Search Results (8,912)

Background/Objectives: Intestinal dysbiosis is a pivotal trigger of type 2 diabetes mellitus (T2DM). Our previous studies confirmed that composite probiotics derived from fermented camel milk (CPCM), containing Lactobacillus harbinensis and 13 other strains, can ameliorate glucose and lipid metabolism in T2DM mice by reshaping bile acid profiles, and its effect may be associated with the PPARγ-LXRα-NPC1L1 signaling pathway. Methods: Metagenomic analysis characterized alterations in intestinal microbiota structure and functional genes post-CPCM intervention, proteomic analysis detected changes in protein expression profiles related to glucose and lipid metabolism in mice, and Caco-2 cells were used for in vitro validation to clarify the regulatory effect of exopolysaccharides (EPS) (the active component of CPCM) on the PPARγ-LXRα-NPC1L1 signaling pathway. Results: The results showed that CPCM significantly improved glucose and lipid metabolism and remodeled the intestinal flora structure in mice, markedly enriching beneficial bacteria such as Lactobacillus and Akkermansia and enhancing the expression of functional genes related to the peroxisome proliferator-activated receptor (PPAR) signaling pathway and short-chain fatty acid synthesis in the microbiota. Proteomic analysis revealed that CPCM reversed the expression of key proteins involved in fatty acid oxidation and transport, thereby restoring the function of the PPAR signaling pathway. In vitro experiments validated that extracellular polysaccharides, the active component of CPCM, significantly upregulated the expression of PPARγ and liver X receptor α (LXRα) and inhibited the expression of Niemann–Pick C1-Like 1 (NPC1L1), a cholesterol absorption transporter, in Caco-2 cells. Conclusions: In conclusion, CPCM ameliorates glucose and lipid metabolic disorders in T2DM through multiple mechanisms: reshaping the intestinal probiotic community, enhancing its beneficial metabolic functions, restoring the activity of the PPARγ-LXRα signaling pathway, and subsequently downregulating NPC1L1. Full article

Recognition and binding to β-galactose-containing carbohydrates and lipids are crucial for several fundamental biological processes that are mediated primarily by a family of proteins known as galectins (S-type lectins). Galectins in the human placenta regulate critical processes such as maternal–fetal immune tolerance, trophoblast invasion, vascular remodeling and angiogenesis, ensuring proper fetal development and preventing pregnancy complications such as preeclampsia and miscarriage. Gestational diabetes mellitus (GDM) is a widespread complication of pregnancy, affecting approximately 1 in 7 pregnancies, and its incidence is increasing globally, indicating a particularly strong association with the obesity pandemic. Profiles of placental expression and distribution of individual galectins significantly change during the course of GDM. This is accompanied by placental dysfunction, which is especially severe with poor glycemic control. The aim of this review is to present the current state of knowledge on the involvement of abnormal galectin signaling in the pathomechanisms of GDM-associated placental dysfunction. Further research is needed to determine whether changes in placental galectins occur secondary to metabolic abnormalities in GDM or are involved as a primary cause. Galectins present in placental tissue and serum should be validated as potential biomarkers of GDM. Full article

Gibberellins (GAs) play a crucial regulatory role in the growth and development of cotton (Gossypium hirsutum L.). Through bioinformatics analyses, we identified a total of 39 GA2ox genes (encoding gibberellin 2-oxidases) in the cotton genome, designated GhGA2ox1 to GhGA2ox39. Based on phylogenetic analysis, these genes were classified into five groups. We further examined their gene structures, conserved motifs, and chromosomal distributions, revealing that members within the same group shared similar structural and motif organizations. Collinearity and cis-element analyses provided important insights into the evolutionary history and regulatory potential of the GA2ox gene family in cotton. Notably, using nucleotide diversity (π) and population differentiation (F_ST) analyses across the entire family, we screened and identified nine candidate genes that underwent strong artificial selection during cotton domestication and improvement. Further haplotype-phenotype association analysis identified GH_D09G0919 (GhGA2ox31) as a key regulator of Plant Height (PH). To validate their regulatory roles, we analyzed the genotype distribution in accessions with extreme phenotypes. The results revealed divergent selection histories for these two loci: the favorable allele of GH_D01G0720 (GhGA2ox23) was already fixed in the tested population, whereas GH_D09G0919 maintained significant natural variation. Specifically, the Hap2 allele of GH_D09G0919 was significantly enriched in the shortest accessions compared to the tallest ones. Importantly, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed that the Hap2 allele drives significantly higher gene expression in leaves, suggesting that enhanced GA catabolism underlies the compact phenotype. Additionally, transcriptomic profiling revealed the tissue-specific expression patterns of candidate genes, implying their functional roles in development. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene (AtGA2ox8) confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. These results uncover valuable genetic resources for molecular breeding to shape compact cotton architecture. Collectively, this study aims to analyze the evolutionary patterns of the cotton GA2ox gene family and to identify key genes that regulate plant height under artificial selection, providing theoretical support for molecular breeding of compact plant types. Full article

Loss of ovarian hormones following menopause or ovariectomy is associated with increased anxiety, cognitive impairment, and dysregulation of hypothalamic neuroendocrine pathways. MicroRNAs (miRNAs) and tRNA-derived fragments (tRFs) are emerging classes of small non-coding RNAs that act as post-transcriptional regulators of stress, inflammation, and synaptic function; however, their coordinated involvement in estradiol-mediated hypothalamic regulation remains poorly understood. In this study, adult female mice were assigned to control, estradiol-treated, ovariectomized (OVX), or OVX plus estradiol groups. Anxiety- and cognition-related behaviors were assessed using the open field, Y-maze, and elevated plus maze tests. Circulating estradiol levels and hypothalamic gonadotropin-releasing hormone (GnRH) expression were quantified by ELISA. Hypothalamic mRNA, miRNA, and tRF expression profiles were analyzed by RNA sequencing, followed by differential expression analysis, functional enrichment, integrative network construction, and quantitative real-time PCR validation. Ovariectomy induced anxiety-like behaviors, impaired working memory, reduced estradiol levels, and increased hypothalamic GnRH expression, all of which were reversed by estradiol treatment. Transcriptomic analysis identified 376 differentially expressed miRNAs, 182 differentially expressed tRFs, and 439 differentially expressed mRNAs, enriched in pathways related to stress responses, neuroendocrine regulation, synaptic signaling, metabolic homeostasis, and neuroinflammation. Integrated miRNA–mRNA and tRF–mRNA network analyses revealed several estradiol-responsive miRNAs (including miR-200a-5p, miR-182/183-5p, miR-381-3p, miR-148a-3p, and miR-10 family members) predicting key hub genes such as Gcg, Wnt4, Prkacb, Sgk1, Fpr2, and Aldoa, and key tRFs like tRFdb-1003, tRFdb-1013, tRFdb-1026, tRFdb-3001a and tRFdb-5020a, targeting hub genes such as Wnt4, Prkacb, Sh3rf2, Hpse, Cxcr2 and Zbtb16 respectively. Collectively, these findings demonstrate that estradiol ameliorates OVX-induced behavioral and endocrine dysfunction by reorganizing hypothalamic miRNA- and tRF-mediated regulatory networks involved in stress adaptation, synaptic homeostasis, and neuroimmune signaling. Full article

Background: Oils from medicinal plants, including thyme (Thymus vulgaris), cinnamon (Cinnamomum verum), and black seed (Nigella sativa), are recognized for their antibacterial and antioxidant properties. While several studies have investigated individual oils and binary combinations, fewer reports have examined ternary mixtures using systematic optimization approaches. Accordingly, the present study aimed to optimize the antibacterial and antioxidant performance of combinations of these three plant-derived oils using a statistical mixture design strategy supported by in silico exploration. Methods: An Augmented Simplex Centroid Mixture Design was applied to evaluate the individual and combined effects of thyme, cinnamon, and black seed oils. Antibacterial activity was assessed by determining the minimum inhibitory concentrations (MICs) against Escherichia coli and Staphylococcus aureus, while antioxidant activity was measured using the DPPH radical scavenging assay (IC₅₀). The experimental data were fitted to a special cubic model, and model validity was verified through ANOVA parameters, including F-values, R², and adjusted R². Multi-response optimization was performed using a desirability function. Potential interactions among oils were further examined using checkerboard assays. Molecular docking and ADMET predictions were conducted as supportive, hypothesis-generating tools. Results: The special cubic model was statistically significant for all responses (p < 0.0001), with R² values of 0.9763, 0.9944, and 0.9841 for MIC_{E. coli}, MIC_{S. aureus}, and DPPH IC₅₀, respectively. Response surface analysis and multi-response optimization identified the optimal oil mixture as thyme (41.7%), cinnamon (41.7%), and black seed (16.7%), achieving MIC values of 0.5 µL/mL for E. coli and 0.517 µL/mL for S. aureus, and a DPPH IC₅₀ of 5.32 ± 0.52 mg/mL. Checkerboard assays confirmed synergistic interactions for the optimized formulation, with ΣFIC values of 0.15 and 0.29 against E. coli and S. aureus, respectively. Cytotoxicity testing of the optimized formulation on WI-38 normal fibroblasts indicated high cell viability (>92%) at all tested concentrations. In silico docking showed favorable binding affinities of major oil constituents with bacterial targets, and ADMET analysis suggested acceptable pharmacokinetic and safety profiles. Conclusions: The study demonstrated that specific combinations of thyme, cinnamon, and black seed oils can synergistically enhance antibacterial and antioxidant activities. The optimized formulation exhibited enhanced antibacterial and antioxidant activities with minimal cytotoxicity, while in silico analyses provided supportive mechanistic insights. Full article

Background/Objectives: Head and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study, we developed the GARD pipeline (Genomic Alteration-based Repurposing for Drugs), designed to uncover repurposing candidates for HNC using genomic and network-based approaches. Methods: GARD integrates multi-omics data from The Cancer Genome Atlas (TCGA), including copy number variation (CNV) and somatic mutations (SOM). The cohort was stratified by human papillomavirus (HPV) status. Risk-associated genes were identified and then expanded via high-confidence protein–protein interaction (PPI) networks. Top candidate genes were filtered through comprehensive analysis of publicly available literature data in PubMed using LLMs to validate the relationship between the identified genes and HNC. The top risk genes and their network-expanded neighbors were mapped against DrugBank, and through statistical significance testing and literature validation, established significant drug–gene associations. Results: Significant genes associated with HNC, inferred by genomics alteration, were identified across HPV-positive and HPV-negative subgroups, such as PIK3CA, SOX2, TP53, EIF4G1, TLR7, CLDN1, PRKCI, and EPHA2. Further expansion through the PPI network identified other targetable genes such as EGFR, ERBB2, and the FGFRs. Literature-based validation efforts ensured confidence in the gene–disease association. Drug–gene mapping revealed candidates spanning those already in clinical trials for HNC (e.g., Afatinib, Cabozantinib, Dasatinib, Brigatinib, Lenvatinib, Capivasertib, and Erdafitinib) and emerging or repurposing candidates (Amuvatinib, XL765 (Voxtalisib), Golotimod, Artenimol, Quercetin, and Acetylsalicylic Acid), offering opportunities for precision repurposing. Conclusions: The GARD pipeline demonstrates a genomics-driven, network-informed framework for systematic drug repurposing in HNC. HPV stratification enhances precision, literature-based validation strengthens confidence, and integrated drug mapping enables refinement of existing therapies and discovery of novel candidates for personalized treatment strategies. Code Availability: The full implementation of the GARD pipeline, including preprocessing scripts, statistical analysis modules, and visualization tools, is publicly available on GitHub. Full article

Glycemic assessment in patients with chronic kidney disease (CKD) Stage V on hemodialysis (HD) is limited by the inaccuracy of hemoglobin A1c (HbA1c), mainly due to anemia, shortened erythrocyte lifespan, and erythropoiesis-stimulating agent (ESA) therapy. Glycated albumin (GA), independent of erythrocyte turnover, may better reflect glycemic exposure. We evaluated the diagnostic performance and clinical utility of GA as a biomarker of poor glycemic control and cardiovascular risk in patients with diabetes mellitus (DM). A cross-sectional analysis and five-year prospective follow-up were conducted in three subgroups: HD+DM+ (n = 40), HD- DM+ (n = 15), and HD+DM– (n = 22). Glycemic markers (mean plasma glucose over 3 months (PG₃m), GA, and HbA1c) were compared between groups. GA levels were significantly higher in HD+DM+ patients (p < 0.001) and showed the strongest correlation with PG₃m. GA independently predicted poor glycemic control (OR 3.23; 95% CI 1.54–6.77; p = 0.002) and demonstrated high diagnostic accuracy (AUC 0.873; optimal cut-off 10%). During the five-year follow-up, CV mortality was 35%, and 85% of deceased patients had GA > 10%. Although Cox regression did not reach statistical significance, GA showed a consistent trend toward higher CV mortality risk after adjustment for age and HD duration (HR 2.56; 95% CI 0.57–11.44; p = 0.21), whereas HbA1c was not prognostic (HR 1.39; 95% CI 0.49–3.91; p = 0.28). GA appears to be a clinically useful marker of glycemic control in diabetic patients with CKD Stage V receiving maintenance hemodialysis. In this cohort, GA showed high diagnostic accuracy and a more balanced sensitivity/specificity profile compared with HbA1c, with a consistent trend toward association with cardiovascular mortality. In this regard, the wider use of this marker in clinical practice is worth considering. Nevertheless, larger prospective studies are warranted to validate these observations. Full article

Background: Healthcare professionals experience continuous biological and psychosocial stressors that may disturb oral and systemic homeostasis. Alterations in salivary secretion, mucosal immunity, and microbiome composition reflect adaptive cellular responses to chronic occupational stress. Understanding these mechanisms may provide a biological framework for resilience and wellbeing in everyday clinical practice. Objective: To narratively review the evidence linking oral cellular and molecular mechanisms—salivary biomarkers, epithelial and immune cell activity, and microbiome dynamics—with stress, fatigue, burnout, and wellbeing outcomes among healthcare professionals. Methods: This narrative review employed a PRISMA-guided literature search of PubMed, Scopus, Web of Science, and Cochrane Oral Health to enhance transparency and coverage across databases. Given the heterogeneity of study designs and outcomes, data were synthesized thematically without quantitative pooling or formal meta-analysis. Methodological strength was evaluated qualitatively, focusing on biomarker validity, sampling conditions, and conceptual relevance. Eligible designs included observational, experimental, and interventional studies. Results: Evidence from 99 studies suggests that chronic occupational stress elevates salivary cortisol, oxidative stress markers, and pro-inflammatory cytokines (IL-6, TNF-α), while reducing protective salivary immunoglobulin A and microbiome diversity. Balanced oral immune and microbial profiles were associated with better psychological adaptation and lower fatigue indices. Conclusions: Oral cellular homeostasis offers a promising window into the biological underpinnings of occupational stress and resilience in healthcare professionals. Systematic integration of salivary and mucosal biomarkers into workplace wellbeing programs could enhance early detection of dysregulated stress physiology. Future interdisciplinary research should bridge oral biology, occupational medicine, and mental health to strengthen sustainable wellbeing strategies across the health workforce. Full article

Rhodiola species are traditionally used to mitigate hypoxia-related symptoms, but comparative evidence on their chemical bases and active constituents is limited. We implemented an integrated “qualitative analysis–pharmacological exploration–correlation analysis–molecular validation” workflow to compare Rhodiola crenulata, R. kirilowii, and R. rosea. Ultra-high-performance liquid chromatography–Q Exactive mass spectrometry (UPLC-QE-MS) profiling identified 175 metabolites across the three species, of which 161 were shared; multivariate analyses (principal component analysis, PCA; partial least squares–discriminant analysis, PLS-DA) revealed 30 differential compounds. In a normobaric hypoxia mouse model using herbal powder solutions, all three species significantly increased survival time versus control (p < 0.05), with mean survival times of 48.16 min (RR), 47.07 min (RC), and 44.82 min (RK) compared with 44.34 min for the positive control. Chemometric correlation (partial least squares regression, PLSR) combined with grey relational analysis (GRA) prioritized 14 compounds consistently associated with anti-hypoxia efficacy; six representative metabolites—epicatechin, 3-O-galloylquinic acid, salidroside, p-coumaric acid-4-O-glucoside, citric acid, and geraniol—were selected for in silico assessment. Molecular docking against hypoxia-inducible factor-1α (HIF-1α) yielded favorable binding poses (docking scores < −4.0), providing preliminary molecular-level plausibility without claiming mechanistic proof. This multi-level approach clarifies chemical–pharmacological relationships among Rhodiola species and provides prioritized candidate compounds for targeted isolation and mechanistic validation. Full article

Powder-bed arc additive manufacturing (PBAAM) may reduce the cost of powder-bed metal additive manufacturing and enable thicker layers than laser powder bed fusion (LPBF), but melt-track stability limits are not well established. Here, 316L stainless steel powder (15–53 µm) was melted by a TIG-based arc in a custom powder-bed system while varying current, travel speed, layer thickness and hatch distance. Single tracks on an inclined bed (≈0–0.4 mm thickness) were used to identify continuity loss and melt-pool width, quantified from top-view images via width profiles, a gap-based continuity metric and the coefficient of variation. Parallel-track tests at 0.15, 0.20 and 0.25 mm layer thickness with hatch distances set to 25%, 50% and 75% of the measured melt-pool width assessed inter-track bonding and lack of fusion, and selected parameters were validated in five-layer builds. Higher current with low-to-moderate travel speeds produced wider, more stable melt pools on the inclined bed. Hatch ratios of 25–50% were the most effective for sustaining fusion in single layers and multi-layer builds, whereas 75% promoted unbonded regions and narrow-track morphologies. Overall, PBAAM can process substantially thicker layers with relatively simple equipment, but requires a narrow, carefully tuned window to balance continuity, fusion and heat accumulation. Full article

Background: Building on our previous systematic review that synthesized eight core sustainable appetitive traits central to food behavior research, the present study extends this framework through an empirical investigation of Generation Z university students in Greece. We have established the conceptual foundation by mapping emotional, sensory, and behavioral regulation drivers of eating behavior, underscoring their relevance for nutrition and sustainability. However, empirical applications of this multidimensional framework to Generation Z remained scarce. Objectives: This study addresses this gap by examining eating behaviors among approximately 800 students at the University of Ioannina using a validated post-pandemic questionnaire. Methods & Results: Results revealed heterogeneity across six domains, with consensus observed only in sensory-driven eating (M = 3.88) and openness to new foods (M = 4.00). Cluster analysis identified two distinct profiles: Exploratory and Hedonic Responders and Emotionally Regulated and Satiety-Oriented Responders. These clusters delineate a novel profile of Generation Z, portraying them as digitally immersed, sustainability-oriented, and emotionally sensitive, yet divided between impulsive exploration and regulated satiety. Conclusions: The study contributes new empirical insights into post-pandemic food behavior. It establishes a comprehensive evidence base for designing culturally sensitive wellness programs and targeted nutritional interventions that support sustainable dietary practices. The continuity between the two papers underscores both theoretical importance and the practical necessity of integrating emotional, sensory, and regulatory dimensions in advancing sustainable eating futures among young adults. Full article

Background: Early diagnosis of familial hypercholesterolemia (FH) is crucial to improve long-term outcomes. FH diagnosis relies on elevated low-density lipoprotein cholesterol (LDL-C) levels, familial clinical characteristics, and identification of pathogenic variants in FH-related genes. Secondary factors, such as overweight and obesity, are known to influence lipid profiles in the general population. More recently, polygenic risk scores based on single-nucleotide polymorphisms (SNPs) have been proposed as additional determinants of LDL-C levels. Methods: We enrolled 214 pediatric subjects with LDL-C levels ≥95th percentile (after 6 months of dietary intervention) and with at least one parent with LDL-C levels ≥ 95th percentile. All participants underwent biochemical and auxological assessment and genetic testing for FH. In a subgroup of 60 subjects, LDL-C polygenic scores based on 6- and 12-SNPs were calculated. Results: Pathogenic variants confirming heterozygous FH were identified in 190 subjects (variant-positive, V+); 17 were variant-negative (V−), yielding a mutation detection rate of 91.8%. An additional seven patients carrying variants of uncertain significance were excluded from the primary analysis. LDL-C was modestly higher in V+ than V− subjects using both Friedewald (212 vs. 188 mg/dL; p = 0.035) and Martin–Hopkins formulas (208 vs. 187 mg/dL; p = 0.041), while the other main clinical and laboratory parameters were similar. In V+, LDL-C was higher in subjects with null variants, compared to those with defective variants. Body mass index (BMI SDS) was inversely correlated with HDL-C (p < 0.001), and obesity (BMI z-score > 2 SDS) was associated with lower HDL-C and higher LDL-C, non-HDL-C, and ApoB. With regard to the polygenic scores, 12- and 6-SNP scores showed overlap between V+ and V−, and published cut-offs did not discriminate lipid severity in our population; however, in V+ subjects, the 12-SNP score acted as a phenotype modifier, being independently associated with higher LDL-C and non-HDL-C levels after adjustment for age, sex, and BMI SDS. Conclusions: In children selected by LDL-C ≥ 95th percentile, together with autosomal dominant familial hypercholesterolemia, genetic confirmation of FH is achieved in the vast majority of cases. Variant type (null vs. defective), BMI, and polygenic background contribute to phenotypic heterogeneity, supporting the need to address other factors alongside genetic diagnosis. Further validation is needed before polygenic scores can be implemented in routine clinical practice. Full article

The human ALKBH gene family comprises nine Fe²⁺/α-ketoglutarate-dependent dioxygenases that catalyze the oxidative demethylation of DNA, RNA, and proteins, thereby influencing key cellular processes. Consequently, dysregulation of these enzymes has been implicated in various human diseases, particularly cancer. Although the transcriptomic profiles of certain members (e.g., ALKBH8, FTO) have been characterized, a comprehensive analysis of the entire ALKBH family remains unclear. In the present study, we investigated the alternative splice variants of the ALKBH genes through direct RNA sequencing across cancerous and non-cancerous cell lines. Novel splicing events were validated by NGS, while RT-qPCR was employed to assess transcript abundance and expression patterns. Additionally, in silico analysis was performed to predict the coding potential of the detected transcripts. Results: Bioinformatics analysis revealed previously uncharacterized alternative transcripts for the human ALKBH gene family members. Expression profiling demonstrated distinct expression patterns between cancerous and non-malignant cells, suggesting a potential role of these demethylases in tumor biology. The investigation of their coding capacity revealed that most of the newly detected transcripts were predicted to encode protein isoforms, highlighting the structural and predicted coding potential of the ALKBH family. Conclusions: Our findings provide the first comprehensive overview of the transcriptional diversity within the human ALKBH gene family. These results enhance our understanding of the demethylation mechanisms and their dysregulation in cancer. Full article

Injectable skin boosters currently in use mainly provide short-lived volumization or depend on inflammation-mediated collagen stimulation, raising concerns regarding durability and safety. Injectable particulate human acellular dermal matrix (phADM) is a biologically derived extracellular matrix scaffold designed to support constructive dermis remodeling. This randomized, split-face, double-blinded clinical trial evaluated the efficacy of phADM as a facial skin booster in 20 adults with moderate cheek roughness. phADM was injected on one facial side, with hyaluronic acid serving as the contralateral control. Multiple skin parameters were assessed over 20 weeks using validated imaging and biophysical instruments. Mechanistic validation was conducted using complementary in vitro, ex vivo human skin, and in vivo rat models. Clinically, the phADM-treated side demonstrated greater improvements in skin density, volume, elasticity, wrinkle depth, pore area, hydration, and barrier-related parameters at multiple time points compared with HA. In ex vivo human skin, phADM showed homogeneous dermal distribution and preservation of extracellular matrix architecture, along with restoration of basement membrane-associated proteins following UVB irradiation. In vivo rat studies revealed fibroblast infiltration and localized neocollagenesis within the implanted matrix. In vitro assays further indicated enhanced fibroblast proliferation and extracellular matrix synthesis, increased hyaluronan production, suppression of pro-inflammatory cytokines in activated macrophages, and downregulation of melanogenesis-related genes in melanoma cells. No serious adverse events were observed during the clinical study. These findings indicate that phADM functions as a restorative skin booster that promotes durable dermis remodeling and functional rejuvenation with a favorable safety profile. Full article

Soymilk solid content (%) is a critical quality indicator that is directly related to product classification and regulatory compliance in food manufacturing. However, conventional optical refractometer-based measurements often suffer from blurred scale boundaries and subjective reading errors, leading to poor reproducibility under varying illumination conditions. This study proposes an image-based signal analysis framework that quantitatively interprets blurred liquid-scale boundaries by analyzing pixel intensity profiles, their gradients, and effective boundary widths. Instead of relying on human visual judgment, the proposed method characterizes boundary uncertainty using Gaussian-smoothed intensity signals and derivative-based feature extraction. Quantitative validation against ground-truth concentration values over 150 images demonstrates an overall mean absolute error (MAE) of 1.90 and a root mean squared error (RMSE) of 3.85. Illumination conditions yielding stable, single-peak derivative responses achieve an overall MAE of 0.23, whereas severe illumination conditions associated with unstable or distorted derivative patterns result in substantially higher errors (MAE = 8.57, RMSE = 8.60). These results quantitatively confirm that derivative-based boundary signal stability is directly linked to measurement accuracy. By transforming visual ambiguity into quantifiable signal features, this work provides a practical and reproducible alternative to subjective refractometer readings and offers a foundation for reliability-aware optical concentration measurement systems in industrial environments. Full article