Search Results (2,944)

This study investigates the impact of FinTech on the monetary policy dynamics of the four major payment channels of banks in Nigeria, namely the automated teller machine (ATM), mobile payment (MOBPAY), web payment (WEBPAY), and Point-of-Sale (POS), from 2012 to 2025. The paper employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine the relationships between the variables, whilst conducting a robustness check using dynamic ordinary least squares (DOLS). The study shows that POS transaction values have a positive and statistically significant impact on both the monetary policy rate (MPR) and the treasury bill rate (TBR). The findings also indicate that the savings deposit rate (SDR) increases both the MPR and the TBR, whereas the maximum lending rate (MLR) does not affect these policy rates. Mobile payments lead to significantly lower treasury bill and monetary policy rates. These findings empirically affirm that FinTech channels have expanded over the years, driven by the central bank’s cashless policy and banks’ response to the introduction of FinTech start-ups into the financial system. Thus, FinTech channels are important determinants of monetary policy transmission, justifying the need for the monetary authority to examine channel-specific sensitivities to its effectiveness in Nigeria’s fast-growing digital payment ecosystem. Full article

Textile waste has become a major environmental challenge associated with increasing levels of production and consumption in the fashion industry. The fast fashion business model, characterised by rapid production cycles, low prices, and frequent replacement of clothing items, contributes significantly to growing volumes of textile waste and the depletion of natural resources. This study examines students’ perceptions of the environmental impacts of textile waste and fast fashion, with particular emphasis on sustainable consumption practices and textile waste management in Croatia. The study combines a review of the scientific literature with an online questionnaire survey conducted among a non-probability convenience sample of 79 students enrolled in different study programmes in Croatia. The results indicate a high level of environmental awareness and familiarity with textile waste issues among respondents. However, despite generally positive attitudes towards sustainability, willingness to modify purchasing behaviour or pay higher prices for sustainable clothing remained limited, indicating a clear attitude–behaviour gap. Price emerged as a particularly important factor influencing purchasing decisions, while limited access to textile collection facilities was identified as an important barrier to proper textile waste management. Chi-square tests of independence did not identify statistically significant associations between environmental concern and support for sustainable fashion or between level of education and the examined sustainability-related consumption responses. The findings suggest that environmental awareness alone may not be sufficient to encourage sustainable consumption and highlight the importance of combining environmental education with economically accessible sustainable alternatives and adequate textile collection infrastructure. The study provides exploratory insight into the relationship between environmental awareness, consumer behaviour, and self-reported textile management practices among the surveyed students and contributes to the discussion on promoting more sustainable textile consumption within a circular economy. Full article

Seedling growth is an essential stage for the future growth of trees, and Paulownia is treated as a rapidly growing hardwood tree species with wide industrial application. There is a knowledge gap in the modeling and analysis of the seedling growth pattern of Paulownia hybrid clones under field nursery conditions. A total of 300 saplings belonging to 25 Paulownia hybrid clones (named PT1–PT25, 12 saplings per clone) were observed 16 times after flat stubble treatment, yielding 4800 records. After accounting for mortality under field nursery conditions, 118 saplings survived, resulting in 1888 valid records for model construction. Seven theoretical growth equations with clone-specific dummy variables were fitted using nonlinear mixed-effects models (NLMM) with an AR(1) correlation structure to account for the hierarchical structure of the repeated measurements. Among the seven candidate models, Hossfeld IV was selected as the optimal model for both ground diameter (AIC = 8250.62, RMSE = 1.47 mm, conditional R² = 0.9892) and tree height (AIC = 15586.26, RMSE = 10.48 cm, conditional R² = 0.9916). However, because the Hossfeld IV model lacks an analytical third derivative, the standard logistic model was adopted to calculate the biologically meaningful fast-growing period boundaries. PT24 exhibited the highest growth potential among all clones, with asymptotic maximum values of 86.76 mm for ground diameter and 490.00 cm for tree height. However, its low survival rate (25%, n = 3) limits its practical recommendation. In addition, height-to-diameter (H/D) ratio analysis revealed considerable variation among clones, ranging from 3.89 cm∙mm⁻¹ (PT22) to 8.06 cm∙mm⁻¹ (PT3). The H/D ratio showed no significant correlation with ground diameter A (r = 0.286, p = 0.166), but a significant positive correlation with tree height A (r = 0.660, p < 0.001). PT24 maintained a moderate H/D ratio (6.92) despite its superior growth, indicating favorable stem stability. PT6 (91.67% survival, moderate growth) represents a more robust alternative for breeding programs prioritizing establishment success. This study demonstrates that a dual-model strategy provides a robust framework for evaluating clone-specific growth potential and supports informed breeding decisions in Paulownia improvement programs. Full article

The Min pig, a Chinese indigenous breed, is valued for its excellent meat quality and stress tolerance. Nevertheless, its growth rate falls considerably short of commercial pig breeds, a pattern typical of most unselected indigenous populations, and marked individual variation further undermines its economic viability. To explore the genetic basis of this variation, we evaluated a series of nonlinear fixed-effects and mixed-effects models based on the Gompertz, Logistic, and von Bertalanffy functions using body weight records from 92 Min pigs. Model selection was based on AIC, BIC, and leave-one-out cross-validation. The best-fitting model was a Logistic nonlinear mixed-effects model with individual-level random effects on all three growth parameters (Asymptotic weight, timing parameter, and be parameter), which clearly outperformed models with simpler random-effect structures and fixed-effects models. From this model, we identified three characteristic growth transition points: the early transition point (Growth Rate Index, GRI) at 94.83 days (22.32 kg), the single inflection point (Maximum Growth Rate, MGR) at 166.06 days (52.80 kg), and the late transition point (Late Growth Rate Index, LGRI) at 237.29 days (83.29 kg), with a maximum absolute growth rate of 488.2 g/day. These points partitioned growth into initial acceleration, rapid growth, deceleration, and Asymptotic growth phases. Using individual fitted growth curves, we selected five fast-growing and five slow-growing pigs that reached approximately 90 kg during the plateau phase, defined as a predicted body weight of at least 95% of the individual Asymptotic weight. The fast-growing group reached 90 kg at 240.5 ± 20.42 days, whereas the slow-growing group reached the same weight at 286.67 ± 19.20 days. At the 90 kg slaughter weight, we collected longissimus dorsi muscle samples from these pigs during the plateau phase and performed RNA-seq. Transcriptome analysis revealed 864 differentially expressed genes between the two groups, with 540 upregulated and 324 downregulated in the fast-growing group. Pathway enrichment implicated the PI3K-Akt and TGF-β signaling pathways in muscle development, and differential expression of IGFN1, DCN, COL3A1, MYOC, COL1A2, COL1A1, and IGF2 may explain the growth variation between the groups. In summary, the Logistic mixed-effects model with individual-level random effects on all growth parameters effectively captures the growth pattern of Min pigs, and the PI3K-Akt and TGF-β pathways likely mediate growth differences in this breed. Full article

Blockchain consensus still forces a hard choice among scalability, security, and energy use. Redbelly, a leaderless Byzantine Fault Tolerance protocol, largely settles the scalability-versus-energy side of that tension, yet it accepts any cryptographically valid transaction without judging whether it is economically fraudulent or whether the node behind it is misbehaving. That blind spot is what we target. We present ML-Redbelly, a formally specified extension that attaches four learning components to the Redbelly pipeline: a LightGBM gradient-boosted fraud classifier, an Isolation Forest behavioural anomaly detector, a tabular Q-Learning agent for adaptive committee selection, and a Paillier-based federated learning aggregator that keeps model updates private. We prove that this layer leaves Redbelly’s safety and liveness intact, give pseudocode and complexity bounds for every component, and measure the system on the IEEE-CIS Fraud Detection benchmark (400,000 transactions) paired with a faithful discrete-event Redbelly simulator parameterised from measured inputs and validated against the published Redbelly deployment. LightGBM reaches an F1 of 0.783 (precision 0.858, recall 0.719, AUROC 0.963), a 34 percent relative F1 gain over the conference-baseline Random Forest at five times the inference speed. The Isolation Forest detector attains recall 0.885 at a false-positive rate of 0.047, and the Q-Learning agent settles into a stable policy within about 200 rounds across normal, bursty, and Byzantine-attack conditions. End to end, the framework sustains 48,844 TPS on 32 validators (mean over 30 seeds), and because the leaderless superblock commits every proposer’s block in parallel, this throughput advantage over leader-based BFT grows with the validator count (5.0 times PBFT and 2.9 times HotStuff at 32 validators). The learning layer costs only about 4 percent in throughput, since the measured ML inference is small next to the geo-distributed consensus round. Per-transaction energy is comparable across BFT protocols, being dominated by signature verification, and is orders of magnitude below proof-of-work chains, which expend energy on mining. One federated update epoch takes 36 s across 10 nodes with 2048-bit Paillier keys and reconstructs gradients with negligible error. All performance figures are emergent outputs of the discrete-event simulation, which reproduces the published Redbelly benchmark to within a conservative factor of about 1.7. Taken together, these results outline a simulation-validated design for making consensus intelligent as well as fast and identify the steps needed toward real-cluster deployment. Full article

Eukaryotic translation initiation factor 5A (eIF5A) is a highly conserved protein family unique to eukaryotes, yet its functional characterization in woody plants remains limited. In this study, we identified four eIF5A genes (PtoeIF5A1–PtoeIF5A4) from the genome of Populus tomentosa, a fast-growing tree species indigenous to China, and characterized their expression patterns and functional roles through bioinformatics analysis, quantitative real-time PCR, stable overexpression in Arabidopsis thaliana, and transient expression in Nicotiana benthamiana leaves. Our results demonstrated that all PtoeIF5A proteins contain a conserved OB-fold domain and multiple phosphorylation sites, with PtoeIF5A1 showing predominant expression in roots and secondary xylem. Functional assays revealed that PtoeIF5A1 overexpression accelerated inflorescence stem elongation and early flowering in Arabidopsis, induced visible chlorosis and programmed cell death (PCD) in tobacco leaves, and significantly enhanced salt tolerance under NaCl treatment. Collectively, these findings establish PtoeIF5A1 in poplar as a pleiotropic regulator integrating developmental cues, programmed cell death, and stress responses; and as a valuable genetic resource for breeding stress-resilient woody plants. Full article

A. filiculoides is a fast-growing aquatic fern with potential for laboratory-scale biomass production, nutrient recovery and biorefinery-oriented bioprocessing. However, its cultivation in controlled bioreactors remains limited by insufficient integration of treatment formulation, physicochemical monitoring and predictive optimization. This study evaluated A. filiculoides biomass production for 30 days in semi-closed 5 L glass bioreactors under three cultivation conditions: Hoagland-type mineral solution (T1), Murashige and Skoog (MS) medium (T2), and an aqueous growth-regulator treatment containing 6-benzylaminopurine and indole-3-acetic acid (BAP–IAA; 1 mg L⁻¹ each) (T3). The initial biomass was standardized at 0.10 g FW L⁻¹. By day 30, T3 showed the highest final fresh biomass concentration 1.208 ± 0.043 g FW L⁻¹, followed by T1 0.948 ± 0.025 g FW L⁻¹ and T2 0.538 ± 0.033 g FW L⁻¹. Principal component analysis and k-means clustering showed that dissolved oxygen, oxidation–reduction potential, electrical conductivity, resistivity, pH and water temperature structured the cultivation environment. The physicochemical-modulated Gompertz model showed high internal predictive performance, with training R² = 0.997, RMSE = 0.016 and MAE = 0.013, and cross-validation R² = 0.986, RMSE = 0.033 and MAE = 0.024. Model-based optimization identified T3 at day 30 as the optimal condition, with predicted biomass of approximately 1.224 g FW L⁻¹. The associated operating window corresponded to pH 7.34–7.52, dissolved oxygen 5.70–6.30 mg L⁻¹, ORP 75.40–102.00 mV, EC 983.90–1077.80 µS cm⁻¹ and resistivity 0.928–1.016 kΩ cm. These results support the use of coupled temporal monitoring, multivariate analysis and kinetic modeling for laboratory-scale optimization of Azolla biomass production. Full article

A self-driven terahertz metamaterial liquid biosensor composed of channel-structured metamaterials and a quartz microcavity is proposed for glioblastoma sample detection. The device transports liquid samples via capillary force. The permittivity (ε_eff) of liquid suspensions is comprehensively analyzed to provide theoretical support for the detection. For suspensions with the same contents, ε_eff decreases with increasing concentration, while under the same concentration condition, ε_eff decreases as particle size grows. An electric dipole resonance is excited at ~1.54 THz with theoretical sensitivity ≥ 242 GHz/RIU (where RIU denotes refractive index unit). For the same type of cell discrimination, the frequencies of the biosensor’s feature peaks shift from ~1.14, ~1.18, and ~1.20 THz with the rise in cell concentration of glioblastoma stem cell (GSC) suspension from 4 × 10⁵, 6 × 10⁵ to 8 × 10⁵ cells/mL, respectively. In addition, the GSC, U87 and U251—whose average diameters increase in that order—tested at the same concentration of 4 × 10⁵ cells/mL lead to feature peak shifts from ~1.14, ~1.17, and ~1.20 THz. Clear THz differences exist between healthy and patient serum, with peaks at 1.18 and 1.19 THz. The sensor effectively distinguishes cell suspensions but has limited serum discrimination capacity. The sensor retains cell morphology, requires little pretreatment, and is low-cost and fast for rapid glioblastoma clinical screening. Full article

Background: Mycobacterium marinum is a slow-growing nontuberculous mycobacterium associated with aquatic environments and may cause chronic skin and soft-tissue infections following minor skin trauma. Diagnosis can be delayed because clinical manifestations may mimic conventional bacterial infections. We report an unusual case in a kidney transplant recipient with a positive QuantiFERON-TB Gold test and subsequent M. marinum infection of the hand. Case presentation: A 53-year-old man with a history of kidney transplantation and long-term immunosuppressive therapy developed progressive swelling, pain, erythema, and functional impairment of the right third finger. After independently discontinuing tacrolimus, mycophenolate mofetil, and prednisone following a positive QuantiFERON-TB Gold test, he developed a progressive hand infection despite empirical ciprofloxacin therapy. He reported repeated exposure to a domestic freshwater aquarium and frequent contact with aquarium water and filtration equipment, with minor skin abrasions. Surgical exploration revealed dense, whitish, caseous-appearing material. Histopathology demonstrated chronic granulomatous inflammation, while Ziehl–Neelsen staining showed acid-fast bacilli. Culture yielded slow-growing photochromogenic colonies at 28–32 °C, and species-specific PCR confirmed M. marinum. No antimicrobial susceptibility testing was performed. Following surgical drainage and six days of empirical ciprofloxacin, no targeted antimycobacterial therapy was administered. The patient achieved complete clinical resolution, and immunosuppressive therapy was gradually reintroduced approximately four weeks after surgery. Conclusions: This case highlights the importance of considering M. marinum in persistent or treatment-refractory hand infections, particularly in patients with aquarium exposure and impaired immunity. Early tissue sampling, appropriate culture conditions, and molecular identification are essential for diagnosis. A positive QuantiFERON-TB Gold result should be interpreted cautiously because cross-reactivity with M. marinum is possible. The favorable outcome observed after surgical source control and a short empirical course of ciprofloxacin is unusual and should not be interpreted as evidence supporting short-course monotherapy for deep M. marinum infection. Because antimicrobial susceptibility testing and serial follow-up cultures were unavailable, the contribution of ciprofloxacin to microbiological clearance cannot be determined. Full article

Background: Improving meat quality while maintaining growth efficiency remains a major challenge in poultry production. However, the molecular mechanisms underlying breed-specific meat quality variation remain unclear. This study aimed to investigate how breed-specific growth patterns influence meat quality and elucidate metabolic and transcriptional mechanisms involved. Methods: Pectoralis major meat quality traits and multi-omics profiles were characterized in three genetically distinct chicken breeds—the fast-growing Small White-Feathered chicken (XBJ), the slow-growing Huiyang Bearded chicken (HXJ), and the layer-type Hy-Line Brown chicken (HLH)—at 50, 180, and 300 days of age. Twelve birds per breed per age were used for phenotypic measurement (n = 108 in total), and eight birds per breed per age were subjected to metabolomic and transcriptomic profiling. Phenotypes were analyzed using linear mixed-effects models with breed, age, and their interaction as fixed effects and pen nested within breed as a random effect, followed by Tukey-adjusted pairwise comparisons (p < 0.05). Differential metabolites were screened by OPLS-DA (VIP > 1, p < 0.05), and differentially expressed genes were identified using DESeq2 (|log2FC| ≥ 1, FDR < 0.05). Integrative analyses were performed to identify key genes, metabolites, and pathways associated with meat quality. Results: Phenotypic evaluation revealed a breed-dependent growth–meat quality trade-off, with XBJ exhibiting superior growth but poorer water-holding capacity and meat color, whereas HXJ and HLH showed better tenderness and color at the expense of growth. Metabolomic analysis revealed lipid metabolism as a major contributor to breed-specific divergence, with triglyceride-driven divergence predominating at early and middle stages, whereas later-stage differences involved glycerophospholipid and amino acid metabolism. Transcriptomic analysis revealed significant breed-specific differences in expressed genes at 50 and 180 days, enriched in pathways related to muscle structure, ECM remodeling, and energy metabolism, consistent with metabolic and phenotypic divergence. Integrated analyses identified 28 candidate genes and 71 core metabolites associated with meat quality traits, with PLIN1 and SLC1A6 emerging as key regulators associated with TG species, drip loss, shear force, and BMW. Conclusions: These findings reveal molecular mechanisms underlying the growth–meat quality trade-off and highlight lipid metabolic regulation as a key contributor to meat quality variation. The identified gene–metabolite networks provide insights for molecular breeding to improve chicken meat quality. Full article

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive synovial inflammation, joint destruction, and metabolic abnormalities. In recent years, there has been growing interest in intermittent fasting (IF) as a potential dietary strategy for modulating inflammatory and immunometabolic processes in RA. Preliminary data suggest that IF may lead to reduced joint pain, lower inflammatory markers, improved well-being, and weight loss, but the available evidence is scattered and heterogeneous. The aim of this scoping review was to provide a comprehensive overview of the current state of knowledge regarding the effects of IF on inflammatory, immunological, and metabolic processes in patients with RA. Methods: The review was conducted in accordance with the Joanna Briggs Institute methodology and the PRISMA-ScR guidelines. The databases PubMed, Scopus, Web of Science, EBSCO, the Cochrane Library, and Google Scholar were searched (16 March to 12 April 2026) using the Population–Concept–Context model. Full-text observational and experimental studies, as well as reviews, on intermittent fasting in RA were included in the analysis. Results: Of the 137 publications identified, 9 studies were included in the review, covering populations from Iran, Luxembourg, Tunisia, Mexico, China, and Turkey. The results indicate that IF may lead to improvements in disease activity, quality of life, and selected metabolic parameters. Several studies reported a beneficial effect of IF on markers of oxidative stress and selected pro-inflammatory cytokines, although other analyses did not confirm significant changes in inflammatory biomarkers. Preclinical data have demonstrated strong anti-inflammatory and immunoregulatory effects of IF, including a reduction in pro-inflammatory cytokines and an increase in the Treg population. The heterogeneity of IF protocols, population differences, and small sample sizes limit the ability to interpret the results unequivocally. Conclusions: The available evidence suggests that intermittent fasting may represent a promising, nonpharmacological strategy to support the treatment of RA, particularly in terms of improving immunometabolic parameters and subjective disease symptoms. However, due to methodological limitations and the lack of long-term studies, further well-designed randomized clinical trials are needed to evaluate the efficacy and safety of IF in this population. Full article

The growing demand for multifunctional textile materials has stimulated extensive research into the development of antimicrobial finishing agents capable of providing long-term protection against pathogenic microorganisms while preserving the performance characteristics of fabrics. In this study, cotton fabrics were functionalized using a nitrogen- and sulfur-containing antiseptic composition based on sulfosalicylic acid, copper acetate treated fabrics were characterized by Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA/DTG) to investigate their structural, morphological, and thermal properties. The antimicrobial activity of the modified fabrics was evaluated against representative microorganisms. In addition, the influence of the antiseptic treatment on the functional properties of the cotton fabrics, including tensile strength, elongation at break, wrinkle resistance, abrasion resistance, hygroscopicity, air permeability, color fastness, and water permeability, was assessed. The results demonstrated successful incorporation of the antiseptic composition onto the fiber surface, improved thermal stability, and pronounced antimicrobial activity. Furthermore, the treated fabrics retained satisfactory mechanical and hygienic properties, indicating the suitability of the developed composition for the production of protective and hygienic textile materials. The proposed approach offers a promising route for the fabrication of multifunctional cellulose-based textiles with enhanced performance and biological protection. Full article

Despite a growing range of effective monotherapies for childhood myopia control, a subset of children continues to show suboptimal control, prompting interest in combination therapy. This narrative mini-review summarises recent evidence on combining pharmacological, optical, and device-based treatments to slow myopia progression, with emphasis on axial length (AL) as the benchmark of efficacy. The most studied combination is low-dose atropine plus orthokeratology (OK), with multiple studies and meta-analyses reporting greater slowing of AL elongation than OK alone, particularly in younger children and faster progressors. Emerging evidence supports combining low-dose atropine with other refractive interventions, such as defocus-incorporated multisegment (DIMS) and highly aspherical lenslets (HALs), and dual-focus soft contact lenses, although findings vary by study design, atropine dose, and cohort characteristics. Repeated low-level red light (RLRL) therapy combined with OK or DIMS spectacles has also shown improved AL outcomes in some studies, but retinal safety signals and rebound after cessation require careful monitoring. Combination therapy may be most appropriate for fast progressors, notably those with greater than 0.2 mm over 12 months or for inadequate responders to monotherapy, with stepwise escalation guided by AL response, safety, and adherence. Further long-term, randomised trials with standardised endpoints and responder definitions are needed. Full article

The complexity of voltage stability assessment in modern smart grids has increased significantly with the growing penetration of renewable energy sources and the dynamic nature of load variations. Although standard analytical methods are accurate, they are computationally expensive and unsuitable for real-time applications. This paper proposes a hybrid analytical–machine learning framework for efficient voltage stability assessment and classification. The proposed approach consists of two stages. First, a power flow analysis is performed to compute the Fast Voltage Stability Index (FVSI) and quantify the proximity of the system operating conditions to voltage instability. Then, the FVSI values are converted into binary stability labels to formulate a supervised classification problem. In the second stage, the Extreme Gradient Boosting (XGBoost) algorithm is employed to learn the relationship between system operating variables and the corresponding stability states. The performance of the proposed method is evaluated on the IEEE 30-bus system and compared with that of conventional machine learning and deep learning models, such as Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Deep Neural Networks (DNNs). The simulation results show that the XGBoost-based framework outperforms the benchmark models in terms of classification accuracy, robustness, and computational efficiency. The proposed method provides a fast, reliable, and interpretable solution for real-time voltage stability monitoring. Therefore, it is suitable for modern smart grid applications. Full article

Macrobrachium nipponense is a commercially significant freshwater prawn species in China, with larger individuals commanding higher market prices than smaller ones. Previous transcriptomic analyses have shown that a facilitated trehalose transporter gene Tret1-like (Tret1) exhibits significantly elevated expression levels in fast-growing individuals compared to their slow-growing counterparts, suggesting a potential involvement of this gene in modulating growth performance. In the present study, we explored the functional roles of Mn-Tret1 in growth regulation using reverse transcription quantitative real-time PCR (RT-qPCR) and RNA interference (RNAi) techniques. The full-length cDNA sequence of Mn-Tret1 spans 1605 bp and encodes a 535 amino acid (aa) protein. Phylogenetic analysis indicated that the deduced amino acid sequence of Mn-Tret1 shares the closest evolutionary relationship with that of Macrobrachium rosenbergii. Tissue distribution analysis via RT-qPCR revealed that Mn-Tret1 is ubiquitously expressed across all examined tissues, implying its potential involvement in multiple physiological processes. Notably, the highest transcript abundance was detected in muscle tissue, further suggesting its putative role in governing growth performance in M. nipponense. Subsequent RT-qPCR analysis validated the knockdown efficacy of the synthesized dsTret1 on Mn-Tret1 expression. Compared with the dsGFP-injected control group, the dsTret1-injected group exhibited a statistically significant reduction in body mass gain percentage, with the divergence becoming apparent from day 6 in females and day 12 in males (p < 0.05). Moreover, histopathological examination revealed abdominal muscle atrophy in individuals subjected to dsTret1 treatment. Collectively, these findings substantiate a positive regulatory role of Mn-Tret1 in governing growth performance. This study thereby contributes to a deeper mechanistic understanding of growth regulation in M. nipponense. Full article