SEARCH · PubMed Health

Results for “environmental variability”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed1979

Cellular and environmental variables determining numbers of flagella in temperature-shocked Naegleria.

Naegleria gruberi amebae normally transform into biflagellated cells. When subjected to high temperatures during flagellate differentiation, populations develop an average of 4-5 flagella/flagellate. Attempts to maximize this phenomenon by altering cellular and environmental variables revealed that: (a) few Naegleria isolates become multiflagellated: strain NB-1 gives the greatest response to heat shocks; (b) temperature is the most critical variable: highest numbers of flagella are obtained only if cells are temperature-shocked at precisely 38.2 +/- 0.1 C, then returned to 19-22 C to complete differentiation; (c) although pH alone does not affect numbers of flagella, a pH optimum of 5.5-7.0 exists for temperature-shocked cells; and (d) single cells in microdrops become multiflagellated, but the population response is density-dependent. Optimal conditions are described for growing, washing, and transforming amebae to generate reproducibly highest numbers of flagella.

Amoeba↗

PubMed2026

Climate-Driven Niche Tracking and Genomic Resilience Shape Future Distribution of a Widespread Agricultural Weed.

Understanding how agriculturally important species respond to environmental change is critical for maintaining productivity, mitigating agroecosystem threats and sustaining resilience. While crops have traditionally been the focus in agroecosystems, agricultural weeds are integral components that often face even stronger selective pressures, making them powerful models for investigating ecological and evolutionary responses to climatic and human-mediated challenges. Insights from how weeds adapt rapidly under these pressures can inform strategies to improve agricultural outcomes, since both pests and crops evolve under the same multivariate selective pressures. Here, we integrate two centuries of distribution records with whole-genome sequencing from natural populations of the most damaging weed in Europe-Alopecurus myosuroides (blackgrass) - to examine its ecological and evolutionary responses in agroecosystems. Blackgrass largely maintained its historical climatic niche, expanding its range primarily by tracking environments analogous to those it historically occupied. Genome-wide analyses revealed a polygenic basis of environmental responses, with most loci linked to single environmental variables and a subset showing limited environmental pleiotropy, indicating modular adaptation to the complex selective pressures of managed agricultural landscapes. Coupling these genomic-environment relationships with projected climate change and genomic offset analyses indicated that most blackgrass populations will remain well aligned with future conditions. Our findings show that ecological niche tracking and polygenic adaptation allow agricultural weeds like blackgrass to persist under rapid environmental change, offering insights relevant not only for weed management but also for designing resilient cropping systems under future climates.

Plant Weeds↗

PubMed2026

Rapid and exceptionally small-scale adaptation of the alpine plant Cardamine resedifolia to mining-contaminated soils in multi-stress condition.

The mechanisms by which plants tolerate soil contamination have been studied in details in controlled laboratory conditions, but they still remain largely unexplored in natural conditions where mixtures of contaminants are present in soils and their effects might interact with other environmental variables. This is especially true in high-altitude alpine environments, where abiotic stress is naturally heightened, but which so far have received little attention in environmental pollution studies. As we were interested in the tolerance mechanisms at play on very fine spatiotemporal scales for alpine plants growing under multi-stress conditions, we chose Cardamine resedifolia as our biological model. This plant is indeed frequently found in areas contaminated by Trace Metals and Metalloids and Polycyclic Aromatic Hydrocarbons in high elevation. We studied populations from former copper, silver-lead, and coal mines in alpine environments, along with populations growing on nearby reference soils. We measured genetic variability within populations as well as genetic differentiation between them, and tested for local adaptation to soil contamination using reciprocal transplants. Population pairs showing signs of local adaptation were then examined using genome scans to identify genes potentially under selection. We found high levels of genetic differentiation between populations growing on contaminated and reference soils a few dozen meters apart. In most cases local adaptation was detected, especially in former copper mines. Genome scans identified genes involved in metal stress management as potentially being under selection. This study provides evidence for rapid adaptation to human-induced pollution in alpine plants at remarkably small spatial scales. It offers new insights into the short-term ecological and evolutionary consequences of mining activities in alpine ecosystems, particularly in relation to substrate-driven differentiation.

Alpine plants↗

PubMed2026

Phylogenetic Constraints and Environmental Filtering Jointly Drive Adaptive Evolution in Phragmites australis: From Genetic Structure to Trait Decoupling on the Mongolian Plateau.

The Mongolian Plateau, a typical arid and semi-arid zone in Eurasia, is characterized by highly heterogeneous and fragmented wetland habitats. Phragmites australis, a common wetland species in this region, exhibits remarkable adaptability. Unraveling the coordination between phylogenetic history and local environmental filtering is crucial for elucidating its adaptive mechanisms. Integrating landscape genomics and trait-based phylogenetic analyses, we analyzed transcriptome-wide SNPs, multidimensional functional traits, and environmental variables across 90 individuals from 30 natural P. australis populations. This study aims to reveal the genetic and phenotypic variation patterns underlying population genetic structure and trait variation, specifically distinguishing the roles of geographic isolation, environmental filtering, and phylogenetic history. Results reveal a significant drainage-dependent pattern in genetic structure. Populations in hydrologically connected basins show extensive admixture, whereas those in isolated endorheic basins form distinct lineages. While geographic isolation underpins genetic differentiation, environmental filtering independently explains ~33.84% of the genetic variation, driven primarily by moisture heterogeneity (precipitation seasonality and soil moisture). Crucially, we observed differentiated evolutionary trajectories across functional traits. Structural traits (e.g., plant height, leaf thickness) are phylogenetically conserved; in contrast, physiological traits (e.g., water use efficiency) are decoupled from phylogeny, showing patterns consistent with high plasticity regulated by local environments. This evolutionary decoupling strategy enables P. australis to flexibly adapt to heterogeneous habitats while maintaining structural stability. This study uncovers the synergistic mechanisms by which geographic isolation and environmental filtering jointly shape the genetic patterns of this cosmopolitan species at a regional scale, clarifies that its evolutionary responses may depend heavily on the differentiated plasticity of trait types, and provides valuable regional insights into how widespread wetland species adapt to heterogeneous environments under global change.

Mongolia Plateau↗

PubMed2026

Metagenomics Reveals Microbial Community Shifts Associated With Contrasting Anthropogenic Impacts in Freshwater Sources of A Coastal Protected Area in Southeastern Brazil.

This study aimed to characterize freshwater microbial communities, environmental drivers, and anthropogenic impact patterns across three sites on Marambaia Island (southeastern Brazil) using metagenomics. Samples collected from freshwater sources used for human consumption were processed through concentration, nucleic acid extraction, and sequencing on the Illumina NextSeq 2000 platform. A total of 67.2 million reads were assembled into 89,230 bacterial contigs, mostly attributed to Gammaproteobacteria, Alphaproteobacteria, and Betaproteobacteria. Sites under lower anthropogenic influence exhibited higher microbial diversity, whereas impacted sites showed enrichment of opportunistic and fecal-associated genera. A heterogeneous anthropogenic impact profile was observed across sites, corroborated by the proposed Anthropogenic Impact Index (AII). Fourteen antimicrobial resistance genes conferring resistance to beta-lactams, quinolones, sulfonamides, tetracyclines, and macrolides were detected predominantly in sewage-impacted areas, indicating potential diffuse contamination. Redundancy analysis revealed that environmental variables explained 88.1% of microbial community variation, with conductivity, salinity, and turbidity as key drivers. These findings demonstrate the applicability of metagenomics as a powerful tool for assessing microbial diversity, ecological dynamics, and contamination risks in vulnerable freshwater systems.

Brazil↗

PubMed2026

A marine-derived fungal genome of Annulohypoxylon annulatoides reveals AT-rich isochores with putative regulatory functions.

Marine and coastal fungi experience intense environmental variability, yet the genomic features associated with tolerance to such conditions remain unclear. From 56 fungal isolates collected along the Lailai rocky shore in northern Taiwan, we selected the coastal isolate Annulohypoxylon annulatoides RYS0019 for phenotypic and genomic investigation because of its prevalence and distinctive stress-response profile. Compared with 5 bark-derived conspecific strains, RYS0019 showed distinct growth and recovery dynamics under salinity, temperature, and UV-associated stress treatments. We generated a high-quality 41.8 Mb de novo genome assembly with 11,523 predicted proteins and compared it with 15 other Hypoxylaceae genomes. Across Annulohypoxylon genomes, we identified variably sized and dispersed AT-rich isochores that are repeat-enriched and gene-poor. Despite variation in AT content, core gene content and Pfam domain profiles remained broadly conserved. Most AT-rich isochores were embedded within syntenically conserved regions and showed limited positional conservation across species, supporting recurrent, lineage-specific formation or expansion after species divergence. These regions also exhibit several sequence and structural features consistent with scaffold/matrix attachment regions, raising the possibility that they influence higher-order genome organization or context-dependent regulation. Together, our findings identify repeat-rich genome architecture as a dynamic feature of Annulohypoxylon genome evolution and provide a framework for testing how such regions may contribute to fungal environmental flexibility.

Genome, Fungal↗

PubMed2026

Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.

White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.

Animals↗

PubMed2026

Targeted population genomics uncovers demographic history and genetic divergence in north American wild cranberry.

Wild populations of North American cranberry (Vaccinium macrocarpon Aiton) are reservoirs of genetic variation that may contribute to the improvement of breeding-relevant traits. However, the extent to which wild genetic variation is geographically structured and represented in elite germplasm remains unclear. We analysed 179 wild cranberry accessions from the upper Midwest and Eastern North America to estimate nucleotide diversity (π), population structure, and loci associated with genetic differentiation and environmental variables using a genome-informed targeted genotyping panel. Additionally, 14 demographic scenarios were evaluated using site-frequency-spectrum-based inference to identify historical events that could explain current genetic diversity. We observed extremely low nucleotide diversity within the targeted panel (π = 5 × 10-6). Rare allele distributions strongly influenced π and Tajima's D values, suggesting constrained diversity in the genomic regions assayed that is not captured by heterozygosity-based estimates alone. However, we interpreted these results as conservative lower bounds on genome-wide neutral diversity because the targeted panel is enriched for genic and conserved regions. A clear separation between the Midwest and East populations was observed, with inbreeding coefficients ranging from -0.13 to 0.15. Furthermore, site frequency spectrum inference from the targeted panel supported a demographic scenario consistent with a significant population reduction ≈15-14 thousand years ago (kya), followed by a divergence between the two regions ≈12 kya, and an asymmetric gene flow ≈1.3 kya. We detected 254 candidate loci showing regional allele-frequency differentiation. Several of these loci colocalized with candidate genes linked to stress response, development, and metabolic processes. To evaluate the representation of geographically differentiated wild alleles in a breeding context, we analysed Rutgers breeding materials (n = 484) and found that this panel is enriched for common alleles in Eastern wild populations. These findings indicate regionally structured allele-frequency variation in wild cranberry, with potential relevance to environmental response and breeding. This study extends prior wild cranberry population-genetic research by providing targeted-panel estimates of diversity, comparisons of demographic models, and breeding insights on geographically differentiated alleles, while highlighting the importance of conserving wild cranberry germplasm for use in modern breeding programs.

Journal Article↗

PubMed2026

Engineering cold stress resilience in capsicum annuum through functional genomics and precision breeding.

This review synthesizes the molecular mechanisms of cold tolerance in pepper, integrating multi-omics data,genome editing, and precision breeding strategies to accelerate the development of cold-resilient cultivars. Cold stress is a significant environmental factor that affects the growth, productivity, and fruit quality of Capsicum annuum by impairing membrane integrity photosynthesis and cellular redox homeostasis. Although pepper has several endogenous cold-responsive regulators such as CaNAC035 and CabHLH035, along with antioxidant defense systems, its cold tolerance remains limited due to low transcriptional activation of key regulators, functional redundancy among cold-responsive genes, and the polygenicity of cold tolerance. These complexities, combined with low genetic diversity and linkage drag, have hindered the improvement of cold-resistant cultivars through conventional breeding. This review brings together the recent progress in understanding the molecular mechanisms of cold stress perception, signal transduction, transcriptional regulation, metabolic reprogramming, and phytohormone interactions in pepper. Precision Breeding 2.0 is a new innovation that combines the integration of multi-omics-based target identification with next-generation genome-editing techniques, allowing precise and multiplex engineering of complex and interconnected regulatory networks instead of single genes. We cover new approaches such as engineering the DREB/CBF pathway, allele-specific editing and targeted disruption of negative regulators to enhance the pathway(s) involved in cold response. Moreover, we propose a roadmap for integration of transcriptomics, proteomics, metabolomics, high-throughput phenomics, and speed breeding to accelerate the identification, validation, and deployment of superior alleles to boost cold tolerance. This review provides a foundation for developing climate-resilient pepper cultivars by connecting functional genomics with precision genome engineering approaches to maintain productivity under variable environmental conditions.

Capsicum↗

PubMed2026

ALPHA-1 antitrypsin genotype, sex, and lung cancer: Clinical and molecular characterisation.

INTRODUCTION AND OBJECTIVES: Alpha-1 antitrypsin deficiency is associated with lung and liver disease, but its role in lung carcinogenesis remains unclear. This study aimed to compare the clinical, functional, and molecular characteristics of lung cancer according to alpha-1 antitrypsin (AAT) genotype and, additionally, to explore differences by sex and the possible influence of environmental exposures. PATIENTS AND METHODS: We conducted a cross-sectional, single-centre study including 407 patients with incident lung cancer diagnosed between 2020 and 2023. Clinical, functional, radiological, molecular, and environmental variables were collected. Comparisons were performed between carriers and non-carriers of altered AAT alleles and between women and men. RESULTS: Of the 394 patients with available genotyping, 24.4% carried at least one altered allele. No significant differences were observed by genotype in smoking status, radon exposure, comorbidities, lung function, or histological subtype. Carriers showed significantly lower serum AAT levels and a higher frequency of values < 116 mg/dL (p < 0.001). PD-L1 expression ≥ 50% was more common in carriers (28.1% vs. 19.4%; p = 0.036). In the multivariable analysis, the altered AAT genotype remained independently associated with a higher probability of PD-L1 expression ≥ 50% (aOR = 2.04; 95% CI: 1.09-3.80; p = 0.026). Women had lower cumulative tobacco exposure, lower prevalence of emphysema and COPD, greater biomass exposure, higher frequency of adenocarcinoma, and more EGFR mutations (p < 0.001). CONCLUSIONS: Patients carrying altered AAT alleles did not exhibit a distinctly different clinical profile, although they showed higher PD-L1 expression (≥50%). Furthermore, significant differences were observed between women and men in terms of exposure, histology and molecular alterations.

Humans↗

PubMed2025

Immune Aging in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a life-long autoimmune disease caused by the confluence of genetic and environmental variables that lead to loss of self-tolerance and persistent joint inflammation. RA occurs at the highest incidence in individuals >65 years old, implicating the aging process in disease susceptibility. Transformative approaches in molecular immunology and in functional genomics have paved the way for pathway paradigms underlying the replacement of immune homeostasis with autodestructive immunity in affected patients, including the process of immune aging. Patients with RA have a signature of premature immune aging, best understood for CD4+ T cells, which function as pathogenic effectors in this HLA class II-associated disease. Premature immune aging is present in healthy HLA-DRB1*04+ individuals, placing accelerated immune aging before joint inflammation. Aging-related molecular abnormalities directly implicated in turning RA CD4+ T cells into proinflammatory effector cells are linked to malfunction of subcellular organelles, such as mitochondria, lysosomes, lipid droplets, and the endoplasmic reticulum. Resulting changes in T cell behavior include cellular hypermobility, tissue invasiveness, unopposed mammalian target of rapamycin complex (mTORC)1 activation, excessive release of tumor necrosis factor, lysosomal failure, clonal expansion, and immunogenic cell death. Aged and metabolically reprogrammed T cells in patients with RA are accompanied by age-associated B cells, which specialize in autoantibody production. Clonal hematopoiesis drives myeloid cell aging by producing aged monocytes and hypermetabolic macrophages, which sustain the process of inflammaging. Here, we synthesize insights into the relationship of RA risk and immune aging and discuss mechanisms through which immune aging can cause autoimmunity.

Humans↗

PubMed2026

Panmixia in a Widespread Butterfly: High Dispersal and Ecological Generalism Buffer Against Landscape Fragmentation.

Habitat fragmentation is widely expected to reduce population connectivity and increase genetic differentiation, although the strength of these effects depends on species-specific traits such as dispersal ability. Here, we investigated the population genetic structure of the cosmopolitan butterfly, Pieris rapae L. (Lepidoptera: Pieridae), across western Germany using genome-wide single-nucleotide polymorphism (SNP) data. To analyze the effects of landscape structure on genetic connectivity, we applied a paired study design comprising four landscape pairs, each consisting of a highly intensified, modern agricultural landscape and a more heterogeneous, traditional landscape. Our results revealed no evidence of genetic differentiation. Pairwise FST values were close to zero; we detected no isolation by distance, and clustering analyses supported a single genetic population. No meaningful associations between genetic variation and environmental variables were detected, with landscape effects explaining less than 0.4% of genomic variation. Consequently, we found no evidence for stronger genetic structuring in modern compared to more connected traditional landscapes. Our results suggest that extensive habitat fragmentation does not necessarily translate into reduced genetic connectivity in highly mobile, generalist species. In P. rapae , high dispersal ability and ecological generalism appear to buffer against the genetic consequences of landscape modification, resulting in panmictic population structure even across strongly contrasting agricultural landscapes.

Pieris rapae↗

PubMed2026

Finlay-Wilkinson random regression for yield and yield stability prediction in cereals.

Year-to-year climate variability poses a challenge for agriculture by increasing crop yield variability; therefore, there is a need to identify genotypes that can withstand these fluctuations. With the right selection criteria, genotypes with yield stability across variable environmental conditions can be selected. Methods such as Finlay-Wilkinson random regression (FWRR) may allow us to use sparse datasets-common in plant breeding pipelines-and incorporate genomic data to leverage phenotypic information from related genotypes to predict yield stability. Our objective was to examine how the number of environments and the variance among those environments affect stability predictions. We also integrate FWRR as a genomic prediction tool for characterizing yield stability, comparing it to the traditional genomic prediction models as a reference. We used three datasets: one highly unbalanced dataset for oats (Avena sativa L.) and two completely balanced datasets with different numbers of environments for barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.). We fit standard Finlay-Wilkinson (FW) and FWRR models to estimate grain yield and stability under various scenarios. We found that the estimated stability values obtained were similar using balanced datasets for FW or FWRR. FWRR also achieved moderate predictive ability for stability using unbalanced datasets under 10-fold cross-validation (CV1) with new genotypes. In terms of environmental representation, selecting the right set of environments for inclusion in the model was more important than adding more environments. Our results suggest the possibility of using FWRR to select stable genotypes earlier in line development, as well as to design resource-efficient stability-testing schemes.

Hordeum↗

PubMed2026

Proteomic profiling of bone for the estimation of post-mortem interval and post-mortem submersion interval: a systematic review.

Accurate estimation of the Post-Mortem Interval (PMI) and Post-Mortem Submersion Interval (PMSI) remains a persistent challenge in forensic science, especially when traditional morphological and entomological methods fail due to advanced decomposition or in aquatic environments. Proteomic profiling of bone tissues has recently emerged as a promising approach, leveraging the predictable degradation patterns of bone proteins to estimate time since death more reliably. This systematic review, conducted in accordance with PRISMA guidelines, analyzed 24 peer-reviewed studies focusing on the application of proteomic techniques to bone tissue for PMI and PMSI estimation. The included studies were evaluated based on sample type, analytical techniques used, identified biomarkers, environmental conditions assessed, and the overall reliability and reproducibility of the findings. The review found that specific bone proteins, particularly collagen, osteocalcin, fetuin-A, etc. exhibited consistent degradation patterns that correlated strongly with elapsed post-mortem time. Cortical bone was identified as a more stable and informative matrix compared to trabecular bone. Mass spectrometry, especially LC-MS/MS, emerged as the predominant analytical technique due to its high sensitivity and accuracy in detecting low-abundance proteins over extended PMIs and PMSIs. However, protein degradation rates were significantly influenced by environmental variables such as temperature, humidity, soil pH, and microbial activity. This review also emphasizes the transformative role of bone proteomics in advancing forensic science while identifying key gaps that must be addressed to achieve global standardization and practical implementation in diverse forensic contexts. The integration of proteomics with other emerging technologies, such as machine learning algorithms and computational modeling, may further enhance the precision of PMI and PMSI estimation in future applications.

Postmortem Changes↗

PubMed2026

Development and Characterization of Microsatellite Markers for the Euryhaline Polychaete Laeonereis acuta (Annelida: Nereididae) in the Southwestern Brazilian Coast.

Laeonereis acuta is a polychaete species typically found at high abundance in estuarine and coastal lagoon environments. Due to its association with polluted habitats, it is commonly used in ecotoxicological studies. Moreover, its occurrence in spatially discontinuous environments with high environmental variability makes it a suitable model for evolutionary studies of local adaptation, genetic landscape, and early stages of speciation. This study aimed to develop primers and characterize microsatellite markers for L. acuta sampled from three coastal lagoons in southwestern Brazil. A total of 10 loci were characterized based on the genotyping of 40 individuals. The number of alleles per locus ranged from 2 to 19. Evidence of null alleles was detected at five loci, although their frequency decreased when coastal lagoons were analyzed separately. When considering all individuals as a single population, five loci showed positive and significant FIS values, and seven loci deviated from Hardy-Weinberg equilibrium. Maricá and Guarapina exhibited heterozygote excess at several loci, whereas Jaconé showed evidence of population genetic isolation. The 10 microsatellite loci were polymorphic and suitable for population genetic analysis in L. acuta, although these patterns may not necessarily be representative of other geographic regions. These markers may contribute to ecotoxicological studies by clarifying whether physiological responses to pollutants are associated with genetic differentiation among populations. Furthermore, they provide valuable tools for investigating genetic structure and connectivity in discontinuous environments.

Animals↗

PubMed1979

Fluorescein mercuric acetate as a probe of the dynamic structure of double-helical DNA.

Fluorescein mercuric acetate causes the unwinding of DNA and binds to the separated bases. The kinetics of this unwinding process were studied using both untreated DNA and sonicated DNA at various pH values (6.8--9.3) and Na+ concentrations (10--250 mM). The unwinding process is explained by assuming a nucleation in the middle of DNA (as a function of time) as well as at the helix ends (immediately after addition of this reagent) and the subsequent growth of the nuclei. The frequency of the nucleation in the middle of DNA appears to be markedly affected by pH and Na+ concentration. In contrast, the reaction rate of this reagent with heat-denatured DNA was almost insensitive to these environmental variables. The growth rate of the unwinding nuclei in double-stranded DNA also appears insensitive. The most important implication of this study is that in the low pH range (6.8--7.5) the reactivity of thermally-induced locally open regions in the middle of double-helical DNA toward this reagent appears much higher than that of heat-denatured DNA. Since this reagent is negatively charged, these findings are discussed in view of its electrostatic interaction with the locally open regions.

Chemical Phenomena↗

PubMed2026

Forensic taphonomy in fluvial water: A systematic review.

Human remains are frequently recovered from fluvial (lotic) water environments. Rivers, streams, canals and other flowing water bodies pose distinct challenges in forensic practice, particularly due to their current. Compared to other aquatic contexts, fluviatile taphonomy is underrepresented in the forensic literature and the last comprehensive summary was written over a decade ago. Therefore, a systematic review was performed to collect and summarise the current knowledge in forensics about fluvial taphonomy, including decomposition of remains, transport characteristics, search, postmortem submersion interval (PMSI) estimation, taphonomic alterations, and differences to other water bodies. 92 reports met the inclusion criteria for this review, most of them showed a moderate risk of bias. Their main findings were summarised and two major challenges identified. First, predictions about fluvial transport of human bodies pose a tremendous issue in forensic practice, leading to later detection and lower recovery rate of remains, complicating various subsequent analyses. Second, PMSI estimations are difficult particularly due to variable environmental conditions in fluviatile systems. Recommendations for future research in the area of fluvial forensic taphonomy include that case-related data such as the detailed decomposition state and river characteristics need to be made available. More standardised research protocols are required for a facilitated comparison between studies, environments and regions. This review provides forensic practitioners with a comprehensive, updated resource for the investigation of fluvial remains. It also guides future research towards a more efficient practice to build the basis for a broader, more robust and comprehensive synthesis, subsequently supporting analyses in forensic casework.

Humans↗

PubMed2026

Functional convergence of rTCA-related carbon-fixation potential and biochemical residue accumulation in seagrass sediments.

Seagrass meadows are globally significant blue carbon ecosystems, yet the microbial and biochemical mechanisms driving sediment organic carbon (SOC) accumulation remain poorly understood. To address this, we employed an integrated approach combining metagenomic sequencing, biochemical assays, and structural equation modeling to investigate carbon cycling in the seagrass and adjacent unvegetated sediments of Swan Lake, China. A total of 115,179 carbon fixation genes and 119,615 decomposition genes were identified, revealing distinct microbial community structures among the habitats. Seagrass sediments harbored more diverse carbon-fixing (CFMs) and decomposing microorganisms (CDMs), with 83 medium-to high-quality metagenome-assembled genomes (MAGs) recovered. While neutral community model analysis indicated that stochastic processes predominantly governed community assembly, functional analyses highlighted specific drivers of sequestration. The reductive tricarboxylic acid (rTCA) cycle emerged as the dominant carbon fixation pathway, with key genes (e.g., aclA, korA) showing strong positive correlations with SOC. Conversely, decomposition pathways for starch and lignin were negatively associated with SOC. Furthermore, seagrass sediments exhibited elevated concentrations of total amino sugars (TAS) and lignin phenols (TLP), which linked significantly to carbon fixation rather than decomposition. PLS-SEM revealed statistically significant associations among seagrass traits, environmental variables, microbial carbon-fixation potential, biochemical residue pools, and SOC, supporting a mechanistic pathway in which enhanced microbial functional potential drives the accumulation of recalcitrant biochemical residues, thereby facilitating long-term carbon retention in sediments. These findings emphasize the pivotal role of microbial anabolism and the accumulation of biosynthetic residues in sediment carbon storage, suggesting a functional convergence in seagrass-driven carbon sinks.

Metagenomics↗