Search Results (17,093)

Background: Staphylococcal bloodstream infections (BSIs) and infective endocarditis (IE) are associated with high morbidity and mortality. Among the different antimicrobial combination strategies proposed to enhance antibacterial activity, the association of daptomycin and ceftobiprole may be valuable. The aim of this study was to assess the PK/PD target attainment, safety, and clinical outcomes of such combination therapy for BSI and IE treatment. Methods: This retrospective monocentric study included adult patients with targeted treatment of staphylococcal BSI or IE with daptomycin plus continuous infusion (CI) ceftobiprole. Therapeutic drug monitoring (TDM) was performed for both agents, including Bayesian estimation of daptomycin 24 h area under the concentration–time curve (AUC_24h). PK/PD targets were defined as daptomycin AUC_24h/MIC ≥666 and ≥1081, and ceftobiprole steady-state concentration/MIC ≥4. Dose adjustments, safety, microbiological response, and clinical outcomes were assessed. Results: Twenty-three patients (11 BSI and 12 IE) were included. Methicillin-resistant Staphylococci were identified in 91.3% of cases. At first TDM assessment, daptomycin PK/PD targets were achieved in all patients, while ceftobiprole targets were achieved in 91.6% of BSI cases and in all IE cases. PK-/PD-guided dose de-escalation was frequently feasible. Clinical cure was observed in 77.8% of evaluable patients with BSI and in 91.7% with IE. Creatine phosphokinase elevations occurred in two patients, while hyper-eosinophilia was observed in 69.6% and was manageable with monitoring. Conclusions: Targeted therapy with daptomycin plus CI ceftobiprole achieved high PK/PD target attainment and favorable clinical outcomes in staphylococcal BSI and IE. TDM and model-informed precision dosing may enable dose optimization and may improve the balance between efficacy and safety. Multicenter studies are warranted. Full article

Background/Objectives: Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is linked to poorer overall survival and a higher risk of brain metastases compared to HER2-negative breast cancer. Current preclinical studies lack robust HER2+ metastatic syngeneic mouse models for investigating targeted and immunomodulatory therapies. This study aims to develop effective HER2+ mouse models to investigate response dynamics to HER2-targeted therapy and immunotherapy. Methods: The human HER2 gene (WT or mutant p.A775_G776insYVMA, GFP-tagged at the C-terminus) was introduced into triple-negative breast cancer (TNBC) mouse mammary carcinoma cells with known metastatic potential (4T1 and EO771) via lentiviral transduction. HER2 expression and phosphorylation were analyzed using Western blotting and immunohistochemistry. Tumors were treated with HER2-targeted therapy (trastuzumab and tucatinib), immune checkpoint blockade (anti-PD-1 and anti-CTLA-4), and anti-HER2 antibody–drug conjugate (ADC) to evaluate treatment efficacy. Metastatic potential was assessed with brain fluorescence imaging. Statistical analysis included ANOVA and Kaplan–Meier tests. Results: Newly established lines demonstrated expression of HER2+, with HER2^YVMA lines showing higher phosphorylation than HER2^WT lines. Cells were tumorigenic, demonstrating in vivo tumor take rates at 100% for 4T1-HER2 and 15–30% for EO771-HER2. HER2 overexpression led to a 30% increase in spontaneous brain metastasis in the 4T1-HER2 models. Trastuzumab alone did not reduce primary tumor size but significantly reduced brain GFP signal by 17% ± 8% and 26% ± 7% in the 4T1-HER2^WT and 4T1-HER2^YVMA models, respectively. Combinational therapies with anti-HER2 therapy and immune checkpoint blockade effectively suppressed primary tumor growth and prolonged survival in EO771-HER2^YVMA model. T-Dxd, but not T-DM1, demonstrated partial treatment response in the EO771-HER2^WT model. Conclusions: HER2+ syngeneic tumor models were developed that spontaneously metastasize to the brain and demonstrate variable responses to immunotherapies and ADCs. These models are valuable for advancing molecular imaging modalities for HER2+ brain metastasis, studying blood–brain barrier penetration of HER2-targeted drugs, and exploring the combination of therapies, including immunotherapy. Full article

Background/Objectives: Programmed death ligand 1 (PD-L1) is often overexpressed in triple-negative breast cancer (TNBC), where it helps the tumor evade the immune system and promotes tumor growth. Interleukin-24 (IL-24) is recognized for its anti-tumor activity, although its role in immune regulation remains unclear. In this study, we examined the role of IL-24 in regulating PD-L1 and its anti-cancer activity in TNBC cells. Methods: The study used TNBC cell lines treated with IL-24, delivered via a non-replicating adenovirus vector expressing the IL-24 gene. Assays included MTT for cell viability, Annexin V for apoptosis, Western blot for protein analysis, and qRT-PCR for mRNA analysis. Results: We found that the highly aggressive MDA-MB-231 cells had significantly higher PD-L1 levels. We discovered that treatment with IL-24 reduced cell growth, induced apoptosis, and significantly decreased PD-L1 protein levels in MDA-MB-231 cells. Mechanistically, we identified PKR, also known as eukaryotic translation initiation factor 2 alpha kinase 2, as a key mediator of IL-24–induced PD-L1 suppression. Additionally, doxorubicin, a primary chemotherapy drug used to treat triple-negative breast cancer, decreases PD-L1 expression and increases the sensitivity when combined with IL-24. Conclusions: In this study, we show that IL-24 decreases PD-L1 expression in MDA-MB-231 cells through PKR activation, enhances the anti-tumor effects of Doxorubicin, and may enable lower doses that reduce toxicity and further decrease PD-L1 levels. These findings suggest that IL-24 could serve as a valuable target for therapeutic intervention and suggest that it can improve doxorubicin’s effectiveness against aggressive breast cancer. Full article

Parkinson’s disease (PD) is associated with progressive gait deterioration; however, widely used clinical scales such as the Hoehn & Yahr (H&Y) stage are limited in capturing continuous severity changes due to subjectivity and discrete grading. This study proposes a two-stage explainable AI framework using vertical ground reaction force (VGRF) signals to achieve reproducible PD detection and continuous severity estimation. In the first stage, three deep learning models, temporal convolutional network (TCN), BiGRU with attention, and FCNN-Transformer, were trained using windowed VGRF signals under repeated subject-wise data segmentation. All models achieved high discrimination performance (AUC ≥ 0.93), with FCNN-Transformer showing the highest mean AUC (0.940) and statistically superior performance (paired Wilcoxon test, p < 0.05). Stability-based explainable AI using Integrated Gradients consistently identified variability-related VGRF features as the most informative, which were also significantly different between groups at the data level (p < 0.001, FDR-corrected). In the second stage, XGBoost regression was applied to PD subjects to predict continuous H&Y severity, achieving strong correlation with clinical grades (Spearman ρ = 0.921, p < 0.001), low error (MAE = 0.158, RMSE = 0.241), and high determination (R² = 0.953). This shows that gait-based features are a sensitive enough signal to continuously quantify disease progression. In addition, in the TREND prospective longitudinal cohort (n = 696), wearable walking indicators differed significantly from those of non-patients prior to diagnosis, and a decline in walking pace was observed approximately four years before Parkinson’s disease diagnosis, providing the basis for early screening and monitoring using gait-based digital biomarkers. These results demonstrate that gait-based digital biomarkers can objectively quantify both PD presence and disease progression. The proposed framework provides a reproducible, explainable, and clinically interpretable AI-based decision support approach for PD assessment. Full article

Background/Objectives: The aztreonam/avibactam combination represents a promising therapeutic option for severe infections caused by multidrug-resistant Gram-negative pathogens, particularly in critically ill patients. Due to marked pharmacokinetic variability and the need to achieve joint pharmacokinetic/pharmacodynamic (PK/PD) targets of both agents, therapeutic drug monitoring (TDM) may play a pivotal role in optimizing treatment. This study aimed to develop and validate two rapid, accurate, and sensitive UHPLC–qTOF MS/MS sequential methods for quantifying aztreonam and avibactam in human plasma, suitable for routine clinical TDM. Methods: Plasma concentrations were determined by means of ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC–qTOF MS/MS), operating in positive and negative electrospray ionization modes for aztreonam and avibactam, respectively. Sample preparation consisted of protein precipitation with isotopically labeled internal standards. The method’s validation was performed according to the European Medicines Agency guidelines, by assessing selectivity, linearity, precision, accuracy, recovery, matrix effects, carry-over, and stability. Clinical applicability was evaluated by reprocessing plasma samples, which were already previously collected for routine clinical practice from 20 hospitalized patients undergoing treatment with ceftazidime-avibactam plus aztreonam. Results: The methods showed excellent linearity (R² ≥ 0.999) over ranges of 0.2–100 µg/mL for aztreonam and 0.1–50 µg/mL for avibactam. Lower limits of quantification were 0.2 µg/mL and 0.1 µg/mL, respectively. Intra- and inter-day precision and accuracy met the EMA criteria at all of the quality control levels. Extraction recovery exceeded 90% for both analytes, and matrix effects were effectively compensated by internal standards. Stability testing highlighted the need for careful sample handling, particularly for aztreonam under repeated freeze–thaw conditions. Clinical application revealed substantial inter-individual variability in steady-state concentrations. Conclusions: The validated UHPLC–qTOF MS/MS assays provide robust and sensitive sequential quantification of aztreonam and avibactam in human plasma, supporting TDM-guided dose optimization in clinical practice. Full article

Green synthesis of nanoparticles has become one of the most popular research areas in recent decades due to its environmentally friendly nature and the minimization of harmful chemical by-products. This review focuses on the mechanism of palladium nanoparticle (PdNP) biosynthesis using bacteria, fungi, algae, and plants, and their potential biological activities, such as antibacterial, anticancer, antioxidant, and other properties, with the aim of their further biomedical applications. The role of various biomolecules in these processes is also discussed. Full article

Recent revisions of personality disorder (PD) classifications have moved from categorical diagnoses toward dimensional models, raising renewed questions about the nosological status and clinical utility of borderline personality disorder (BPD). This narrative review traces the development of the borderline construct from early descriptions of patients positioned between neurosis and psychosis, through its theoretical consolidation within the concept of borderline personality organization, to the operationalization of BPD in DSM-III and subsequent diagnostic revisions. A central section summarizes contemporary controversies regarding the validity and utility of BPD features. Arguments for abandoning the diagnosis emphasize the absence of a distinct borderline factor in factor analytic studies, the tendency of the construct to capture fluctuating symptoms and patterns of behaviour rather than stable maladaptive personality traits, the stigmatizing and non-selective use of the label, and the lack of disorder-specific treatment approaches. In contrast, converging evidence supports the view that core borderline symptoms frequently function as markers of general PD pathology and of the severity of impairments in self and interpersonal functioning. The paper integrates the concept of the borderline level of personality functioning, conceptualizing borderline pathology as a dynamic dimension of dysfunction with potential transient regressions, and links this concept to the Level of Personality Functioning (LPF, Criterion A) within the DSM 5 Alternative Model for Personality Disorders (AMPD). Retaining borderline pathology as a dimension may support contemporary PD assessment by offering a clinically recognizable marker of overall dysfunction, a guide for rating severity, an indicator of personality structure and need for psychotherapy, without disrupting continuity with an extensive clinical and research tradition. Full article

Background/Objectives: Mild cognitive impairment (MCI) is common in Parkinson’s disease (PD) and significantly impacts quality of life. Non-invasive brain stimulation (NIBS) techniques have emerged as potential therapeutic interventions. This systematic review analyzes the current evidence regarding the efficacy of Transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) on cognitive domains in patients with PD-MCI. Methods: A systematic search was conducted across the PubMed, Scopus, Web of Science, and Medline Ultimate databases up to 20 November 2025. We included studies investigating the effects of NIBS compared to sham stimulation on neuropsychological outcomes in diagnosed PD-MCI patients. Results: Eight studies involving different stimulation protocols were included. Interventions primarily used TMS or tES targeting the left dorsolateral prefrontal cortex (DLPFC). Episodic memory and global cognition were the most responsive domains, assessed with specific neuropsychological scales. Findings for executive functions and attention were heterogeneous, while visuospatial abilities generally showed limited immediate response. Conclusions: NIBS represents a promising but low-certainty-evidence adjunctive therapy for PD-MCI, with improvements found in memory and global cognition. Future research should prioritize larger sample sizes, combined interventions (NIBS plus cognitive rehabilitation), and extended follow-ups to evaluate long-term neuroplasticity. Full article

Nanotechnology combined with photodynamic therapy (PDT) has been explored to enhance antitumor and antimicrobial photobiological activity. Aluminum phthalocyanine chloride (Al-Pc-Cl), with or without magnetic nanoparticles (MagNPs), was incorporated into polymeric nanoparticles (PNPs) to improve the PDT for treating tumors and infectious diseases. Three batches of the nanoparticles (MagNPs, PNPs-PS and PNPs-PS-MagNPs) were developed and characterized in terms of size, PdI, morphology by TEM, release study, and antitumor (against A549 cells) and antimicrobial (against MRSA and C. albicans) photobiological activity. The developed nanoparticles were nanometric in size, with MagNPs, PNPs-PS, and PNPs-PS-MagNPs showing 33.6, 186.9, and 333.5 nm, respectively, maintained the magnetic properties (for MagNPs and PNPs-PS-MagNPs), and provided slow and sustained release of the photosensitizer. PNPs-PS and PNPs-PS-MagNPs showed excellent antitumor photobiological activity with cell viabilities of 42 and 34%, respectively, and were not cytotoxic in the dark, with cell viabilities above 70%. PNPs-PS showed strong antibacterial activity against MRSA with an IC₅₀ of 8.26 μg/mL, which was lower to free Al-Pc-Cl with an IC₅₀ of 14.22 μg/mL after I radiation. The results of the antifungal photobiological activity against C. albicans were excellent, with IC₅₀ values of 3.75 and 3.5 μg/mL for PNPs-PS and PNPs-PS-MagNPs, respectively, values which were significantly lower with p < 0.05 than free PS (IC₅₀ > 30 μg/mL) after irradiation with light and fluconazole (IC₅₀ > 30 μg/mL), the reference antifungal agent. PNPs-PS showed promising results regarding antitumor, antibacterial, and antifungal photobiological activity. However, PNPs-PS-MagNPs showed weak results for antibacterial photobiological activity against MRSA but with promising results for tumor cells and C. albicans. Full article

Glyphosate, one of the most widely used herbicides worldwide, has raised significant concerns regarding its potential involvement in hepatotoxicity and molecular changes associated with liver cancer biology. These concerns highlight the need to better understand its underlying molecular mechanisms in hepatoma cells. Emerging evidence suggests that glyphosate exposure may increase the risk of liver cancer and chronic liver disease. However, the precise molecular alterations and promising biomarkers associated with glyphosate-induced hepatic toxicity and disease remain largely unexplored. In this study, an RNA-Seq-based in silico systems biology approach was employed to elucidate glyphosate-induced differential transcriptional profiling in hepatoma cells. This analysis revealed significant transcriptional profiling characterized by the upregulated hub genes ATF3, JUNB, ALDOA, FOSB, PFKFB3, G6PD, ENO2, HK2, FOS and PGK1. These genes were primarily associated with glucose metabolism, TNF-α/NF-κB signaling, epithelial–mesenchymal transition (EMT) and cellular stress responses. Conversely, several key genes were significantly downregulated, including PIK3R1, FYN, CEBPA, MLXIPL, PPARA, CD36, PCK2, PNPLA3, NR1H4 and MGLL, which were involved in lipid metabolism, immune regulation and non-alcoholic fatty liver disease (NAFLD) pathways. Notably, all hub genes demonstrated strong diagnostic performance, highlighting their potential as sensitive biomarkers of glyphosate exposure. Collectively, this study provides comprehensive insights into gene expression changes associated with glyphosate exposure in hepatoma cells, linking them to hepatic metabolic dysregulation and immune modulation and suggesting a panel of hub genes with potential diagnostic and therapeutic significance. Full article

Objective: Radiotherapy remodels the tumor microenvironment (TME) and may enhance the efficacy of immunotherapy in cancer treatment, particularly in patients with large, unresectable hepatocellular carcinoma (HCC) complicated by portal vein tumor thrombus (PVTT). Because of these unique effects, a growing body of research has found that stereotactic body radiation therapy (SBRT) combined with transcatheter arterial chemoembolization (TACE) or programmed death protein 1 (PD-1) inhibitors has a synergistic impact on unresectable advanced hepatocellular carcinomas (HCCs) larger than 5 cm in diameter. We aim to explore the efficacy of these treatment modalities through a network meta-analysis (NMA). Methods and Analysis: We evaluated the efficacy and safety of different SBRT-based treatment modalities for large advanced HCCs with PVTT (tumor diameter ≥ 5 cm), with primary endpoints including overall survival (OS), progression-free survival (PFS), and grade 3–4 severe adverse events (SAEs). Results: Eighteen studies comprising 2303 patients were included. SBRT combined with transcatheter arterial chemoembolization (SBRT + TACE) demonstrated significantly superior overall survival compared with other monotherapy or combination strategies. Most other treatment regimens showed comparable PFS outcomes. Notably, SBRT alone and SBRT combined with PD 1 inhibitors (SBRT + PD 1) were associated with significantly lower incidences of severe adverse events compared with other treatment modalities; all of these reported SAEs were manageable with appropriate clinical intervention. Conclusions: For patients with large (≥5 cm) advanced HCC with PVTT, SBRT combined with TACE was associated with superior OS and PFS compared with other treatment strategies. These findings suggest potential synergistic interactions between SBRT and TACE or immunotherapy. Further high-quality prospective trials are warranted to validate these observations and clarify the underlying molecular mechanisms. Our results provide evidence to inform therapeutic decision-making in advanced HCC. Full article

Smart energy networks, including electricity distribution and district heating, are increasingly operated as sensor-enabled infrastructures where maintenance decisions must be made under heterogeneous and time-varying operating conditions. In these settings, time-to-event data are rarely complete; preventive actions and limited observation horizons routinely introduce censoring and truncation, so models and validation procedures must account for partially observed lifetimes to avoid biased inference and misleading performance estimates. This review surveys survival models for predictive maintenance (PdM) and remaining useful life (RUL) estimation, spanning non-parametric, semi-parametric, parametric, and learning-based approaches, with emphasis on censoring-aware formulations and the use of static and time-varying covariates derived from sensor, inspection, and contextual information. A structured taxonomy and a systematic mapping of model families to data types, core assumptions (proportional hazards versus parametric distributional structure), and decision-oriented outputs such as risk ranking, horizon failure probabilities, and RUL distributions are presented. Evaluation practice is also synthesized by covering discrimination metrics, censoring-aware RUL accuracy measures, and probabilistic assessment via proper scoring rules, including the time-dependent Brier score and Integrated Brier Score (IBS). The review provides researchers and practitioners with a practical guide to selecting, fitting, and evaluating survival models for risk-informed maintenance planning in smart energy networks. Full article

Background: First-line chemoimmunotherapy (I + C) is the standard of care for advanced non-squamous non-small cell lung cancer (NSCLC) without oncogenic mutation. Bevacizumab has been shown to enhance the efficacy of chemotherapy in non-squamous NSCLC, yet its added value when combined with I + C (I + C + B) remains unclear. To address this gap, we conducted a real-world comparative study and a network meta-analysis to evaluate I + C + B versus I + C in this setting. Methods: This retrospective study included patients with advanced EGFR/ALK-negative non-squamous NSCLC treated with first-line I + C + B or I + C. Propensity score matching (PSM) was employed to balance baseline characteristics between groups. Efficacy endpoints were progression-free survival (PFS) and overall survival (OS). Subgroup analyses examined outcomes by PD-L1 expression, age, metastases, and chemotherapy, among other factors. In parallel, a network meta-analysis of four randomized trials (n = 2026) indirectly compared I + C + B against I + C for PFS, OS, and safety outcomes. Results: A total of 277 patients were included, with 167 (60.3%) receiving I + C + B and 110 (39.7%) receiving I + C. Before PSM, the I + C + B regimen significantly prolonged PFS versus I + C (hazard ratio [HR] = 0.69, 95% CI 0.52–0.92, p = 0.010), with this benefit maintaining post-matching (HR = 0.70, 95% CI 0.49–0.99, p = 0.045). However, OS did not differ significantly between groups in either the pre-PSM (HR = 0.93, 95% CI: 0.67–1.30; p = 0.665) or matched analyses (HR = 0.84, 95% CI: 0.54–1.29; p = 0.421). Subgroup analyses suggested greater PFS benefit from I + C + B among PD-L1-negative, older patients, those with brain metastases or multiple metastatic sites, and in patients receiving specific chemotherapy doublets. The network meta-analysis confirmed a PFS advantage for I + C + B over I + C (HR = 0.84, 95% CI: 0.71–0.98) without an OS benefit (HR = 0.95, 95% CI: 0.79–1.14). Toxicity was higher with I + C + B; rates of grade 3–5 adverse events, serious adverse events, and treatment discontinuation were all significantly increased compared to I + C. Conclusions: In the first-line treatment of advanced EGFR/ALK-negative non-squamous NSCLC, adding bevacizumab to I + C improved PFS but did not translate into an OS gain. Although PFS benefits were observed in certain subgroups, these were accompanied by significantly increased treatment-related toxicities. Our findings suggest that no clear subgroup has been identified where the benefit outweighs the risks, necessitating extreme clinical caution. Full article

Background: Transarterial chemoembolization (TACE) is an established image-guided, minimally invasive therapy for unresectable hepatocellular carcinoma (HCC). However, post-embolization hypoxia often triggers compensatory angiogenesis and an immunosuppressive microenvironment, limiting long-term efficacy. We hypothesized that the immediate image-guided hepatic arterial infusion (HAI) of a PD-1 inhibitor following TACE could synergistically enhance local tumor control. Methods: In this retrospective, propensity-score-matched study, 226 patients with unresectable HCC (January 2021–June 2024) were analyzed. After 1:1 matching, 84 pairs were included: Study Group (TACE + HAI-nivolumab) and Control Group (TACE alone). Nivolumab (3 mg/kg) was infused via the hepatic artery under fluoroscopic guidance immediately after embolization. Primary endpoints were overall survival (OS) and progression-free survival (PFS); secondary endpoints included objective response rate (ORR) by mRECIST and changes in serum angiogenesis/immune biomarkers. Results: The Study Group demonstrated significantly longer median OS (16.2 vs. 12.8 months; HR 0.62, 95% CI: 0.44–0.88, p = 0.007) and median PFS (9.8 vs. 6.5 months; p < 0.001). ORR was higher with combination therapy (58.3% vs. 36.9%, p = 0.006). Mechanistically, HAI-nivolumab suppressed the post-TACE surge in VEGF and Ang-2 (p < 0.001) and increased the peripheral CD4+/CD8+ T-cell ratio. Grade 3/4 adverse events were comparable between groups (14.3% vs. 10.7%, p = 0.485). Conclusions: The image-guided combination of TACE with immediate HAI of nivolumab is associated with improved survival and tumor response in unresectable HCC. This strategy may counteract the adverse post-embolization microenvironment by simultaneously inhibiting angiogenesis and reactivating local immunity, representing an advanced image-guided combination therapy with strong translational relevance. Full article

Background/Objectives: Protein–protein interactions (PPIs) involving oncogenic drivers remain among the most intractable targets in cancer biology due to their dynamic conformations and limited accessibility to conventional small molecules. Although antibodies and inhibitors have achieved clinical success against targets such as PD-1/PD-L1 and MYC, challenges persist related to tissue penetration, intracellular delivery, resistance, and incomplete blockade of key interface hotspots. The objective of this study is to develop an integrated computational framework for systematically designing hotspot-conditioned de novo miniprotein binders to target these interfaces. Methods: We present DesignForge, a computational protein design pipeline that integrates energetic hotspot identification, generative backbone design, sequence optimization, and structural confidence evaluation. The framework combines hotspot mapping using an open force-field-based energetic analysis module with generative backbone sampling using BindCraft, sequence optimization using ProteinMPNN, and structural validation using AlphaFold2. This in silico pipeline was applied to three representative oncogenic interfaces: PD-1/PD-L1, MYC/MAX, and KRAS/RAF. Results: Computationally generated designs exhibited high predicted structural confidence, favorable interface energetics, and consistent engagement of identified hotspot residues across targets. AlphaFold2-Multimer structural modeling indicated that the candidate PD-1 mimetic scaffolds, MYC/MAX interface binders, and KRAS interaction candidates can adopt conformations compatible with the target interfaces. Energetic contact analysis further supported predicted engagement of key hotspot residues. These findings support the computational feasibility of hotspot-conditioned binder generation using a unified design workflow. Conclusions: DesignForge provides a reproducible computational framework for hotspot-guided de novo protein binder design targeting oncogenic protein–protein interfaces. The designs reported here represent computational predictions derived from structural modeling and energetic analysis. Experimental biochemical and cellular validation will be required to determine the functional activity of the proposed binders. Full article