Search Results (138)

Background: Sodium–glucose cotransporter 2 (SGLT2) inhibitors have transformed type 2 diabetes mellitus (T2DM) management by promoting glucosuria, lowering glycated hemoglobin (HbA1c), blood pressure, and weight; however, their use is limited by genitourinary infections and ketoacidosis. Phytocannabinoids—bioactive compounds from Cannabis sativa—exhibit multi-target pharmacology, including interactions with cannabinoid receptors, Peroxisome Proliferator-Activated Receptors (PPARs), Transient Receptor Potential (TRP) channels, and potentially SGLT2. Objective: To evaluate the potential of phytocannabinoids as novel modulators of renal glucose reabsorption via SGLT2 and to compare their efficacy, safety, and pharmacological profiles with synthetic SGLT2 inhibitors. Methods: We performed a narrative review encompassing the following: (1) the molecular and physiological roles of SGLT2; (2) chemical classification, natural sources, and pharmacokinetics/pharmacodynamics of major phytocannabinoids (Δ⁹-Tetrahydrocannabinol or Δ⁹-THC, Cannabidiol or CBD, Cannabigerol or CBG, Cannabichromene or CBC, Tetrahydrocannabivarin or THCV, and β-caryophyllene); (3) in silico docking and drug-likeness assessments; (4) in vitro assays of receptor binding, TRP channel modulation, and glucose transport; (5) in vivo rodent models evaluating glycemic control, weight change, and organ protection; (6) pilot clinical studies of THCV and case reports of CBD/BCP; (7) comparative analysis with established synthetic inhibitors. Results: In silico studies identify high-affinity binding of several phytocannabinoids within the SGLT2 substrate pocket. In vitro, CBG and THCV modulate SGLT2-related pathways indirectly via TRP channels and CB receptors; direct IC₅₀ values for SGLT2 remain to be determined. In vivo, THCV and CBD demonstrate glucose-lowering, insulin-sensitizing, weight-reducing, anti-inflammatory, and organ-protective effects. Pilot clinical data (n = 62) show that THCV decreases fasting glucose, enhances β-cell function, and lacks psychoactive side effects. Compared to synthetic inhibitors, phytocannabinoids offer pleiotropic benefits but face challenges of low oral bioavailability, polypharmacology, inter-individual variability, and limited large-scale trials. Discussion: While preclinical and early clinical data highlight phytocannabinoids’ potential in SGLT2 modulation and broader metabolic improvement, their translation is impeded by significant challenges. These include low oral bioavailability, inconsistent pharmacokinetic profiles, and the absence of standardized formulations, necessitating advanced delivery system development. Furthermore, the inherent polypharmacology of these compounds, while beneficial, demands comprehensive safety assessments for potential off-target effects and drug interactions. The scarcity of large-scale, well-controlled clinical trials and the need for clear regulatory frameworks remain critical hurdles. Addressing these aspects is paramount to fully realize the therapeutic utility of phytocannabinoids as a comprehensive approach to T2DM management. Conclusion: Phytocannabinoids represent promising multi-target agents for T2DM through potential SGLT2 modulation and complementary metabolic effects. Future work should focus on pharmacokinetic optimization, precise quantification of SGLT2 inhibition, and robust clinical trials to establish efficacy and safety profiles relative to synthetic inhibitors. Full article

Cancer remains one of the most formidable challenges to human health; hence, developing effective treatments is critical for saving lives. An important strategy involves reactivating tumor suppressor genes, particularly p53, by targeting their negative regulator MDM2, which is essential in promoting cell cycle arrest and apoptosis. Leveraging a drug repurposing approach, we screened over 24,000 clinically tested molecules to identify new MDM2 inhibitors. A key innovation of this work is the development and application of a selective cleaning algorithm that systematically filters assay data to mitigate noise and inconsistencies inherent in large-scale bioactivity datasets. This approach significantly improved the predictive accuracy of our machine learning model for pIC₅₀ values, reducing RMSE by 21.6% and achieving state-of-the-art performance (R² = 0.87)—a substantial improvement over standard data preprocessing pipelines. The optimized model was integrated with structure-based virtual screening via molecular docking to prioritize repurposing candidate compounds. We identified two clinical CB1 antagonists, MePPEP and otenabant, and the statin drug atorvastatin as promising repurposing candidates based on their high predicted potency and binding affinity toward MDM2. Interactions with the related proteins MDM4 and BCL2 suggest these compounds may enhance p53 restoration through multi-target mechanisms. Quantum mechanical (ONIOM) optimizations and molecular dynamics simulations confirmed the stability and favorable interaction profiles of the selected protein–ligand complexes, resembling that of navtemadlin, a known MDM2 inhibitor. This multiscale, accuracy-boosted workflow introduces a novel data-curation strategy that substantially enhances AI model performance and enables efficient drug repurposing against challenging cancer targets. Full article

Background: Up to one-third of patients with gastroesophageal reflux disease (GERD) have persistent symptoms despite proton-pump inhibitor (PPI) therapy. E-Gastryal^® + MgAlg (Aurora Biofarma, Italy) is a mucosal protective agent that enhances barrier function against acid and non-acidic reflux. This study assessed its efficacy in combination with omeprazole versus omeprazole alone and as maintenance therapy. Methods: Patients with symptomatic GERD and Grade A reflux esophagitis confirmed by endoscopy were randomized to receive omeprazole 20 mg plus E-Gastryal^® + MgAlg or omeprazole 20 mg alone. The primary endpoint was the number of rescue medications used over 28 days. Secondary endpoints included symptom relief and quality-of-life assessments using the Reflux Symptom Index (RSI), Gastroesophageal Reflux Disease Impact Scale (GIS), GERD-Health-Related Quality of Life (GERD-HRQL), and Global Assessment of Performance (IGAP). Results: Ninety-six patients were included. The combination group used significantly fewer rescue medications (mean: 21 vs. 40.9 tablets; p = 0.002). At week 4, the combination group showed greater improvement in RSI, GIS, and GERD-HRQL scores (p < 0.001). Symptom relief was sustained during weeks 5–26 with E-Gastryal^® + MgAlg alone. Conclusions: E-Gastryal^® + MgAlg combined with omeprazole improves symptom control compared to PPI monotherapy. Continued use as maintenance therapy supports its role in long-term GERD management (NCT04130659). Full article

Background: Administering intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS) on direct oral anticoagulants (DOACs) remains a clinical challenge. Current guidelines restrict IVT within 48 h of DOAC intake unless anticoagulant activity can be confidently excluded. However, reliable medication histories are often unavailable, and conventional coagulation tests inadequately detect DOAC activity. This study evaluated whether viscoelastic point-of-care testing (ClotPro^®) could identify the absence of anticoagulant effect in AIS patients on DOACs, thus enabling IVT administration and potentially improving clinical outcomes. Methods: We conducted a prospective observational cohort study of 40 AIS patients with documented DOAC use, admitted between February 2023 and May 2025. ClotPro^® was performed at admission using the Russell’s viper venom (RVV) assay for factor Xa inhibitors and the ecarin clotting time (ECT) assay for dabigatran. Subtherapeutic anticoagulation was defined as a clotting time (CT) of <100 s for RVV and <180 s for ECT, respectively. Patients identified as being subtherapeutic were assessed for IVT eligibility. To evaluate IVT effects, we performed propensity score-matched bootstrap resampling (1000 iterations), matching patients by age, admission National Institutes of Health Stroke Scale (NIHSS), and pre-stroke modified Rankin Scale (mRS). Primary endpoints were NIHSS-shift (change from admission to 72 h) and mRS-shift (change from pre-stroke mRS to 90-day mRS). Predictors of outcomes were analyzed using multivariate regression models. Results: ClotPro^® identified 15/40 patients (37.5%) as subtherapeutic, all on factor Xa inhibitors. Of these, seven received IVT. In matched analyses, IVT-treated patients showed a numerically greater neurological improvement than untreated patients (mean NIHSS-shift: −2.83 vs. 3.94; mean difference: −6.76, 95% confidence interval [CI]: −24.00 to 7.55; p = 0.495). Functional outcome by mRS-shift showed only minor differences between groups (2.74 vs. 2.10 mean difference: 0.64; 95% CI: −2.00 to 2.50; p = 0.510). IVT showed a favorable trend for early neurological recovery (p = 0.081) but was not independently associated with functional outcome (p = 0.380). Conclusions: ClotPro^® identified a substantial subset of AIS patients on DOAC therapy without measurable anticoagulant activity, enabling IVT in cases that would otherwise have been excluded based on medication history. These findings support the feasibility of ClotPro^®-guided decision-making in acute stroke care and highlight its potential to improve IVT selection by enabling real-time assessment of coagulation status at the bedside. Full article

Background/Objectives: Vancomycin-induced nephrotoxicity (VIN) remains a significant clinical challenge, with no effective nephroprotective agent currently established. This study aimed to evaluate the protective effects of the sodium–glucose cotransporter 2 (SGLT2) inhibitor dapagliflozin (DAPA) against VIN in a Wistar albino rat model. Methods: Rats were randomly assigned to four groups: control, VA (vancomycin), DAPA (dapagliflozin), and VA+DAPA. Renal function was assessed by measuring serum urea and creatinine. Oxidative stress markers [malondialdehyde (MDA), total oxidant status (TOS), and myeloperoxidase (MPO)], antioxidant enzyme activities [total antioxidant status (TAS), glutathione peroxidase (GPx), catalase (CAT), and superoxide dismutase (SOD)], apoptotic mediators (Bax, Bcl-2, and caspase-3), and pro-inflammatory cytokines [tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6)] were evaluated. Histopathological and immunohistochemical analyses of kidney tissues were also performed. Results: Administration of VA led to significant renal dysfunction, increased oxidative stress, heightened apoptotic activity, and notable histopathological damage. Co-administration of DAPA with VA significantly reduced serum urea and creatinine levels and decreased caspase-3 activity and was associated with a trend toward reduction in both MDA levels and TNF-α expression, as well as the amelioration of histopathological renal injury. However, reductions in IL-1β and IL-6 levels were not statistically significant. Overall, these findings indicate that DAPA exerts nephroprotective effects against VIN by modulating oxidative stress, inflammation, and apoptotic pathways. Conclusions: Dapagliflozin may serve as a potential protective agent against vancomycin-induced nephrotoxicity. Further long-term and large-scale clinical studies are warranted to validate these preclinical findings and explore their therapeutic implications. Full article

Water injection is widely recognized as one of the most important operational approaches for enhanced oil recovery in oilfields. However, this process faces significant challenges due to the formation of sulfate and carbonate mineral scales caused by high salinity in both injected water and formation water. To address this issue, the use of mineral scale inhibitors has emerged as a valuable solution. In this study, we evaluated the performance of seven machine learning algorithms (Gradient Boosting Machine; k-Nearest Neighbors; Decision Tree; Random Forest; Linear Regression; Neural Network; and Gaussian Process Regression) to predict inhibitor efficiency. The models were trained on a comprehensive dataset of 661 samples (432 for training; 229 for testing) with 66 features including temperature; concentrations of various ions (sodium; calcium, magnesium; barium; strontium; chloride; sulfate; bicarbonate; carbonate, etc.), and inhibitor dosage levels (DTPMP, PPCA, PBTC, EDTMP, BTCA, etc.). The results showed that GPR achieved the highest prediction accuracy with R² = 0.9608, followed by Neural Network (R² = 0.9230) and Random Forest (R² = 0.8822). These findings demonstrate the potential of machine learning approaches for optimizing scale inhibitor performance in oilfield operations Full article

Background: Chronic rhinosinusitis with or without nasal polyps (CRSwNPs/CRSsNPs) is an inflammatory disease that is becoming increasingly associated with laryngopharyngeal reflux disease (LPRD). Although symptom-based questionnaires, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score (RSS), are widely used, there is a lack of objective endoscopic tools for assessing the nasopharyngeal and nasal manifestations of reflux. The Nasopharyngeal Reflux Endoscopic Score (NRES) is a novel endoscopic scoring system that was developed to address this issue. Objective: The objective of this study was to evaluate the diagnostic accuracy of the NRES in identifying LPRD in patients with CRS, compared with a clinical reference standard. Methods: A prospective diagnostic accuracy cohort study was conducted at two tertiary care centers in Astana, Kazakhstan, from September 2023 to February 2025. A total of 216 adults were enrolled and divided into three groups: CRS with suspected LPRD (n = 116), CRS without LPRD (n = 69), and healthy controls (n = 31). CRS was diagnosed according to the EPOS 2020 criteria. LPRD was defined using a composite reference standard comprising clinical assessment, RSS > 13, RSI, and selective 24 h pH monitoring and gastrointestinal endoscopy. All participants underwent nasopharyngeal and laryngeal endoscopy, with NRES, L-K, RFS, RSI, and RSS assessments at baseline and at 6 and 12 months. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance, and Wilcoxon tests were used to analyze the changes in scores. Correlation and regression analyses were used to explore associations between scales and predictive factors. Results: At baseline, NRES scores were significantly higher in the CRS with LPRD group (mean: 11.59) than in the CRS without LPRD group (mean: 3.10) and the healthy control group (mean: 2.16) (p < 0.001). ROC analysis demonstrated excellent diagnostic accuracy, with an area under the curve (AUC) of 0.998 (95% confidence interval (CI): 0.994–1.000), a sensitivity of 98% (95% CI: 94–100%) and a specificity of 96% (95% CI: 91–99%) at an optimal cut-off point of 8.5. NRES scores showed strong correlations with RSI, RSS, and RFS scores (r > 0.76, p < 0.001). A longitudinal assessment revealed significant reductions in all scores after treatment with proton pump inhibitors and lifestyle modifications, with sustained improvement at 12 months. Regression analysis found no significant effect of age, gender, or GERD severity (LA classification) on NRES scores. Conclusions: The NRES is a highly sensitive and specific endoscopic tool for identifying nasopharyngeal changes associated with LPRD in CRS patients. It demonstrates strong correlations with established symptom-based and laryngoscopic reflux assessments and responds to anti-reflux therapy over time. The NRES may, therefore, be a valuable objective adjunct in the comprehensive evaluation and longitudinal monitoring of LPRD-associated CRS. Full article

The COVID-19 infection, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has evoked a worldwide pandemic. Even though vaccines have been developed on an enormous scale, but due to regular mutations in the viral gene and the emergence of new strains could pose a more significant problem for the population. Therefore, new treatments are always necessary to combat future pandemics. Utilizing an antiviral peptide as a model biomolecule, we trained a generative deep learning algorithm on a database of known antiviral peptides to design novel peptide sequences with antiviral activity. Using artificial intelligence (AI), specifically variational autoencoders (VAE) and Wasserstein autoencoders (WAE), we were able to generate a latent space plot that can be surveyed for peptides with known properties and interpolated across a predictive vector between two defined points to identify novel peptides that exhibit dose-responsive antiviral activity. Two hundred peptide sequences were generated from the trained latent space and the top peptides were subjected to a molecular docking study. The docking analysis revealed that the top four peptides (MSK-1, MSK-2, MSK-3, and MSK-4) exhibited the strongest binding affinity, with docking scores of −106.4, −126.2, −125.7, and −127.8, respectively. Molecular dynamics simulations lasting 500 ns were performed to assess their stability and binding interactions. Further analyses, including MMGBSA, RMSD, RMSF, and hydrogen bond analysis, confirmed the stability and strong binding interactions of the peptide–protein complexes, suggesting that MSK-4 is a promising therapeutic agent for further development. We believe that the peptides generated through AI and MD simulations in the current study could be potential inhibitors in natural systems that can be utilized in designing therapeutic strategies against SARS-CoV-2. Full article

Background/Objectives: As a monocyclic β-lactam antibiotic, aztreonam has regained attention recently because combining it with β-lactamase inhibitors helps fight drug-resistant bacteria. This study aimed to systematically characterize the plasma and tissue concentration-time profiles of aztreonam in rats, mice, dogs, monkeys, and humans by developing a multi-species, physiologically based pharmacokinetic (PBPK) model. Methods: A rat PBPK model was optimized and validated using plasma concentration-time curves determined by liquid chromatography–tandem mass spectrometry (LC-MS/MS) following intravenous administration, with reliability confirmed through another dose experiment. The rat model characteristics, modeling experience, ADMET Predictor (11.0) software prediction results, and allometric scaling were used to extrapolate to mouse, human, dog, and monkey models. The tissue-to-plasma partition coefficients (K_p values) were predicted using GastroPlus (9.0) software, and the sensitivity analyses of key parameters were evaluated. Finally, the cross-species validation was performed using the average fold error (AFE) and absolute relative error (ARE). Results: The cross-species validation showed that the model predictions were highly consistent with the experimental data (AFE < 2, ARE < 30%), but the deviation of the volume of distribution (V_ss) in dogs and monkeys suggested the need to supplement the species-specific parameters to optimize the prediction accuracy. The K_p values revealed a high distribution of aztreonam in the kidneys (K_p = 2.0–3.0), which was consistent with its clearance mechanism dominated by renal excretion. Conclusions: The PBPK model developed in this study can be used to predict aztreonam pharmacokinetics across species, elucidating its renal-targeted distribution and providing key theoretical support for the clinical dose optimization of aztreonam, the assessment of target tissue exposure in drug-resistant bacterial infections, and the development of combination therapy strategies. Full article

Background: High-grade gliomas (HGGs), particularly glioblastoma (GBM), are associated with exceptionally high mortality and inevitable recurrence. In considering novel treatment options for these devastating diseases, immunotherapies represent promising candidates. Immunotherapies have demonstrated efficacy for several advanced tumors outside the central nervous system, highlighting a potential role for these agents in treating HGGs. However, multiple challenges to immunotherapy efficacy have tempered therapeutic benefit in practice, including local and systemic immunosuppression, intratumoral heterogeneity, and various mechanisms of intrinsic and acquired resistance. In the past 30 years, diverse immunotherapeutic subclasses have been assessed for benefit against HGGs. Methods: We performed a PubMed search for randomized clinical trials performed within the last 30 years evaluating the following immunotherapy agents for high-grade gliomas: immune checkpoint inhibitors, vaccines, oncologic viruses, cytokines, and CAR T-cells. The present review offers a critical analysis of key pre-clinical and clinical trials that have shaped the immunotherapy landscape for high-grade gliomas over the past two decades. Results/Conclusions: Across the different immunotherapeutic methods and modalities explored thus far, a recurring theme emerges: while therapeutic strategies with a compelling conceptual basis are continually under development and even demonstrate a benefit in preclinical and early-phase trials, larger and later-phase trials consistently fail to produce concordantly significant outcomes. To date, no large-scale clinical trial has demonstrated a benefit of sufficient consequence to change practice. Continued critical appraisal of the strengths and pitfalls of prior investigative work, optimization of treatment development and delivery, and innovative approaches to combination therapy design will collectively be integral to future therapeutic advancement. Full article

Background: Mixed urinary incontinence (MUI), particularly the urge-predominant subtype, involves both stress urinary incontinence (SUI) and urge urinary incontinence (UUI), posing a therapeutic challenge. Duloxetine, a serotonin–norepinephrine reuptake inhibitor (SNRI), enhances urethral tone, while tolterodine, an antimuscarinic agent, reduces detrusor overactivity. Their combination may offer synergistic benefits. Aim: The aim of this study was to evaluate the efficacy of duloxetine and tolterodine combination therapy in urge-predominant MUI and identify factors influencing treatment success. Method: A retrospective study was conducted on 106 patients (mean age: 56.45 years) with urge-predominant MUI treated with duloxetine (40 mg twice daily) and tolterodine (4 mg once daily) for 12 weeks. Treatment outcomes were evaluated using the overactive bladder symptom score (OABSS), International Consultation on Incontinence Questionnaire Short Form (ICIQ-SF), 24 h pad test, and Clinical Global Impression Scale (CGI). Univariate and multivariate regression analyses were performed to determine predictors of success. Results: Significant improvements were observed: OABSS decreased from 11.08 to 6.95, ICIQ-SF decreased from 15.69 to 8.84, and pad use decreased from 3.58 to 0.73/day (all p 0.0001). Bladder capacity increased from 315.09 mL to 436.32 mL. Baseline ICIQ-SF scores were independent predictors of success (odds ratio [OR] = 2.919, p = 0.001). Patient satisfaction reached 77.4%, with mild side effects (constipation and dizziness) in 14 patients. Conclusions: Duloxetine and tolterodine combination therapy significantly improved symptoms and quality of life in urge-predominant MUI. Baseline ICIQ-SF scores may predict treatment success. Further prospective studies are needed. Full article

Antibody–drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN, a novel hybrid Graph Neural Network architecture for predicting ADC payload activity and toxicity. Integrating MPNN, GAT, and GraphSAGE layers, DumplingGNN captures multi-scale molecular features using both 2D and 3D structural information. Evaluated on a comprehensive ADC payload dataset and MoleculeNet benchmarks, DumplingGNN achieves state-of-the-art performance, including BBBP (96.4% ROC-AUC), ToxCast (78.2% ROC-AUC), and PCBA (88.87% ROC-AUC). On our specialized ADC payload dataset, it demonstrates 91.48% accuracy, 95.08% sensitivity, and 97.54% specificity. Ablation studies confirm the hybrid architecture’s synergy and the importance of 3D information. The model’s interpretability provides insights into structure–activity relationships. DumplingGNN’s robust toxicity prediction capabilities make it valuable for early safety evaluation and biomedical regulation. As a research prototype, DumplingGNN is being considered for integration into Omni Medical, an AI-driven drug discovery platform currently under development, demonstrating its potential for future practical applications. This advancement promises to accelerate ADC payload design, particularly for Topoisomerase I inhibitor-based payloads, and improve early-stage drug safety assessment in targeted cancer therapy development. Full article

Unconventional heavy oil reservoirs are particularly susceptible to steam breakthrough, which significantly reduces crude oil production. Profile control is a crucial strategy used for stabilizing oil production and minimizing production costs in these reservoirs. Conventional plugging agent systems used in the thermal recovery of heavy oil currently fail to meet the high-temperature, high-strength, and deep profile control requirements of this process. Precipitation-type calcium salt blocking agents demonstrate long-term stability at 300 °C and concentrations up to 250,000 mg/L, making them highly effective for profile control and channeling blockage during the steam injection stages of heavy oil recovery. This study proposes two types of precipitation-type calcium salt blocking agents: CaSO₄ and CaCO₃ crystals. The precipitation behavior of these agents was investigated, and their dynamic growth patterns were examined. The calcium sulfate blocking agent exhibits a slower crystal precipitation rate, allowing for a single-solution injection, while the calcium carbonate blocking agent precipitates rapidly, requiring a dual-solution injection. Both systems incorporate scale inhibitors to delay the growth of calcium salt crystals, which aids in deep profile control. Through microscopic visualization experiments, the micro-blocking characteristics of the calcium salt blocking agent systems within pores were compared, elucidating the blocking positions of the precipitated calcium salts under porous conditions. Calcium sulfate crystals preferentially precipitate in and block larger pore channels, whereas calcium carbonate crystals are more evenly distributed throughout the pore channels, reducing the reservoir’s heterogeneity. The final single-core displacement experiment demonstrated the sealing properties of the precipitation-type calcium salt blocking agent systems. The developed precipitation-type calcium salt blocking agent systems exhibit excellent profile control performance. Full article

Background/Objectives: Cardiac resynchronization therapy (CRT) and angiotensin receptor–neprilysin inhibitors (ARNIs) are cornerstone therapies for patients with heart failure with reduced ejection fraction (HFrEF). However, nearly 30% of patients show no significant response to CRT alone. The potential of ARNI to enhance CRT outcomes—especially in non-responders—is an emerging field of interest. The objective of this review is to systematically evaluate and synthesize the available evidence on the clinical outcomes of combining CRT with ARNI therapy in patients with HFrEF. Methods: We conducted a comprehensive search of PubMed, Scopus, and Google Scholar up to September 2024, using the keywords “CRT and ARNI” and “cardiac resynchronization therapy and sacubitril/valsartan”. We included retrospective and prospective clinical studies, observational studies, and review articles reporting on patients with HFrEF treated with both CRT and ARNI. Studies not in English, animal studies, and those without full-text availability were excluded. Study selection and data extraction were performed in duplicate by independent reviewers, using PRISMA guidelines for transparency. The final selection included 8 studies published in the last four years, summarized by design, population, outcomes, and statistical significance. Results: The reviewed studies suggest that ARNI therapy, when combined with CRT, may contribute to improvements in left ventricle ejection fraction (LVEF), NYHA functional class, and ventricular remodeling, particularly in CRT non-responders. Some studies also report a potential reduction in ventricular arrhythmias and implantable cardioverter-defibrillator (ICD) interventions. However, outcomes varied across subgroups, and the influence of ARNI timing relative to CRT implantation remains inconclusive. Limitations: Heterogeneity in study designs and small sample sizes in some included studies limited the ability to conduct a meta-analysis. This review is not registered. Conclusions: ARNI therapy shows promise in enhancing CRT response in patients with HFrEF, particularly in non-responders. Further large-scale, prospective studies are needed to clarify optimal patient selection and treatment sequencing. Full article

Fibroblast activation protein (FAP) is a serine protease selectively expressed in cancer-associated fibroblasts (CAFs), fibrotic tissues, and areas of active tissue remodeling, making it an attractive target for diagnostic imaging across a spectrum of disease. FAP inhibitors (FAPIs) labeled with PET tracers have rapidly advanced as a novel imaging modality with broad clinical applications that offers several advantages, including rapid tumor accumulation, low background uptake, and high tumor-to-background ratios. In oncology, FAPI PET has demonstrated excellent performance in visualizing a wide range of malignancies, including those with low glycolytic activity, such as pancreatic cancer, cholangiocarcinoma, and certain sarcomas. Its high sensitivity and specificity for the stromal component enables improved tumor delineation, staging, and response assessment. Additionally, the potential to guide theranostic approaches, where the same tracer can be labeled with therapeutic radionuclides, positions FAPI as a key player in precision oncology. Beyond oncology, FAPI PET has shown promise in imaging conditions characterized by fibrotic and inflammatory processes. In the cardiovascular field, FAPI PET imaging is being investigated for its ability to detect myocardial fibrosis and active cardiac remodeling, crucial in conditions like heart failure, post-myocardial infarction remodeling, and hypertrophic cardiomyopathy. This review highlights the expanding clinical applications of FAPI-based PET imaging across oncology, inflammation, and cardiovascular disease. While the current data are promising, further large-scale studies and multicenter trials are essential to validate these findings and establish standardized protocols. The versatility and broad applicability of FAPI PET underscore its potential as a transformative tool in precision medicine. Full article