The gut microbiota, a dynamic and metabolically active microbial ecosystem, plays a pivotal role in regulating host digestion, immune homeostasis, metabolism, and hormone signaling. Among its specialized functions, the estrobolome (a collection of bacterial genes involved in estrogen metabolism) has emerged as a key regulator of systemic estrogen levels. Through microbial β-glucuronidase activity, estrogens undergo deconjugation and reabsorption, influencing the pathogenesis of hormone-receptor-positive breast cancers. Disruption of the gut microbial balance, termed dysbiosis, can result from dietary changes, antibiotic use, environmental toxins, and psychosocial stress. Dysbiosis alters intestinal permeability, immune responses, and microbial metabolite profiles, contributing to chronic inflammation and endocrine disruption. Mechanistic links between gut microbiota and breast cancer include altered estrogen recirculation, immunomodulation, shifts in microbial metabolites (e.g., SCFAs, bile acids, tryptophan derivatives), and stress-mediated signaling through the microbiota–gut–brain axis. Accumulating preclinical and clinical evidence reveals distinct microbial signatures in breast cancer patients, supporting a causal or contributory role of gut dysbiosis in tumorigenesis. In parallel, biotics (including probiotics, prebiotics, synbiotics, and postbiotics) offer promising avenues for modulating the microbiota. Certain strains of Lactobacillus (L.) and Bifidobacterium (B.) exhibit anti-inflammatory and estrogen-modulating effects, while dietary fibers and microbial metabolites may enhance epithelial integrity and immunocompetence. This review critically examines the interplay between gut microbiota and breast cancer, elucidates the mechanistic pathways involved, and evaluates the current evidence on microbiota-targeted interventions. We also highlight research gaps, safety considerations, and the potential for integrating microbiome modulation into personalized oncologic care. This review uniquely integrates mechanistic pathways with those supported by preclinical and clinical evidence on biotics, highlighting microbiome-based precision strategies for breast cancer prevention and management.

The gut microbiota a dynamic and metabolically active microbial ecosystem plays a pivotal role in regulating host digestion, immune homeostasis, metabolism, and hormone signaling. Among its specialized functions, the estrobolome (a collection of bacterial genes involved in estrogen metabolism) has emerged as a key regulator of systemic estrogen levels. Through microbial β-glucuronidase activity, estrogens undergo deconjugation and reabsorption, influencing the pathogenesis of hormone-receptor-positive breast cancers. Disruption of the gut microbial balance, termed dysbiosis, can result from dietary changes, antibiotic use, environmental toxins, and psychosocial stress. Dysbiosis alters intestinal permeability, immune responses, and microbial metabolite profiles contributing to chronic inflammation and endocrine disruption. Mechanistic links between gut microbiota and breast cancer include altered estrogen recirculation, immunomodulation, shifts in microbial metabolites (e.g., SCFAs, bile acids, tryptophan derivatives), and stress-mediated signaling through the microbiota-gut-brain axis. Accumulating preclinical and clinical evidence reveals distinct microbial signatures in breast cancer patients, supporting a causal or contributory role of gut dysbiosis in tumorigenesis. In parallel, biotics (including probiotics, prebiotics, synbiotics, and postbiotics) offer promising avenues for microbiota modulation. Certain strains of Lactobacillus and Bifidobacterium exhibit anti-inflammatory and estrogen-modulating effects, while dietary fibers and microbial metabolites may enhance epithelial integrity and immunocompetence. This review critically examines the interplay between gut microbiota and breast cancer, elucidates mechanistic pathways, and evaluates current evidence on microbiota-targeted interventions. We also highlight research gaps, safety considerations, and the potential for integrating microbiome modulation into personalized oncologic care.

Understanding how key insect pests have evolved over time and what it implies for the future of agriculture depends on knowing about their past of existence. Advanced genomic techniques are applied in this work to investigate the evolutionary background of important insect pests. It examines their population changes throughout time as well as their evolving traits. This study provide population genetic research and next generation sequencing-based evolutionary relationships between many pest taxa. Case studies of insects such as the cotton bollworm and the Asian tiger mosquito reveal how genetic diversity shapes population structure and resistance of organisms.

Loss of habitat and fragmentation is the main cause of reductions in butterfly populations and also decreases genetic diversity, dispersal, and increases extinction risk. Conservation efforts so far have not formally included understanding population dynamics such as space and time: continuation of these kinds of activities could increase the population level of conservation content to use in reduced habitat patches. This study uses metapopulation theory explicitly focusing on local extinction, colonization, and processes connectivity; in habitat fragmentation conservation we better understand the dynamics and can manage target populations. Habitat quality, patch size, and the distance between patches were modelled to predict persistence measures and identify priority patches for conservation interventions. The metapopulation approach is compared to traditional single population management actions whereby habitat management only or habitat quality alone, for example, with an increase in connectivity at the landscape scale level without reconciling the spatial distribution of the population to the extent possible. Data was used to compare each approach to use in population viability analysis and to modelling dispersal for three butterflies species with different mobility function traits (e.g. Low, moderate, and high mobility). Our results indicate that using a metapopulation based strategy for the management of butterfly populations can yield significant increases in long-term persistence probabilities (up to 35%!), particularly for species with moderate mobility. Priority management actions include, but are not limited to, conservation actions to enhance the value of stepping-stone areas, increased availability of corridors, and conservation of central larger patches. Integrating spatial and temporal population dynamics into management plans produces better butterfly metapopulations and generates a template for similar applications in other fragmented animal taxa.