Search Results (2,312)

Mitochondrial dysfunction is an early driver of Alzheimer’s disease (AD), and the decline in sex hormones, including 17β-estradiol (E2), at menopause has been linked to AD risk in women. While E2 exerts potent neuroprotective and mitochondrial-regulatory effects, its clinical utility in estrogen replacement therapy (ERT) may be limited by thrombotic and oncologic risks. Estetrol (E4), a fetal estrogen with a selective safety profile, may represent a promising alternative. This study evaluated the impact of E4 on mitochondrial bioenergetics and neuronal morphology in human SH-SY5Y neuroblastoma cells, including models of AD-related amyloidopathy (amyloid precursor protein overexpression) and tauopathy (P301Ltau mutation overexpression). E4 significantly enhanced ATP levels, mitochondrial membrane potential, and oxidative respiration in all cell models, notably outperforming E2 in P301L cells. E4 also promoted significant neurite outgrowth, alleviating deficits observed in AD models. In addition, we demonstrated that the bioenergetic effects of E4 were mediated by the estrogen receptors ERα, ERβ, and GPER1. Furthermore, E4 modulated the expression of key mitochondrial genes, specifically upregulating the phosphate carrier SLC25A23 while downregulating the complex I subunit NDUFA1. In conclusion, E4 improves mitochondrial health and supports neuronal integrity via a multi-receptor mechanism, highlighting its potential as a safe neuroprotective therapy for AD. Full article

Globally, chronic kidney disease (CKD) affects over 800 million individuals and is characterized by significant genetic complexity. More than 600 genes are associated with hereditary kidney disease, which may manifest as isolated kidney issues or as part of a syndrome that also includes extrarenal manifestations. The aim of this study was to identify genetic variants in a group of ten patients who presented with clinical signs suggestive of genetic syndromes associated with CKD, or who were asymptomatic but had a positive family history of CKD. Extensive genetic testing (targeted gene panels and whole-exome sequencing—WES) identified a mutation in the PKD1 gene in 3 out of 10 cases. In one patient, a known mutation in the PKD2 gene was identified. Another four patients were diagnosed with Alport syndrome: three of these presented with de novo missense mutations in the COL4A5 gene, and one patient had a mutation in the COL4A3 gene. One patient was diagnosed with MODY5, caused by a known mutation in the HNF1B gene, and one patient was diagnosed with Bartter syndrome type 1, resulting from a known mutation in the SLC12A1 gene. We present genotype–phenotype correlations, highlighting the particularities of each patient within their family context. Our findings emphasize the importance of genotype–phenotype correlations in refining diagnosis, personalizing therapeutic management, and providing essential genetic counseling for at-risk relatives. Full article

Background/Objectives: Obesity and prediabetes are overlapping global epidemics. This systematic review synthesises evidence on gene-diet interactions in adults with obesity, prediabetes, or related cardiometabolic risks. It evaluates Mediterranean and DASH dietary patterns, macronutrient quality, and energy restriction across both single-variant and polygenic score approaches. Methods: PubMed was searched for English language papers published in the last 5 years (last run: 31 October 2025). Fewer than 200 studies were retained after excluding those lacking explicit statistical testing for gene-diet interactions or relevant endpoints. Results: Evidence supports restricting saturated fat and preserving carbohydrate quality as general baseline targets, with associations heterogeneous by genotype. Effect modification was observed: healthy dietary patterns were associated with lower risk in high polygenic-risk strata (OR~0.53) but little or no benefit in low-risk groups. TCF7L2 variants were associated with macronutrient thresholds (e.g., protein > 18%, carbohydrate < 48%) affecting visceral adiposity, while APOA2 variants showed genotype-dependent inflammation, including paradoxical increases in markers with higher dietary antioxidant capacity. Interpretation was limited by underpowered interaction tests, multiplicity, and uneven ancestry representation (e.g., unique SLC16A11 and CREBRF signals). Conclusions: While anti-inflammatory dietary substitutions improve biomarkers irrespective of some variants (e.g., TCF7L2), genotype-informed nutrition appears to yield the largest absolute risk reduction in high-risk populations. Clinical implementation should therefore combine baseline diet-quality guidance with targeted strategies for genotype-specific response patterns (e.g., APOA2 antioxidant heterogeneity and TCF7L2 carbohydrate thresholds), rather than rely on uniform recommendations alone. Future progress requires preregistered, genotype-stratified trials and locally trained polygenic scores to address ancestry-specific genetic architecture. Full article

Suicidal behavior is a multifactorial and highly heritable phenotype; however, data concerning its genetic determinants in disparate ethnic groups remain limited. Genes implicated in serotonergic neurotransmission and stress response regulation are regarded as primary candidates for elucidating biological vulnerability to suicide. The objective of this study is to investigate the relationship between suicide attempts and candidate gene polymorphisms in an ethnically homogeneous Kazakh population from Astana, Kazakhstan. The study’s sample population comprised 126 patients with a documented history of suicide attempts and 120 age- and gender-matched controls without a history of suicidal behavior. A comprehensive genotyping analysis was conducted, encompassing polymorphisms in genes associated with serotonergic signaling, stress response, and neuroplasticity (TPH1, TPH2, HTR2A, MAOA, SLC6A4, ANKK1, BDNF, COMT, CXCL8, SKA2, and FKBP5). The associations were assessed across several genetic models, using odds ratios with 95% confidence intervals. A substantial correlation was identified between the HTR2A rs6311 polymorphism and suicide attempts. The CC genotype exhibited a protective effect (p = 1.36 × 10⁻⁵), while the TT genotype was associated with an elevated risk (OR = 3.16; 95% CI: 1.72–5.81). The association remained robust after stratification by sex, with an even stronger effect observed in women (OR = 4.70; 95% CI: 2.08–10.64). A nominal sex-specific association was observed for the SKA2 rs7208505 variant, suggesting a potential role in stress-response mechanisms in women; however, this association was no longer statistically significant after adjustment for multiple comparisons. These results identify HTR2A rs6311 as a potential genetic marker of suicide risk in the Kazakh population and support the involvement of serotonergic receptor regulation in the biological mechanisms underlying suicidal behavior. The results underscore the significance of sex-specific genetic influences, thereby enhancing our understanding of the polygenic underpinnings of suicidality. Full article

Background: The Xinjiang Black pig is an excellent breed developed by the Xinjiang Production and Construction Corps in the 1990s; however, it has been endangered by the impact of commercial breeds. Methods: Whole genomes of 224 individuals from the Xinjiang Black pig conservation population were resequenced. Results: Genetic structure and diversity analyses revealed that Xinjiang Black pigs underwent severe inbreeding and were genetically closely linked to Landrace pigs. The genetic diversity of the F₂ generation was well preserved in the existing breeding scheme. A total of 686 significant selection regions and 406 candidate genes were identified using F_ST and θπ complementary methods, with Xinjiang Black pigs, Min pigs, and Laiwu pigs as ancestral populations, and F₂. Based on Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and quantitative trait loci annotations, potential germplasm candidate genes were identified. Among these, SOX5, HMG20A, and NEDD4 are associated with fat deposition; SPRY1, MNS1, DMXL2, and ALB are closely associated with male reproductive ability; ARPP19 and TLN2 are strongly associated with oestrous cycle regulation and oocyte maturation; and SLC4A4 and SLC12A1 are extremely important for osmotic regulation and foetal survival. Conclusions: These findings deepen our understanding of the genetic mechanisms of artificial selection in Xinjiang Black pigs and provide a theoretical basis for subsequent breeding and genetic research on this breed. Full article

Background/Objectives: Pediatric sleep-disordered breathing (SDB) is influenced by craniofacial morphology and host susceptibility. Evidence integrating cephalometric airway features with targeted genetic variation in symptomatic skeletal Class II children remains limited. We explored whether children with skeletal Class II mandibular retrognathia and SDB symptoms harbor selected genetic variants and whether carriers show distinct cephalometric airway characteristics. Methods: This cross-sectional study included 48 children with skeletal Class II malocclusion, mandibular retrognathia, and snoring/mouth-breathing symptoms. Craniofacial and airway parameters were assessed on lateral cephalograms. SDB burden was evaluated by a baseline home sleep study (respiratory event index, REI). Targeted sequencing screened TNFRSF1A, PSTPIP1, SLC6A4 (5HTT), ACE, APOE, IRS1, and additionally PHOX2B and PMP22. Exploratory group comparisons used Student’s t-test. Results: Variants were identified in 13/48 participants (27%) in TNFRSF1A, PSTPIP1, SLC6A4, ACE, APOE, and IRS1; none were detected in PHOX2B or PMP22. C3–H was higher in variant carriers (39.90 ± 6.40 vs. 36.48 ± 3.95 mm; p < 0.05). HH1 (perpendicular distance from the hyoid bone to the C3–RGN line) was higher but not significant (16.99 ± 7.58 vs. 14.61 ± 5.25 mm; p > 0.05). Conclusions: In this clinically screened pediatric skeletal Class II cohort with SDB symptoms, selected genetic variants co-occurred with specific hyoid–cervical cephalometric features. Given the cross-sectional design, absence of a control group, and small number of carriers, findings are exploratory and require replication in larger, controlled cohorts with standardized phenotyping. Full article

Aging is associated with complex physiological changes that influence drug pharmacokinetics, including alterations in mitochondrial function and gastrointestinal (GI) drug transporter activity. Mitochondrial dysfunction—characterized by reduced oxidative phosphorylation, mitochondrial DNA damage, and increased reactive oxygen species—is a hallmark of aging and may affect energy- and redox-dependent cellular processes in the gut. At the same time, aging can modulate the expression and function of key intestinal drug transporters from the ATP-binding cassette (ABC) and solute carrier (SLC) families, which play a central role in oral drug absorption and bioavailability. This review examines the molecular links between age-related mitochondrial dysfunction and regulation of GI drug transporters, with a focus on their pharmacokinetic consequences in older adults. We summarize evidence of mitochondrial decline in the aging intestine and discuss how mitochondrial signals—such as cellular energy status and oxidative stress—regulate transporter expression and activity via pathways including AMPK (AMP-Activated Protein Kinase), Sirtuin–FOXO (Forkhead box O transcription factors), Nrf2 (Nuclear factor erythroid 2-related factor 2), and NF-κB (Nuclear Factor kappa B). We highlight clinical examples of drugs showing age-related changes in bioavailability that may be attributable to transporter dysfunction. Finally, we discuss therapeutic implications for geriatric pharmacotherapy, including dose adjustment, management of transporter-mediated drug–drug interactions, and strategies aimed at preserving mitochondrial health. Full article

Nonsyndromic hearing loss (NSHL) is a highly prevalent, genetically heterogeneous condition, yet its molecular basis in the Singaporean population remains underexplored. We performed whole-exome sequencing and integrative bioinformatics analysis in 115 patients with NSHL to define population-specific genetic biomarkers. A molecular diagnosis was achieved in 57% of cases, with 76% of identified variants classified as pathogenic or likely pathogenic and 24% exhibiting high pathogenic potential. Common East Asian NSHL genes, including GJB2, SLC26A4, and OTOF, were frequently detected alongside less prevalent genes such as ACTG1, CEACAM16, COL11A2, DIAPH1, KCQN4, MYH14, MYO6, MYO7A, MYO15A, SLC17A8, SMPX, STRC, TJP2, TMC1, TMPRSS3, highlighting extensive genetic heterogeneity. Notably, multiple novel variants, including MYO6 c.554-2A>G, and TNC p.N750Y, were identified, expanding the known mutational spectrum of NSHL. Genotype–phenotype correlations revealed that GJB2 variants were primarily associated with mild to moderate hearing loss, whereas SLC26A4 variants correlated with severe to profound phenotypes in the Singaporean populations. Collectively, our study provides important insights into the genetic architecture of NSHL in Singapore’s population. In addition, it supports improved molecular diagnosis yield and informed clinical management decisions as well as the advancement of precision medicine approaches aimed at reducing the burden of hearing loss in the region. Full article

Iron overload, a key driver of ferroptosis, results from excessive iron accumulation in tissues and contributes to organ injury, including renal dysfunction. Increasing evidence indicates that ferroptosis plays an important role in the pathogenesis of kidney diseases. Natural antioxidants capable of regulating ferroptosis have therefore attracted growing attention. Quercetin (Que), a naturally occurring flavonoid, possesses well-documented antioxidant and anti-inflammatory properties and may provide protection against iron overload-induced renal injury. Present study aimed to clarify the molecular mechanisms underlying iron overload-induced nephrotoxicity and to evaluate the protective effects of Que through modulation of ferroptosis-related signaling pathways. Using in vivo and in vitro experimental approaches, we found that Que markedly reduced oxidative stress by regulating reactive oxygen species (ROS) levels, intracellular iron homeostasis, and the expression of ferroptosis-related proteins in renal tissues and HK-2 cells. The results demonstrate that iron overload induces renal injury primarily through activation of ferroptosis, characterized by iron-dependent lipid peroxidation and subsequent cellular damage. Importantly, Que significantly attenuated iron overload-induced renal injury by activating the NRF2/SLC7A11 (xCT)/GPX4 signaling pathway, thereby restoring antioxidant capacity and inhibiting ferroptotic cell death. In conclusion, Que protects against iron overload-induced renal injury by enhancing antioxidant defenses and maintaining iron homeostasis through inhibition of ferroptosis. These findings suggest that Que may represent a potential therapeutic strategy for kidney diseases associated with iron overload. Full article

Dendrobium officinale exhibits hepatoprotective potential against acetaminophen-induced liver injury (AILI). Fermentation has been proposed as a strategy to enhance the utilization and efficacy of herbal medicines. However, whether yeast fermentation improves the hepatoprotective effects of D. officinale remains unclear. This study investigated whether fermentation of D. officinale flower extract with Saccharomyces cerevisiae (1002S) enhances its protective effects against AILI, compared with a nonfermented extract (DOFE). Hepatoprotective efficacy was evaluated in male C57BL/6 mice, which received 1002S or DOFE (500 mg/kg, oral gavage) for 7 days before an acute acetaminophen challenge. Untargeted metabolomics and network pharmacology analyses were used to characterize fermentation-associated metabolic alterations and to explore potential pathways related to the observed effects. Metabolomic profiling revealed distinct metabolic differences between 1002S and DOFE. Network pharmacology analysis indicated predicted targets of fermentation-associated metabolites were associated with the phosphoinositide 3-kinase (PI3K)/ protein kinase B (Akt) and Janus kinase (JAK)/signal transducer and activator of transcription proteins (STAT) signaling pathways. In vivo, 1002S more effectively alleviated hepatocellular necrosis and significantly reduced serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels. Increased expression of nuclear factor erythroid 2-related factor 2 (Nrf2), superoxide dismutase 2 (SOD2), solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) was observed in liver tissues. Molecular docking suggested hemsleyanoside may contribute to these effects. Collectively, S. cerevisiae fermentation enhanced the antioxidant and hepatoprotective efficacy of D. officinale flower extract, supporting its potential development for AILI prevention. Full article

Background: Imaging-transcriptomic analysis, through the integration of multimodal magnetic resonance imaging (MRI) and transcriptomic data, provides complementary structural, functional, and molecular information that is crucial for the early detection and mechanistic exploration of Alzheimer’s disease (AD). However, effectively extracting features from heterogeneous multimodal data and capturing the associations between microscopic molecular variations and macroscopic brain alterations remain key challenges. Recent advances in deep learning and multimodal integration have enhanced the ability to model nonlinear cross-modal relationships, enabling more accurate identification of imaging-transcriptomic biomarkers and subtypes. Developing robust multimodal frameworks is therefore essential for early AD detection, subtype identification, and advancing precision medicine in neurodegenerative diseases. Methods: In this study, a two-stage method of multimodal Feature Extraction based on Association Analysis and Graph Convolutional Network with Self-Attention and Self-Expression framework (MFEAA-GCNSASE) for early diagnosis of AD and effective identification of subtypes of MCI with different progression to AD is proposed. In the first stage, the MFEAA model is applied to integrate multiple association analysis methods on sMRI, PET, and transcriptomic data to identify key multimodal biomarkers for AD and mild cognitive impairment (MCI). In the second stage, the GCNSASE model enhances classification accuracy between AD and MCI patients through self-attention and self-expression layers. Additionally, unsupervised clustering was performed on MCI samples using top multimodal biomarkers to explore subtype heterogeneity and conversion risk. Reliable MCI subtypes were also identified through a consensus clustering approach. Results: The proposed algorithm integrates sMRI, PET, and transcriptomic data, identifying robust biomarkers including the Left Hippocampus, Left Angular Gyrus, and key genes such as SLC25A5 and GABARAP. To ensure statistical robustness given the extreme class imbalance, we employed a rigorous repeated stratified cross-validation (RSCV) framework. GCNSASE achieved state-of-the-art discrimination performance with mean AUC values ranging from 0.946 to 0.961 across feature subsets (10–50%), significantly outperforming MOGONET (mean AUC: 0.844–0.875, p < 0.001) and conventional machine learning models with tighter 95% confidence intervals, indicating superior stability despite the limited AD sample size. Clustering analysis revealed two distinct MCI subtypes with divergent molecular landscapes: Subtype A was enriched in energy metabolism and cellular maintenance pathways, whereas Subtype B was enriched in neuroinflammatory and aberrant signaling pathways. Notably, the majority of MCI patients who subsequently converted to AD were concentrated in the immune-inflammatory Subtype B. These findings highlight that neuroinflammation coupled with bioenergetic failure constitutes a critical mechanism driving the conversion from MCI to AD. Conclusions: The proposed methods not only provide the key multimodal biomarkers and enhance the accuracy of the classification model for early AD diagnosis but also identify biologically and clinically meaningful MCI subtypes with distinct molecular signatures and conversion risks. Exploring these associated multimodal biomarkers and MCI subtypes is of great significance, as they help elucidate the heterogeneous mechanisms underlying AD onset and progression, enable the identification of high-risk individuals likely to convert to AD, and provide a foundation for targeted therapeutic strategies and individualized clinical management. These findings have important implications for understanding disease heterogeneity, discovering potential intervention targets, and advancing precision medicine in neurodegenerative diseases. Full article

Metabolic reprogramming constitutes a fundamental hallmark of malignancy, enabling cancer cells to sustain proliferation and survival under physiological stress. While aerobic glycolysis is well characterized, fatty acid oxidation (FAO) has emerged as a decisive driver of oncogenic progression and therapeutic resistance. Acylcarnitines (ACs), obligatory intermediates for the mitochondrial transport of long-chain fatty acids, have transcended their traditional categorization as passive metabolic byproducts to function as potent signaling entities and functional readouts of mitochondrial oxidative throughput. This review delineates the AC metabolic axis in oncology, examining the coordinated biochemical machinery, including the carnitine palmitoyltransferase (CPT) system, carnitine–acylcarnitine translocase (CACT; SLC25A20), and organic cation/carnitine transporter 2 (OCTN2), that governs cellular AC homeostasis. We further evaluate the clinical utility of altered AC profiles as non-invasive biomarkers for early diagnosis and risk stratification across diverse malignancies, highlighting their capacity to reflect metabolic bottlenecks and flux dynamics. Additionally, we scrutinize therapeutic strategies targeting the AC-FAO axis, demonstrating how the inhibition of key transporters and enzymes sensitizes tumors to conventional chemotherapy and immunotherapy. Ultimately, deciphering the systemic and spatial dynamics of ACs remains essential for advancing precision metabolic oncology and developing personalized therapeutic strategies based on metabolic profiling. Full article

Renal cell carcinoma (RCC) is a common and deadly urological cancer, for which there are no robust prognostic biomarkers or personalized treatment strategies. Paraptosis, a distinct form of regulated cell death marked by cytoplasmic vacuolization, is being increasingly recognized for its roles in tumorigenesis and therapy responses, yet its functional implications in RCC remain poorly defined. Transcriptomic profiles and corresponding clinical metadata from the TCGA-KIRC and GSE33371 datasets were systematically analyzed to characterize the paraptosis-related gene (PaRG) expression profile in renal cell carcinoma (RCC). Patients were categorized into two subtypes via consensus clustering, 574 overlapping differentially expressed genes (DEGs) were identified, and a four-gene (COL7A1, RNASE2, SLC10A2, and APOLD1) prognostic signature was constructed using LASSO and multivariate Cox regression. We analyzed the signature’s associations with tumor microenvironment (TME) features, cancer stem cell (CSC) indices, and tumor mutation burden (TMB), and validated the expression of the signature genes in RCC cell lines via qRT-PCR and Western blot. The four-gene signature showed robust prognostic performance (1-, 3-, and 5-year AUC: 0.751, 0.735, and 0.733 in the total cohort; 0.735, 0.731, and 0.767 in the training cohort), with high-risk patients having significantly poorer overall survival than the low-risk group. The low-risk group exhibited higher Stromal, Immune, and ESTIMATE scores (enriched immune/stromal infiltration), while the high-risk group had elevated CSC content and TMB, and the signature correlated with differential sensitivity to multiple chemotherapeutics. Both qRT-PCR and Western blot confirmed upregulation of COL7A1 and RNASE2 and downregulation of SLC10A2 and APOLD1 in RCC cell lines. Our study establishes a paraptosis-based two-subtype classification and four-gene prognostic signature for RCC that can reliably predicting patient survival, delineate TME characteristics, and guide personalized therapy, with COL7A1 emerging as a potential therapeutic target for advancing our understanding of paraptosis in RCC pathogenesis and optimizing treatment. Full article

Male infertility, a global health issue marked by spermatogenic failure, hinges on selenium (Se) as a key element for normal spermatogenesis. Among different Se species, Se-methylselenocysteine (MeSeCys) has been developed as a natural organic Se supplement with potent antioxidant and anti-inflammatory properties, but its direct effects on male reproduction need to be further explored. This study investigated the effect of MeSeCys on GC-1 spg (GC-1) and GC-2 spd (ts) (GC-2) cell lines, which mimic early stages. Treatment with 75 μmol/L MeSeCys for 24 h markedly enhanced the viability of both cell lines, with a more pronounced effect observed in GC-1 than in GC-2 cells. Moreover, this study demonstrated that MeSeCys enters cells through SLC7A11 or LRP8 channels and elevates intracellular Se levels in both GC-1 and GC-2 cells, with higher levels observed in GC-1 cells. RNA sequencing (RNA-seq) and bioinformatics analysis revealed that MeSeCys may regulate selenocompound metabolism and the glutathione metabolism pathway in both cell lines, increasing their intracellular glutathione (GSH) levels. Importantly, in GC-1 cells, MeSeCys specifically modulates the mTOR pathway, which further modulates glutathione metabolism and intracellular redox balance. This finding provides novel insights into the beneficial effects of MeSeCys on male reproductive cells, highlighting its potential as a nutritional supplement for male reproductive health. Full article

With the rapid development of genomic big data and genome-wide association study technologies, massive genomic data are available for the genetic dissection, development and utilization of important economic traits. Various GWAS algorithms have become increasingly efficient, enabling high-performance processing of these massive datasets. This has made it possible to conduct genetic dissection of economic traits based on big data and advanced statistical methods, which will provide accurate target loci for future trait improvement and genetic manipulation, greatly accelerating the process of genetic breeding. In this study, genotyping of 426 fish was performed using the T7 sequencing platform and 555,242 SNPs distributed across all the chromosomes were screened by data cleaning. We compared the performance of two GWAS methods, GCTA and GEMMA, in both single-trait and multi-trait frameworks. Twenty-nine SNPs significantly associated with seven traits were identified through single and multi-trait combined GWAS. Single-trait GWAS analysis using GCTA identified 1047 and 1452 significant loci for six growth traits and one sex trait (phenotypic sex, male or female) respectively, ultimately revealing 10 candidate genes, including slc48a1a, filip1L, nedd9, Crebbpa, LOC134024622, zbtb18, LOC117378376, LOC131530706, syde2, and col24a1. Similarly, 671 and 642 significant SNPs were detected with GEMMA for single-trait GWAS associated with six growth traits and the sex trait, respectively. In total, 16 candidate genes were mapped for these seven traits. Multi-trait GWAS was also performed using GEMMA for the six growth traits (sex was included as a covariate). The traits were grouped into five combinations based on their genetic correlations. A total of 37 SNPs were identified, corresponding to 10 candidate genes: LOC131530706, LOC134022516, abat, maml3, cica, LOC124013321, slc25a12, dnah10, syt9a, and LOC136932979. Notably, five overlapping candidate genes (LOC131530706, LOC134022516, abat, slc25a12 and dnah10) were also identified in both single- and multi-trait GWAS methods of GEMMA, highlighting their genetic stability and significance. The two GWAS methods, GCTA and GEMMA, identified two genes that were the same. The results of this study provide molecular markers and genetic resources for the improvement of growth traits in Plecoglossus altivelis. Full article