Association of body mass, gender and race with heart failure primarily due to hypertension

OBJECTIVES: This study was performed to determine the association between clinical characteristics, particularly body mass and race, and the likelihood of hypertension as the primary etiology for heart failure (HTNCM). BACKGROUND: Although held to be important in the development of heart failure, the clinical characteristics predictive of HTNCM have not been well delineated. METHODS: The study analysis was conducted using 680 patients from the University of North Carolina Heart Failure Database. This data set is racially diverse (44% African-American) and contains data concerning baseline clinical characteristics and cardiac function in patients with and without HTNCM. Logistic regression techniques determined independent predictors of HTNCM among the entire study population as well as the subgroup of study patients with hypertension. RESULTS: Hypertension was present in 51% of the study patients but was the primary etiology of heart failure in only 25%. Body mass, race, gender and baseline systolic blood pressure were identified as significant independent predictors of the likelihood of HTNCM (all p < 0.001). These characteristics were predictors in the total study population and also in the subgroup of study patients with hypertension. CONCLUSIONS: Hypertension remains a common etiologic factor for the development of heart failure but was the primary cause of heart failure in a minority of study patients. However, the presence of increased body mass, female gender, African-American ethnic origin or elevated baseline systolic blood pressure significantly increased the likelihood of HTNCM

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

Diffusion models have been shown to be capable of generating high-quality images, suggesting that they could contain meaningful internal representations. Unfortunately, the feature maps that encode a diffusion model's internal information are spread not only over layers of the network, but also over diffusion timesteps, making it challenging to extract useful descriptors. We propose Diffusion Hyperfeatures, a framework for consolidating multi-scale and multi-timestep feature maps into per-pixel feature descriptors that can be used for downstream tasks. These descriptors can be extracted for both synthetic and real images using the generation and inversion processes. We evaluate the utility of our Diffusion Hyperfeatures on the task of semantic keypoint correspondence: our method achieves superior performance on the SPair-71k real image benchmark. We also demonstrate that our method is flexible and transferable: our feature aggregation network trained on the inversion features of real image pairs can be used on the generation features of synthetic image pairs with unseen objects and compositions. Our code is available at https://diffusion-hyperfeatures.github.io.Comment: NeurIPS 202

Differentiation of Equine Mesenchymal Stromal Cells into Cells of Neural Lineage: Potential for Clinical Applications

Mesenchymal stromal cells (MSCs) are able to differentiate into extramesodermal lineages, including neurons. Positive outcomes were obtained after transplantation of neurally induced MSCs in laboratory animals after nerve injury, but this is unknown in horses. Our objectives were to test the ability of equine MSCs to differentiate into cells of neural lineage in vitro, to assess differences in morphology and lineage-specific protein expression, and to investigate if horse age and cell passage number affected the ability to achieve differentiation. Bone marrow-derived MSCs were obtained from young and adult horses. Following demonstration of stemness, MSCs were neurally induced and microscopically assessed at different time points. Results showed that commercially available nitrogen-coated tissue culture plates supported proliferation and differentiation. Morphological changes were immediate and all the cells displayed a neural crest-like cell phenotype. Expression of neural progenitor proteins, was assessed via western blot or immunofluorescence. In our study, MSCs generated from young and middle-aged horses did not show differences in their ability to undergo differentiation. The effect of cell passage number, however, is inconsistent and further experiments are needed. Ongoing work is aimed at transdifferentiating these cells into Schwann cells for transplantation into a peripheral nerve injury model in horses

Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation

Many fine-grained classification tasks, like rare animal identification, have limited training data and consequently classifiers trained on these datasets often fail to generalize to variations in the domain like changes in weather or location. As such, we explore how natural language descriptions of the domains seen in training data can be used with large vision models trained on diverse pretraining datasets to generate useful variations of the training data. We introduce ALIA (Automated Language-guided Image Augmentation), a method which utilizes large vision and language models to automatically generate natural language descriptions of a dataset's domains and augment the training data via language-guided image editing. To maintain data integrity, a model trained on the original dataset filters out minimal image edits and those which corrupt class-relevant information. The resulting dataset is visually consistent with the original training data and offers significantly enhanced diversity. We show that ALIA is able to surpasses traditional data augmentation and text-to-image generated data on fine-grained classification tasks, including cases of domain generalization and contextual bias. Code is available at https://github.com/lisadunlap/ALIA.Comment: Update: replaced Planes dataset with Waterbirds & updated results after bug fi

Using Language to Extend to Unseen Domains

It is expensive to collect training data for every possible domain that a vision model may encounter when deployed. We instead consider how simply verbalizing the training domain (e.g. "photos of birds") as well as domains we want to extend to but do not have data for (e.g. "paintings of birds") can improve robustness. Using a multimodal model with a joint image and language embedding space, our method LADS learns a transformation of the image embeddings from the training domain to each unseen test domain, while preserving task relevant information. Without using any images from the unseen test domain, we show that over the extended domain containing both training and unseen test domains, LADS outperforms standard fine-tuning and ensemble approaches over a suite of four benchmarks targeting domain adaptation and dataset bias

Randomized Controlled Trial of a Remote Coaching mHealth Adherence Intervention in Youth Living with HIV

Youth living with HIV (YLWH) in the US have low rates of viral suppression (VS). In a prospective randomized clinical trial (ATN152) that enrolled 89 YLWH on antiretroviral therapy (ART) with detectable viral load, we evaluated a 12 week triggered escalating real-time adherence (TERA) intervention with remote coaching, electronic dose monitoring (EDM), and outreach for missed/delayed doses compared to standard of care (SOC). Median [Q1, Q3] percent days with EDM opening was higher in TERA (72% (47%, 89%)) versus SOC (41% (21%, 59%); p&lt;0.001) and incidence of numbers of 7 day gaps between openings were lower (TERA to SOC ratio: 0.40; 95% CI 0.30, 0.53; p&lt;0.001). There were no differences in VS at week 12 (TERA 35%; 95% CI 21%, 51% versus SOC 36%; 95% CI 22%, 51%; p&gt;0.99) or later time-points. The intervention improved adherence but not VS in heavily ART-experienced YLWH. Remote coaching more closely tailored to the unique dosing patterns and duration of need for youth struggling to reach VS warrants further investigation

Prospectus, September 14, 1977

TWO VIE FOR VEEP POST: STUDENT GOVERNMENT ELECTIONS TODAY; Elections scheduled today and tomorrow; District 505 entitled to minimum credit grants; Activities postponed; Unopposed; Shiloh\u27s and Sonshine Circle to perform; Survival of democratic society topic at forum; Vets must go by book; \u27Self Defense\u27 is under attack; Youngest brew master is nun; Warners, women battle over \u27Jump On It\u27; Male prostitute makes history; News From \u27Her Say\u27: Ten women earn wings; UAW asks Congress for maternity benefits \u27as soon as possible\u27; Career Awareness Course for women Wednesday eve.; Instructors earn high grades from PC students; Back orders on home insulation cause woes; Blowing of the shofar means Rosh Hashanah, start of 5,738 New Year; Springfield news: senior citizens, equal language; The gas man cometh...; Holograph exhibit at PC tomorrow; Letting out some Slack...: Answers for queries on PC; Chicago painter displays at KCPA; Prospectus Pigskin Preview: Cobra Grid Schedule, Parkland Roster, Fight on Cobras; Alaskan wilderness is summer home to Basler; Parkland Learning Laboratory: Early help available to students; Stu-Go explores check cashing for PC people; PC music groups have many openings; Jumers: German touch; \u27Elite\u27 women to get public house; Home care topic to be presented; Classifieds; X-country opens Saturday; Spikettes look good; Sports shorts; Bio instructor Cox wins Fast Freddy; Intramural sign up closing; The continuing battle for Number 1; Parkland to host nationalshttps://spark.parkland.edu/prospectus_1977/1013/thumbnail.jp