To enhance the synthesis efficiency of ethyl acetate, a key flavor compound in Baijiu (Chinese liquor), a co-fermentation system was developed by integrating the high ethyl acetate-producing yeast Wickerhamomyces anomalus YF1503 with the high ethanol-producing yeast Saccharomyces cerevisiae YF1914. Metabolic interactions and process parameters influencing ethyl acetate biosynthesis were systematically investigated. In synchronously inoculated 1:1 mixed culture, S. cerevisiae YF1914 growth was unaffected, whereas W. anomalus YF1503 biomass decreased significantly. Sequential inoculation strategies markedly inhibited growth of delayed-inoculated strains. Cell-free filtrate assays confirmed that inhibition arose not only from carbon source competition but also from antagonism over other essential nutrients. Optimal conditions were identified as sorghum hydrolysate medium (12 °Bx), initial pH 3.0, 1:1 inoculation ratio (2 × 10⁶ CFU/mL total), and a two-stage fermentation: static incubation of W. anomalus YF1503 (28°C, 24h) followed by S. cerevisiae YF1914 inoculation and shaking incubation (28°C, 180rpm, 36h). Under these conditions, ethyl acetate yield reached 4.30g/L, representing a 3.8-fold increase over single-culture fermentation. This study elucidates the metabolic interaction patterns of functional yeasts in Baijiu fermentation and introduces a targeted co-fermentation strategy for directional enhancement of ethyl acetate production, providing a framework for aroma optimization in traditional liquor manufacturing.

Mangrove ecosystems contain abundant lignocellulosic biomass and mangrove microorganisms that are capable of degrading plant polymers. In this study, a shotgun metagenomic approach was employed to explore the bacterial communities from Tanjung Piai National Park, Malaysia and their genes involved in lignocellulosic biomass degradation. A total of 148 of carbohydrate active enzymes (CAZy) genes spanning GH, CE, and AA families were identified with lignocellulolytic abilities. These enzymes included 20 cellulases, 46 hemicellulases, and 82 lignin-modifying enzymes. Approximately 89.19% of these genes were found from underexplored bacterial lineages. A set of lignocellulolytic genes derived from diverse bacterial taxa highlighted the synergistic action of mangrove bacteria in lignocellulose degradation. To validate the functionality of these genetic resources, one of the genes (BGL3_GH1) encoding a β-glucosidase was selected for expression and characterisation. The recombinant enzyme showed optimal activity at 60 ℃ and pH 7, retained up to 75% activity at 10% (w/v) NaCl. The enzyme exhibited a 1.6 to 2.1-fold in enzyme activity with glucose concentration up to 2 M. In a two-step saccharification assay using sugarcane bagasse, supplementation with recombinant BGL3_GH1 enhanced the saccharification yield (0.0674 g g− 1 biomass) compared with treatments using commercial cellulase or recombinant BGL3_GH1 alone. These findings reveal the functional diversity of lignocellulose-degrading genes in mangrove bacteria and identify recombinant BGL3_GH1 as a potential enzyme candidate for biomass conversion application.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13205-026-04788-x.

The online version contains supplementary material available at 10.1007/s13205-026-04756-5.

The online version contains supplementary material available at 10.1007/s13205-026-04763-6.

This study develops and evaluates a bioconversion system designed to enhance the growth of Black Soldier Fly (BSF) larvae and convert organic solid waste into feed protein and organic fertilizer. Two systems, the modified clay jug and the biopond, were developed using solid waste collected from restaurants, residences, and marketplaces as substrates. One gram of BSF eggs was mixed with one kilogram of each type of waste, with an additional kilogram introduced weekly for three weeks. The measured parameters included larval biomass, waste reduction, conversion efficiency, proximate composition, and compost characteristics. The clay jug system utilizing restaurant solid waste generated larvae with the highest fresh and dry weights, optimal solid reduction rate, most effective waste conversion, and maximum survival rate. Proximate analysis revealed that larvae sourced from restaurant waste contained the highest concentrations of fat, caloric content from fat, and total energy, whereas larvae obtained from market waste showed increased levels of ash, protein, and carbohydrates. All compost produced complied with Indonesian National Standards. The integration of clay jug technology with restaurant waste demonstrated a novel, cost-effective, and highly efficient BSF bioconversion method, providing enhanced nutrient recovery and waste valorization compared to conventional systems.

Genome editing techniques, especially clustered regularly interspaced short palindromic repeats (CRISPR), brought researchers into a new era of molecular plant breeding because it enabled them to make targeted modifications in plant genomes and transcriptomes. However, the successful incorporation of large DNA segments into plant genomes, necessary for high genetic gains and desired traits, remains a critical challenge. As there is an increasing demand for technologies that support chromosomal integration of large DNA inserts suitable for application in synthetic biology and plant breeding, PrimeRoot editors have presented a revolutionary solution to this issue, as they integrate enhanced prime editing guide RNA (PegRNA) designs, improved plant prime editor systems and advanced recombinases, helping in the precise insertion of DNA fragments of up to 11.1kb into the plant genomes. Third-generation PrimeRoot editors further enhanced the precision and efficiency of transformation under different gene delivery systems. This technology holds enormous promise for accurately inserting long DNA sequences across different species of plants. This review highlights expected developments, opportunities, applications, advantages and challenges associated with PrimeRoot editors as well as the significance of expanding their applicability to more varieties of plants.

The emergence of personalized medicine represents a significant change in medicine and offers more accurate and personal approaches to treatment. Neurodegenerative diseases, based on progressive deterioration of the neurons, pose a considerable challenge because of their multifactorial etiological and heterogeneous clinical phenotypes. The present paper dwells on one of the prevalent neurodegenerative diseases: Parkinson's Disease. Parkinson's Disease is linked to motor symptoms, which include bradykinesia, tremor, rigidity, and posture instability. Parkinson's, as a significant movement disorder, reflects the urgency of the new treatment methods. The existing interventions, like Levodopa, Catechol-O-Methyltransferase inhibitors, and surgical procedures like Deep Brain Stimulation, are used as the current interventions. Nonetheless, these therapeutics cannot work in all patients with great success, and the response of the patients to them differs greatly. This contradiction especially highlights the gap in the contemporary paradigms of treatment and the need to transition into more individualized approaches. The use of personalized medicine with Parkinson's Disease marks a shift in the historically used one-size-fits-all approach, instead shifting to a more personalized approach. Through genetic, biomarker, and phenotypic information, personalized medicine will enhance the accuracy of diagnosis, disease progression forecasting, and treatment regimes. This literature review provides an explanation of the need for personalized medicine in Parkinson's, discusses the latest developments, techniques, limitations, and analyzes the innovative technologies and strategies. By identifying key developments and ongoing challenges, the paper aims to provide a comprehensive understanding of how personalized medicine could transform the future of Parkinson's disease management.

The online version contains supplementary material available at 10.1007/s13205-026-04733-y.

Drought stress was a critical environmental factor limiting plant growth, metabolism, and secondary metabolite production. Among these compounds, rosmarinic acid (RA) plays a key role due to its antioxidant and pharmaceutical properties, making its biosynthesis highly sensitive to water availability. Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) had been shown to enhance stress tolerance by modulating physiological, biochemical, and molecular responses. This study investigated the effects of AMF (Funneliformis mosseae) and PGPR (Pseudomonas fluorescens and Azospirillum lipoferum), both individually and in combination, on rosmarinic acid biosynthesis and molecular mechanisms in M. officinalis under drought stress (50% field capacity, FC) and optimal irrigation (100% FC). The results revealed that microbial inoculation significantly improved rosmarinic acid accumulation, particularly under drought conditions, with dual inoculation (P. fluorescens + F. mosseae) leading to an 8.08mg g⁻¹ DM increase in rosmarinic acid content 50.9% higher than non-inoculated plants. Furthermore, microbial treatments upregulated key genes involved in rosmarinic acid biosynthesis, including PAL, 4CL, and RAS, with the highest expression levels observed in P. fluorescens + F. mosseae treated plants under water deficit conditions (PAL: 7.84-fold, 4CL: 7.90-fold, RAS: 7.24-fold). Inoculation also enhanced antioxidant enzyme activities (superoxide dismutase, catalase, peroxidase) and reduced oxidative damage by lowering lipid peroxidation and hydrogen peroxide levels. These findings indicate that arbuscular mycorrhizal fungi and plant growth-promoting rhizobacteria synergistically enhance drought tolerance in M. officinalis by improving water status, increasing antioxidant defense, and upregulating molecular pathways involved in rosmarinic acid biosynthesis. This study highlighted the potential application of microbial inoculants as sustainable biofertilizers to enhance secondary metabolite production and stress resilience in medicinal plants.

Cervical cancer ranks as the fourth most prevalent cancer among women worldwide. The increasing incidence and mortality rates are largely attributed to limited screening infrastructure, a shortage of skilled medical personnel, and inadequate awareness-particularly in developing nations. Conventional diagnostic methods, including the Pap smear, HPV testing, histopathology, and visual inspection with acetic acid (VIA), are often prone to human error due to subjective interpretation by clinicians. To address these limitations, this study proposes a robust automated framework for cervical cancer detection and cervix type classification using advanced deep learning techniques with minimal data requirements. A total of 915 histopathology images and over 4,000 colposcopy images were collected from public repositories and local healthcare institutions. Several pre-trained convolutional models were evaluated for cervix type classification. The proposed system employs a lightweight GoogleNet architecture to identify the transformation zone, followed by an EfficientMobileNet model for cervix type classification and cancer detection. Experimental results demonstrate superior performance, achieving 96% accuracy for cervix type classification, 95% accuracy for cervical cancer detection, and 99% mean average precision (mAP) for region-of-interest (ROI) localisation. The proposed approach offers an effective and resource-efficient diagnostic solution, particularly beneficial for regions with constrained healthcare infrastructure and limited clinical expertise. The proposed model gives 97% recall, 97% specificity, 97% accuracy, 96% mAP, 97% F1-measure and 99.8% AUC, respectively, compared to existing approaches like VGG16, ResNet50, CNN, ConvNet_1, ConvNet_5 and ConvNet_10.