Search Results (24,035)

Aluminum chloride (AlCl₃)-induced rat models are widely used to investigate Alzheimer-like neurodegeneration, yet substantial methodological variability limits cross-study comparability. A structured synthesis focused specifically on the methodological architecture of these models, including dose, exposure duration, route of administration, and behavioral assessment, remains lacking. This review aimed to synthesize the behavioral paradigms used to assess learning and memory in rat models of aluminum chloride-induced Alzheimer’s disease, with particular emphasis on dose, duration, and route of administration. A structured narrative review incorporating systematic elements was conducted following PRISMA-informed procedures using PubMed, Web of Science, and Scopus. The reviewed literature showed a predominance of oral administration, low-to-moderate AlCl₃ doses and subchronic exposure durations, most commonly 31–60 days. Behavioral assessment was dominated by hippocampal-dependent paradigms, particularly the Morris water maze and Y-maze. Across studies, AlCl₃ exposure was associated with multidomain behavioral impairment accompanied by consistent hippocampal and cortical histopathological abnormalities and convergent biochemical and molecular changes, including cholinergic dysfunction, oxidative stress, neuroinflammation, and amyloid- and tau-related alterations. Overall, the available literature does not support a standardized experimental protocol or a clear overall dose–effect or duration–effect relationship. Greater harmonization of study design is needed to improve reproducibility and translational relevance. 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

Background/Objectives: A central question in molecular genetics concerns how transcriptional regulatory sequences and de novo genes originate and reach evolutionary fixation. In this study, we utilize the human bicistronic gene SMIM45 as a model to analyze the evolutionary trajectories of gene development. This locus comprises several functional units: three enhancers (one featuring an embedded silencer), an exonic silencer that partially overlaps an ORF, a highly conserved ancestral sequence encoding a 68 aa microprotein, and a human-specific de novo gene encoding a 107 aa protein expressed spatiotemporally in embryonic brain tissues. Methods: The alignment of gene sequences from different species was used to determine the evolutionary development of enhancers and silencers, and the development of the exonic silencer was determined through application of the cultivator model and assessment of nearest-neighbor bases. Results: We identify significant disparities in formation mechanisms; for example, the LOC127896430 NANOG hESC enhancer originated simply via two Alu insertions that constitute the enhancer. In contrast, the exonic silencer (a segment of the LOC130067579 ATAC-STARR-seq lymphoblastoid silent region 13815)—a distinct, novel type of silencer—originated from a combination of diverse mechanisms, including a “cultivator gene” process of base pair fixation, consistent with the cultivator model proposed by Li Zhao and coworkers. Conclusions: SMIM45 exemplifies novel development mechanisms occurring over hundreds of millions of years, culminating in the birth of a human-specific, de novo 107 aa cistron. The associated complex of enhancers and silencers suggests intricate regulation of the 107 aa protein in fetal brain tissues. Full article

To elucidate coalbed methane (CBM) adsorption mechanisms in deep coal reservoirs, the macromolecular structures of coal samples with different coal ranks were characterized using FTIR, XPS, and C NMR, followed by the construction of corresponding molecular models. Grand Canonical Monte Carlo (GCMC) simulations were employed to investigate methane adsorption behavior within the coal matrix at 313.15 K and pressures up to 20 MPa. The results showed that as coal rank increased (R_o,max = 1.63% to 3.18%), the coal macromolecular structure transformed from a side-chain-rich configuration to a highly aromatized and directionally stacked structure. This structural maturation leads to a more compact coal matrix, evidenced by a reduction in free volume from 5108.39 ų to 3999.87 ų and a decline in accessible free volume from 8.23% to 6.26%, thereby restricting the effective space for methane storage. At 20 MPa, although the pore walls of high-rank coal exhibit stronger localized adsorption capacity, the bulk adsorption capacity follows the order: DZ > ZC > SH. This suggests that under deep, high-pressure conditions, the pore-volume compression effect associated with increasing coal rank governs the upper limit of adsorption per unit mass of coal. As pressure increases into the deep reservoir regime, the state of methane in coal micropores gradually shifts from surface adsorption to a high-density, quasi-liquid filling behavior. Consequently, the influence of specific surface area diminishes, while effective free volume emerges as the primary determinant of high-pressure adsorption capacity. The impact of coal rank on deep methane adsorption reflects a competition between enhanced adsorption potential and restricted storage space. The densification-induced compression of effective free volume is identified as the dominant factor limiting the adsorption capacity of deep CBM. This study provides a molecular-scale understanding of deep CBM occurrence mechanisms and establishes a theoretical framework for resource evaluation. Full article

Feto-maternal microchimerism (Mc) refers to the exchange of cells between the fetus and mother, and fetal–fetal Mc to the exchange between fetuses during pregnancy. This phenomenon occurs across mammalian species, including humans, mice, and cattle. Key data on Mc cells and theoretical considerations regarding the presence of fetal-derived material, such as trophoblast cells, cell-free fetal DNA (cffDNA), and exosomes in maternal blood are summarized. This review aims to first, synthesize current knowledge on feto-maternal and fetal–fetal Mc across mammals, second, address three core questions: how and where Mc has been demonstrated in animals, what techniques have been used over time to detect fetal-derived material and Mc, and how placental structures influence the frequency of Mc. Finally, it aims to identify gaps in the literature for species such as horses, goats, and pigs. This article concludes that Mc is a widespread phenomenon among mammals, but detection methods and reported frequencies vary significantly by species and placental type. A biological model is presented in this article in which multinucleated trophoblast cells undergo apoptosis, releasing cffDNA that enters the maternal blood circulation after multinucleated trophoblast invasion. Advances in molecular biology technology have improved the ability to detect fetal-derived material, cells, DNA, and exosomes in maternal blood. However, notable research gaps remain for Mc in horses, goats, and pigs, highlighting the need for targeted studies to better understand species-specific patterns or a general biological model. Full article

Background: Microfibrillar-associated protein 2 (MFAP2) is implicated in various malignancies, yet its specific role and molecular mechanisms in glioblastoma (GBM) progression remain poorly understood. Methods: We analyzed MFAP2 expression in human clinical specimens and murine models. Functional impacts were assessed in U251 cells via gain- and loss-of-function assays. Mechanistic studies explored the interplay between autophagic flux and Wnt/β-catenin signaling. An orthotopic GL261 syngeneic orthotopic model validated these findings in vivo. Results: MFAP2 was significantly overexpressed in GBM, correlating with poor patient prognosis. In vitro, MFAP2 markedly enhanced U251 viability, migration, and invasion while suppressing apoptosis. Mechanistically, MFAP2 triggered autophagic flux, subsequently activating the Wnt/β-catenin cascade and its downstream targets (MMP9, c-Myc, Cyclin D1). Pharmacological inhibition of either autophagy or Wnt signaling effectively abrogated these oncogenic phenotypes. In vivo, MFAP2 knockdown reduced tumor volume by 62.4% and suppressed the autophagy–Wnt axis. Conclusions: MFAP2 is an oncogenic regulator in glioblastoma models that links autophagy activity to Wnt/β-catenin signaling. Our findings support MFAP2 as a candidate prognostic biomarker and a potential therapeutic target; however, additional validation in larger molecularly annotated clinical cohorts and multiple GBM models is warranted. Full article

Essential oils (EOs) are complex plant-derived mixtures increasingly investigated for their anti-inflammatory, antioxidant, and vasoprotective properties. Thromboinflammation, a process integrating coagulation, platelet activation, endothelial dysfunction, and inflammatory signaling, plays a central role in vascular pathology; however, the contribution of EOs to this process remains insufficiently characterized. This narrative review aims to synthesize current molecular and experimental evidence regarding the effects of EOs and their major bioactive constituents on pathways converging toward thromboinflammation. A focused PubMed/MEDLINE search, supplemented by manual reference screening, was conducted to identify experimental and translational studies on EOs and selected constituents relevant to inflammatory mediators, oxidative stress, endothelial dysfunction, platelet activation, and thrombotic pathways. Available data from predominantly preclinical experimental models indicate that EOs can exert multi-target effects, including modulation of cytokine production, attenuation of oxidative stress, improvement in endothelial function, and inhibition of platelet aggregation, thereby influencing key components of thromboinflammatory pathways. Despite these promising findings, heterogeneity in chemical composition, limited standardization, uncertain exposure relevance, and the predominance of preclinical data remain important limitations. In conclusion, EOs represent a promising but still largely preclinical class of natural compounds capable of modulating interconnected mechanisms relevant to thromboinflammation; however, further translational and clinical studies are required to validate their therapeutic potential. Full article

Cyclin-Dependent Kinase-Like 5 (CDKL5) Deficient Disorder (CDD) is a rare X-linked developmental and epileptic encephalopathy characterized by early-onset refractory epilepsy, severe neurodevelopmental impairment, and lifelong disability. Although more than thirty anti-seizure medications are available, most CDD patients remain pharmaco-resistant. Gene-based therapies are emerging, but therapeutic development is hindered by marked clinical heterogeneity, small patient populations, and the lack of robust, translatable brain-based biomarkers for clinical trials. Genetically engineered Cdkl5 mouse models recapitulate many cognitive, behavioral, and molecular features of CDD, yet their utility is limited by the absence of overt seizures, precluding seizure-based outcome measures. Here, we establish high-definition brain network (HDBN) biomarkers using advanced diffusion MRI tractography combined with graph-theoretical analysis to quantify whole-brain network organization in Cdkl5 knockout mice. Diffusion MRI enables non-invasive mapping of axonal connectivity by leveraging anisotropic water diffusion, while high-angular-resolution acquisition overcomes key limitations of conventional diffusion tensor imaging in regions with complex fiber architecture. We demonstrate that Cdkl5 knockout mice exhibit reproducible and region-specific disruptions in brain network organization, prominently affecting the somatosensory and somatomotor cortex, hippocampus, hypothalamus, amygdala, and superior colliculus—regions implicated in cognition, learning and memory, homeostasis, anxiety, and visual–motor function. In contrast, networks within the entorhinal cortex remain largely preserved. These findings identify HDBN metrics as sensitive, non-invasive biomarkers that capture clinically relevant circuit-level abnormalities in CDD. Because diffusion MRI–based network analyses are directly translatable across species, HDBN biomarkers provide a unified framework for therapeutic evaluation in mouse models, large animals, and human clinical trials, enabling longitudinal monitoring of disease progression and treatment response. Full article

Background/Objectives: Spontaneous remission (SR) of acute myeloid leukemia (AML) offers unique clinical insights into host anti-tumor immunity. However, the comprehensive clinical landscape and molecular dynamics of blast clearance and subsequent relapse remain unclear. This study aimed to elucidate these dynamics. Methods: We conducted a two-phase observational study: a systematic pooled analysis of 66 adult AML SR cases (1990–2024) to define clinical triggers and outcomes and longitudinal molecular tracking of two institutional cases to map clonal shifts (with immune profiling for Patient 1 and genomic tracking for both). Results: In the pooled analysis, infection was the predominant trigger, accounting for 78.6% (95% CI: 65.6–88.4%) of SR events. The dataset showed male predominance and monocytic leukemia enrichment (57.6% [95% CI: 44.1–70.4%]), suggesting lineage-specific susceptibility. SR duration and relapse risk were independent of the infection trigger, AML subtype, or age. When integrated with these clinical patterns, institutional tracking was consistent with a biphasic evolutionary model: an acute IL-8 surge alongside NKT and CD4+ T cell activation coincided with blast clearance, as observed primarily in Patient 1. Subsequently, the emergence of TP53 or NRAS mutations within persistent DNMT3A-mutated clones during relapse raised the hypothesis that unresolved chronic inflammation could potentially exert selective pressure favoring resistant subclones. Such interpretations remain correlational and require prospective validation. Conclusions: Our findings outline a clinical–evolutionary framework for AML SR. Remission durability likely relies on balancing acute immune activation with underlying clonal stability. These observational insights highlight complex immune-genomic crosstalk, generating hypotheses for future prospective investigations. Full article

Objectives: This study aimed to investigate the biological role and molecular mechanism of the RNA m⁵C methyltransferase NSUN4 in cervical cancer progression, with a focus on its involvement in ferroptosis regulation. Methods: Differential expression and survival analyses were performed using TCGA and GEPIA datasets. Functional enrichment and GSEA identified pathways associated with NSUN4 dysregulation. NSUN4 expression was validated in clinical tissues by qRT-PCR, Western blot, and immunohistochemistry. Gain- and loss-of-function assays, including CCK-8, colony formation, and Transwell assays, were conducted to assess cell proliferation and invasion. Furthermore, a nude mouse subcutaneous xenograft model was established to validate the oncogenic role of NSUN4 in vivo. Ferroptosis was evaluated using specific inhibitors and measurement of GSH and ferroptosis-related proteins. RIP, m⁵C-RIP, RNA stability, and dual-luciferase assays were performed to explore the underlying mechanism. Results: NSUN4 was markedly upregulated in cervical cancer tissues and correlated with poor prognosis. Functionally, NSUN4 enhanced tumor cell growth, migration, and invasion while inhibiting ferroptosis. Mechanistically, NSUN4 bound to and stabilized C-MYC mRNA via m⁵C methylation, activating the PI3K/Akt signaling pathway and promoting ferroptosis resistance. Conclusions: NSUN4 promotes cervical cancer progression by stabilizing C-MYC mRNA through m⁵C modification, leading to PI3K/Akt activation and suppression of ferroptosis. These findings identify NSUN4 as a novel oncogenic regulator and potential therapeutic target in cervical cancer. Full article

Background: Cytokine-like receptor family 1 (CRLF1) has been implicated in tumor progression, yet its prognostic function and mechanistic actions in prostate cancer (PCa) remain elusive. Objective: This investigation sought to clarify the functional role, molecular mechanisms, and clinical relevance of CRLF1 in the progression of PCa. Methods: We conducted extensive bioinformatics analyses utilizing the protein interaction networks and the TCGA-PRAD dataset. CRLF1 and cartilage oligomeric matrix protein (COMP) expression were validated in clinical samples by qRT-PCR and Western blot (WB). Functional assessments, including Transwell invasion, flow cytometry, CCK-8, and wound healing, were conducted in vitro. An in vivo xenograft tumor model was used for further validation. Mechanistic investigations involved genetic perturbation (overexpression and inhibition) of CRLF1 and COMP. Results: Compared to benign tissues, the levels of CRLF1 and COMP were markedly elevated in PCa tissues. Bioinformatics assessments illustrated a robust positive relationship between CRLF1 and COMP, suggesting COMP may function as a downstream mediator. In vitro and in vivo investigations illustrated that silencing CRLF1 significantly suppressed PCa cell growth, invasion, and tumor progression, while enhancing apoptosis. Importantly, suppressing COMP counteracted the cancer-promoting effects triggered by CRLF1 overexpression. At the mechanistic level, CRLF1 facilitates tumor progression by modulating COMP to activate the FAK/PI3K/AKT signaling cascade. Conclusions: Our outcomes demonstrate that CRLF1 promotes PCa progression by targeting COMP to stimulate the FAK/PI3K/AKT signaling axis. This newly identified CRLF1/COMP/FAK/PI3K/AKT pathway underscores CRLF1 as a potential biomarker and therapeutic target for PCa. Full article

Human neutrophil elastase (HNE) is a key driver of inflammatory lung disorders, promoting extracellular matrix degradation and tissue damage. Although inhibitors such as Sivelestat and Alvelestat are clinically relevant, their performance within the oxidative microenvironment of diseased lungs remains poorly understood. Here, we employed an integrated in vitro and in silico approach to investigate their behavior under physiological and oxidative conditions and to provide a molecular-level interpretation. Under physiological conditions, enzymatic assays and steady-state kinetics confirmed that both compounds act as competitive inhibitors, with Sivelestat displaying higher baseline potency. Under oxidative stress, however, Sivelestat exhibited a marked reduction in inhibitory potency, whereas Alvelestat retained its efficacy. Molecular modeling and molecular dynamics simulations of native and oxidized HNE variants provided a structural rationale for this divergence. Alvelestat, as a non-covalent inhibitor, maintains stable binding despite increased flexibility of the active site, whereas Sivelestat, acting via a reversible covalent mechanism, requires a precise pre-acylation geometry. Oxidation-induced remodeling of the S1 pocket disrupts the near-attack configuration required for covalent bond formation, thereby impairing inhibition. Overall, these findings indicate that oxidative stress may selectively compromise covalent inhibition while preserving enzymatic activity, and suggest that context-dependent redox-related structural effects may represent a consideration for the design of next-generation HNE inhibitors. Full article

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive stage of metabolic dysfunction-associated steatotic liver disease characterized by lipid dysregulation, oxidative stress, inflammation, and fibrosis. Because these processes occur simultaneously, compounds targeting multiple pathways may offer therapeutic benefit. Naringin, a citrus-derived flavonoid, has reported antioxidant and anti-inflammatory properties, but its integrated effects in MASH remain unclear. In this study, the effects of naringin were evaluated using combined in silico analysis and in vivo experiments. Network pharmacology and molecular docking predicted targets related to lipid metabolism, oxidative stress, inflammation, and fibrosis, which were validated in a methionine- and choline-deficient diet-induced mouse model. Naringin reduced hepatic lipid accumulation and improved serum AST and ALT levels. It modulated oxidative stress-related genes, attenuated inflammatory responses, and reduced fibrogenic markers. Naringin also decreased Ly6Chigh inflammatory monocytes and Kupffer cell activation, and reduced hypothalamic microglial activation. These findings suggest that naringin exerts multi-target effects across hepatic, systemic, and central pathways, supporting its potential as a therapeutic candidate for MASH. Full article

Dehydrothyrsiferol (DT), a brominated oxasqualenoid from the red alga Laurencia viridis, represents a compelling example of this framework. This review establishes DT as a model Smart Secondary Metabolite based on the convergence of a unique molecular architecture of rigid stereogroups connected by flexible bonds; a high metabolic yield (0.42% w/w of crude extract); potent selective bioactivity against kinetoplastids and drug-resistant tumors; multi-target modulation of protein phosphatase 2A (PP2A) and cell-surface integrins; and distinctive chemotaxonomic relevance within Macaronesian communities. Its biosynthesis proceeds through stereocontrolled epoxide-opening cascades, generating an evolutionarily refined scaffold. Ecologically, DT operates as a multifunctional shield, providing antifouling protection and deterring herbivory. Pharmacologically, it acts as a selective signaling modulator, triggering integrin-mediated cell death (IMD) in resistant cancer cells and inducing mitochondrial collapse in protozoa. In vivo studies in murine models of cutaneous leishmaniasis have demonstrated an 87% reduction in lesion size, reinforcing its promise as a lead structure. Full article

Background/Objectives: Alzheimer’s disease (AD) remains a progressive neurodegenerative disorder with limited therapeutic options. This study aimed to develop an integrative multi-omics computational pipeline to identify diagnostic biomarkers and prioritize druggable therapeutic targets for AD. Methods: We integrated transcriptomic data from 1047 samples (547 AD, 500 controls) using weighted gene co-expression network analysis (WGCNA) and three machine learning algorithms (LASSO, Random Forest, SVM) with strict separation of training, feature selection, and evaluation. Single-cell RNA sequencing of 48,481 nuclei from entorhinal cortex, two-sample Mendelian randomization (MR) with Bayesian colocalization, and structure-based molecular docking with triplicate 500 ns molecular dynamics (MD) simulations were also employed. Results: Machine learning identified 10 consensus biomarker genes involved in synaptic vesicle cycling, ion transport, and calcium homeostasis (internal test AUC = 0.891, 95% CI: 0.836–0.946; external validation on GSE48350: AUC = 0.847, 95% CI: 0.798–0.896). Covariate-adjusted differential expression and MR with Bayesian colocalization converged on eight immune-related therapeutic targets including APOE, TREM2, and TYROBP ($p<0.05$; Bonferroni-corrected threshold $p<0.00625$). Single-cell analysis revealed oligodendrocyte expansion in AD (28.5% versus 24.8%), with target genes predominantly expressed in microglia and astrocytes. Virtual screening of 2634 FDA-approved drugs prioritized 10 exploratory repurposing candidates; indomethacin–TREM2 and celecoxib–CSF1R are primary exploratory candidates given structurally validated binding pockets. Triplicate MD simulations (15 $\mathsf{\mu }$s aggregate) showed force-field-consistent structural stability (RMSD ≤ 3.2 Å). A quantitative multi-omics convergence framework identified four Tier 1 targets (APOE, TREM2, TYROBP, CX3CR1) supported by ≥5 analytical layers ($P_{\mathrm{perm}}=0.0003$; note: three of five layers share the same transcriptomic input). Conclusions: These findings provide a multi-evidence computational framework linking diagnostic biomarkers and druggable neuroinflammatory targets for AD. All predictions require experimental validation in biochemical and cellular models before clinical conclusions can be drawn. Full article