Characteristics of Viscoelastic-Surfactant-Induced Wettability Alteration in Porous Media

Wettability alteration is one of the most important mechanisms of surfactant flooding. In this work, the combined Amott/USBM (United States Bureau of Mines) method was applied to study the average wettability alteration of initially neutral cores after viscoelastic-surfactant (VES) filtration. The effects of static aging, dynamic aging, VES concentration, filtration flow rate, and pore radius on the alteration of a core’s average wettability were studied. The wettability-alteration trends measured by Amott and USBM were consistent, demonstrating that the overall hydrophilicity of the core was enhanced after VES filtration. The wettability alterations of the core brought about by dynamic aging were more significant than by static aging. The viscoelastic properties of the VES played an important role in altering the wettability. In addition, the ability of the VES to affect the core’s wettability was significantly enhanced when the VES concentration was increased, which was beneficial in increasing VES adsorption on the pore-wall surface, thus altering the overall wettability of the core. Increasing filtration flow rates can destroy those high-viscosity VES aggregates via the higher shear rate. A higher retention of VES makes the core more hydrophilic. The difference in the wettability of cores with different pore radius after VES filtration was not significant. The alteration of average wettability caused by VES in porous media provides a new vision for studying the EOR mechanism of VES.

Improved supervised prediction of aging-related genes via weighted dynamic network analysis

Background This study focuses on the task of supervised prediction of aging-related genes from -omics data. Unlike gene expression methods for this task that capture aging-specific information but ignore interactions between genes (i.e., their protein products), or protein–protein interaction (PPI) network methods for this task that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions. However, a dynamic aging-specific subnetwork did not improve prediction performance compared to a static aging-specific subnetwork, despite the aging process being dynamic. This could be because the dynamic subnetwork was inferred using a naive Induced subgraph approach. Instead, we recently inferred a dynamic aging-specific subnetwork using a methodologically more advanced notion of network propagation (NP), which improved upon Induced dynamic aging-specific subnetwork in a different task, that of unsupervised analyses of the aging process. Results Here, we evaluate whether our existing NP-based dynamic subnetwork will improve upon the dynamic as well as static subnetwork constructed by the Induced approach in the considered task of supervised prediction of aging-related genes. The existing NP-based subnetwork is unweighted, i.e., it gives equal importance to each of the aging-specific PPIs. Because accounting for aging-specific edge weights might be important, we additionally propose a weighted NP-based dynamic aging-specific subnetwork. We demonstrate that a predictive machine learning model trained and tested on the weighted subnetwork yields higher accuracy when predicting aging-related genes than predictive models run on the existing unweighted dynamic or static subnetworks, regardless of whether the existing subnetworks were inferred using NP or the Induced approach. Conclusions Our proposed weighted dynamic aging-specific subnetwork and its corresponding predictive model could guide with higher confidence than the existing data and models the discovery of novel aging-related gene candidates for future wet lab validation.

Dynamic Aging: Channeled Through Microenvironment

Aging process is a complicated process that involves deteriorated performance at multiple levels from cellular dysfunction to organ degeneration. For many years research has been focused on how aging changes things within cell. However, new findings suggest that microenvironments, circulating factors or inter-tissue communications could also play important roles in the dynamic progression of aging. These out-of-cell mechanisms pass on the signals from the damaged aging cells to other healthy cells or tissues to promote systematic aging phenotypes. This review discusses the mechanisms of how senescence and their secretome, NAD+ metabolism or circulating factors change microenvironments to regulate systematic aging, as well as the potential therapeutic strategies based on these findings for anti-aging interventions.

“He Needed Just About Everything”: Caring for Aging Adults Postincarceration

Little is known about the experiences of caregivers for older adults reentering communities following incarceration. We sought to explore the challenges faced by such caregivers in Central North Carolina. Methods: We conducted a thematic analysis on semi-structured interviews with 11 caregivers. Results: Caregivers discussed how prior incarceration coupled with aging present barriers to housing, employment, and safety-net benefits—making caregiving more difficult. Caregivers assist their older care recipients to develop essential life skills (e.g., scheduling tasks, applying for services) and navigate the dynamic aging process (e.g., loneliness, illness). Caregivers struggle to gain care recipients’ trust, often due to their past trauma. Discussion: Caregivers play essential roles supporting older adults postincarceration, yet they experience significant challenges with limited resources. This study informed the development of a resource guide to assist caregivers. Dedicated programs and policies are needed to address these needs at the local level.