Despite growing interest in mine tailings valorization, most previous studies on thermally induced mineral transformations have focused on monomineralic systems, leaving the behavior complex, multimineral mine residues comparatively unexplored. Thermal treatment of fine-grained mining wastes is proposed as a method to enhance their reuse within the mining industry itself or in other related industries like civil and chemical engineering. Four fine-grained mining wastes (three mine tailings and one sludge from an acid mine water treatment plant) were chemically and mineralogically characterized across a temperature range of 40 °C to 950 °C using a combined TGA, XRD and SEM-EDS approach. The three mine tailings correspond to deposits classified as IOCG-type (iron‑copper‑gold oxides), volcanogenic massive sulfides (MSS), and carbonatites. Depending on their initial mineralogy, one or more of the following mineral transformations were observed: 1) conversion of gypsum to bassanite and anhydrite within the ranges of 100–200 °C and 850–950 °C, respectively; 2) a two-steps transformation of chlorite (i.e. chamosite) into a diffraction X-ray-amorphous phase, tentatively termed “meta-chlorite” by analogy with meta-kaolinite, between 650 °C and 800 °C and a concomitant neoformation of hematite and a Si-rich matrix; 3) transformation of carbonates (i.e., calcite and dolomite) into oxides (i.e., lime and periclase) within the 800–950 °C range. These mineral transformations confer greater reactivity to the residues, showing strong potential as low-cost precursors for alkali-activated cementation processes, thereby supporting the valorization of mine residues within a circular economy framework, with direct applications in underground mine galleries backfilling, construction materials (plasters and 3D-printing pastes), and other industrial uses as alkaline reagents.
Rising greenhouse gas (GHG) emissions have intensified the need for effective carbon mitigation strategies, making carbon capture, utilization and storage (CCUS) a key technology for achieving long-term decarbonization. Future deployment of CCUS projects is expected to be supported by the Paris Agreement's Article 6 mechanisms, together with India's emerging domestic carbon market and carbon-pricing frameworks. Owing to its extensive sedimentary basins, India possesses significant geological potential for long-term CO2 storage. This review provides a comprehensive assessment of the geological CO2 storage potential of major subsurface formations in India and evaluates their suitability for long-term geological CO2 storage and future CCUS development. A systematic review of the published literature from 2000 to 2025 was conducted using peer-reviewed journal articles, conference proceedings, books, government reports, and publications from internationally recognized organizations. The review critically evaluates geological storage options, storage-capacity estimation approaches, reservoir characteristics, monitoring strategies, uncertainty assessment, and recent policy developments. In addition, a bibliometric analysis based on the Scopus database was performed to identify publication trends and emerging research directions. The bibliometric analysis identified 1138 publications, demonstrating a substantial increase in geological CO2 storage research, particularly after 2020. India comprises approximately 3.4 million km2 of sedimentary basins with an estimated national geological CO2 storage potential of 400–500 Gt CO2. Deep saline aquifers constitute the largest storage resource (300–400 Gt CO2), followed by basalt formations (200–400 Gt CO2), while depleted oil and gas reservoirs (5–10 Gt CO2) and unmineable coal seams (∼5 Gt CO2) provide additional storage opportunities. The review also proposes an Integrated Geological Storage Potential Framework (IGSPF) for comparative screening and prioritization of Indian sedimentary basins based on storage capacity, reservoir quality, injectivity, caprock integrity, geological maturity, and data availability. Deep saline aquifers are identified as the most promising option for long-term geological CO2 storage in India, while basalt formations offer additional potential through mineral carbonation. Overall, the findings highlight the need for standardized storage-capacity assessment, detailed reservoir characterization, robust monitoring and risk management, and supportive policy frameworks. As the storage-capacity estimates presented in this review are derived from published literature, future CCUS deployment will require site-specific characterization, reservoir modelling, and pilot-scale validation before field-scale implementation.
Abstract Alzheimer's disease (AD) is accompanied by persistent disturbances in brain energy metabolism, and microglial glucose metabolic reprogramming constitutes an important link among pathological protein deposition, neuroinflammation, and impaired clearance. This review examines these metabolic changes across disease stages, brain regions, and plaque‐associated microenvironments and proposes a dynamic state‐composition model. In this model, microglia in different metabolic states coexist, and their relative proportions and spatial distribution change as AD progresses. In early disease or during active phagocytosis, some microglia show enhanced glycolytic and oxidative phosphorylation (OXPHOS) programs. Under persistent pathological stress, increased glucose uptake may not translate into effective energy production and can coexist with inflammation and impaired lipid metabolism. In late disease, microglia with reduced metabolic capacity and impaired phagocytosis become more prevalent. However, higher expression of OXPHOS‐related genes in some microglial states associated with tau pathology does not necessarily indicate improved mitochondrial respiration. These population‐level patterns do not imply that individual microglia follow a fixed sequence of metabolic changes. Longitudinal cell tracking and microglia‐specific metabolic flux measurements are needed to test this model and inform interventions tailored to disease stage and microglial state.
Abstract INTRODUCTION Data on how sleep architecture relates to progression of plasma Alzheimer's disease biomarkers remains limited. METHODS Sixty‐four cognitively unimpaired older adults (ages 55–90) underwent plasma collection twice 2.6 years apart and polysomnography proximate to the first plasma collection. Plasma amyloid beta (Aβ) 42 and 40 were measured via mass spectrometry. RESULTS Frontal slow‐wave activity (SWA) was inversely associated with plasma Aβ42/40 at cross‐section in bivariate analysis and in a covariate‐adjusted model. In comparison, low rapid eye movement (REM) sleep percentage was associated with a large longitudinal decline in annualized blood‐based Aβ42/40. In exploratory analyses, the association between low REM sleep percentage and faster decline in Aβ42/40 ratio was stronger in the amyloid‐positive group. DISCUSSION In cognitively unimpaired older adults, non‐REM SWA correlates with cross‐sectional amyloid load, whereas REM sleep may predict accelerated amyloid accumulation in preclinical stage, suggesting both may serve as early biomarkers and modifiable interventional targets.
Abstract INTRODUCTION The concentration of endogenous tau microtubule‐binding region containing residue‐243 in plasma (eMTBR‐tau243) has been proposed to be a sensitive biomarker of tangle pathology in Alzheimer's disease (AD). We assessed eMTBR‐tau243 and phosphorylated tau217 (p‐tau217) with tau and Aβ‐positron emission tomography (PET) across different AD clinical phenotypes. METHODS Plasma eMTBR‐tau243, p‐tau217, and the ratio of non‐phosphorylated to phosphorylated tau217 (%p‐tau217) were measured in 20 Aβ‐PET positive AD patients representing four clinical phenotypes and 10 cognitively unimpaired controls. Plasma levels were correlated with PET, demographic and cognitive variables. RESULTS Plasma eMTBR‐tau243, p‐tau217, and %p‐tau217 levels were greater in AD than controls, with greatest levels observed in motor‐predominant AD. Plasma biomarker levels correlated with cortical flortaucipir‐PET uptake; eMTBR‐tau243 correlations were strongest. In AD, eMTBR‐tau243 levels were undetectable in patients with mild/focal flortaucipir‐PET uptake (45%). Only eMTBR‐tau243 correlated with cognition. DISCUSSION Plasma eMTBR‐tau243 may be an excellent biomarker for tau deposition and cognition in AD across different phenotypes.
