Search Results (13,915)

Lung cancer is classified as either Non-Small Cell (NSCLC) and Small Cell Lung Cancer (SCLC) and still represents the leading cause of cancer-related mortality worldwide. Prognosis of NSCLC and SCLC patients is grim; thus, novel therapies are needed. In this context, plant-derived compounds, such as olive leaf extract (OLE), recently attracted much interest for their anti-cancer properties. We investigated the impact of OLE on cell proliferation and apoptosis (by flow cytometry) and migration (by scratch test and transwell assay) of NSCLC and SCLC cell lines, underlying the mechanisms involved. Synergistic effects with cisplatin were also evaluated. OLE differentially impaired cell proliferation and induced apoptosis in LC cell lines. Notably, such effects were higher in SCLC than in NSCLC cell lines. Further analyses were performed on GLC-1 and SKMES cells, identified as OLE-sensitive and OLE-resistant models, respectively. Indeed, OLE triggered the intrinsic apoptotic pathway by activating cleaved caspase-9, -3 and -7, and induced DNA damage response and cellular stress molecules in GLC-1 cells only. In contrast, OLE affected migratory capacity of SKMES cell line and modulated stress adaptation and survival pathways. Finally, OLE synergized with cisplatin in the induction of apoptosis in GLC-1 cells. OLE exerted multiple anti-tumor effects on LC cells in vitro. Its ability to enhance cisplatin-induced apoptosis supports further investigation of OLE as a potential dietary adjunct to chemotherapy. Although OLE has an established safety profile, in vivo studies are required to validate its efficacy, and assess potential interactions with chemotherapeutic drugs before any clinical application. Full article

Background: Artificial intelligence (AI) is transforming pharmacology and pharmacotherapy by enabling the integration of large, heterogeneous datasets to support precision and personalised medicine. However, the reliability of AI-assisted therapeutic decision-making depends fundamentally on the selection, quality, and interpretation of pharmacological and clinical input features or parameters. Current AI models frequently overlook the multidimensional complexity of drug- and patient-specific factors, limiting their clinical applicability and generalisability. Methods: This narrative review was prepared based on 45 years of experimental work and relevant published research in drug design, development, and clinical experience in iron chelation therapy and personalised treatment approaches. Additional literature was identified through targeted searches of PubMed and Scopus using terms related to AI, machine learning, pharmacology, pharmacotherapy, and personalised medicine. Key pharmacological and clinical input features relevant to AI-assisted personalised drug selection include physicochemical drug properties, absorption, distribution, metabolism, excretion and toxicity characteristics, route of administration, drug interactions, pharmacokinetics, pharmacodynamics, multi-omics data, therapeutic efficacy, diagnostic biomarkers, statistical validation, governance, and explainable AI. A conceptual framework for AI-assisted personalised drug selection is also proposed as an example. Results: It is suggested that reliable AI-assisted pharmacotherapy requires the integration of diverse, interdependent datasets and parameters describing drug characteristics, patient variability, clinical outcomes, and real-world evidence. The incorporation of pharmacogenomics, electronic health records, diagnostic imaging and profiling, and validated computational descriptors can improve prediction of drug efficacy, toxicity, interactions, and therapeutic response. Furthermore, robust model validation, data governance, cybersecurity, and continuous monitoring are identified as essential prerequisites for safe clinical implementation. The proposed conceptual framework illustrates how clinical admissibility filtering, model-based ranking, local attribution, and clinically supervised decision support may enhance personalised drug selection while maintaining human oversight. Conclusions: Artificial intelligence has considerable potential to improve drug selection and personalised pharmacotherapy. However, its success depends on comprehensive integration of pharmacological knowledge with high-quality clinical data, rigorous validation, and responsible governance. The multidimensional framework presented here provides a foundation for the potential development of clinically interpretable, reliable, and patient-centred AI systems capable of supporting safer and more effective precision medicine. Full article

Background/Objectives: Oral solid dosage (OSD) forms are historically categorized as low-risk vectors for leachables under the assumption that solid-state matrices impose severe kinetic barriers against migrant migration and reactivity. This study investigates an unexpected unknown impurity, detected as part of a routine ICH Q3B testing program to control drug product impurities in a blister-packed tablet. Since the impurity exceeded the ICH Q3B identification threshold applicable for this drug product (1.0% w/w relative to API or 5 µg total daily intake (TDI), whichever is lower), a forensic investigation into the origins and identity of the impurity was performed. Methods: Placebo and packaging line studies were performed to isolate the origin of the impurity. Systematic structure elucidation was carried out using high-resolution mass spectrometry (HRMS), isotopic fine structure analysis, and de novo chemical synthesis. To enable definitive characterization, preparative HPLC was utilized to isolate the compound for high-field 2D-NMR spectroscopy (801 MHz). Results: The impurity was proven to be independent of active pharmaceutical ingredient degradation, forming only when tablet excipients were stored in sealed PVC blister packaging. Co-incubation of the PVC heat stabilizer derivative dimethyltin bis(2-ethylhexyl mercaptoacetate) (DMTE) with pyrrolidin-2-one (a povidone excipient degradation product) generated an identical chromatographic and MS/MS spectral profile. NMR spectroscopy unambiguously identified the structure as 2-ethylhexyl 2-((5-oxopyrrolidin-2-yl)thio)acetate. Conclusions: This study provides the first direct evidence of an organotin-catalyzed solid-state reaction between a packaging leachable and a tablet excipient under 25 °C/60% RH storage conditions. While this implies that the impurity should not be evaluated under the ICH Q3B guidelines, the findings directly challenge the assumed “low-risk” status of OSD packaging regarding leachables and highlight the necessity for interaction-focused, chemistry-based risk assessments, as outlined in emerging ICH Q3E guidelines. Full article

Aim of the Study: The aim of this study was to characterize the volatile phytochemical composition of Cannabis sativa L. essential oil (CSEO) and evaluate its in vitro inhibitory activity against selected digestive enzymes and its antiglycation activity. Molecular docking and ADMET analyses were additionally performed to explore the possible interactions and predicted pharmacokinetic properties of the major identified constituents. Materials and Methods: The chemical composition of CSEO was characterized by Gas Chromatography–Mass Spectrometry (GC-MS). Its in vitro inhibitory activity was evaluated against α-amylase, α-glucosidase, and pancreatic lipase, while its antiglycation activity was assessed by monitoring the formation of glycation products at different stages of the glycation process. Molecular docking simulations were performed to investigate the potential interactions of major identified terpenes with the active sites of the investigated enzymes. In addition, ADME analysis was conducted to predict selected pharmacokinetic and drug-likeness properties of the major constituents. Results: gc-ms analysis revealed a complex terpenoid profile, with β-caryophyllene as the major constituent, followed by selina-3,7(11)-diene (8.00%), cubenol (6.62%), γ-eudesmol (6.57%), epiglobulol (6.04%), and valencene (5.80%). CSEO showed significant in vitro inhibitory activity against α-amylase, α-glucosidase, and pancreatic lipase. The essential oil also exhibited antiglycation activity, with inhibition observed at different stages of glycation-product formation. Molecular docking analysis indicated that several major sesquiterpenes could interact with the investigated enzyme targets through different binding interactions. ADME analysis provided predicted pharmacokinetic and drug-likeness profiles for the major constituents. Conclusions: The findings demonstrate that Cannabis sativa L. essential oil possesses in vitro digestive-enzyme inhibitory and antiglycation activities. The docking results provide molecular-level insights into possible interactions between major essential-oil constituents and the investigated enzyme targets. These findings support further investigation of CSEO and its major constituents using appropriate in vivo and mechanistic studies to determine their biological relevance and potential applications. Full article

Hyperforin, a polyprenylated acylphloroglucinol and major bioactive constituent of Hypericum perforatum L. (H. perforatum, St. John’s Wort), has attracted considerable interest because of its pleiotropic pharmacological properties. Although historically investigated primarily for its contribution to the antidepressant activity of H. perforatum, experimental studies have identified broader neuroprotective, anti-inflammatory, antioxidant, immunomodulatory, antimicrobial, metabolic, anticancer, and tissue-regenerative actions. However, the evidence remains heterogeneous, and an important distinction exists between findings obtained with purified hyperforin and those derived from multicomponent H. perforatum preparations. Unlike previous reviews that have primarily summarized the pharmacological activities of hyperforin, the present review adopts a translational evidence framework that distinguishes purified hyperforin from multicomponent H. perforatum preparations and evaluates the maturity of evidence from molecular mechanisms and preclinical models through pharmacokinetics, human studies, safety, and clinical development. A comprehensive narrative review was conducted according to the Scale for the Assessment of Narrative Review Articles (SANRA) recommendations. PubMed/MEDLINE, Scopus, Web of Science, Embase, and Google Scholar were searched from database inception through 25 July 2026. Mechanistic, in vitro, animal, translational, pharmacokinetic, and clinical studies, together with relevant systematic reviews and meta-analyses, were critically synthesized according to intervention type, disease-specific evidence, pharmacokinetic and formulation characteristics, safety, and translational relevance. Hyperforin acts as a pleiotropic signaling modulator affecting interconnected pathways involved in neurotransmission and neuroplasticity, inflammatory and redox regulation, mitochondrial and cellular homeostasis, immune function, and metabolism. Extensive cellular and animal evidence supports biological activity across neuropsychiatric, neurodegenerative, inflammatory, immune-mediated, cardiometabolic, oncological, gastrointestinal, infectious, dermatological, and other chronic disease settings. Nevertheless, evidence maturity differs markedly among indications. The strongest human evidence concerns standardized hyperforin-containing H. perforatum preparations for mild-to-moderate depression, whereas most other applications remain preliminary or predominantly preclinical. Adequately powered randomized controlled trials of purified hyperforin are lacking, preventing attribution of the clinical effects of H. perforatum preparations specifically to hyperforin. Translation is further constrained by poor aqueous solubility, chemical instability, variable bioavailability and formulation composition, limited compound-specific pharmacokinetic data, and clinically important herb–drug interactions, particularly through PXR-mediated induction of CYP3A4 and P-glycoprotein. Hyperforin is a pharmacologically promising multifunctional natural compound, but its experimental activity currently exceeds the strength of compound-specific clinical evidence. Future research should prioritize chemically defined and preferably purified formulations, rigorous pharmacokinetic and dose-finding studies, biomarker-supported target-engagement assessment, and adequately powered randomized controlled trials, together with long-term safety, interaction, standardization, and regulatory evaluation. Demonstrating predictable human exposure, biologically relevant target engagement, clinically meaningful efficacy, and an acceptable long-term safety profile will be essential for determining whether hyperforin can progress from experimental promise to evidence-based therapeutic application. Full article

Identifying the associations between non-coding RNAs and drug resistance (RDRAs) is crucial for uncovering resistance mechanisms and screening effective biomarkers. However, existing graph-based methods typically rely on purely data-driven learning and commonly assume a simplified noise independence hypothesis, overlooking the complex dependencies among feature, structural, and label noise in biomedical networks. This leads to issues such as spurious associations, poor generalization, and lack of interpretability for noisy association prediction tasks. To address these challenges, we propose Prior-RDRGSE, a prior-knowledge-guided dependency-aware graph learning framework. This framework integrates both dependency-aware graph noise modeling and domain knowledge into graph representation learning. Specifically, we first construct a heterogeneous bipartite graph and employ a deep generative inference encoder to jointly infer the underlying clean graph structure and the association signals, thereby explicitly modeling and purifying the intertwined complex noise within the network. Next, we design a resistance-semantics-conditioned interaction module that injects disease-specific and mechanism-related semantic priors into attention queries, explicitly guiding subnetwork interactions in a biologically plausible manner. Furthermore, we introduce a resistance consistency constraint based on KL divergence, which regularizes model training by aligning the learned association distribution with prior distributions derived from clinical and literature data. Comprehensive experiments demonstrate that Prior-RDRGSE achieves state-of-the-art performance in RDRA prediction and significantly outperforms existing methods. Full article

Background: The administration of direct oral anticoagulants to older adults requires careful risk stratification against a backdrop of polypharmacy and age-related renal function decline. The role of single nucleotide polymorphisms in cytochrome P450 genes and efflux transporters in this context remains a clinically understudied issue. This study aimed to investigate the association of ABCB1, CYP3A4, and CYP3A5 allelic variants with the safety of rivaroxaban therapy in geriatric patients with non-valvular atrial fibrillation (AF). Materials and Methods: This prospective cohort study consecutively enrolled 94 patients (mean age 83.2 ± 9.2 years). Rivaroxaban trough plasma concentrations ($C_{min,ss}$ ) were quantified using a validated high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) assay. Real-time polymerase chain reaction was utilized for the molecular genetic profiling of the ABCB1 (rs1045642, rs2032582), CYP3A4*22 (rs35599367), and CYP3A5*3 (rs776746) loci. Comorbidity severity and the spectrum of drug–drug interactions were evaluated as additional predictors. Results: Clinically relevant hemorrhagic complications were documented in 36.2% (n = 34) of the monitored patients. A significant association was established between the homozygous CC genotype at the ABCB1 rs1045642 locus and increased bleeding propensity (odds ratio [OR] 2.42; 95% CI: 1.02–5.74; p = 0.042), whereas the alternative TT variant was associated with a pronounced protective effect. No statistically significant correlations were identified for biotransformation isoenzyme markers (CYP3A4*22, CYP3A5*3). Anticoagulant metrics were comparably distributed across groups and showed no dependence on genetic status. The leading non-genetic factors associated with hemorrhage were advanced age (p < 0.0001), progressive glomerular filtration rate decline (CKD stages 3b–4; p = 0.0009), and pharmacokinetic/pharmacodynamic interference from the co-administration of amiodarone (OR 3.61), non-steroidal anti-inflammatory drugs, and antiplatelet agents. The validated HAS-BLED score demonstrated no predictive power within the comorbid conditions of this cohort (p = 0.052). Conclusions: The ABCB1 rs1045642 (C3435T) polymorphism is associated with the occurrence of hemorrhagic events. Implementing pharmacogenetic testing of the P-glycoprotein transporter combined with a rigorous audit of renal excretory function and concomitant therapy management may optimize the safety profile of rivaroxaban in geriatric practice. These findings warrant confirmation in a larger cohort. Full article

Highly aggressive gliomas remain difficult to treat because of their marked invasiveness, frequent recurrence, and association with glioma-related epilepsy. Increasing evidence suggests that ion channels expressed in glioma cells, including voltage-gated Na⁺ channels, large-conductance Ca²⁺-activated K⁺ (BK_Ca) channels, intermediate-conductance Ca²⁺-activated K⁺ (IK_Ca) channels, and inwardly rectifying K⁺ (Kir) channels, contribute to these malignant phenotypes and represent potential therapeutic targets. This perspective summarizes current evidence for eight representative drugs and phytoconstituents—perampanel, valproic acid, cilostazol, berberine, oxaliplatin, temozolomide, arecoline, and triptolide—that modulate these ion channels. Perampanel and valproic acid suppress voltage-gated Na⁺ current in glioma cells and may provide additional benefits in controlling glioma-associated epilepsy. Cilostazol activates BK_Ca channels, whereas berberine, oxaliplatin, and temozolomide inhibit IK_Ca channel activity. Arecoline suppresses IK_Ca and Kir channel activity, while triptolide inhibits Kir channels. These observations suggest that ion channel modulation may influence glioma cell proliferation, migration, invasion, and excitability. To complement the available experimental evidence, we performed molecular docking analyses as a hypothesis-generating approach to explore potential ligand–channel interactions. Because these computational predictions have not been experimentally validated, they should be interpreted cautiously and viewed as a framework for future mechanistic studies rather than definitive evidence of binding. We also discuss important translational considerations, including the limited clinical evidence and the toxicity profiles of several compounds. In particular, arecoline is associated with carcinogenicity and neurotoxicity, triptolide with significant systemic toxicity, berberine with poor oral bioavailability and potential drug interactions, and oxaliplatin with dose-limiting neurotoxicity. Overall, this perspective highlights ion channels as promising therapeutic targets in glioma while emphasizing the need for rigorous experimental validation and careful evaluation of safety before clinical translation. Full article

Human immunodeficiency virus (HIV) is one of the viruses that has co-evolved within human populations for a considerable time. With the evolution of new drug-resistant HIV strains, the necessity to discover novel drugs has become an issue of great concern, especially those that have increased binding affinities and inhibitory activity towards RT enzymes. This study used an in silico approach to identify potential HIV-RT inhibitory candidates from Origanum vulgare (oregano). An initial in silico screening of approximately 820 compounds was conducted, and based on molecular docking-derived binding energy scores, four compounds (IMPHY000687, IMPHY007084, IMPHY004619, and IMPHY012021), with docking scores of −9.42, −9.32, −9.24, and −9.23 kcal/mol, respectively, were selected as the top-ranked phytocompounds and were subsequently validated using multiple computational approaches. These compounds were geometrically optimized using quantum-chemical calculations, and detailed interaction analyses were performed using a redocking procedure. Reproducibility of the dynamic behavior was evaluated by carrying out independent replica molecular dynamics simulations for 300 ns each for all complexes. The ligand-dependent conformational dynamics were identified using RMSD and RMSF analyses, along with variations in positional changes during simulation times. PCA and FEL analyses helped in identifying the conformations sampled by the system under study. In addition, QM/MM calculations provided complementary information on the electronic characteristics of the individual protein–ligand systems. Machine learning-based quantitative structure–activity relationship (QSAR) prediction of experimentally validated HIV-RT inhibitors was applied to predict inhibitory potency, yielding predicted pIC50 values for the selected phytochemicals compared with the reference molecule. All in all, comprehensive computational analyses have ranked these phytochemicals as HIV-RT inhibitors that need further experimental verification. Full article

The transport mechanisms for substrates and nutrients within the heme pathway of the Toxoplasma gondii apicoplast remain poorly understood. However, studies on heme metabolic enzymes have employed disparate genetic manipulation approaches, limiting direct phenotypic comparisons among different enzymes. This research involved screening potential apicoplast proteins in Toxoplasma gondii by cross-referencing and analyzing protein–protein interaction networks. Within the heme enzyme pathway of the apicoplast, eight enzymes were found to be predominantly conserved in the Sarcocystide family. Utilizing the CRISPR-Cas9 system alongside a U1 snRNP-mediated gene-silencing approach, we developed inducible knockdown strains—iKD-PBGD, iKD-UROS, and iKD-UROD—targeting three key metabolic enzymes crucial for the parasite lytic cycle, as demonstrated through replication experiments. To investigate the transport mechanisms for heme-related nutrients or substrates, we knocked down these three enzymes, using TgGRA12 as an initial marker. Continuous fluorescence signals highlighted the parasitophorous vacuole (PV) membrane surrounding tachyzoites during both early and late replication stages, particularly at 48 h post-rapamycin treatment, indicating a transformation of the cyst-like PV resembling that in Toxoplasma gondii. Phenotypically, knockdown of these heme enzymes led to the formation of slowly replicating, cyst-like parasitophorous vacuoles. However, this morphological change did not significantly affect the acute virulence of the parasites in vivo, as determined by mouse survival assays. This study explored the functional roles of the three intermediate metabolic enzymes, offering a novel viewpoint on the gradual demise of Toxoplasma gondii as a potential target for drug development. Full article

Acne vulgaris is a multifactorial inflammatory disorder involving bacterial colonization, oxidative stress, and lipid-mediated inflammation, necessitating a comprehensive multitarget approach. This study evaluated the anti-acne potential of five morphological parts of Limonia acidissima L. using an integrated in vitro and in silico approach. Ultrasound-assisted extracts were evaluated for antibacterial activity against Cutibacterium acnes and Staphylococcus epidermidis, antioxidant activity using DPPH and ABTS assays, and total phenolic and flavonoid contents (TPC and TFC). TOPSIS was applied to minimize selection bias and identified the leaf extract as the optimal candidate (closeness coefficient = 0.88325). LC-MS/MS tentatively identified major metabolites, including vitexin, quercetin, cyanidin-3-O-galactoside, caffeate, methyleugenol, indole, and linolenic acid. Molecular docking predicted favorable interactions of linolenic acid with C. acnes KAS III (Rerank Score = −78.470) and 15-lipoxygenase (15-LOX) (Rerank Score = −101.025), as well as cyanidin-3-O-galactoside with S. epidermidis (Rerank Score = −109.588) and KEAP1 (Rerank Score = −132.253). SwissADME analysis further suggested favorable drug-likeness and skin-permeation profiles. Collectively, these findings support the potential of L. acidissima leaf extract as a promising multitarget anti-acne candidate. Full article

Alzheimer’s disease (AD) is an unremitting neurodegenerative disorder characterized by the presence of extracellular β-amyloid (Aβ)-containing neuritic plaques, intracellular tau-positive neurofibrillary tangles and loss of selected neurons in the brain. Evidence suggests that aggregation of Aβ and tau via synergistic interactions initiates a cascade of events, leading to development of AD pathology. Thus, many studies are being pursued to develop small molecules/drugs that can target both Aβ and tau as an effective AD treatment strategy. In this study, we evaluated effects of native PLGA nanoparticles on tau-mediated Aβ1-42 aggregation using biophysical, structural, spectroscopic and biochemical approaches. Our results show that 0N4R tau seeds enhanced Aβ1-42 aggregation, and that this effect is mitigated by native PLGA. Additionally, PLGA inhibited Aβ1-42 aggregation induced by both 0N4R and 2N4R tau isoforms. The presence of PLGA during the formation of tau seeds or pretreatment of tau seeds with PLGA attenuates subsequent Aβ1-42 aggregation. Interestingly, monomeric 0N4R tau, unlike 0N4R tau seeds, suppressed Aβ1-42 aggregation, which is diminished further by PLGA nanoparticles. However, we have not addressed the implications of native PLGA on tau/Aβ1-42 interaction using any cellular or animal models of AD. Nevertheless, our results reveal that tau seeds and monomeric tau can differentially influence Aβ1-42 aggregation, which is mitigated by native PLGA under in vitro conditions, providing a rationale to study it further under an in vivo paradigm to examine its significance in AD pathogenesis. Full article

Background: Liver cirrhosis is associated with portal hypertension and its gastrointestinal complications, but non-variceal gastroduodenal mucosal injury and its relationship to Helicobacter pylori (H. pylori) infection and hepatic disease severity remain incompletely characterized. Methods: This retrospective, cross-sectional study included 162 patients undergoing first upper gastrointestinal endoscopy (61 with cirrhosis, 101 controls), assessed using a composite gastroduodenal mucosal injury score (range 0–16) across the antrum, gastric corpus, duodenal bulb, and second duodenal portion. Results: Cirrhosis was independently associated with a higher injury burden after adjusting for H. pylori status, nonsteroidal anti-inflammatory drug (NSAID), antiplatelet, anticoagulant, and proton pump inhibitor (PPI) use (adjusted count ratio [aCR] = 1.33, 95% CI: 1.09–1.63, p = 0.006); and H. pylori infection was independently and separately associated with higher injury burden (aCR = 1.25, 95% CI: 1.01–1.54, p = 0.037), while none of the four medication classes showed an independent association. This excess injury was concentrated almost exclusively in the gastric corpus (adjusted aCR = 3.04, p < 0.0001), with no significant differences at other sites. Injury severity did not correlate with Child–Pugh class or tests of the liver’s biosynthetic capacity (all p > 0.05). Only patients with concurrent cirrhosis and H. pylori infection showed significantly elevated injury relative to unexposed controls (adjusted aCR = 1.87, 95% CI: 1.38–2.53, p < 0.0001), with a significant, exploratory cirrhosis × H. pylori interaction (aCR = 1.56, p = 0.037). Conclusions: Cirrhosis is therefore associated with a corpus-predominant pattern of gastroduodenal injury, compatible with, though not proof of, a portal hypertension-related mechanism, and shows a significant positive multiplicative interaction with concurrent H. pylori infection; given the exploratory nature of this analysis, these findings are hypothesis-generating and warrant prospective confirmation before informing endoscopic screening or infection-screening practice. Full article

Multiple myeloma (MM) is a blood cancer characterized by the accumulation of abnormal plasma cells within the bone marrow (BM). The neoplastic expansion progressively disrupts normal blood cell production by outcompeting healthy hematopoietic cells. The disease is characterized by terminally differentiated B cells that secrete antibodies as part of an adaptive immune response. A serious threat confronting small drug molecule therapy for MM is the lack of selective drug targeting, ultimately resulting in insufficient accumulation of drugs to target cells, and harmful off-target drug effects. We now report on the use of cellular lipid extracts (LEs) originating from two different human multiple myeloma (target) cell lines, RPMI 8226 and NCI H929, to develop RPMI 8226 LE- and NCI H929 LE-modified nanoliposomes, respectively. Other ingredients included phospholipid DOPC (dioleoyl-phosphatidylcholine) and/or Chol (cholesterol). Additional cell lines included non-target (Y79-retinoblastoma, U937-lymphoma, K562-GFP-chronic myeloid leukemia) and (off-target) normal healthy PBMCs—peripheral blood mononuclear cells. The LE-modified nanoliposomes stably incorporated various cytotoxic agents, demonstrating novel formulation characteristics and cell-interaction profiles. RPMI 8226 LE enhanced nanoliposome targeting to source-originating RPMI 8226 cells, with diminished uptake by Y79 and PBMCs. The inclusion of Chol reduced targeting to RPMI 8226 cells. The RPMI 8226 LE enhanced nano-formulation effects against RPMI 8226 cells, but not against the Y79 control. Consistent with these findings, RPMI 8226 LE-modified nano-formulations enhanced extracellular lactate dehydrogenase release against RPMI 8226 cells, but not against the Y79 control. NCI H929 LE material also enhanced targeting and nano-formulation effects against source and non-originating source tumor cells from the BM. Designing nanoliposomes to mimic tumor cell membranes may represent a powerful strategy to treat multiple myeloma. Significance: Cellular membrane lipid extracts derived from multiple myeloma cells enhanced targeting and cytotoxicity while limiting damage to normal healthy cells. The inclusion of LE materials in drug delivery systems may represent a promising strategy to enhance cellular targeting and drug therapy for multiple myeloma. Full article

Background: Metabolic disturbances have been implicated in intervertebral disc degeneration (IVDD) and low back pain, but the contribution of circulating metabolites remains uncertain. Objectives: We examined associations of genetically proxied plasma metabolites and metabolite ratios with IVDD outcomes defined at different anatomical locations and with a related pain phenotype. Methods: Summary statistics for metabolite exposures were obtained from the Canadian Longitudinal Study on Ageing (CLSA) plasma metabolome genome-wide association study (GWAS). The outcomes were Intervertebral Disc Degeneration of Cervical Spine (IVDD_Cervical), Intervertebral Disc Degeneration of Thoracic, Thoracolumbar, and Lumbosacral Spine (IVDD_TTL), and Low Back Pain (Pain_Lowback). IVDD_Cervical and IVDD_TTL represented IVDD outcomes defined at different anatomical locations of the spine, whereas Pain_Lowback was analysed separately as an IVDD-related pain phenotype. One genome-wide significant sentinel single-nucleotide variant (SNV) was used for each exposure, and Mendelian randomization (MR) estimates were calculated with the Wald ratio. The within-outcome Bonferroni threshold was 6.25 × 10⁻⁴. Results: Eighty metabolites and metabolite ratios were evaluated. Two associations were significant, both for IVDD_TTL. Higher genetically proxied dimethylarginine (SDMA + ADMA), mapped to DDAH1, was associated with lower IVDD_TTL risk (odds ratio [OR] = 0.80; 95% confidence interval [CI]: 0.72–0.90; p = 2.5 × 10⁻⁴), whereas higher alpha-hydroxyisovalerate, mapped to LDHA, was associated with higher risk (OR = 1.08; 95% CI: 1.04–1.13; p = 4.6 × 10⁻⁴). No significant association was identified for IVDD_Cervical or Pain_Lowback; 23 associations were classified as suggestive significant. DrugBank annotation identified compounds interacting with DDAH1 and LDHA. Conclusions: The results highlight DDAH1-linked methylarginine metabolism and LDHA-linked glycolytic and lactate-related biology as candidate pathways for IVDD_TTL. Findings for IVDD_Cervical, Pain_Lowback, and cross-outcome overlap remain exploratory. Full article