Temperature stability and enhanced transport properties by surface modifications of silica nanoparticle tracers for geo-reservoir exploration

Tracer tests are an important tool for characterizing and monitoring subsurface reservoir properties. However, they are limited both because of the tracer molecules constraining factors such as irreversible adsorption, retention, and degradations, i.e. interaction processes of fluorophore molecule with surrounding media resulting in a large variation in transport properties. Elaborate tests utilizing more than one tracer to distinguish time or location of injection are complex and interpretation is ambiguous because each tracer interacts differently. In this study, we present an approach to increase tracer stability and enhance the transport uniformity of different tracers, thus making tests utilizing multiple tracers simpler and more feasible. We present this concept of tracer multiplicity by encapsulating an anionic, cationic or amphoteric fluorophore inside mesoporous silica nanoparticle carriers coated with a protective titania layer. Upon encapsulation, increased thermal resistance and drastically lowered sorption affinity towards quartz sand was detected in batch and flow-through experiments. An additional advantage of the presented nanoparticle tracers over molecular tracers is their modularity, which is demonstrated by surface modifications and application of additives that greatly reduce sorption and increase recovery rates in the flow experiments. With the here presented concept of tracer multiplicity, we introduce a new approach for colloidal tracer design that has the potential to expand and enhance measurable parameters, measurement accuracy and simplicity of analysis

Nanoparticle-based tracing techniques in geothermal reservoir: Advances, challenges and prospects

Accurate knowledge of reservoir geometry and flow paths are critical parameters for successful geothermal operations. They are essential for evaluating the long-term behavior and sustainability of geothermal reservoirs. Conventional hydraulic testing and tracer tests are often inconclusive or provide limited information due to complex and challenging reservoir conditions (multiple well systems, complex reservoir geometry, and fracture network, etc.). Recently, a new class of tracer techniques has emerged in order to overcome the major drawbacks of molecular tracers: nanoparticle-based tracers. The main advantages of nanoparticle tracers compared to molecular tracers are their tunable properties and modular structure. Functional and smart nanoparticle tracers such as the threshold-triggered temperature nanotracer enabled the simultaneous evaluation of multiple reservoir conditions (flow paths, temperature distribution, etc.) and created an entirely new field of research. As new areas of research often require detailed insights into fundamental processes, there are still open questions about the interactions between particles, fluids, and rock minerals and their performance in complex geothermal environments. As an example, the application of embedded or surface-bound tracing features (e.g., fluorescent molecules, DNA, etc.) within or on a silica matrix prevents the tracing function from being affected by the environment (e.g., pH changes, salinity effects, redox sensitivity). Although silica has low hydro(thermal) stability and loses its protective function at high temperatures or long-term applications, nanoscience offers a comprehensive set of tools to design and protect the silica matrix. Another advantage is the possibility of surface modifications, which can help to achieve minimum sorption and retention by adapting the ζ-potential of the nanoparticles. In this study, we address recent advances in increasing long-term stability, improving hydrothermal stability of silica nanoparticles, sorption control. Furthermore, we present strategies for the development and functionalization of nanoparticle-based tracers

Functional Amyloid Formation within Mammalian Tissue

Amyloid is a generally insoluble, fibrous cross-β sheet protein aggregate. The process of amyloidogenesis is associated with a variety of neurodegenerative diseases including Alzheimer, Parkinson, and Huntington disease. We report the discovery of an unprecedented functional mammalian amyloid structure generated by the protein Pmel17. This discovery demonstrates that amyloid is a fundamental nonpathological protein fold utilized by organisms from bacteria to humans. We have found that Pmel17 amyloid templates and accelerates the covalent polymerization of reactive small molecules into melanin—a critically important biopolymer that protects against a broad range of cytotoxic insults including UV and oxidative damage. Pmel17 amyloid also appears to play a role in mitigating the toxicity associated with melanin formation by sequestering and minimizing diffusion of highly reactive, toxic melanin precursors out of the melanosome. Intracellular Pmel17 amyloidogenesis is carefully orchestrated by the secretory pathway, utilizing membrane sequestration and proteolytic steps to protect the cell from amyloid and amyloidogenic intermediates that can be toxic. While functional and pathological amyloid share similar structural features, critical differences in packaging and kinetics of assembly enable the usage of Pmel17 amyloid for normal function. The discovery of native Pmel17 amyloid in mammals provides key insight into the molecular basis of both melanin formation and amyloid pathology, and demonstrates that native amyloid (amyloidin) may be an ancient, evolutionarily conserved protein quaternary structure underpinning diverse pathways contributing to normal cell and tissue physiology

Circadian Rhythm and Sleep Disruption: Causes, Metabolic Consequences and Countermeasures.

Circadian (∼ 24 hour) timing systems pervade all kingdoms of life, and temporally optimize behaviour and physiology in humans. Relatively recent changes to our environments, such as the introduction of artificial lighting, can disorganize the circadian system, from the level of the molecular clocks that regulate the timing of cellular activities to the level of synchronization between our daily cycles of behaviour and the solar day. Sleep/wake cycles are intertwined with the circadian system, and global trends indicate that these too are increasingly subject to disruption. A large proportion of the world's population is at increased risk of environmentally-driven circadian rhythm and sleep disruption, and a minority of individuals are also genetically predisposed to circadian misalignment and sleep disorders. The consequences of disruption to the circadian system and sleep are profound and include myriad metabolic ramifications, some of which may be compounded by adverse effects on dietary choices. If not addressed, the deleterious effects of such disruption will continue to cause widespread health problems; therefore, implementation of the numerous behavioural and pharmaceutical interventions that can help restore circadian system alignment and enhance sleep will be important

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.ObjectivesThe primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and MethodsIn a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).ResultsJointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.ConclusionsElucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics

Parallel- and serial-contact electrochemical metallization of monolayer nanopatterns: A versatile synthetic tool en route to bottom-up assembly of electric nanocircuits

Contact electrochemical transfer of silver from a metal-film stamp (parallel process) or a metal-coated scanning probe (serial process) is demonstrated to allow site-selective metallization of monolayer template patterns of any desired shape and size created by constructive nanolithography. The precise nanoscale control of metal delivery to predefined surface sites, achieved as a result of the selective affinity of the monolayer template for electrochemically generated metal ions, provides a versatile synthetic tool en route to the bottom-up assembly of electric nanocircuits. These findings offer direct experimental support to the view that, in electrochemical metal deposition, charge is carried across the electrode–solution interface by ion migration to the electrode rather than by electron transfer to hydrated ions in solution