.
Particulate matter (PM) pollution is a leading cause of cardiovascular risk and illness, including elevated blood pressure (BP). The purpose of this study was to test the efficacy of in-home air purifiers to reduce BP for adults living adjacent to highways. We conducted a pragmatic randomized crossover trial of the effect of high-efficiency particulate arrestance (HEPA) vs sham filtration on BP. Residences were randomized to start with 1 month of HEPA filtration or 1 month of sham filtration. A 1-month wash out period with no filtration was followed by 1 month of the alternate filtration. Participant questionnaire data and BP were collected 4 times, at the start and end of each filtration period. PM concentrations were measured in a subset of residences. Linear mixed models were used to compare the mean change in BP between the HEPA and sham filtration periods. Models were adjusted for time invariant and time-varying covariates. A total of 154 participants were analyzed. The mean age was 41.1 years, 59.7% were women, 68.2% were non-Hispanic White, and a majority were of higher socioeconomic status. The mean baseline brachial systolic blood pressure (SBP)/diastolic BP was 118.8/76.5 mm Hg. HEPA filtration significantly reduced PM in comparison to both indoor sham and outdoor levels. Participants' SBP at the start of the intervention period moderated the efficacy of the intervention (P = 0.03). Participants who had elevated brachial SBP (≥120 mm Hg) had a significant 2.8-mm Hg mean reduction in SBP after HEPA filtration (P = 0.03) and a 0.2-mm Hg mean increase in SBP after sham filtration (P = 0.85). The net result was a significant 3.0-mm Hg mean difference in favor of HEPA filtration (P = 0.04). There was no significant benefit on diastolic BP or for participants with normal SBP (<120 mm Hg). The use of in-home HEPA air purifiers resulted in clinically important reductions in SBP for people with elevated SBP in environments with relatively low PM2.5 concentrations.
Introduction and Objective: Low-income adults face barriers to healthy eating. This study assessed the relative importance of sociodemographic and behavioral factors associated with diet quality in a sample of low-income patients with prediabetes or type 2 diabetes (T2D) to identify modifiable targets for a tailored diabetes self-management education and support (DSMES) program. Methods: Baseline surveys collected demographic (e.g., age, race/ethnicity), social needs (e.g., food and housing security), and behavioral (e.g., mental health, physical activity) factors. Primary outcome was Healthy Eating Index-2020 (HEI) diet quality score (range 0-100, higher=healthier). Random forests were fit and Shapley Additive Explanation values were used to determine relative importance of factors in predicting HEI. Results: Of 278 participants, 42% had prediabetes and 58% had T2D. Median age (IQR) was 52 (43, 57); 58% were Hispanic. Top 6 behavioral factors associated with lower HEI were current smoking, fewer distinct foods eaten per day, longer time sitting per day, lower sleep quality, worse depression symptoms, and cannabis use. The Figure displays radar plots of HEI component scores for the top 4 factors. Conclusion: We identified important behavioral risk factors for lower diet quality which could be targeted in a DSMES program tailored for low-income populations. K.D. Gu: None. D. Shinnick: None. T. Thaweethai: None. J. Cheng: None. D.J. Wexler: Other Relationship; Novo Nordisk. A.N. Thorndike: None. National Institutes of Health F32DK141094
