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PubMed2025

Identification of Plant Chromatin Interaction Networks Using IP-MS and co-IP.

Proteins often act in concert to perform their function. Thus, the identification of protein complexes is crucial if we want to understand how they work. In this chapter, we present a highly sensitive protocol for the immunoprecipitation of nuclear chromatin-linked proteins in Arabidopsis thaliana that does not rely on time-consuming nuclei extraction. Interaction partners are identified using mass spectrometry and confirmed by co-immunoprecipitation. To help solubilize chromatin-bound proteins and eliminate nonspecific interactions of proteins binding the same DNA stretch, we include an enzymatic digestion step to remove DNA before immunoprecipitation. Our protocol offers a simplified process using optimized buffers, which facilitates quick and effective immunoprecipitation. The outcome is high-quality eluates that are ideal for identifying proteins through MS.

Chromatin↗
PubMed2026

Plant-derived and microbial biostimulants in sustainable agriculture: mechanisms, applications, and challenges.

Plant biostimulants have emerged as transformative and sustainable tools for improving crop productivity, resource-use efficiency, and resilience under rapidly intensifying environmental stresses. Unlike conventional agrochemicals, biostimulants function by activating physiological, biochemical, and molecular processes that optimize plant performance without directly supplying nutrients or exerting pesticidal effects. This review comprehensively examines the integrated roles of plant-derived and microbial biostimulants in sustainable agriculture, with particular emphasis on microbial-mediated mechanisms underlying plant stress adaptation and rhizosphere functioning. Plant-derived biostimulants, including seaweed extracts, humic substances, protein hydrolysates, amino acids, and chitosan, enhance nutrient acquisition, root architecture, hormonal regulation, and antioxidant defense systems. More importantly, microbial biostimulants, such as plant growth-promoting rhizobacteria (PGPR), endophytic microorganisms, mycorrhizal fungi, actinomycetes, yeasts, and cyanobacteria, exert multifunctional effects through biological nitrogen fixation, mineral solubilization, phytohormone biosynthesis, volatile signaling, osmolyte accumulation, pathogen suppression, and modulation of stress-responsive genes. These beneficial microorganisms reshape rhizosphere microbial communities, improve nutrient cycling, and enhance plant tolerance to drought, salinity, heat, and heavy metal toxicity. Emerging evidence from genomics, transcriptomics, metabolomics, and microbiome-based investigations has further revealed the molecular networks and signaling pathways governing biostimulant-induced resilience and plant-microbe interactions. Despite their substantial promise, inconsistent field performance, formulation instability, regulatory limitations, and inadequate mechanistic understanding continue to restrict their large-scale adoption. This review highlights recent advances in microbial and plant-derived biostimulants while identifying critical knowledge gaps and future opportunities for precision biostimulant engineering, microbiome manipulation, and climate-resilient crop management. The integration of next generation biostimulant technologies into sustainable agricultural systems may significantly reduce dependence on agrochemicals while improving crop productivity, environmental sustainability, and global food security.

Agriculture↗
PubMed1979

Studies on the mobilization of iron from ferritin by isolated rat liver mitochondria.

Rat liver mitochondria and rat liver mitoplasts mobilize iron from ferritin by a mechanism which depends on a respiratory substrate (preferentially succinate), a small molecular weight electron mediator (FMN, phenazine methosulphate or methylene blue) and (near) anaerobic conditions. The release process under optimized conditions (approx. 50 mumol/1 FMN, 1 mmol/l succinate, 0.35 mmol/1 Fe(III) (as ferritin iron), 37 degrees C and pH 7.40) amounts to 0.9--1.2 nmol iron/mg protein per min. The results suggest that ferritin might function as an intermediate in the cytosolic transport of iron to the mitochondria.

Animals↗
PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗
PubMed2025

Retinal hypoxia reversal with PLGA-oxygen nanobubbles.

Pathologies associated with retinal hypoxia, including diabetic retinopathy, central/branch retinal artery occlusion (CRAO/BRAO), central/branch retinal vein occlusion (CRVO/BRVO), retinopathy of prematurity, sickle cell retinopathy, etc., have limited effective therapeutic intervention strategies. To address this shortcoming, herein we propose a biocompatible and biodegradable poly (lactic-co-glycolic acid) shell-based oxygen nanobubbles (PLGA-ONBs) platform, formulated with PLGA, polyvinyl alcohol (PVA), and NaHCO3. The formulation of a novel PLGA-ONBs was proposed, and the synthesis process was optimized with respect to dependent (sonication power, PVA, and NaHCO3 concentrations) and response (hydrodynamic diameter and oxygen capacity) variables. The optimized formulation has a concentration of (13.8 ± 0.01) × 1010 particles per ml with a hydrodynamic diameter of 142.83 ± 11.46 nm, and oxygen loading capacity of 47.2 ± 2.4 mg L-1. After 4 weeks of storage, the ONBs were found to have an oxygen concentration of 38.9 ± 2.9 mg L-1, indicating excellent oxygen retention capability. The PLGA-ONBs tested in vitro in Muller and R28 retinal cell lines demonstrated excellent biocompatibility and potential to mitigate hypoxia. In addition, the PLGA-ONBs treatment on hypoxic cells demonstrated restoration of mRNA expression of three key hypoxic genes (HIF-1α, PAI-1, and VEGF-A) to normoxic states, indicating hypoxia reversal potential. Biosafety of the PLGA-ONBs was demonstrated in a rabbit model, demonstrating promise in clinical translation. The PLGA-ONBs developed exhibited excellent oxygen loading and retention, potential in hypoxia mitigation, and a safety profile that could be a promising route to treating ischemic diseases of the eye.

Polylactic Acid-Polyglycolic Acid Copolymer↗
PubMed2025

Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data.

MOTIVATION: Taxonomic analysis of environmental microbial communities is now routinely performed thanks to advances in DNA sequencing. Determining the role of these communities in global biogeochemical cycles requires the identification of their metabolic functions, such as hydrogen oxidation, sulfur reduction, and carbon fixation. These functions can be directly inferred from metagenomics data, but in many environmental applications metabarcoding is still the method of choice. The reconstruction of metabolic functions from metabarcoding data and their integration into coarse-grained representations of biogeochemical cycles remains a difficult bioinformatics problem today. RESULTS: We developed a pipeline, called Tabigecy, which exploits taxonomic affiliations to predict metabolic functions constituting biogeochemical cycles. In a first step, Tabigecy uses the tool EsMeCaTa to predict consensus proteomes from input affiliations. To optimize this process, we generated a precomputed database containing information about 2404 taxa from UniProt. The consensus proteomes are searched using bigecyhmm, a newly developed Python package relying on Hidden Markov Models to identify key enzymes involved in metabolic function of biogeochemical cycles. The metabolic functions are then projected on coarse-grained representation of the cycles. We applied Tabigecy to two salt cavern datasets and validated its predictions with microbial activity and hydrochemistry measurements performed on the samples. The results highlight the utility of the approach to investigate the impact of microbial communities on biogeochemical processes. AVAILABILITY AND IMPLEMENTATION: The Tabigecy pipeline is available at https://github.com/ArnaudBelcour/tabigecy. The Python package bigecyhmm and the precomputed EsMeCaTa database are also separately available at https://github.com/ArnaudBelcour/bigecyhmm and https://doi.org/10.5281/zenodo.13354073, respectively.

Metagenomics↗
PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗
PubMed1975

Electrodecantation of serum proteins.

The sedimentation of albumin under the action of the electric and gravitational fields was determined as a function of time in discontinuous experiments in a rectangular cell, using serum with the albumin fraction stained blue. It was shown that even under the influence of strong electric fields, the upper boundary of the albumin layer fell no further than the mid-point of the cell. In continuous single-stage separation of gamma-globulin from other serum proteins, only about half the gamma-globulins can be obtained from the solution because it remains homogeneously distributed throughout the solution and is only free from albumin and other proteins in the upper half of the cell. In experiments with continuously operated triangular cells, the process was optimized to give gamma-globulin of 97.5% purity in a yield of 80%, at serum flow-through rates of up to 0.5 l/h in a block composed of 40 cells.

Animals↗
PubMed1979

Elongation of DNA complementary to the 5' end of the avian sarcoma virus genome by the virion-associated RNA-dependent DNA polymerase.

RNA-dependent DNA synthesis in a virion-associated reaction has been described as being dependent upon the detergent concentration used for disruption of the virion. In this study, the Triton X-100 concentration was found to affect the elongation of the initially synthesized DNA complementary to the last approximately 100 nucleotides at the 5' end of the RNA (cDNA100). Whereas elongation of cDNA100 increased with time of incubation at the optimal detergent concentration, this process was retarded at higher detergent concentrations. At the optimal detergent concentration, elongated DNA was of low chemical complexity, indicating that extension of cDNA100 occurred at a unique site on the RNA. Higher than optimal detergent concentrations resulted in nonspecific elongation and in DNA of high chemical complexity. This was shown by oligopyrimidine tract analysis. Furthermore, actinomycin D was observed to inhibit the elongation of cDNA100 at the optimal detergent concentration. The nature of the elongation process was elucidated by analysis of DNA synthesized in a virion-associated reaction in the presence of bacteriophage Qbeta RNA. At the optimal detergent concentration DNA complementary only to avian sarcoma virus RNA was synthesized, whereas at higher concentrations DNA was copied from both avian sarcoma virus and Qbeta RNA. We conclude that the elongation mechanism of cDNA100 is affected by the detergent concentration and elongation is unspecific at higher than optimal detergent concentrations. The mechanism by which the nonionic detergent stimulates DNA synthesis has not yet been resolve. We assume that other factors in addition to DNA polymerase are involved in elongation of cDNA100.

Alpharetrovirus↗
PubMed2026

Microalgae-Mediated Synthesis of Gold Nanoparticles from Indonesian Chlorella vulgaris InaCC M205 with Potential Anticancer Properties for Biomedical Application.

Sustainable nanomaterial synthesis has emerged as a critical strategy to reduce the environmental burden associated with conventional chemical synthesis method. Microalgae-derived biomolecules offer a promising platform for the green production of metal nanoparticles due to their rich bioactive compounds capable of acting as natural reducing and stabilizing agents. Here, we report the eco-friendly synthesis of gold nanoparticles (AuNPs) using extract of Indonesian microalga Chlorella vulgaris extract. To optimize the synthesis process, the effects of precursor-to-extract ratio, temperature, and incubation time were evaluated. Optimal synthesis of C5-AuNPs was obtained at 37 °C for 20 h with precursor to extract ratio of 6:4, resulting in moderately stable C5-AuNPs characterized by a surface plasmon resonance (SPR) peak at 541 nm. Furthermore, Fourier-transmission infra-red (FT-IR) analysis revealed the involvement of functional groups of C. vulgaris extract in the interaction with Au+ during the production of C5-AuNPs. Transmission electron microscopy (TEM) demonstrated the formation of uniformly spherical nanoparticles with an average diameter of approximately 8.8 nm. Biological evaluation showed that the synthesized C5-AuNPs exerted pronounced dose-dependent cytotoxicity against MCF-7 breast cancer cells with an IC50 threshold of 21.17 ppm, while no toxicity appears in normal HEK293 cells. Mechanistically, the C5-AuNPs induced early apoptosis and inhibit cell-cycle progression at the stage of G0/G1. Collectively, these findings demonstrate that C. vulgaris-mediated AuNPs represent a promising preliminary in vitro findings for cancer therapy candidate.

Gold↗
PubMed1978

[Optimal dental radiography by means of expert film processing].

The processing of the dental radiographic films in the darkroom is decisive of the optimal information content of dental radiographs. Proper storage of the films, darkroom lighting according to regulations and standardized film developing are the basic conditions for stable film quality. The indications given are above all intended for aiding the stomatological nurse in taking dental radiographs.

Radiography, Dental↗
PubMed2024

New vectors and optimal conditions for allelic exchange in hypervirulent Klebsiella pneumoniae.

The emergence of antibiotic-resistant Klebsiella pneumoniae is a significant global health threat that has led to increased morbidity and mortality. This resistance also hinders basic research, as many strains are no longer susceptible to antibiotics commonly used in microbial genetics. Addressing this requires the development of new genetic tools with alternative selective markers. In this report, we introduce new allelic exchange vectors for use in drug-resistant strains. These vectors feature a conditional R6K origin of replication, an origin of transfer, SacB counter-selection, and alternative selectable markers. We validated the vectors by generating unmarked deletions in the K. pneumoniae KPPR1S bla (β-lactamase) and lacZ (β-galactosidase) genes. During this process, we defined optimized conditions for SacB-mediated allelic exchange in KPPR1S, significantly enhancing the efficiency of mutant generation. Furthermore, we demonstrated that lacZ is dispensable for virulence and that the lacZ mutant can serve as a surrogate for wild-type strains in competition assays using the Galleria mellonella infection model. Our findings provide new tools for the efficient genetic manipulation of K. pneumoniae and other drug-resistant bacteria.

Klebsiella pneumoniae↗
PubMed2027

Optimized Amplicon Strategy for Long-Read Sequencing of the Chikungunya Virus Genome.

Chikungunya virus (CHIKV) is a positive-sense RNA alphavirus transmitted to humans primarily by Aedes aegypti and Aedes albopictus mosquitoes. Its global circulation and significant public health impact underscore the need to better understand the molecular mechanisms driving CHIKV pathogenesis and transmission. Although robust molecular biology methods exist for CHIKV genome sequencing, a major limitation for surveillance and research is the inability to determine whether two nucleotide variations co-occur within the same viral genome when they are separated beyond the span of typical short-read designs. Here, we describe an optimized approach for processing CHIKV RNA samples that generates large amplicons suitable for long-read nanopore sequencing. This protocol enables amplification of the complete CHIKV genome in only two or three amplicons and facilitates detection of co-occurring nucleotide variations across 4-7.5 kb within the same molecule, thereby simplifying sequencing workflows and improving resolution in studies of viral evolution.

Chikungunya virus↗
PubMed2024

Effects of initial corncob particle size on the short-term composting for preparation of cultivation substrates for Pleurotus ostreatus.

The short-term composting based on corncob for preparing Pleurotus ostreatus cultivation medium originated from agricultural production practices and so lacked systematic investigation. In this study, the influences of a Dafen (15 mm, DFT) and Xiaofen (5 mm, XFT) initial particle size (IPS) of corncob on the microbial succession and compost quality were examined. Results demonstrated that XFT compost was better suited for mushroom cultivation due to its high biological efficiency of 70 % and the absence of contamination. The composting microbes differed significantly between the DFT and XFT composts. During composting, the genera of Bacillus, Acinetobacter, Lactobacillus, Streptomyces, and Paenibacillus were majorly found in the DFT compost, while Acinetobacter, Lactobacillus, Puccinia, Bacteroides, and Bacillus genera dominated the XFT compost. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that throughout the thermophilic phase, XFT compost had much greater relative abundances of sequences relevant to energy, carbohydrate, and amino acid metabolism than DFT compost. Analysis of network correlations and Mantel tests indicated that IPS reduction could increase microbial interactions. Overall, adjusting the IPS of corncob to 5 mm increased microbial interactions, improved compost quality, and thereby boosted the P. ostreatus yield. These findings will be pertinent in optimizing the composting process of cultivation medium for P. ostreatus.

Composting↗
PubMed2024

Assessment of antibiotic resistance genes in soils polluted by chemical and technogenic ways with poly-aromatic hydrocarbons and heavy metals.

Anthropogenic activities are leaving lots of chemical footprints on the soil. It alters the physiochemical characteristics of the soil thereby modifying the natural soil microbiome. The prevalence of antimicrobial-resistance microbes in polluted soil has gained attention due to its obvious public health risks. This study focused on assessing the prevalence and distribution of antibiotic-resistance genes in polluted soil ecosystems impacted by industrial enterprises in southern Russia. Metagenomic analysis was conducted on soil samples collected from polluted sites using various approaches, and the prevalence of antibiotic-resistance genes was investigated. The results revealed that efflux-encoding pump sequences were the most widely represented group of genes, while genes whose products replaced antibiotic targets were less represented. The level of soil contamination increased, and there was an increase in the total number of antibiotic-resistance genes in proteobacteria, but a decrease in actinobacteria. The study proposed an optimal mechanism for processing metagenomic data in polluted soil ecosystems, which involves mapping raw reads by the KMA method, followed by a detailed study of specific genes. The study's conclusions provide valuable insights into the prevalence and distribution of antibiotic-resistance genes in polluted soils and have been illustrated in heat maps.

Soil Pollutants↗
PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗
PubMed2025

Unlocking Zeptomolar Single-Molecule Detection by Synergizing Digital Microfluidics and Digital CRISPR.

Accurate diagnosis relies on the highly sensitive and quantitative detection of multiple immune-related biomarkers. However, current detection methods still face significant limitations in sensitivity, specificity, and background signal control. Here, we introduce DDA (Dual-Digital immunoAssay), a fully automated, universal immunoassay platform that synergizes digital microfluidics with digital Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based amplification. This "dual-digital" strategy pushes the detection limit into the zeptomolar (zM) regime, enabling unprecedented sensitivity for single-molecule analysis. The DDA platform is built upon a digital microfluidic microwell array chip, integrating magnetic bead-based immunocapture with RNA-guided CRISPR/Cas13a signal amplification. This system enables a fully automated, "sample-in, answer-out" workflow. By systematically optimizing the entire process, DDA significantly reduces background noise and enhances detection sensitivity, achieving a limit of detection (LOD) down to 100 zM for key protein biomarkers. This represents a >100-fold improvement over leading commercial ultrasensitive assays. With single-molecule resolution and full automation, DDA provides a robust solution for the precise quantification of low-abundance immune biomarkers. As a proof-of-concept, we demonstrate its ability to accurately quantify key heart-failure-associated biomarkers, including NT-proBNP (LOD: 1 aM), IL-6 (LOD: 1.5 aM), and TNF-α (LOD: 2.5 aM), directly in complex serum samples. This platform holds great promise for automated multibiomarker screening and risk assessment, showcasing its powerful potential for the early diagnosis of major diseases such as cardiovascular diseases, cancers, neurodegenerative disorders, and infectious diseases.

Humans↗