Alzheimer’s disease (AD), the most prevalent form of dementia, is expected to rise dramatically in incidence due to the global population aging. Traditional diagnostic approaches, such as cerebrospinal fluid analysis and positron emission tomography, are expensive and invasive, limiting their routine clinical use. Recent advances in blood-based biomarkers, including amyloid-beta, phosphorylated tau, and neurofilament light, offer promising non-invasive alternatives for early AD detection and disease monitoring. This review synthesizes current research on these blood-based biomarkers, highlighting their potential to track AD pathology and enhance diagnostic accuracy. Furthermore, this review uniquely integrates recent findings on protein-protein interaction networks and microRNA pathways, exploring novel combinations of proteomic, genomic, and epigenomic biomarkers that provide new insights into AD’s molecular mechanisms. Additionally, we discuss the integration of these biomarkers with advanced neuroimaging techniques, emphasizing their potential to revolutionize AD diagnostics. Although large-scale validation is still needed, these biomarkers represent a critical advancement toward more accessible, cost-effective, and early diagnostic tools for AD.

Alzheimer's disease (AD) is the most prevalent form of dementia. With the global aging population, the incidence of AD and related dementias is projected to rise dramatically, posing significant public health challenges. Traditionally, the diagnosis of AD has relied on the detection of amyloid-beta (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau in the brain, assessed through invasive cerebrospinal fluid (CSF) analysis and costly positron emission tomography scans. However, these methods are not feasible for widespread screening or use in low-resource settings. Recent advances in blood-based biomarkers offer a promising alternative for the early detection and monitoring of AD. These biomarkers provide a minimally invasive, cost-effective means of tracking the pathological progression of AD before the onset of clinical symptoms, potentially enabling earlier and more accurate diagnosis. Blood-based biomarkers, including those related to Aβ, phosphorylated tau, and neurofilament light polypeptide, have demonstrated significant potential in reflecting the underlying neuropathology of AD and correlating with traditional CSF and imaging biomarkers. This review synthesizes the latest research on blood-based biomarkers in AD, highlighting their role in the disease's etiopathogenesis, diagnostic accuracy, and prognostic value. We discuss the emerging evidence on proteinopathies, neuroinflammation, vascular pathology, and bioenergetic profiles, emphasizing the clinical applicability of these biomarkers. Furthermore, we explore the integration of blood-based biomarkers with advanced neuroimaging techniques and their potential to revolutionize the diagnostic landscape of AD, particularly in resource-limited settings. We have integrated protein-protein interaction (PPI) and miRNA network analyses to enhance the analysis. By incorporating these, we can explore the interactions and relationships between different proteomic, genomic, and epigenomic biomarkers, potentially unveiling new insights into the underlying biological mechanisms of AD. The continued development and validation of these biomarkers could lead to more accessible and equitable AD diagnostics, ultimately improving patient outcomes.

Background: Subjective happiness or well-being is an important aspect of positive psychology and is determined by several external factors, based on several of which, the World Happiness Report ranks the countries annually. India’s happiness ranking has consistently declined over the years compared to the neighboring countries. Methods: The present study considered relevant socio-demographic factors and assessed their association, if any, in subjective happiness using multiple linear regression analysis among the eastern Indian Bengali population. A total of 191 participants were recruited for the study and their subjective happiness scores were measured using a well validated Subjective Happiness Scale. Results: The result showed a significant association of 3 factors viz. individual’s ‘choice to stay or work in a group or alone’ (p ≤ 0.0001); ‘frequency of feeling sad in daily life (p ≤ 0.0001); and ‘personal relationship satisfaction’ (p ≤ 0.0001) with subjective happiness scores in both males and females. Eight other variables showed a gender-specific association with happiness (p ≤ 0.05). Conclusion: These three socio-demographic factors might thus be the key determinants in regulating subjective well-being in this section of the world population. This information might thus be helpful in future counselling of individuals suffering from distress or severe depression and keep their better mental health.

The present study investigates the spatial distribution, physicochemical attributes, and ecological implications of co-occurring microplastic (MPs) and heavy metals in mangrove sediments of the Indian Sundarbans. MPs abundance ranged from 33 ± 8 to 131 ± 24 particles kg⁻¹ dry weight, showing clear spatial heterogeneity driven by anthropogenic inputs, tidal energy, and sediment characteristics. Fibre filaments (50%) and fragments (40%) predominated, indicating secondary origins from fishing and packaging materials. Raman spectroscopic analysis identified polyethylene (PE) and polyethylene terephthalate (PET) as the dominant polymers, highlighting their high persistence and buoyancy that favour estuarine retention. Sediment quality indices, including the Pollution Load Index (PLI = 1.0–2.19), Polymer Hazard Index (PHI = 108–309), and Potential Ecological Risk Index (PERI = 133–696), classified sites S4–S6 as high-risk zones under synergistic MPs–metal contamination. Elevated Cd, Cu, and Pb concentrations in these zones confirmed anthropogenic influences from aquaculture, port activities, and domestic effluents. High-throughput 16S rRNA metagenome sequencing revealed that co-contaminant stress substantially reduced bacterial diversity, with Proteobacteria and spore-forming Bacillales dominating the community structure at contaminated sites. Alpha diversity indices (Shannon, Simpson, ACE, and Chao1) demonstrated significant reductions in richness and evenness. Enzymatic assays further indicated inhibition of phosphatase, β-glucosidase, urease, and arylsulfatase activities, reflecting metabolic suppression and nutrient cycling disruption. Collectively, these results highlight that the synergistic toxicity of MPs and heavy metals not only enhances sediment pollution but also drives microbial community restructuring and functional impairment.