Search Results (538)

Limulus amebocyte lysate (LAL) detects bacterial endotoxin through a serine-protease coagulation cascade in which Factor C responds to lipopolysaccharide and Factor G to (1,3)-β-D-glucan. Sustainable LAL production depends on collection buffers that prevent amebocyte degranulation while preserving these clotting factors. We previously showed that caffeine buffer inhibits degranulation, but caffeine-collected pellets aggregated upon resuspension in 5 mM CaCl₂, unlike phosphate-buffered saline (PBS). We therefore developed a PBS-caffeine collection solution and compared it with caffeine buffer. Over one bleeding season, 121 crabs were bled; blood was collected in caffeine, PBS-caffeine, or PBS-caffeine supplemented with EDTA, EGTA, or both, and LAL activity was measured by chromogenic and turbidimetric assays. Both buffers prevented degranulation and gave comparable LAL activity, but PBS-caffeine reduced aggregation and clotting. Treating PBS-caffeine LAL with 10% PEG-8000 selectively abolished endotoxin-sensitive Factor C activity while preserving (1,3)-β-D-glucan–sensitive Factor G activity, and the resulting Factor G lysate, formulated in 20 mM acetate (pH 5.6), remained stable for 27 months. These results define an improved collection buffer and identify conditions that selectively stabilize Factor G zymogen in liquid form. Full article

Plant cytochrome P450 monooxygenases (CYPs) are valuable biocatalysts for the regioselective hydroxylation of aromatic compounds. However, their expression in bacterial hosts is hampered by poor solubility, membrane anchoring and the requirement for redox partners. In this work, we report the design and characterization of modular expression systems that enable the functional production of SbCYP82D1.1 from Scutellaria baicalensis (SbF6H) in Escherichia coli. Both independent expression and synthetic fusion systems were evaluated by combining a CYP with a compatible reductase (ATR2_tr from Arabidopsis thaliana) to catalyze the conversion of chrysin into baicalein. A combinatorial library of N-terminal variants, host strains, media, and induction strategies was constructed and screened. Among the tested host, E. coli DH 10-beta provided the highest product titers, particularly when cultures were supplemented with 5-aminolevulinic acid. Truncation of the native transmembrane anchor significantly improved catalytic performance, whereas the addition of the heterologous MALLLAVF tag decreased activity. Fusion systems outperformed separate expression formats, showing approximately two-fold higher activity, with the flexible glycine–serine linker (L_GS) supporting the highest hydroxylation product formation. The corresponding fusion construct showed an apparent conversion of 0.1 mM chrysin to baicalein of up to 90% under the applied whole-cell reaction and analytical conditions, although this value should be interpreted with caution due to the concurrent instability of baicalein observed in all reactions and culture conditions. This result nevertheless indicates a marked improvement in whole-cell baicalein formation compared with previously reported bacterial systems. Together, these results demonstrate that rational N-terminal engineering combined with fusion protein design can enable efficient bacterial expression of plant CYPs, representing a promising step toward scalable production of hydroxylated flavonoids. Full article

LRRK1 is essential for osteoclast-mediated bone resorption, and loss of LRRK1 function causes osteopetrosis in mice and humans. However, the mechanisms by which LRRK1 regulates osteoclast activity remain incompletely defined. We previously identified that phosphorylation of OSTM1 at threonine 328 and serine 329 was compromised in LRRK1-deficient osteoclasts. To test the role for OSTM1 phosphorylation in LRRK1 regulation of osteoclast functions, we expressed a phosphomimetic OSTM1 variant in LRRK1-null osteoclasts. Overexpression of phosphomimetic, but not a dephosphomimetic variant, partially restored resorptive activity in LRRK1-deficient osteoclasts in vitro. To test OSTM1’s role in rescuing defective bone resorption in Lrrk1-null mice, we generated Ostm1-T328E/S329D knock-in (KI) mice and crossed them onto the Lrrk1-deficient background. Ostm1-T328E/S329D KI mice displayed normal skeletal development and bone remodeling. When crossed to the Lrrk1-deficient background, OSTM1-T328E/S329D expression increased osteoclast resorptive activity and bone formation and partially improved trabecular architecture, although bone volume remained unchanged. These findings demonstrate that OSTM1 phosphorylation contributes to LRRK1-dependent regulation of osteoclast function and identify the LRRK1–OSTM1 pathway as a mechanistic node controlling bone resorption. Our work provides new insight into the molecular basis of LRRK1-mediated osteoclast function and highlights OSTM1 phosphorylation as a potential therapeutic target for metabolic bone diseases. Full article

For the first time in this study, the ability for methylotrophic growth on methanol was demonstrated in representatives of the genus Sphaerotilus. The analysis of 20 genomes and the physiological verification of genomic predictions regarding C1 compound metabolism were carried out using Sphaerotilus montanus HS^T, Sphaerotilus hippei DSM 566^T, and Sphaerotilus sulfidivorans D-501^T as model strains. Genes involved in the direct oxidation of methanol to carbon dioxide were identified, including the lanthanide-dependent methanol dehydrogenase XoxF, the NAD-dependent methanol dehydrogenase Mdh2, genes of the tetrahydromethanopterin (H₄MPT) and tetrahydrofolate (H₄F) pathways, and the NAD-dependent formate dehydrogenase. In addition, a number of genes associated with C1 assimilation were identified, including genes of the Calvin–Benson–Bassham cycle and the incomplete serine cycle. Experimental data suggest that the bacteria are capable of using two strategies of methylotrophic growth: methanol oxidation via the lanthanide-dependent methanol dehydrogenase XoxF and the H₄MPT pathway, as well as oxidation via the NAD-dependent methanol dehydrogenase Mdh2 and the H₄F pathway. Both strategies provide CO₂ assimilation via the Calvin–Benson–Bassham, but additionally the second strategy demonstrates additional involvement of the incomplete serine cycle in the process of the C1 compounds. A hypothetical model of C1 compound assimilation in representatives of the genus Sphaerotilus was constructed. Full article

Diabetic neuropathy (DN) is a multifactorial complication of diabetes mellitus driven by chronic hyperglycemia, insulin resistance, and disturbed metabolic homeostasis, leading to progressive injury of both the peripheral and central nervous systems. This study investigated whether L-serine supplementation could attenuate DN through dose-dependent metabolic and neuroprotective mechanisms in a high-fat diet (HFD) plus streptozotocin (STZ)-induced diabetic rat model. Male Wistar rats (n = 8 per group) were allocated to five groups: normal control (NC), diabetic control (DC), pioglitazone (PIO; 1.5 mg/kg/day), low-dose L-serine (S1; 200 mg/kg/day), and high-dose L-serine (S2; 400 mg/kg/day). After 60 days of oral gavage, behavioural testing, glucose and insulin profiling, HOMA-IR calculation, brain histopathology, nerve growth factor (NGF) immunohistochemistry, and LC–MS/MS-based proteomic analysis of cerebral tissue were performed. Diabetic rats exhibited marked hyperglycaemia (355.33 ± 4.72 mg/dL), hyperinsulinaemia, severe insulin resistance (HOMA-IR 16.8 ± 3.2; a 14-fold increase), impaired thermal nociception, motor dysfunction, and pronounced neuronal degeneration. L-serine supplementation significantly improved metabolic status: S1 reduced HOMA-IR by 77.4% and S2 by 87.5% relative to diabetic controls (p < 0.001). High-dose L-serine produced greater improvements in thermal sensitivity, motor coordination (rotarod latency 26.67 ± 1.52 s vs. 16.1 ± 0.85 s in DC; p < 0.05), and NGF expression (8.6-fold increase vs. DC). Histopathology confirmed attenuation of neuronal injury and gliosis in both treatment groups. Exploratory, group-level proteomic profiling identified dose-specific molecular signatures: S1 was predominantly associated with carbohydrate, lipid, and biosynthetic pathways, whereas S2 was associated with synaptic, neurotransmission-related, and proteostasis pathways. Within the constraints of an exploratory design—group-level pooled proteomics, analysis of cerebral rather than peripheral-nerve tissue, and only two doses—these findings indicate that L-serine attenuates the metabolic and behavioural features of experimental diabetic neuropathy and generates the testable hypothesis of dose-dependent neuro-metabolic remodelling. The proteomic signatures are hypothesis-generating and require orthogonal validation before any mechanistic or translational inference can be drawn. Full article

Prediction models for standardized ileal amino acid digestibilities (SIAADs) of sorghums in yellow-feathered chickens have not been previously reported. This study characterized the chemical composition of 10 sorghum samples from different sources, assessed their SIAADs in medium-growing yellow-feathered chickens, and subsequently developed and validated prediction models based on chemical composition and amino acid profiles. A total of 276 Tianluma roosters (60 d of age) were randomly assigned by body weight (average 1.32 kg per bird) to 11 dietary treatments, including a nitrogen-free diet (NFD) group and 10 sorghum-based diet groups. Each treatment included 6 replicate cages, with 4 birds per replicate cage for the sorghum-based diet groups and 6 birds per replicate cage for the NFD. Birds were fed the experimental diets from d 63 to 67, after which ileal digesta were collected to determine SIAADs of 10 sorghum samples. Data from 9 sorghum samples were used to establish prediction equations using stepwise regression, while the remaining sample was used for model validation. Sorghum source significantly influenced (p ≤ 0.002) the SIAADs of most amino acids. Arginine (Arg) exhibited the highest standardized ileal digestibility (SID) (68.2%), whereas tyrosine (Tyr) showed the lowest value (49.0%). Eighteen preliminary prediction models were developed for the SIDs of valine (Val, R² = 0.981, p = 0.001), methionine (Met, R² = 0.978, p < 0.001), isoleucine (Ile, R² = 0.983, p < 0.001), leucine (Leu, R² = 0.981, p < 0.001), threonine (Thr, R² = 0.748, p = 0.016), phenylalanine (Phe, R² = 0.981, p < 0.001), lysine (Lys, R² = 0.988, p < 0.001), histidine (His, R² = 0.988, p = 0.004), Arg (R² = 0.986, p < 0.001), tryptophan (Trp, R² = 0.934, p < 0.001), aspartic acid (Asp, R² = 0.986, p < 0.001), serine (Ser, R² = 0.980, p < 0.001), glutamic acid (Glu, R² = 0.988, p < 0.001), glycine (Gly, R² = 0.898, p = 0.007), alanine (Ala, R² = 0.983, p < 0.001), cysteine (Cys, R² = 0.968, p = 0.003), Tyr (R² = 0.898, p = 0.001), and proline (Pro, R² = 0.944, p = 0.002). The models for the SIDs of Lys, His, and Glu exhibited the highest coefficients of determination (R² = 0.988, p ≤ 0.004), whereas the model for the Thr SID exhibited the lowest fit (R² = 0.748, p = 0.016). Except for Leu and Tyr, the predicted values of the remaining amino acids were generally consistent with the determined values in the validation sample. These preliminary models provide a basis for estimating amino acid digestibilities in sorghums for medium-growing yellow-feathered chickens. Full article

Type 1 diabetes (T1D) is driven by autoreactive CD4⁺ T-cell responses to pancreatic beta cell antigens presented by disease-associated human leucocyte antigen (HLA) class II molecules. However, the molecular mechanisms by which subtle antigenic modifications promote pathogenic immunity remain incompletely defined. Recent immunopeptidomic studies have identified a cysteine-to-serine substitution at position 19 of the insulin B chain, referred to as InsC19S, as a microenvironment-driven neoepitope that can be presented by HLA class II molecules, including HLA-DQ8, and is recognized by diabetogenic CD4⁺ T cells. In this study we explore potential structural and thermodynamic mechanisms that may contribute to the enhanced immunogenicity associated with this single-amino-acid modification. Using molecular dynamics simulations combined with coarse-grained free-energy-perturbation analyses, we compared HLA DQ8 complexes bound to wild-type (WT) insulin and InsC19S peptides. The InsC19S variant is predicted in simulations to exhibit enhanced binding stability, characterized by increased hydrogen bond occupancy, reduced peptide conformational mobility, and a more favorable binding free energy. In addition, the modified peptide is predicted to induce peptide-dependent conformational adjustments within the HLA-DQ8 peptide-binding groove, resulting in expansion of the conformational landscape and stabilization of distinct low-energy states that are not accessed by the WT complex. Principal component analysis and free-energy landscape mapping suggest that this mutation may promote altered collective motions within HLA DQ8 that are consistent with enhanced peptide major histocompatibility complex (MHC) persistence and optimized antigen presentation geometry. Together, these computational observations suggest a structural framework that may help explain the preferential presentation and pathogenic recognition of InsC19S reported in experimental studies. These findings provide a molecular-level framework that may help link microenvironment-driven insulin neoepitope formation to altered peptide–MHC stability and conformational dynamics in HLA-DQ8. Full article

Buffalo milk is a rich source of various nutritional components and bioactive peptides, offering significant health benefits. Endogenous peptides, which occur naturally in milk, represent a valuable source of bioactive peptides with potential nutraceutical applications. However, research on endogenous peptides in buffalo milk remains limited. This study employed a quantitative peptidomic approach to characterize endogenous peptides across different lactation stages. A total of 2099, 2946, and 4418 peptides were identified in colostrum, transitional milk, and mature milk, respectively. The majority of these peptides were derived from β-casein, followed by α_S1-casein, κ-casein, and other proteins. Notably, variations in precursor proteins contributing to peptide production were observed throughout lactation. Phosphorylation levels of endogenous peptides were highest in mature milk, with serine residues predominating. Enzymatic cleavage analysis identified cathepsin D as the key enzyme involved in endogenous peptide production, while proline endopeptidase and plasmin exhibited stage-specific activities. Bioinformatics analysis revealed differentially expressed precursor proteins linked to complement cascades and NF-κB signaling, emphasizing the immune protective role of colostrum. Furthermore, 54 potentially bioactive peptides with favorable water solubility were identified in colostrum, of which 17 were predicted to possess anti-inflammatory properties. These findings contribute to a deeper understanding of the molecular basis of buffalo milk’s functional properties, highlighting its potential as a source of bioactive peptides for both nutritional and pharmaceutical applications. Full article

Artisanal raw milk cheeses harbour complex microbial communities that drive cheese making and shape sensory quality. Previous work on Idiazabal cheese identified rennet as a major microbial source, although all reservoirs contributed to varying degrees. However, their impact in terms of enzyme-encoding genes related to technological quality of cheese remained unexplored. Building on that, this study draws on metagenome-assembled genomes (MAGs) from cheeses and dairy environments to comprehensively identify enzyme-encoding genes involved in key biochemical processes. In cheese MAGs (Lacticaseibacillus paracasei), protease-encoding genes were dominated by ATP-dependent metalloproteases (M41), carbohydrate-active enzyme-encoding genes (CAZymes) by glycoside hydrolases (GH) and glycosyltransferases (GT), while esterase, lipase, and related-enzyme-encoding genes were restricted to sparse ‘GDXG’, type-B and esterase D families. Dairy environments emerged as major reservoirs of enzyme-encoding genes, with notable differences among sample types (p ≤ 0.001). The richest sources of protease-encoding genes were grass (610 genes), linked primarily to Pantoea agglomerans, and rennet (318), mainly related to Basfia sp. and Moraxella sp., dominated by metalloproteases (M23, M38) and serine proteases (S15). The largest reservoirs of CAZyme-encoding genes were food contact surfaces (1550), associated mainly with Salinisphaera sp. and Dietzia sp., and rennet (1505), related to, e.g., Bacteroides pyogenes, Alloprevotella sp., and Lentilactobacillus buchneri. Food contact surfaces were also the richest source of esterase, lipase and related-enzyme-encoding genes (1209), mainly linked to Dietzia sp., Corynebacterium sp., and Brevibacterium aurantiacum. Similarly, aroma-related enzyme-encoding genes (e.g., oppA, pepA, GH13, esterase D) were consistently detected in environmental matrices. These results provide novel insights into dairy microbiomes as functional reservoirs of aroma precursors, revealing their relevance for artisanal PDO cheese production and future biotechnological applications. Full article

The genus Chimarrogale is an ideal group to study the evolutionary mechanisms of semi-aquatic adaptation, but there is a lack of data on its genomic data and molecular mechanisms. Using Illumina sequencing, this study assembled mitogenomes of C. himalayica and C. styani (newly characterized), alongside C. leander, covering all Chimarrogale species in China. Results showed that three complete circular mitochondrial genomes were successfully assembled, with full lengths of 17,202–17,218 bp, including the 37 typical genes: 13 protein-coding genes (PCGs), 22 tRNAs, two rRNAs, and a D-loop region. There were nine overlapping regions and 14 intergenic spacer regions identified, showing significant AT bias. Relative synonymous codon usage (RSCU) analysis showed that Serine (Ser) was used most frequently. Selection pressure analysis showed that the Ka/Ks ratios of PCGs in 44 Soricidae mitogenomes were less than 1, indicated strong purification selection and functional conservation. Among them, the evolution rate of the ATP8 gene was the fastest. The phylogenetic analysis using Maximum Likelihood (ML) and Bayesian Inference (BI) methods showed that the three Chimarrogale species clustered into a monophyletic clade, which formed a sister group with Nectogale elegans within the tribe Nectogalini. This study fills the gap in mitochondrial genome data of semi-aquatic shrews and offers fundamental references for the conservation of shrews. Full article

Background/Objectives: Clinical application of Doxorubicin (Doxo) is limited by cardiotoxicity, a process strongly associated with an interplay between oxidative stress and inflammatory signaling, particularly Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation and Nucleotide oligomerization domain-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome engagement. Identifying strategies capable of mitigating these interconnected pathways is of critical importance in cardio-oncology. Simvastatin (SIM) is a promising option since it modulates oxidative stress, inflammation, and cell death through its pleiotropic effects, so this study aimed to evaluate whether SIM attenuates Doxo-induced inflammatory responses. Methods: Human Cardiomyocyte (HCM) cells were pre-treated with SIM (10 µM) for 4 h and then co-exposed to SIM and Doxo (1 µM) for 20 h. Cytofluorimetric analysis was used to evaluate inducible nitric oxide synthase (iNOS), Connexin 43 (Cx43), and Cx43 phosphorylated at Serine 368 (p^S368Cx43) levels. Real-time qPCR was performed to evaluate iNOS gene expression, while Nitric oxide (NO) release was evaluated by spectrophotometric analysis. Interleukin (IL)-1β, IL-18, IL-6, tumor necrosis factor alpha (TNF-α) production, and NLRP3 levels were evaluated by means of ELISA assay. Expression levels of inhibitor of nuclear factor kappa B alpha (IκB-α), Caspase-1, and Gasdermin D (GSDMD) were evaluated by Western Blot analysis. Nuclear translocation of NF-κB was evaluated by immunofluorescence assay. Results: In our experimental model, SIM significantly (p < 0.01) reduced Doxo-induced nitrite release, as well as iNOS gene expression (p < 0.05) and protein levels (p < 0.01). SIM also markedly attenuated Doxo-induced NF-κB signaling, pro-inflammatory cytokines production (TNF-α and IL-6, p < 0.01), and inflammosome-related responses (cleaved caspase-1, IL-1β, N-terminal domain of GSDMD), and NLRP3 expression p < 0.05). Additionally, SIM significantly attenuated the overexpression of Cx43 and its phosphorylated form (p^S368Cx43), which are responsible for impairing intercellular communication and electrical coupling in cardiomyocytes and contribute to arrhythmias and conduction abnormalities characteristic of acute Doxo-induced cardiotoxicity. Conclusions: Overall, these findings demonstrate that SIM exerts a multifaceted cardioprotective effect against Doxo-induced injury, thereby targeting interconnected inflammatory and pro-arrhythmic pathways implicated in Doxo cardiotoxicity. Full article

This study developed a two-stage, explainable machine learning framework to predict 18-month MMSE-based cognitive status from baseline multimodal data in community-dwelling older adults in Japan. A hierarchical design was used in which Stage 1 distinguished cognitively Normal participants from those with any abnormality (Possible Mild Cognitive Impairment (MCI) or Impaired), and Stage 2 further separated Possible MCI from Impaired within the abnormal subgroup. Both an Imbalanced-Learn Random Forest and a penalized logistic regression baseline were trained under Leave-One-Out Cross-Validation, yielding fair discrimination in Stage 1 (Random Forest AUC = 0.72, accuracy = 0.71; logistic regression AUC = 0.71, accuracy = 0.76) and apparently strong separability in Stage 2 (Random Forest AUC = 0.95, accuracy = 0.96; logistic regression AUC = 0.82, accuracy = 0.92) in a small sample size with high class imbalance. SHapley Additive exPlanations (SHAP) with TreeExplainer for Random Forest and LinearExplainer for logistic regression were used to identify interpretable biomarkers at each stage though feature attribution. In Stage 1, both models highlighted renal and systemic metabolic markers (e.g., creatinine, uric acid, blood urea nitrogen), amino acid and redox-related metabolites (including D-serine, D-amino acid proportions, L-asparagine, alanine, L-glutamic acid, cysteine, methionine sulfoxide), and wearable-derived activity variability (e.g., fluctuation coefficients and steps per minute), with the Simpson index of gut microbiome diversity also contributing in the logistic model. In Stage 2, the models converged on a distinct signature involving glucose and albumin, uric acid and uridine, choline and carnitine, multiple amino acids (such as phenylalanine, proline, ornithine, tryptophan, threonine, and short-chain amino acids), oxidative/energy markers (niacinamide, methionine, methionine sulfoxide, ergothioneine), hematologic indices, and high-MET activity fluctuation metrics. Collectively, these results support a stage-dependent, multisystem view of cognitive aging in which broad renal–metabolic, amino acid, and behavioral vulnerabilities characterize early abnormality, whereas more pronounced alterations in energy metabolism, nucleotide and choline pathways, oxidative stress, and activity irregularity accompany progression from Possible MCI to Impaired status. By combining routine clinical chemistry, targeted metabolomics, gut microbiome diversity, and wearable-derived behavioral measures within an explainable AI framework, this two-stage approach illustrates a scalable, biologically grounded strategy for stage-aware risk stratification and monitoring of cognitive decline in community settings. Full article

Background: D-amino acids are increasingly recognized as bioactive molecules with diverse physiological and pathological roles in humans, particularly in the gut, kidneys, and nervous system. Advances in analytical techniques have revealed their widespread presence in biological fluids, including plasma, urine, cerebrospinal fluid, amniotic fluid, and saliva, challenging the long-standing assumption that D-amino acids are absent or biologically insignificant in mammals. Scope: This review systematically summarizes the current knowledge on D-amino acid sources, distribution, metabolic regulation, and biological functions, with emphasis on their roles in human physiology and disease. Key findings: Accumulating evidence indicates that major D-amino acids, including D-serine, D-aspartate, and D-alanine, are derived from multiple sources such as diet, intestinal microbiota, and endogenous racemization processes. Rather than being passive metabolic byproducts, D-amino acids are now understood to participate in host–microbe interactions, neurotransmission, and renal physiology. Importantly, a consistent trend across studies is their dual and concentration-dependent nature, exhibiting beneficial effects under physiological conditions but potential cytotoxic effects at elevated levels. Conclusions and perspectives: Overall, D-amino acids represent multifunctional biomolecules with tightly regulated physiological roles and context-dependent pathological implications. However, major gaps remain in understanding their quantitative dynamics, tissue-specific regulation, and microbiota-dependent metabolism. Future studies addressing these mechanisms will be essential for establishing their clinical utility as biomarkers and for developing D-amino acid-based therapeutic and nutritional strategies. Full article

Background: Triple-negative breast cancer (TNBC) remains among the most aggressive and therapeutically unresponsive subtypes due to the absence of ER, PR, and HER2 targets. Casein Kinase II (CK2), a pleiotropic serine/threonine kinase overexpressed in TNBC, represents a compelling target for rational drug design. Methods: Here, we present an AI-integrated benchmarking framework combining virtual drug discovery, molecular dynamics simulations, machine learning-driven QSAR modeling, and quantum-mechanical electronic structure analysis to identify potent CK2 inhibitors from natural product chemical space. Results: A validated XP docking protocol (ROC–AUC = 0.748) screened ~480,000 compounds, yielding seven hits, with superior binding to the reference inhibitor CX-4945. Among these, Anastatin B, 3,4,8,9,10-pentahydroxy-dibenzo-[b,d]pyran-6-one, Rhein, and aloe emodin acetate exhibited highly favorable docking scores (−11.6 to −13.1 kcal mol⁻¹) and stable 200 ns binding dynamics, reflected by RMSD ≤ 2 Å and compact Rg trajectories. MM-PBSA/MM-GBSA analyses confirmed robust thermodynamic stability, while DFT-derived HOMO–LUMO gaps (3.8–4.3 eV) suggested optimal electronic reactivity for kinase inhibition. Machine learning QSAR models demonstrated strong predictive performance, with the best stacking models achieving test R² ≈ 0.69 and consistent cross-validation performance (CV R² ≈ 0.66–0.69), supporting reliable prediction of pIC₅₀ values and prioritization of top-ranked scaffolds. Conclusions: Collectively, this integrative framework bridges AI-based learning and biophysical validation, establishing a reproducible paradigm for de novo CK2 inhibitor discovery in TNBC. Full article

Serine protease-like proteases (SBTs) constitute a distinct class of serine proteases exclusive to plants. Despite the recognized importance of SBTs in various plants, knowledge concerning the evolution and function of SBT genes in Brassica napus is limited. In this study, a total of 140, 63, and 71 SBT genes were identified in B. napus, B. oleracea, and B. rapa, respectively. Phylogenetic analysis classified these 330 identified SBTs into five subfamilies, and collinearity analyses further indicated that gene redundancy and gene loss were strongly associated with polyploidization in Brassicaceae plants. Additionally, analyses of gene structure and conserved motifs suggested that evolutionary changes in exon-intron structures may contribute to the differentiation of coding regions, expression patterns, and even functions within the BnSBT family. Analysis of promoter cis-regulatory elements revealed their predominant association with hormonal responses, abiotic stress, and processes related to plant growth and development. Furthermore, eight differentially expressed genes (DEGs) were identified through a comparative analysis of RNA-Seq data from high- and low-yielding cultivars. qRT-PCR verification also revealed that these eight DEGs (BnSBT1.4b, BnSBT1.4c, BnSBT1.4d, BnSBT1.5c, BnSBT1.6b, BnSBT1.8a, BnSBT3.14a, and BnSBT3.14b) were significantly differentially expressed in the pericarp and seeds. They could be categorized into two distinct groups: BnSBT1.4b, BnSBT1.4c, BnSBT1.4d, BnSBT1.5c, and BnSBT1.8a were highly expressed in high-SPSI material, whereas BnSBT1.6b, BnSBT3.14a, and BnSBT3.14b were highly expressed in low-SPSI material. These results suggest that BnSBTs have diverse potential functions in regulating yield traits in Brassica napus. These findings offer key insights into Brassicaceae SBT genes and highlight the importance of BnSBTs in achieving high yields in Brassica napus. Full article