Search Results (2,216)

Artificial intelligence (AI) and machine learning (ML) are reshaping cancer research and care. In pediatric oncology, early evidence—most robust in imaging—suggests value for diagnosis, risk stratification, and assessment of treatment response. Pediatric endocrine tumors are rare and heterogeneous, including intra- and extra-adrenal paraganglioma (PGL), adrenocortical tumors (ACT), differentiated and medullary thyroid carcinoma (DTC/MTC), and gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN). Here, we provide a pediatric-first, entity-structured synthesis of AI/ML applications in endocrine tumors, paired with a methods-for-clinicians primer and a pediatric endocrine tumor guardrails checklist mapped to contemporary reporting/evaluation standards. We also outline a realistic EU-anchored roadmap for translation that leverages existing infrastructures (EXPeRT, ERN PaedCan). We find promising—yet preliminary—signals for early non-remission/recurrence modeling in pediatric DTC and interpretable survival prediction in pediatric ACT. For PGL and GEP-NEN, evidence remains adult-led (biochemical ML screening scores; CT/PET radiomics for metastatic risk or peptide receptor radionuclide therapy response) and serves primarily as methodological scaffolding for pediatrics. Cross-cutting insights include the centrality of calibration and validation hierarchy and the current limits of explainability (radiomics texture semantics; saliency ≠ mechanism). Translation is constrained by small datasets, domain shift across age groups and sites, limited external validation, and evolving regulatory expectations. We close with pragmatic, clinically anchored steps—benchmarks, multi-site pediatric validation, genotype-aware evaluation, and equity monitoring—to accelerate safe, equitable adoption in pediatric endocrine oncology. Full article

Ovarian cancer (OC), the third most common gynecologic malignancy, is characterized by high mortality largely driven by chemotherapy resistance, leading to recurrence and metastasis. Using transcriptomic data from GSE73935, we constructed a weighted gene co-expression network and identified eight hub genes (IGF1R, CDH2, PDGFRA, CDKN1A, SHC1, SPP1, CAV1 and FGF18) associated with cisplatin resistance, among which CDH2 emerged as the most clinically relevant candidate. CDH2 demonstrated moderate diagnostic potential (AUC = 0.792) and was markedly upregulated in cisplatin-resistant A2780/CP70 cells. Independent validation using clinical single-cell RNA-seq data (GSE211956) confirmed its selective enrichment in resistant tumor cell subpopulations. Gene set enrichment analysis linked elevated CDH2 expression to p53 signaling, DNA replication, nucleotide excision repair, and Toll-like receptor pathways, with qPCR supporting upregulation of key downstream genes in resistant cells. Immune deconvolution further indicated that high CDH2 expression correlated with increased infiltration of NK cells, Tregs, macrophages, and neutrophils, and immunohistochemistry verified CDH2 overexpression in cisplatin-resistant tissues. In addition, virtual screening and drug sensitivity profiling identified several FDA-approved agents with potential relevance to CDH2-associated drug response. These findings indicate that CDH2 may serve as a candidate marker associated with cisplatin response in OC, and its association with immune cell infiltration provides further insight into mechanisms potentially underlying chemoresistance. Full article

Background/Objectives: Neuropathic pain remains a significant clinical challenge, with current treatments often providing inadequate relief and adverse effects. Sigma receptors (SRs) modulate nociception and have emerged as potential therapeutic targets for neuropathic pain. Although putative sigma-1 receptor (S1R) ligands have demonstrated analgesic efficacy in preclinical models, their in vivo efficacy and safety profiles require further clarification. Methods: Analogs of well-known selective S1R ligand UVM147 were synthesized using 3-component Ugi reactions and examined in vitro for receptor affinity in radioligand competition binding assays and in vivo with mouse models of neuropathic and inflammatory pain and adverse effects. Results: Three novel heterocyclic compounds (RO-4-3, RO-5-3, and RO-7-3) displayed in vitro nanomolar affinity with varying selectivity for both SR subtypes (S1R and S2R). When screened in vivo at a dose of 30 mg/kg s.c. in mice first subjected to chronic constriction injury (CCI), RO-5-3 and RO-7-3 possessed anti-allodynic potential, while UVM147 was inactive. Upon full characterization, RO-5-3 significantly attenuated mechanical allodynia in a dose-dependent manner, while RO-7-3 was ineffective at higher doses. Both compounds dose-dependently attenuated nociceptive behaviors in the mouse formalin assay. RO-5-3 induced mild respiratory depression without impairing locomotor activity, whereas RO-7-3 caused transient respiratory depression and locomotor impairment. Additionally, RO-5-3, but not RO-7-3, induced conditioned place aversion consistent with potential S2R involvement. Conclusions: RO-5-3 exerts antinociceptive and anti-allodynic effects with minimal adverse behavioral effects, supporting the role of SRs in pain modulation. These results add to growing evidence supporting the development of SR ligands as efficacious therapeutics for neuropathic pain with fewer clinical liabilities. Full article

Background: Melanin protects skin and hair from the effects of ultraviolet (UV) radiation damage, which contributes to all forms of skin cancer, including melanoma. Human melanocytes produce two main types of melanin: eumelanin provides effective photoprotection, and pheomelanin offers less protection against UV-induced skin damage. The agouti signaling protein (ASIP) antagonizes the melanocortin-1 receptor (MC1R), hinders melanocyte signaling, and shifts pigmentation toward pheomelanin, promoting UV vulnerability. In this study, we aim to discover compounds that inhibit ASIP–MC1R interaction and effectively preserve eumelanogenic signaling. Methods: The ASIP–MC1R interface-based pharmacophore model from ASIP is implicated in MC1R receptor protein engagement. We performed virtual screening with a validated pharmacophore model for ~4000 compounds curated from ZINCPharmer and applied drug-likeness filters, viz. ADMET and toxicity profiling tests. Further, the screened candidates were targeted for docking to the ASIP C-terminal domain corresponding to the MC1R-binding moiety. Top compounds underwent a 100-nanosecond (ns) run of molecular dynamics (MD) simulations to assess complex stability and persistence of key contacted residues. Results: Sequential triage, including pharmacophore, ADME–toxicity (ADMET), and docking/ΔG, yielded a focused group of candidates against ASIP antagonists with a favorable fit value. The MD run for 100 ns supported pose stability at the targeted pocket. Based on these predictions and analyses, compound ZINC14539068 was screened as a new potent inhibitor of ASIP to preserve α-MSH-mediated signaling of MC1R. Conclusions: Our in silico pipeline identifies ZINC14539068 as a potent inhibitor of ASIP at its C-terminal interface. This compound is predicted to disrupt ASIP–MC1R binding, thereby maintaining eumelanin-biased signaling. These findings motivate experimental validation in melanocytic models and in vivo studies to confirm pathway modulation and anti-melanoma potential. Full article

Background: Depression and diabetic neuropathy (DN) commonly complicate diabetes and impair glycemic control and quality of life. Ketamine and its S-enantiomer, esketamine, provide rapid antidepressant and analgesic effects, yet diabetes-related pathophysiology and co-therapies may modify exposure, response, and safety. Methods: We conducted a scoping review following PRISMA-ScR. MEDLINE/PubMed, CINAHL, and APA PsycInfo were searched (January 2020–31 May 2025). Eligible human and animal studies evaluated ketamine, esketamine, or norketamine in the context of diabetes (type 1 [T1DM], type 2 [T2DM], gestational [GDM]), or DN, and reported psychiatric, analgesic, metabolic, or mechanistic outcomes. Two reviewers independently screened and charted data; no formal risk-of-bias assessment was performed. Results: Eleven studies met inclusion criteria: four human case reports/series (three T1DM, one T2DM), one randomized trial in GDM, two narrative reviews of topical ketamine for DN, and four preclinical rodent studies using streptozotocin- or diet-induced diabetes models. Short-term improvements were reported for treatment-resistant depression and neuropathic pain, including opioid-sparing postoperative analgesia in GDM. Glycemic effects varied across settings, with both hyperglycemia and hypoglycemia reported. Mechanistic and clinical drug–drug and drug-disease interactions (particularly involving metformin, GLP-1 receptor agonists, SGLT2 inhibitors, and CYP3A4/CYP2B6 modulators) remain insufficiently studied. We outline a forward-looking population pharmacokinetic (popPK) and pharmacokinetic-pharmacodynamic (PK-PD) research agenda, including priority covariates (eGFR, hepatic function, inflammatory status, HbA1c, genotype, co-medications) and sparse-sampling windows for future model-informed precision dosing. Conclusions: Current evidence supports cautious, selective use of ketamine for refractory depression and DN within multidisciplinary diabetes care. Purpose-built popPK/PK-PD studies in both human and preclinical diabetic models cohorts are needed to quantify variability, define drug–disease–drug interactions and glycemic risk, and inform individualized dosing strategies. Full article

Background/Objectives: As precision medicine advances, attention to sex and gender determinants across epidemiological and clinical domains has intensified. However, in the audio-vestibular field, knowledge on sex- and gender-related aspects remains relatively limited. The main aim of this review has been to analyze the available gender medicine-based evidence in vestibular disorders. In particular, our investigation considered the following: (i) pathophysiology and clinical presentation, including differences in predominant signs and symptoms, diagnostic modalities and findings, underlying biological mechanisms associated with vestibular disorders across sex-specific groups; (ii) prognostic variables, including response to treatment, recovery rates, and long-term functional outcomes; (iii) the potential role of sex- and gender-specific diagnostic and therapeutic approaches in the management of vestibular disorders. Methods: Our protocol was registered on PROSPERO (CRD42025641292). A literature search was conducted screening PubMed, Scopus and Web of Science databases. After removal of duplicates and implementation of our inclusion/exclusion criteria, 67 included studies were identified and analyzed. Results: Several studies reported a higher incidence of vestibular dysfunctions among females, with proposed associations involving hormonal fluctuations, calcium metabolism and vitamin D. Estrogen receptors within the inner ear and their regulatory effects on calcium homeostasis have been proposed as potential mechanisms underlying these sex-specific differences. Furthermore, lifestyle factors, comorbidities and differential health-seeking behaviors between males and females may also modulate disease expression and clinical course. Conclusions: Gender-specific variables could not be independently analyzed because none of the included studies systematically reported gender-related data, representing a limitation of the available evidence. Current evidence suggests the presence of sex-related differences in the epidemiology and clinical expression of vestibular disorders, but substantial gaps remain regarding mechanisms, outcomes, and clinical implications. Future research should prioritize prospective, adequately powered studies specifically designed to assess sex and gender influences, integrating biological, psychosocial, and patient-reported outcomes, and adopting standardized sex- and gender-sensitive reporting frameworks. Full article

Background and Objectives: Contrast-enhanced mammography (CEM) provides both morphological and functional information and may reflect breast cancer biology similarly to Magnetic Resonance Imaging (MRI). Materials and Methods: This single-center retrospective study included 399 women with Breast Imaging Reporting and Data System (BI-RADS) category 0 screening mammograms who subsequently underwent CEM. A total of 76 malignant lesions (68 invasive cancers, 8 ductal carcinoma in situ (DCIS)) with complete imaging and pathology data were analyzed. Invasive cancers were classified into luminal A, luminal B, luminal B/Human Epidermal Growth Factor Receptor 2 (HER2)-positive, HER2-enriched, and triple-negative, and grouped as luminal (Group 1) versus HER2-positive/triple-negative (Group 2). Results: Luminal subtypes predominated (47 of 68, 69%), while 21 of 68 (31%) were HER2-positive or triple-negative. Most cancers appeared as masses with spiculated margins and heterogeneous enhancement. Significant differences were observed in mass shape (p = 0.03) and internal enhancement (p = 0.01). Luminal tumors were more often irregular and spiculated with heterogeneous enhancement, whereas the HER2-positive/triple-negative tumors more frequently appeared round with rim or homogeneous enhancement. Deep learning-derived malignancy scores (iCAD ProFound AI^®) demonstrated good diagnostic performance (area under the curve (AUC) = 0.744, 95% confidence interval (CI) 0.654–0.821, p < 0.001). The median AI score was significantly higher in malignant compared with benign lesions (70% [interquartile range (IQR) 47–93] vs. 38% [IQR 25–61]; Mann–Whitney U test, p < 0.001). Among malignant lesions, iCAD scores varied across molecular subtypes, with higher median values observed in Group 1 versus Group 2 (87% vs. 55%), although the difference was not statistically significant (Mann–Whitney U test, p = 0.35). Conclusions: CEM features mirrored subtype-specific phenotypes previously described with MRI, supporting its role as a practical tool for enhanced tumor characterization. Although certain imaging and AI-derived parameters differed descriptively across subtypes, no statistically significant differences were observed. As deep-learning models continue to evolve, the integration of AI-enhanced CEM into clinical workflows holds strong potential to improve lesion characterization and risk stratification in personalized breast cancer diagnostics. Full article

Background/Objective: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) exhibit neuroprotective properties in preclinical models of Alzheimer’s disease (AD), reducing amyloid accumulation, neuroinflammation, and insulin resistance within the brain. However, clinical evidence regarding their cognitive effects in AD and mild cognitive impairment (MCI) remains inconclusive. To evaluate the effects of GLP-1 RAs on cognitive outcomes in patients with AD or MCI due to AD. Methods: A systematic review was conducted according to PRISMA 2020 and registered in PROSPERO (CRD420251143171). Although the original registry was broad, the identification of a small set of homogeneous randomized controlled trials (RCTs) during screening, prior to data extraction, allowed for a random-effects meta-analysis of cognitive outcomes. RCTs enrolling adults with clinically or biomarker-confirmed AD or MCI were included. Interventions comprised liraglutide or exenatide compared with placebo. Standardized mean differences (SMD) in global cognitive scores were pooled using a random-effects model (restricted maximum likelihood [REML] estimator with Hartung–Knapp adjustment). Results: Three randomized trials (n = 278 participants; 51% women; mean age 68 ± 7 years) met inclusion criteria. Treatment duration ranged from 26 weeks to 18 months. Pooled analysis revealed no significant effect of GLP-1 RAs on global cognition compared with placebo −0.21 (95% CI −0.81 to 0.38; I² = 47%; τ² = 3.77). Sensitivity analyses restricted to liraglutide or studies ≥ 12 months yielded similar results. Conclusions: Current randomized evidence does not support cognitive improvement with GLP-1 RAs in AD or MCI. Full article

Bacteriophage therapy, which employs bacterial viruses to selectively eliminate pathogenic bacteria, has re-emerged as a promising strategy in the face of increasing antimicrobial resistance. However, its widespread clinical implementation is constrained by concerns regarding safety, standardisation, and predictable efficacy. In this review, we examine the key role of genomics in transforming phage therapy from an empirical practice into a standardised and personalised modality of contemporary medicine. We describe how whole-genome sequencing (WGS) provides a basis for safety assessment by enabling systematic screening to exclude virulence factors, antibiotic resistance genes, and markers of lysogeny. WGS also facilitates the prediction of therapeutic efficacy and supports more rational phage selection by identifying receptor-binding proteins and characterising bacterial defence systems. In clinical settings, WGS data are increasingly used to monitor the evolution of bacterial populations and to adapt phage cocktails during treatment, thereby supporting personalised, adaptive phage therapy. Looking ahead, further progress is likely to come from integrating synthetic biology and artificial intelligence to engineer phage-based therapeutics with programmable specificity and predictable properties. Together, these developments are shaping a new paradigm of phage therapy as a scientifically grounded, standardised and controlled strategy to treat infections caused by antibiotic-resistant bacteria. Full article

Glucagon is a peptide hormone secreted by pancreatic alpha cells which elevates blood glucose and plays a critical role in diabetes onset and homeostasis. The accurate assessment of glucagon concentration is challenging due to its structural similarity with other hormones, causing cross-reactivity in antibody-based methods. Rapid and specific glucagon detection is essential, particularly during hypoglycemia. This study aimed to develop glucagon-specific probes combining high specificity, rapid detection, and ease of operation. We designed novel peptide-based probes by screening glucagon-binding peptides from the glucagon receptor sequence using a peptide array method. This strategy, based on receptor amino acid sequences, can be applied to the identification of binding peptides for other hormones, expanding its potential utility. The screened peptides were conjugated with fluorescent dyes to create probes enabling detection within 30 min. The developed probes demonstrated superior specificity for glucagon relative to similar sequence analogs compared with conventional antibody-based methods, with detection limits in the nanomolar range. This study represents a proof-of-concept approach for rapid and highly specific glucagon detection. However, further optimization of probe sensitivity and validation under physiological conditions will be required before clinical or diagnostic application. These improvements in the probe’s properties will enable the reliable blood glucagon detection and accurate diagnostic assessment of diabetes-related diseases. Full article

Transient receptor potential vanilloid 1 (TRPV1) channels are critical mediators of cutaneous allergic inflammation, contributing to pruritus, erythema, and hypersensitivity in allergic skin disorders. Despite their therapeutic potential, clinically available TRPV1 inhibitors remain limited, leaving effective treatment options lacking. Here, we focused on a self-constructed virtual pentapeptide library and identified a highly selective TRPV1 inhibitor that demonstrated pronounced anti-allergic effects in human skin assays. Through structure-based virtual screening of approximately 200,000 peptide conformations, five candidate pentapeptides, especially P5 (DQKNC), exhibited the inhibition. Electrophysiological recordings showed that P5 inhibited TRPV1 currents with nanomolar potency, while exhibiting negligible effects on major cardiac and neuronal ion channels, highlighting its favorable selectivity and safety profile. In capsaicin-induced human skin hypersensitivity tests, topical P5 significantly reduced burning pain, erythema, and pruritus, with simultaneous application providing the most robust relief. These findings reveal a short peptide with strong TRPV1 selectivity and demonstrable efficacy in alleviating skin inflammation and allergic responses, supporting the notion that rationally designed pentapeptides may represent promising topical therapeutics for allergic skin disorders. Full article

Breast cancer (BC) is a malignant tumor that develops in the mammary gland due to uncontrolled cell proliferation. Estrogen receptor (ER) signaling, mediated by 17β-estradiol (E2), plays a crucial role in regulating cell proliferation, differentiation, and survival. Specifically, the binding of E2 to the estrogen receptor alpha (ERα) increases cell proliferation. Conversely, selective estrogen receptor beta (ERβ) agonists inhibit cancer cell proliferation by suppressing the expression of oncogenes, making ERβ an important therapeutic target. Given the urgent need for targeted and effective therapies for BC, we implemented a strategy based on multicomplex pharmacophores modeling of ERβ (MPMERβ) and ERα (MPMERα), performing a virtual cross-screening of databases of clinically approved and experimental drugs to identify those with high affinity and stereoelectronic complementarity with the ERβ agonist pharmacophore hypothesis. The implementation of a chemoinformatic strategy enabled the identification of Sobetirome, Labetalol, and Procaterol as molecular hits on the ERβ pharmacophore map. Procaterol showed the most significant antiproliferative activity in vitro assays, with IC₅₀ values of 21.26 and 36.10 µM in MCF-7 and MDA-MB-231, respectively. It is imperative to note that these findings require experimental validation of the ERβ activation pathways to strengthen the possible therapeutic repurposing of the drugs selected through our in silico approach. Finally, this strategy not only facilitates drug repurposing under in silico simulation but also provides valuable information for the rational design of new drugs against BC. Full article

Type 2 diabetes mellitus (T2DM) is characterised by chronic hyperglycaemia and accumulation of advanced glycation end products (AGEs), driving interest in food-derived peptides as safer multifunctional modulators. Coconut milk is a promising source, but its anti-hyperglycaemic and anti-glycation potential remains largely unexplored. Here, proteins from coconut cream, skimmed and insoluble fractions of coconut milk were enzymatically hydrolysed, and the resulting peptides were profiled by nano-ESI-Orbitrap-LC-MS/MS. One hundred and fourteen peptides were identified and screened in silico against α-glucosidase, α-amylase, aldose reductase and the receptor for AGEs (RAGE). Two peptides, MQIFVK and ADVFNPR, showed the most favourable docking scores and physicochemical properties. However, ADVFNPR inhibited all 3 diabetic targets & RAGE. Molecular dynamics analysis showed that both peptides bind stably to the diabetic targets. Both peptides were synthesised and evaluated in vitro. ADVFNPR significantly inhibited α-glucosidase, α-amylase and aldose reductase with lower IC₅₀ values and displayed competitive inhibition kinetics. It also scavenged methylglyoxal, 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and superoxide radicals at low EC₅₀ values, and showed low hemolytic activity in human erythrocytes. These findings indicate that coconut milk contains multifunctional peptides with anti-hyperglycaemic, anti-glycation and antioxidant activities that may be further developed as food-derived adjuncts for managing T2DM and glycation-related complications. Full article

Toll-like receptor 7 (TLR7) and Stimulator of Interferon Genes (STING) ligands possess a series of immunomodulatory effects such as anti-infection, anti-tumor, and autoimmune-disease-alleviating effects. In this study, porcine TLR7 (pTLR7) and porcine STING (pSTING) were selected as targets, and molecular docking and virtual screening methods were used for screening of dual-target livestock immunomodulators. Finally, two compounds were screened with molecular docking scores higher than the positive control compounds. They have good binding ability with pTLR7 and pSTING proteins, as well as satisfactory predictive safety and pharmacokinetic properties. Molecular dynamics (MD) simulation results also indicated that the above ligands can form stable complexes with two target proteins. The average binding free energies of compound 2 with pTLR7 and pSTING were −28.65 kcal/mol and −30.12 kcal/mol, respectively, and of compound 7 with pTLR7 and pSTING were −35.93 kcal/mol and −31.70 kcal/mol, respectively, which were comparable to that of positive control ligands. The similarity of target proteins between pigs, humans, and mice, as well as the interactions between ligands and TLR7 and STING in different species, were analyzed. And analysis of predicted structure–activity relationship (SAR) was conducted. Briefly, compound 2 and compound 7 were predicted to form stable complexes with pTLR7 and pSTING, with satisfactory predicted physicochemical properties and pharmacokinetic characteristics, and represented candidates for experimental validation. This study supplies a research basis for the development, design, and structural modification of immune enhancers for animals. Full article

Neurotrophic tyrosine receptor kinase (NTRK) fusions function as oncogenes and have been targeted by TRK inhibitors with excellent clinical outcomes. The international expert consensus recommends immunohistochemical (IHC) screening for TRK protein followed by next generation sequencing (NGS) to measure expression of NTRK fusions for tumors with low NTRK fusion expression. To confirm the clinical utility of this recommendation in esophageal and gastric cancers, total TRK protein expression was measured by IHC using anti-pan-TRK antibody in 254 esophageal squamous cell carcinoma (ESCC) and 401 gastric adenocarcinoma (GA) samples. Subsequently, DNA-based NGS and fluorescence in situ hybridization (FISH) were performed for tumors expressing TRK to measure NTRK fusion expression. Further, expression of NTRK fusions was evaluated in esophageal and gastric cancers using public databases. IHC staining revealed TRK was expressed in 10 out of 254 ESCC and 0 out of 401 GC cases. NGS and FISH analyses were performed for 10 TRK positive ESCC cases, identifying that none of these cases harbored NTRK fusions. In silico analyses further confirmed that NTRK fusions are rarely present in esophageal and gastric cancers. IHC screening for TRK protein is recommended to detect NTRK fusions, but this method may include many false-positives cases based on the sequencing analysis. Full article