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This article focuses on agar biopolymer films that offer promise for developing biodegradable packaging, an important solution for reducing plastics pollution. At present there is a lack of data on the mechanical performance of agar biopolymer films using a simple plasticizer. This study takes a Design of Experiments approach to analyze how agar-glycerin biopolymer films perform across a range of ingredients concentrations in terms of their strength, elasticity, and ductility. Our results demonstrate that by systematically varying the quantity of agar and glycerin, tensile properties can be achieved that are comparable to agar-based materials with more complex formulations. Not only does our study significantly broaden the amount of data available on the range of mechanical performance that can be achieved with simple agar biopolymer films, but the data can also be used to guide further optimization efforts that start with a basic formulation that performs well on certain property dimensions. We also find that select formulations have similar tensile properties to thermoplastic starch (TPS), acrylonitrile butadiene styrene (ABS), and polypropylene (PP), indicating potential suitability for select packaging applications. We use our experimental dataset to train a neural network regression model that predicts the Young’s modulus, ultimate tensile strength, and elongation at break of agar biopolymer films given their composition. Our findings support the development of further data-driven design and fabrication workflows.

Introduction Breast cancer remains a leading cause of death among Latinas. Although breast cancer risk assessment models exist and show promise in reducing mortality, few studies have elicited women's interest in and perceptions around breast cancer risk assessment, particularly among underserved populations, like Latinas, who are susceptible to disparities in breast cancer outcomes. These disparities stem from factors such as limited access to healthcare services, lower rates of screening utilization, language barriers, and socioeconomic challenges, all of which compound their risk and hinder effective engagement with risk assessment tools. This qualitative study aims to explore Latinas' perspectives regarding breast cancer risk assessment and implications on future behaviors. Methods Twenty‐three under‐ or uninsured Latinas aged 45–65 with no personal history of breast cancer took part in either a focus group (n = 3, 15 participants) or individual interviews (8 participants). Guided by health behavior theories (Theory of Planned Behavior and Health Belief Model), data were transcribed, translated, and analyzed using a deductive‐inductive approach to thematic content analysis, resulting in four themes. Results Latinas expressed high interest in knowing their breast cancer risk and reported that the benefits of knowing one's risk outweighed the harms. Latinas also stated that they would continue screening as recommended if found to be at low risk, but that they would speak with their provider or increase screening frequency if found to be at increased risk. Moreover, Latinas described the pivotal role of providers and social networks in influencing interest and perceptions around breast cancer risk assessment and preventive behaviors. Conclusion Underserved Latinas viewed breast cancer risk assessment positively and underscored the need for multilevel, culturally tailored strategies to improve breast cancer risk assessment. This study yielded four distinct themes: (1) Interest and Awareness of Personal Breast Cancer Risk, (2) Benefits and Barriers of Knowing Personal Breast Cancer Risk, (3) Screening Implications of Knowing Personal Breast Cancer Risk, and (4) Provider Influence on Breast Cancer Risk Assessment and Behaviors. Potential strategies include efforts to improve provider engagement and communication and leveraging social networks to increase awareness and encourage preventive behaviors. Trial Registration NCI‐2023‐00465

The design of biodegradable polymeric materials is of increasing scientific interest due to accelerating levels of plastics pollution. One area of increasing interest is the design of biodegradable polymer films based on seaweed as a raw material. The goal of the study is to explore whether machine learning techniques can be used to predict the properties of unknown compositions based on existing data from the literature. Clustering algorithms are used, which show how some ingredients components at certain concentration levels alter the mechanical properties of the films. Robust regression algorithms with three popular models, namely decision tree, random forest, and gradient boosting. Their predictive capabilities are compared, resulting in the random forest algorithm being the most stable with the greatest predictive capacity. These analyses offer a decision support system for biomaterials manufacturing and experimentation. The results and conclusions of the study indicate that bioplastics made from seaweed have promising potential as a sustainable alternative to traditional plastics, discovering interesting additives to improve the performance of biopolymers. In addition, the machine learning approaches used provide effective tools for analyzing and predicting the properties of these materials in structured but highly sparse data.

Automated analysis of the scientific literature using natural language processing (NLP) can accelerate the identification of potentially unexplored formulations that enable innovations in materials engineering with fewer experimentation and testing cycles. This strategy has been successful for specific classes of inorganic materials, but their general application in broader material domains such as bioplastics remains challenging. To begin addressing this gap, we explore correlations between the ingredients and physicochemical properties of seaweed-based biofilms from a corpus of 2000 article abstracts from the scientific literature since 1958, using a supervised word co-occurrence analysis and an unsupervised approach based on the language model MatBERT without fine-tuning. Using known relations between ingredients and properties for test scenarios, we discuss the potential and limitations of these NLP approaches for identifying novel combinations of polysaccharides, plasticizers, and additives that are related to the functionality of seaweed biofilms. The model demonstrates a valuable predictive ability to identify ingredients associated with increased water vapor permeability, suggesting its potential utility in optimizing formulations for future research. Using the model further revealed alternative combinations that are underrepresented in the literature. This automated method facilitates the mapping of relationships between ingredients and properties, guiding the development of seaweed bioplastic formulations. The unstructured and heterogeneous nature of the literature on bioplastics represents a particular challenge that demands ad hoc fine-tuning strategies for state-of-the-art language models for advancing the field of seaweed bioplastics.

The ectodysplasin receptor (EDAR) is a tumor necrosis factor receptor (TNF) superfamily member. A substitution in an exon of EDAR at position 370 (EDARV370A) creates a gain of function mutant present at high frequencies in Asian and Indigenous American populations but absent in others. Its frequency is intermediate in populations of Mexican ancestry. EDAR regulates the development of ectodermal tissues, including mammary ducts. Obesity and type 2 diabetes mellitus are prevalent in people with Indigenous and Latino ancestry. Latino patients also have altered prevalence and presentation of breast cancer. It is unknown whether EDARV370A might connect these phenomena. The goals of this study were to determine 1) whether EDARV370A is associated with metabolic phenotypes and 2) if there is altered breast anatomy in women carrying EDARV370A. Participants were from two Latino cohorts, the Arizona Insulin Resistance (AIR) registry and Sangre por Salud (SPS) biobank. The frequency of EDARV370A was 47% in the Latino cohorts. In the AIR registry, carriers of EDARV370A (GG homozygous) had significantly (p < 0.05) higher plasma triglycerides, VLDL, ALT, 2-hour post-challenge glucose, and a higher prevalence of prediabetes/diabetes. In a subset of the AIR registry, serum levels of ectodysplasin A2 (EDA-A2) also were associated with HbA1c and prediabetes (p < 0.05). For the SPS biobank, participants that were carriers of EDARV370A had lower breast density and higher HbA1c (both p < 0.05). The significant associations with measures of glycemia remained when the cohorts were combined. We conclude that EDARV370A is associated with characteristics of the metabolic syndrome and breast density in Latinos.

PurposeThe Sangre Por Salud (SPS) Biobank was established to facilitate biomedical research opportunities for the Latino community by creating an easily accessible prospective cohort for scientists interested in studying health conditions and health disparities in this population.ParticipantsIndividuals self-identifying as Latino, aged 18–85 years, were prospectively recruited from the primary care Internal Medicine clinic at Mountain Park Health Center in Phoenix, Arizona. After obtaining informed consent, detailed medical history questionnaires were captured, and blood samples were obtained for common laboratory tests. Participants authorised the research team to access their electronic health records for research purposes. In addition, participants had serum, plasma and DNA samples isolated and stored at the Mayo Clinic Arizona Biorepository Laboratory for long-term storage and future access. As part of the study, participants consented and agreed to be contacted for potential participation in future research studies.Findings to date3756 participants provided informed consent, of whom 3733 completed all study questionnaires, an oral glucose tolerance test and had blood collected and stored. The SPS cohort is predominantly composed of females (72%), with a median age at time of consent of 42 years. All participants self-identified as Hispanic/Latino, 45% were married, 53% were employed for wages and 60% had less than a high school degree. Around 25% of participants met diagnostic criteria for overweight (BMI 25–29 kg/m2), and 49% met for obesity (BMI≥30 kg/m2). At time of recruitment, hypertension, hyperlipidaemia and depression affected 22%, 20% and 13% of the cohort, respectively.Future plansWe plan to regularly update the participants’ electronic health records and self-reported health data to longitudinal research. Additionally, we plan to obtain a more comprehensive genomic analysis on the entire cohort, ensuring greater research interest and investigation into the underlying genetic factors that contribute to disease susceptibility in this cohort.

Laws mandating that women be informed of mammographic breast density (MBD) with their mammogram results may increase anxiety. We report on changes in self-reported levels of anxiety, worry about developing breast cancer (BC), as well as perceived risk of BC resulting from three MBD notification methods: usual care (mailed notification letter), enhanced care (usual care with MBD educational brochure), or interpersonal care (enhanced care with promotora education), among a Latina population. A randomized controlled clinical trial of three MBD notifications was performed among Latina women aged 40 to 74 years receiving screening mammography at a federally qualified health center (FQHC). Measures of anxiety, BC worry and perceived lifetime BC risk were assessed using a questionnaire. Anxiety was measured using the State-Trait Anxiety Inventory scale (STAI-S). The question: \"How frequently do you worry about getting breast cancer someday\" assessed BC worry. perceived lifetime risk of BC was rated between 0% (no chance) to 100% (definitely will get). Additional surveys were completed at two weeks to six months (T1) and one year (T2) after the intervention. 1332 Latina women were randomized between October 2016 and October 2019. At T0, 51.8% had moderate or severe anxiety. BC worry was reported to be sometimes/ often/ almost all the time among 41.3% of participants. 25.4% reported a perceived lifetime risk of developing BC of > 10%, compared with 6.6% with Gail model estimated lifetime risk score of > 10%. There was no significant difference in the proportion of patients who maintained low or had decrease in their levels of anxiety, BC worry or perceived risk from T0 to either T1 or T2 surveys between intervention groups. This Latina cohort had high levels of anxiety and BC worry which persisted regardless of intervention received. Future work is needed to improve our understanding of factors that could lower anxiety and BC worry and improve BC risk perception in this population.

Chromobacterium violaceum is a facultative anaerobic, Gram-negative rod found in different ecosystems, especially tropical and subtropical areas. Human infections are rare, and just a few cases have been reported in literature. In this paper, we present the first non-lethal infection due to Chromobacterium violaceum, in an adult male with polycystic kidney disease in Colombia. Periareolar soft tissue infection was documented with isolation of Chromobacterium violaceum. Clinical manifestations, treatment, and outcome are shown.

The use of seaweed as fuel has been mentioned in ethnographic and historical sources of different coastal regions. Nevertheless, the archaeological record of seaweed burning is still limited to contexts where preservation is exceptional and macroscopic discrimination of charred remains is possible. Here, we evaluate the effectiveness of Raman spectroscopy in discriminating seaweed vs. plant/wood char. Our dataset ( N  = 92) consists of modern and archaeological seaweed and plant/wood charred remains, including specimens of unknown origin from the Atacama Desert coast, Northern Chile. The charred samples were processed to obtain 13 parameters which were then fed into five supervised machine learning models. The models, built on samples of known origin (seaweed and plant/wood), performed remarkably well in terms of accuracy, kappa, sensitivity, and specificity. The models were used for final predictions on 10 non-identified archaeological charcoals. Our results suggest that Raman spectroscopy combined with machine learning techniques is a robust methodology for discriminating seaweed and plant/wood charred remains in the archaeological record. The predictions on unknown samples confirm that seaweed was used as fuel in a specific funerary ritual in the southern Atacama Desert coast around 5000 cal BP. Furthermore, charred specimens of Lessonia spp. recovered from combustion features in other northern Chile coastal settlements, suggest that seaweed pyrotechnology developed by Atacama Desert coast people is likely a long-term process. As for coastal archaeology, this work encourages new research on seaweed as an alternative/main fuel in coastal deserts and evaluates possible bias for chronologies from coastal archaeological settlements around the globe.

Cholinergic neuron impairment is a significant cause of cognitive decline in Alzheimer’s disease (AD), making acetylcholinesterase (AChE) a key therapeutic target. AChE inhibitors are principal drugs prescribed to alleviate symptoms in AD patients, while up to 50% of these individuals also suffer from depression, frequently treated with selective serotonin reuptake inhibitors (SSRIs). Due to the multisymptomatic nature of AD, there is a growing interest in developing multitargeted ligands that simultaneously enhance cholinergic and serotonergic tone. This study presents the synthesis of novel ligands based on functionalized piperidines, evaluated through radioligand binding assays at the serotonin transporter (SERT) and AChE and butyrylcholinesterase (BuChE) inhibition. The pharmacological results showed that some compounds exhibited moderate inhibitory activity against AChE, with one compound 19 standing out as the most potent, also displaying a moderate BuChE inhibitory activity, while showing low affinity for SERT. On the other hand, compound 21 displayed an interesting polypharmacological profile, with good and selective activity against BuChE and SERT. The results underscore the difficulty of designing promiscuous ligands for these targets and suggest that future structural modifications could optimize their therapeutic potential in AD.