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Global Patterns of Net Ecosystem Exchange in peatlands: A Systematic Review and Meta-analysis of Drivers Across Land Use and Environmental Gradients.

Peatlands play an essential role in the global carbon cycle, storing approximately one-third of the world's soil carbon despite covering less than 3% of the land surface. Peatland degradation from anthropogenic activities and climate change can convert peatlands from net carbon sinks to sources by altering carbon cycling. Net Ecosystem Exchange (NEE), the balance between CO2 uptake and emission, is a critical indicator for assessing peatland condition and restoration efforts. We conducted a systematic quantitative literature review to investigate global patterns of NEE in peatlands and identify key environmental and anthropogenic drivers of CO2 flux variability. Annual NEE values from 120 globally distributed sites reported in peer-reviewed literature were analyzed in relation to climatic zone, land use, vegetation type, peatland condition, and water table depth. Our synthesis revealed significant geographic gaps, with peatland NEE studies substantially underrepresented in the Tropics, Africa, and Oceania. Agricultural peatlands emitted significantly more CO2 than sites under natural land uses or peat extraction, while degraded peatlands were significantly greater net CO2 sources than intact and restored systems. Restored peatlands remained net CO2 sources on average, emphasizing the importance of long-term monitoring and adaptive management following restoration interventions. Water table depth significantly affected NEE variability, with CO2 emissions increasing approximately 7.2 gCO2-C m-2yr-1 for every centimeter of water table drawdown. A substantial variability in measurement methods, data processing software, and protocols highlighted the critical need for methodological standardization. Our findings provide evidence-based targets for peatland conservation and restoration monitoring as nature-based climate solutions.

Ecosystem

Enrichment of Lysobacter in a long-term organically managed agricultural field with low soilborne disease incidence.

Disease-suppressive soils, in which soilborne pathogens are naturally suppressed, offer a promising model for sustainable crop protection, particularly in organic farming systems where chemical disease control options are limited. Although disease suppression in these soils is considered to rely on biological control, the underlying mechanisms remain poorly understood. In this study, we investigated soil from a long-term organically managed field in Shiga Prefecture, Japan, where soilborne disease incidence has remained consistently low, to identify bacterial community features potentially associated with this field. The 16S rRNA gene amplicon sequencing indicated that this soil harbored a bacterial community distinct from those of nearby agricultural soils. Following the application of organic compounds, the genus Lysobacter, a taxon with known antagonistic activity against plant pathogens, was markedly enriched in response to proteinaceous organic inputs. This enrichment was consistent across sampling times and specific to certain proteinaceous organic inputs, whereas minimal effects were observed on chitin, N-acetyl-d-glucosamine, or cysteine. Broader soil surveys indicated that Lysobacter enrichment was not strictly associated with whether soils had been managed under organic or conventional farming practices. Stepwise multiple regression analysis identified 10 co-occurring bacterial genera that were strongly associated with Lysobacter abundance. These findings highlight condition-dependent Lysobacter enrichment as a characteristic microbial response to proteinaceous organic amendments in this low-disease-incidence field and provide microbial insights that may inform microbiome-based strategies for sustainable soil management.

Lysobacter

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids

Evaluation of the effects of domestic tomato processing on biopesticide residue using natural deep eutectic solvents (NADES) extractions.

The present study evaluated the fate of fourteen botanical biopesticides in processed tomato samples. Various processing methods were employed, including washing, dehydration, and the preparation of juice and sauce. The extraction was performed using more sustainable techniques, aimed at minimizing the environmental impact of conventional organic solvents by substituting them with natural deep eutectic solvents (NADES). Solid-liquid extraction (SLE) and dispersive liquid-liquid microextraction with solidification of floating organic drop (DLLME-SFOD) were utilized for solid and liquid tomato samples, respectively. The NADES used was choline chloride:2,3-butanediol (ChClBt) at a 1:4 molar ratio for both techniques, resulting in recovery values ranging from 69.2 to 106.2% for SLE, and extraction efficiencies reaching up to 46.2% for DLLME-SFOD. The impact of these processes was evaluated employing the processing factor (PF), yielding PF values of less than 1 in all cases. Compounds as pyrethrins, azadirachtin, and rotenone persisted after processing, posing a potential consumer risk.

Solanum lycopersicum

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries

Development and validation of a liquid chromatography-tandem mass spectrometry method for the quantification of twenty-five steroids in equine serum.

Steroids are potential biomarkers for monitoring equine pregnancy. However, immunoassays currently used for their quantification suffer from cross-reactivity and limited specificity, thus requiring more accurate methods. This study reports the development and validation of a robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of 25 steroids covering the main biosynthetic pathways of progestogens, corticosteroids, androgens, and estrogens. Steroids were extracted by protein precipitation followed by evaporation, derivatization, and reconstitution before LC-MS/MS analysis. A surrogate matrix was used for calibration and validation to avoid endogenous interference. Validation was performed according to and partly adapted from Clinical and Laboratory Standards Institute guidelines (CLSI), including linearity, trueness, precision, limits of detection and quantification, measurement uncertainty, recovery, matrix effects, carryover, selectivity, and stability. Calibration curves were fitted using the best-performing weighted linear or quadratic regression model, yielding excellent linearity (R2&#xa0;>&#xa0;0.990), trueness between -9.0% and 2.3%, and intra- and inter-day precision <6.3%. Lower limits of quantification ranged from 2.07 to 2250&#xa0;pg/mL depending on physiological analytes concentration. Extraction recovery averaged 24.3-114.9%, matrix effects were acceptable, and accuracy ranged from 94.4% to 98.9%. No carryover or interferences were detected. Measurement uncertainty remained <15%. This study presents the first LC-MS/MS method partially validated per CLSI criteria for the quantification of 24 steroids in equine serum. The method offers a sensitive and specific alternative to immunoassays and provides a robust tool for equine steroid profiling with potential applications in pregnancy monitoring, placentitis diagnosis, and fetal sex determination.

Animals

In vitro EVALUATION OF Beauveria bassiana ISOLATES AGAINST GASTROINTESTINAL NEMATODES FROM GOATS.

Biological control has emerged as a promising alternative for the control of gastrointestinal nematodes in small ruminants. However, additional information is still needed on the nematicidal portencial of Beauveria bassiana and on the early interaction between fungal conidia and infective larvae. In this study, six B. bassiana isolates (LCMS19-LCMS24) were evaluated in vitro using a coproculture assay with fecal samples from naturally infected goats. Larval recovery was compared with that of an untreated control to estimate the percentage reduction in third-stage larvae (L3). The most effective isolate was subsequently examined by scanning electron microscopy (SEM) to characterize its interaction with L3. All isolates reduced L3 recovery compared with the control, although their efficacy differed. LCMS21 showed the greatest reduction in L3 recovery and differed significantly from the other treatments. SEM revealed extensive adhesion of LCMS21 conidia to the L3 cuticle, in the anterior and median regions. However, no clear evidence of conidial germination, germ tube formation, cuticle penetration, or hyphal development was observed after 48 or 72 h. These results indicate that B. bassiana isolates differ in their in vitro activity against gastrointestinal nematodes and identify LCMS21 as the most promising isolate among those tested. The ultrastructural observations support an early fungus-larva interaction, but they do not allow the nematicidal effect to be attributed to adhesion. Further studies are needed to clarify the mechanisms involved and to evaluate the potencial application of this isolate in integrated parasite control programs.

Beauveria bassiana

Continuous Intraperitoneal Insulin Infusion for People With Type 1 Diabetes: A Literature Review and International Position Statement.

Achieving glucose targets without hypoglycaemia is the treatment goal in type 1 diabetes. Structured education, intensified insulin injection regimens, continuous glucose monitoring, automated insulin delivery, and ongoing support from a multidisciplinary team all support people with type 1 diabetes to achieve this goal. Despite these advances, significant barriers to achieving optimal management remain. Continuous intraperitoneal insulin infusion has comparable or better glucose outcomes to continuous subcutaneous insulin infusion and may reduce the frequency of hypoglycaemia, including severe episodes. Intraperitoneal insulin may be considered as a treatment modality for children and adults with type 1 diabetes using optimised intensive insulin therapy for whom subcutaneous insulin has failed due to lipoatrophy, -dystrophy or -hypertrophy, local allergy, subcutaneous insulin resistance or co-existing skin conditions. Failure of subcutaneous insulin may result in recurrent or unexplained severe hypoglycaemia or hyperglycaemia. Intraperitoneal insulin may also be considered as a treatment modality for people with type 1 diabetes with severe needle-phobia, and for those being considered for islet cell or pancreatic transplantation, or where transplantation is not available. This paper summarises current intraperitoneal insulin delivery technology, its potential risks and benefits, and an expert position statement. It is intended for use by diabetes specialist healthcare professionals, and as a reference for other healthcare professionals, commissioners, payors, people with diabetes, their carers, and advocates.

Humans

Acute mild cold exposure with shivering reduces 24 h glucose levels in individuals with type 2 diabetes but not prediabetes.

AIMS/HYPOTHESIS: Repeated cold exposure with shivering has been proposed as a potential strategy to enhance glucose metabolism by increasing energy expenditure and substrate utilisation. However, acute effects/benefits of cold-induced shivering on glucose homeostasis in metabolically compromised individuals are unknown. Here, we aimed to determine whether cold exposure at two different intensities improves 24 h glucose homeostasis in individuals with prediabetes and type 2 diabetes. METHODS: In a randomised crossover trial conducted in the South Limburg/Maastricht region of the Netherlands, men and postmenopausal women with prediabetes (n=12) and stable type 2 diabetes (n=12), aged 40-75 years, body mass index &#x2265;27 and &#x2264;35 kg/m2, non-smoking and sedentary, underwent two whole-body cold exposure sessions using a water-perfused suit. Session order was randomised using an online randomisation tool (randomizer.org); participants were masked to the cold exposure intensity received, but investigators were not. Sessions were designed to elicit ~1.5-fold (mild, 15&#xb0;C) and ~2.5-fold (moderate, 4&#xb0;C) increases in resting metabolic rate (RMR). Continuous glucose monitoring assessed interstitial glucose concentrations over 24 h periods before and after each intervention, with controlled diet and activity. Shivering was confirmed via indirect calorimetry and electromyography. RESULTS: In both study groups and periods, RMR increased significantly vs baseline (p<0.001 for all). In prediabetes, the increase in the final 1 h of cold was 1.53&#xa0;&#xd7;&#xa0;RMR in mild and 1.94&#xa0;&#xd7;&#xa0;RMR in moderate cold. In type 2 diabetes, the increase was 1.57&#xa0;&#xd7;&#xa0;RMR and 2.09&#xa0;&#xd7;&#xa0;RMR in the final 1 h of mild and moderate cold, respectively. In prediabetes, neither mild nor moderate cold exposure altered mean 24 h glucose levels. In contrast, after mild cold exposure the type 2 diabetes group exhibited a significant reduction in mean 24 h glucose levels (-0.6&#xa0;&#xb1;&#xa0;0.5 mmol/l, p=0.003) and fasting glucose (-0.6&#xa0;&#xb1;&#xa0;0.8 mmol/l, p=0.019), as well as an increase in time in normal range (+8.8&#xa0;&#xb1;&#xa0;10.3%, p=0.013) and reduced time in hyperglycaemia (-10.9&#xa0;&#xb1;&#xa0;12.9%, p=0.014). Moderate cold did not significantly affect any of the glucose outcomes in type 2 diabetes. Baseline fasting glucose, age and ALT levels were predictors of the glucose-lowering response, suggesting greater benefits in individuals who have higher baseline glucose levels, are younger and/or have more optimal liver health, i.e. lower ALT. CONCLUSIONS/INTERPRETATION: Acute mild cold exposure with shivering reduced 24 h glucose levels in individuals with type 2 diabetes. No changes were observed in prediabetes. The observed effects appear to depend on baseline metabolic status rather than acute substrate utilisation during cold exposure. These findings support the potential of cold exposure as an adjunct non-pharmacological therapy for type 2 diabetes, although further mechanistic studies and validation in larger cohorts are warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT05576025 FUNDING: Dutch Organisation for Knowledge and Innovation in Health, Healthcare and Well-being (ZonMw): 09120012010062.

Humans

Intraskeletal Variation in Cortical Bone Quantity in a Medieval Italian Sample: A Multivariate Exploratory Approach.

Bioarcheologists interpret skeletal health by examining variability within and between individuals. Studies of bone loss have generated contradictory and conflicting results regarding the onset and severity of age-related bone loss on a global and temporal scale, perhaps due to mismatched methodologies. Intraskeletal comparisons of bone tissue prove challenging precisely because of heterogeneous baselines in quantity and remodeling of cortical bone throughout the skeleton, as well as evolutionary histories and environmental impacts on growth and development. Here we analyze cortical bone indicators from the rib, metacarpal, and femoral cortical bone in a subset of individuals (n&#x2009;=&#x2009;72) regions from the medieval Italian archaeological site of Pieve di Pava. To facilitate intraskeletal comparisons across elements with different biological baselines, we standardize cortical bone parameters using z-scores. Variation in relative intraskeletal cortical bone was assessed using accessible multivariate methods (principal component analysis and hierarchical cluster analysis). Results suggest an association between femoral and metacarpal cortical bone values, with stochastic trends in metacarpal and femoral relative bone quantity in relation to the rib bone quantity at the sample level. Our study demonstrates that while intraskeletal analyses are challenging, they are made more robust by synthesizing multivariate methods alongside exploratory data analysis (EDA) methods to tack between sample-level and individual-level scales and variability. Ultimately, we advocate for leveraging multivariate techniques not as a final step, but rather as a means of generating new hypotheses and challenging tendencies to a priori establish typological groups in the research process.

Skeleton

Association Between 24-Hour Blood Pressure and Rates of Retinal Nerve Fiber Layer Progression in Glaucoma: The Vascular Imaging in Glaucoma Study.

PURPOSE: Low systemic blood pressure (BP) has been implicated as a risk factor for glaucoma progression. The purpose of this study was to investigate the association between 24-hour BP and rates of retinal nerve fiber layer (RNFL) loss in eyes with primary open-angle glaucoma. DESIGN: Prospective cohort study. PARTICIPANTS: Seventy-nine eyes from 42 subjects with glaucoma (mean age, 68.5 &#xb1; 7.6 years) enrolled in the Vascular Imaging in Glaucoma Study at the Bascom Palmer Eye Institute. METHODS: Participants underwent 24-hour ambulatory BP monitoring at baseline. Follow-up evaluations were conducted at 4-month intervals and included ophthalmic examination, BP measurement, and peripapillary RNFL thickness measurement with spectral-domain optical coherence tomography. The association between BP and RNFL loss over time was assessed using linear mixed-effects models adjusted for age, sex, race, baseline RNFL thickness, central corneal thickness, and intraocular pressure. MAIN OUTCOME MEASURES: The effect of baseline 24-hour mean arterial pressure (MAP), systolic BP (SBP), and diastolic BP (DBP) on the rate of average RNFL loss over time. RESULTS: Eyes underwent an average of 13 &#xb1; 3 optical coherence tomography exams over 43 &#xb1; 10 months of follow-up. The mean rate of RNFL loss was -0.34 &#xb1; 0.64 &#xb5;m/y (median: -0.32; interquartile range: -0.66 to -0.04 &#xb5;m/y). After adjusting for confounding factors, every 10 mm Hg lower in 24-hour minimum MAP, SBP, and DBP was associated with -0.542 &#xb5;m/y (P < .001), -0.360 &#xb5;m/y (P = .003), and -0.458 &#xb5;m/y (P = .008) faster RNFL loss, respectively. Eyes in the lowest quartile of average 24-hour MAP (81-90 mm Hg) and minimum 24-hour DBP (35-47 mm Hg) experienced significantly faster progression compared to those in the highest quartile, with differences of -0.68 &#xb5;m/y (P = .017) and -0.63 &#xb5;m/y (P = .030), respectively. CONCLUSIONS: Lower systemic BP, especially minimum MAP, SBP, and DBP measured by 24-hour ambulatory BP monitoring, is associated with faster rates of RNFL loss in primary open-angle glaucoma eyes. 24-hour BP monitoring may help predict glaucoma patients at greater risk of progression.

Humans

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained >&#x2009;70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116&#x202f;cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460&#x202f;cells showed no increase in EdU incorporation at 10 or 100&#x202f;nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c.&#xa0;20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics

A review on the environmental distribution, toxic effects, bioaccumulation characteristics and risk assessment of short-chain chlorinated paraffins.

Chlorinated paraffins (CPs) are synthetic chemicals, widely used as flame retardants and plasticizers. As emerging contaminants, short chain chlorinated paraffins (SCCPs) have attracted tremendous attention due to their persistence, chronic toxicity, long-range transport potential and bioaccumulation potential. This review synthesizes global data on SCCPs' environmental occurrence, toxicological impacts, and bioaccumulation characteristics. SCCPs are ubiquitously detected in various environmental media, including water, sediment, air, soil, and biota. Ecotoxicological studies reveal that SCCPs have lethality, carcinogenicity, growth and developmental toxicities, organs toxicities and endocrine-disrupting effects across species, which pose risks to ecological systems and human health. In addition, the bioaccumulation effects of SCCPs in terrestrial and aquatic ecosystems were analyzed, and proposed the key factors affecting the bioaccumulation of SCCPs. Finally, the risk assessment of SCCPs contamination in the surface water and the soil was carried out, and all soil and most water bodies were found to be low risk. The present study could provide scientific basis and reference for environmental management of CPs products.

Paraffin

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques

Tracking microplastic contamination across seasons in a freshwater reservoir: Evidence from surface water, sediments, and fishes.

Microplastics (MPs) are prevalent contaminants in aquatic environments, posing substantial ecological and health risks. These particles migrate within the different layers of aquatic bodies with time and affect the respective biota. Thus, to get an in-depth understanding of the particles, this current study investigated the seasonal distribution, morphological and chemical characteristics, along with potential ecological and human health impacts in the samples including surface water, sediment, and fish from a drinking water supplying reservoir in eastern India. Across three different seasons, pre-monsoon, monsoon, and post-monsoon samples were collected using optimized methods. Results revealed distinct seasonal trends: MP abundance in surface water peaked during the monsoon (mean: 1.15 MPs/L), while sediment showed the highest concentrations in the pre-monsoon (mean: 596 MPs/kg), indicating temporal accumulation dynamics influenced by runoff, hydrodynamics, and sedimentation. Fish gut analysis confirmed ingestion of MPs across five species, with concentrations ranging from 26 to 100 MPs/kg, depending on feeding habits. The most dominant MP type were fragments, followed by fibers, films, and beads. Polymer analysis via &#xb5;FTIR identified polyethylene, polypropylene, and polyvinyl chloride as prevalent, with hazard assessments (i.e., Polymer Hazard Index (PHI)) indicating medium to very high ecological risks. Heavy metal association was more dominant in the MPs isolated from sediments than the waterborne MPs. Pollution Load Index (PLI) values were > 1 in most seasons, confirming contamination. Health risk analysis suggested potential exposure through both drinking water and fish consumption. This study emphasizes the need for seasonal monitoring, improved waste management, and mitigation strategies to address MP pollution in freshwater ecosystems.

Microplastics