Search Results (236)

Chronic coronary syndrome (CCS) and atrial fibrillation (AF) are prevalent cardiovascular conditions that share numerous risk factors and pathophysiological mechanisms. While clinical scores commonly used in AF—such as CHA₂DS₂VA (which includes congestive heart failure, hypertension, age ≥ 75, diabetes, stroke/TIA, vascular disease, and age 65–74), HAS-BLED (which incorporates hypertension, abnormal renal/liver function, stroke, bleeding history, labile INR, elderly age, and drug/alcohol use), and C₂HEST (incorporating coronary artery disease, COPD, hypertension, elderly age ≥ 75, systolic heart failure, and thyroid disease)—are traditionally applied to rhythm or bleeding risk prediction, their value in estimating the angiographic severity of coronary artery disease (CAD) remains underexplored. We conducted a prospective, single-center study including 131 patients with suspected stable CAD referred for coronary angiography, stratified according to coronary angiographic findings into two groups: significant coronary stenosis (S-CCS) and non-significant coronary stenosis (N-CCS). At admission, AF-related scores (CHA₂DS₂, CHA₂DS₂VA, CHA₂DS₂VA-HSF, CHA₂DS₂VA-RAF, CHA₂DS₂VA-LAF, HAS-BLED, C₂HEST, and HATCH) were calculated. CAD severity was subsequently assessed using the SYNTAX and Gensini scores. Statistical comparisons and Pearson correlation analyses were performed to evaluate the association between clinical risk scores and angiographic findings. Patients in the S-CCS group had significantly higher scores in CHA₂DS₂VA (4.09 ± 1.656 vs. 3.20 ± 1.338, p = 0.002), HAS-BLED (1.98 ± 0.760 vs. 1.36 ± 0.835, p < 0.001), CHA₂DS₂VA-HSF (6.00 ± 1.854 vs. 5.26 ± 1.712, p = 0.021), and C₂HEST (3.49 ± 1.501 vs. 2.55 ± 1.279, p < 0.001). Multivariate logistic regression identified HAS-BLED and C₂HEST as independent predictors of significant coronary lesions. A threshold value of HAS-BLED ≥ 1.5 and C₂HEST ≥ 3.5 demonstrated moderate discriminative ability (AUC = 0.694 and 0.682, respectively), with acceptable sensitivity and specificity. These scores also demonstrated moderate to strong correlations with both Gensini and SYNTAX scores. AF-related clinical scores, especially HAS-BLED and C₂HEST, may serve as practical and accessible tools for early CAD risk stratification in patients with suspected CCS. Their application in clinical practice may serve as supplementary triage tools to help prioritize patients for further diagnostic evaluation, but they are not intended to replace standard imaging or testing. Full article

Adrenocortical carcinoma (ACC) is an aggressive cancer with a poor prognosis. Mitotane, the only FDA-approved treatment for ACC, targets adrenocortical cells and reduces cortisol levels. Although it remains the cornerstone of systemic therapy, its overall impact on long-term outcomes is still a matter of ongoing clinical debate. Drug repurposing is a cost-effective way to identify new therapies, and defactinib, currently in clinical trials as part of combination therapies for various solid tumours, may enhance ACC treatment. We aimed to assess its efficacy in combination with mitotane. We tested the combination of mitotane and defactinib in H295R, SW13, and mitotane-sensitive and -resistant HAC15 cells, using functional assays, transcriptomic profiling, 2D and 3D cultures, bioprinted tissues, and xenografts. We assessed drug interactions with NMR and toxicity in vivo, as mitotane and defactinib have never been previously administered together. Genomic data from 228 human ACC and 158 normal adrenal samples were also analysed. Transcriptomic analysis revealed dysregulation of focal adhesion along with mitotane-related pathways. Focal adhesion kinase (FAK) signalling was enhanced in ACC compared to normal adrenal glands, with PTK2 (encoding FAK) upregulated in 44% of tumour samples due to copy number alterations. High FAK signature scores correlated with worse survival outcomes. FAK inhibition by defactinib, both alone and in combination with mitotane, showed effective anti-tumour activity in vitro. No toxicity or drug—drug interactions were observed in vivo. Combination treatment significantly reduced tumour volume and the number of macrometastases compared to those in the mitotane and control groups, with defactinib-treated tumours showing increased necrosis in xenografts. Defactinib combined with conventionally used mitotane shows promise as a novel combination therapy for ACC and warrants further investigation. Full article

Background: This study aimed to develop a predictive model to assess risk factors and prognoses in pediatric patients with dilated cardiomyopathy (DCM). Methods: A total of 233 pediatric patients with DCM who were hospitalized between January 2019 and June 2024 were enrolled. The children were followed up and categorized into two groups: the death/heart transplantation (D/HT) group and the non-D/HT group. Univariate and multivariate analyses identified risk factors. A nomogram model and a scoring system were developed. The performance of these models was evaluated using the H-L test, ROC analysis, and internal validation. Results: The results demonstrated that the age of onset, cardiac functional classification III–IV, moderate-to-severe mitral regurgitation, low voltage in limb leads on an ECG, and the need for vasoactive drugs are independent predictors of D/HT risk in children with DCM. A nomogram model was developed, achieving an AUC of 0.804 (95% CI: 0.734–0.874), a sensitivity of 80.3%, and a specificity of 66.7%. A scoring system was established: 1 point for age of onset, 10 points for cardiac functional classification III–IV, 2.5 points for moderate-to-severe mitral regurgitation, 4 points for low voltage in limb leads on an ECG, 3 points for the need for vasoactive drugs, or 0 points if none of these criteria were met. When the cumulative score was ≥ 13.25, the sensitivity and specificity increased to 68.9% and 73.9%, respectively. Conclusions: We developed both a nomogram and a scoring system model, which are capable of rapidly and accurately predicting the risk of D/HT in children with DCM. Full article

(1) Background: Although the field of natural product (NP) drug discovery has been extensively developed, there are still several bottlenecks hindering the development of drugs from NPs. The PD-1/PD-L1 immune checkpoint axis plays a crucial role in immune response regulation. Therefore, drugs targeting this axis can disrupt the interaction and enable immune cells to continue setting up a response against the cancer cells. (2) Methods: We have explored the immuno-oncological activity of NPs targeting the PD-1/PD-L1 immune checkpoint by estimating the half maximal inhibitory concentration (IC₅₀) through molecular docking scores and predicting it using machine learning (ML) models. The LightGBM (Light Gradient-Boosted Machine), a tree-based ML technique, emerged as the most effective approach and was used for building the quantitative structure–activity relationship (QSAR) classification model. (3) Conclusions: The model incorporating 570 spectral descriptors from NMR SPINUS was selected for the optimization process, and this approach yielded results for the external test set with a sensitivity of 0.74, specificity of 0.81, overall predictive accuracy of 0.78, and Matthews correlation coefficient (MCC) of 0.55. The strategy used here for estimating the IC₅₀ from docking scores and predicting it through ML models appears to be a promising approach for pure compounds. Nevertheless, further optimization is indicated, particularly through the simulation of the spectra of mixtures by combining the spectra of individual compounds. Full article

Background/Objectives: Ankylosing spondylitis (AS) is a severe chronic inflammatory rheumatic disease involving the spine, sacroiliacs, and peripheral joints. A lack of therapeutic response leads to severe sequelae. Currently, new markers are being tested to identify patients with poor outcomes. Tenascin C (TNC) is involved in triggering some relevant mechanisms of inflammation. Today, it remains unclear whether TNC levels might be useful as a biomarker of persistent activity. The aim of this study was to evaluate in AS whether serum levels of tenascin C are associated with persistent disease activity despite treatment. Methods: We included AS patients who had been treated with conventional synthetic disease-modifying antirheumatic drugs (cs-DMARDS) or anti-TNF agents for at least three months in a cross-sectional study. Response was assessed with the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI); scores ≥ 4 indicate persistent disease activity, while scores < 4 indicate inactive disease. Serum TNC levels, C-reactive protein (CRP) levels, and Erythrocyte Sedimentation Rate (ESR) were determined through the ELISA technique, nephelometry, and the Westergren method, respectively. Results: We evaluated 58 patients with AS (62.1% men); of them, 33 (56.9%) had persistent active disease (BASDAI ≥ 4) despite treatment and 25 (43.1%) had inactive disease (BASDAI < 4). The median TNC level was 18.6 ng/mL. BASDAI correlated with TNC levels (rho: 0.528, p < 0.001), CRP (0.352, p = 0.007), and ESR (0.342, p = 0.009). Patients with persistently active AS had higher serum TNC levels than those with inactive AS (35.2 vs. 6 ng/mL, p < 0.001). No differences in TNC level were found in patients treated with cs-DMARDS vs. anti-TNF agents. The ROC curve for serum tenascin C in active AS patients had an area under the curve = 0.78 (CI 95%: 0.65–0.91) with optimal serum tenascin C cutoff (>13.85 ng/mL). Sensitivity for detecting active AS was higher with TNC compared to ESR and CRP. Conclusions: We suggest that an elevated TNC level may be a useful biomarker of persistent disease activity despite treatment in AS; further studies should investigate the role of TNC levels in predicting the progression of the disease. Full article

Background: This study aims to evaluate the impact of critical illness, defined as the need for preoperative intensive care unit (ICU) admission for invasive monitoring or organ support, on cardiac surgery outcomes for patients with acute infective endocarditis (IE). Methods: A retrospective analysis of prospectively collected data from patients treated between 1 January 2017 and 30 May 2024 at a single Australian tertiary cardiothoracic centre was performed. Data were collected from the Australian and New Zealand Cardiothoracic Society (ANZCTS) database and the Australian and New Zealand Intensive Care Adult Patients Database (ANZICS-APD). Results: Among 342 patients who underwent cardiac surgery for IE, 32 (9.4%) were critically ill. The critically ill patients were admitted to the ICU before surgery with a diagnosis of septic or cardiogenic shock, with 86% (n = 30) requiring mechanical ventilation. Compared to the non-critically ill cohort, critically ill patients were more likely to have a history of intravenous drug use (IVDU) (41% vs. 14%, p = 0.03) and a younger age (median age 49 years [42–56] vs. 61 years [44–70], p = 0.03), and although methicillin-sensitive Staphylococcus aureus (MSSA) was the most common causative organism in both groups, it was found significantly more often in the critically ill cohort (66% and 27%, p = 0.001). The median EuroSCORE II was comparable between the groups (2.1 [1.3–10] vs. 2.8 [1.3–5.7], p = 0.69); however, the APACHE III (57 [49–78] vs. 52 [39–67], p = 0.03) and ANZROD scores (0.04 [0.02–0.09] vs. 0.013 [0.004–0.038], p = 0.00002) were significantly higher in the critically ill patients. The overall 30-day mortality rates were similar between the groups (13% vs. 5%, p = 0.60). The median ICU length of stay (LOS) was significantly longer for the critically ill patients (5 days [IQR 2–10 days] vs. 2 days [1–4 days], p = 0.0004), with a similar hospital LOS (23 days [IQR 14–36] vs. 21 days [12–34], p = 0.46). Renal replacement therapy was three times higher in the critically ill (34% vs. 11%, p = 0.0001). Reoperations for bleeding were similar between the groups (16% vs. 11%, p = 0.74). Conclusions: Despite being associated with higher ANZROD and APACHE III scores, a longer ICU length of stay, and higher use of renal replacement therapy, critical illness did not have an impact on the EuroSCORE II, hospital length of stay, or reoperation rates for bleeding or 30-day mortality among patients with IE undergoing cardiac surgery. The lessons from this study will guide and inform the development of better infective endocarditis databases and registries. Full article

The prognosis of advanced (UICC IIb-IV) primary colorectal cancer (pCRC) remains poor. More effective targeted therapies are needed. Heat shock protein 90 alpha/beta (Hsp90α/β) expression was immunohistologically quantified in 89 pCRCs and multivariately correlated with survival. Pimitespib (Pim, TAS-116), a Hsp90α/β-specific inhibitor, was tested in pCRC cell lines and patient-derived cancer spheroids (PDCS) and referenced to the pan-Hsp90 inhibitor ganetespib (Gan, STA-9090) and standard-of-care therapies. A total of 26.97% pCRCs showed strong tumoral Hsp90α/β expression (Hsp90α/β > 40%), which correlated with reduced PFS (HR: 3.785, 95%CI: 1.578–9.078, p = 0.003) and OS (HR: 3.502, 95%CI: 1.292–9.494, p = 0.014). Co-expression of Hsp90α/β > 40% with its clients BRAF-V600E and Her2/neu aggravated the prognosis (BRAF-V600E mutated: PFS, p = 0.002; OS, p = 0.012; Her2/neu score3: PFS, p = 0.029). The prognostic cut-off Hsp90α/β > 40% was also a predictor for response to Pim-based therapy. Pim efficacy was increased in combination with 5-FU, 5-FU + oxaliplatin, and 5-FU + irinotecan (all p < 0.001). Pim induced sensitization to all chemotherapies in HT-29 (p < 0.001), Caco-2 (p < 0.01), and HCT116 (p < 0.05) cells. Pim combined with encorafenib in HT-29 and with trastuzumab in Caco-2 cells was most effective in dual-target inhibition approaches (HT-29: p < 0.005; Caco-2: p < 0.05). The anti-cancer effect and chemosensitization of Pim-based therapy were prospectively confirmed in PDCS directly generated from Hsp90α/β > 40% pCRCs. Protein profiling combined with functional drug testing stratifies Hsp90α/β > 40% pCRC patients diagnosed with UICC IIb-IV for effective Pim-based therapy. Full article

Neurobehavioral comorbidities in dogs with idiopathic epilepsy (IE) are increasingly recognized, yet their phenotypic variability and clinical implications remain poorly understood. This study aimed to identify behavioral changes following seizure onset and to explore the feasibility of stratifying patients based on neurobehavioral profiles. Seventy client-owned dogs with IE were enrolled and grouped according to treatment: 29 had drug-resistant epilepsy (DRE), 29 were drug-sensitive (DSE), and 12 remained untreated. Owners completed a modified version of the C-BARQ questionnaire, assessing behaviors before and after seizure onset. Nearly one-third of behavioral items showed significant changes, particularly in attachment and attention-seeking behaviors, separation-related behaviors, eating behavior, and signs of cognitive decline such as reduced trainability and dementia-like signs. Principal component analysis followed by cluster analysis revealed two distinct neurobehavioral profiles: Cognitive and Emotional. The Cognitive cluster was associated with a higher total questionnaire score, poorer seizure control (predominantly DRE), and lower owner-perceived quality of life. In contrast, the Emotional cluster was more frequently observed in dogs with DSE or no treatment and was associated with higher quality of life scores. These findings support the clinical relevance of behavioral stratification in canine epilepsy and underscore the need for individualized, multimodal approaches to improve patient care. Full article

Glioblastoma (GBM) presents significant therapeutic challenges due to its invasive nature and resistance to standard chemotherapy, i.e., temozolomide (TMZ). This study aimed to identify gene signatures that predict poor TMZ response and high PD−L1/PD−1 tumor expression, and explore potential sensitivity to alternative drugs. We analyzed The Cancer Genome Atlas (TCGA) biopsy data to identify differentially expressed genes (DEGs) linked to these characteristics. Among 33 upregulated DEGs, 5 were significantly correlated with overall survival. A risk score model was built using these 5 DEGs, classifying patients into low-, medium-, and high-risk groups. We assessed immune cell infiltration, immunosuppressive mediators, and epithelial–mesenchymal transition (EMT) markers in each group using correlation analysis, Gene Set Enrichment Analysis (GSEA), and machine learning. The model demonstrated strong predictive power, with high-risk patients exhibiting poorer survival and increased immune infiltration. GSEA revealed upregulation of immune and EMT-related pathways in high-risk patients. Our analyses suggest that high-risk patients may exhibit limited response to PD−1 inhibitors, but could show sensitivity to etoposide and paclitaxel. This risk score model provides a valuable tool for guiding therapeutic decisions and identifying alternative chemotherapy options to enable the development of personalized and cost-effective treatments for GBM patients. Full article

Background: Lung adenocarcinoma is the most common NSCLC and is associated with metabolic dysregulation. Purine biosynthesis, regulated by PAICS, plays a key role in tumor progression and therapy resistance. Methods: We focused on LUAD using pan-cancer and KEGG enrichment analyses. TCGA-LUAD and three GEO datasets were analyzed to confirm the prognostic relevance of purine biosynthesis. A prognostic model, the Purine Biosynthesis-Related Score (PBRS), was developed using LASSO regression and validated in independent cohorts. Gene set variation analysis, immune profiling, tumor mutational burden analysis, and drug sensitivity analysis were conducted. PAICS expression was validated in LUAD tissues, and its role was assessed via proliferation and migration assays. Results: PBRS classified LUAD patients into high-risk (PBRS-high) and low-risk (PBRS-low) subgroups, with distinct prognostic outcomes. PBRS-high patients showed enrichment in cell cycle regulation and DNA repair pathways and had higher TMB, suggesting potential sensitivity to immunotherapy, although immune escape mechanisms may limit the efficacy of immune checkpoint inhibitors. PBRS-low patients were more responsive to metabolic inhibitors. PAICS overexpression correlated with poor prognosis, while its knockdown suppressed LUAD progression. Conclusion: PBRS is a prognostic tool in LUAD, identifying PBRS-high patients who may benefit from immunotherapy or DDR-targeted therapies. PBRS-low patients exhibit sensitivity to metabolic inhibitors. PAICS is a potential therapeutic target. Full article

Background/Objectives: Bariatric surgery (BS), drugs approved for type-2-diabetes (T2D), obesity, and liver fibrosis (resmetirom) announce the widespread use of fibrosis tests in patients with metabolic liver disease (MASLD). An unmet need is to reduce the uncertainty of biomarkers for the diagnosis of the early stage of clinically significant fibrosis (eF). This can be achieved if three essential but neglected STARD methods (3M) are used, which have a more sensitive histological score than the standard comparator (five-tiers), the weighted area under the characteristic curve (wAUROC) instead of the binary AUROC, and biopsy length. We applied 3M to FibroTest-T2D to demonstrate this reduction of uncertainty and constructed proxies predicting eF in large populations. Methods: For uncertainty, seven subsets were analyzed, four included biopsies (n = 1903), and to assess eF incidence, three MASLD-populations (n = 299,098). FibroTest-T2D classification rates after BS and in outpatients-T2D (n = 402) were compared with and without 3M. In MASLD, trajectories of proxies and incidence against confounding factors used hazard ratios. Results: After BS (110 biopsies), reversal of eF was observed in 16/29 patients (84%) using seven-tier scores vs. 3/20 patients (47%) using five-tier scores (p = 0.005). When the biopsy length was above the median, FibroTest-T2D wAUROC was 0.90 (SD = 0.01), and the wAUROC was 0.88 (SD = 0.1) when the length was below the median (p < 0.001). For the first time, obesity was associated with eF before T2D (p < 0.001), and perimenopausal age with apoA1 and haptoglobin increases (p < 0.0001). Conclusions: Validations of circulating biomarkers need to assess their uncertainty. FibroTest-T2D predicts fibrosis regression after BS. Applying 3M and adjustments could avoid misinterpretations in MASLD surveillance. Full article

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treatment resistance. This study investigates the clinical implications of heme metabolism in LUAD, focusing on its link to ferroptosis and drug sensitivity. Using multi-omics data from TCGA-LUAD, GEO databases, and a single-cell RNA-seq cohort, we identified two molecular subtypes based on heme metabolism-related genes. We further developed a prognostic panel, termed the heme metabolism risk score (HMRS), using LASSO and multivariate Cox regression analyses. The HMRS panel effectively stratified patients into high- and low-risk groups, with high-risk patients showing enhanced tumor proliferation, suppressed ferroptosis, and resistance to chemotherapy. Single-cell analysis revealed elevated heme metabolism risk in epithelial cells correlated with tumor progression. Drug sensitivity predictions were validated in platinum-based chemotherapy cohorts, confirming HMRS as a robust prognostic tool. ABCC2 was identified as a key regulator of ferroptosis and cisplatin resistance, with in vitro experiments demonstrating that ABCC2 knockdown enhanced cisplatin-induced ferroptosis. These findings highlight HMRS as a critical tool for patient stratification and ABCC2 as a promising therapeutic target to overcome cisplatin resistance. Full article

An increasing body of research indicates that the circulating microbiome plays a significant role in cancer initiation and progression and the treatment response. The genomic characteristics of circulating microorganisms may influence the tumor immune microenvironment, thereby affecting cancer progression and therapeutic outcomes. However, whether the circulating microbiome can serve as a prognostic biomarker for cervical cancer patients and its mechanistic role in the tumor immune microenvironment still requires further investigation. Univariate, Lasso, and multivariate Cox regression analyses were utilized to identify the circulating microbial signatures associated with overall survival (OS) in patients with cervical cancer. A circulating Microbial Abundance Prognostic Score (MAPS) model was constructed based on these findings. A nomogram that integrated clinical features and MAPSs was developed to predict the OS rates in patients with cervical cancer. Blood microbiome data were combined with matched tumor RNA-seq data to analyze the differences in the tumor microenvironment between high- and low-MAPS groups, elucidating the impact of the MAPS on the tumor immune microenvironment. Finally, the potential application of the circulating MAPS to predicting the efficacy of immunotherapy and chemotherapy was assessed. The MAPS predictive model, which includes 15 circulating microorganisms, has shown independent prognostic value for patients with cervical cancer. Integrating the MAPS into a nomogram improved the accuracy of the prognostic predictions. Combined microbial and gene analyses revealed potential interactions between prognostic tumor microbiomes and the tumor immune microenvironment. The drug sensitivity analysis indicated the potential of MAPS as a predictor of chemotherapy’s efficacy. Our findings suggest that circulating microbial signatures hold promise as novel prognostic biomarkers and may inform personalized treatment strategies in cervical cancer. Further large-scale and multicenter studies are warranted to validate the clinical utility of the MAPS. Full article

Disease subtyping is essential for personalized medicine, enabling tailored treatment strategies based on disease heterogeneity. Advances in high-throughput technologies have led to the rapid accumulation of multi-omics data, driving the development of integration methods for comprehensive disease subtyping. However, existing approaches often lack explainability and fail to establish clear links between subtypes and clinical outcomes. To address these challenges, we developed EMitool, an explainable multi-omics integration tool that leverages a network-based fusion strategy to achieve biologically and clinically relevant disease subtyping without requiring prior clinical information. Using data from 31 cancer types in The Cancer Genome Atlas (TCGA), EMitool demonstrated superior subtyping accuracy compared to eight state-of-the-art methods. It also provides contribution scores for different omics data types, enhancing interpretability. EMitool-derived subtypes exhibited significant associations with the overall survival, pathological stage, tumor mutational burden, immune microenvironment characteristics, and therapeutic responses. Specifically, in kidney renal clear cell carcinoma (KIRC), EMitool identified three distinct subtypes with varying prognoses, immune cell compositions, and drug sensitivities. These findings highlight its potential for biomarker discovery and precision oncology. Full article

The rapid proliferation of artificial intelligence (AI) across various industries presents both opportunities and challenges, particularly concerning personal data privacy. With the enforcement of regulations like Thailand’s Personal Data Protection Act (PDPA), organizations face increasing pressure to protect sensitive information found in diverse data sources, including product and shipping labels. These labels, often processed by AI systems for logistics and inventory management, frequently contain Personally Identifiable Information (PII). This paper introduces a novel AI-driven system for automated PII redaction on label images, specifically designed to facilitate PDPA compliance. Our system employs a two-stage pipeline: (1) text extraction using a combination of EasyOCR and Tesseract OCR engines, maximizing recall for both Thai and English text; and (2) intelligent redaction using a pre-trained large language model (LLM), Qwen (Qwen/Qwen2.5-72B-Instruct-AWQ), prompted to identify and classify text segments as PII or non-PII based on simplified PDPA guidelines. Identified PII is then automatically redacted via black masking. We evaluated our system on a dataset of 100 drug label images, achieving a redaction precision of 92.5%, a recall of 83.2%, and an F1-score of 87.6%, with an over-redaction rate of 3.1%. These results demonstrate the system’s effectiveness in accurately redacting PII while preserving the utility of non-sensitive label information. This research contributes a practical, scalable solution for automated PDPA compliance in AI-driven label processing, mitigating privacy risks and promoting responsible AI adoption. Full article