Search Results (5,923)

Background and Objectives: Postoperative physical recovery, particularly the acquisition of independent ambulation, is a critical milestone in rehabilitation following living donor liver transplantation (LDLT). Although liver function markers are conventionally used to assess hepatic physiology, emerging evidence has suggested their potential role as prognostic indicators of physical performance. Materials and Methods: This study investigated the association between liver function parameters at the initiation of postoperative physical therapy (total bilirubin [T-Bil], aspartate aminotransferase [AST], and alanine aminotransferase [ALT]) and the independent walking ability of 63 patients who underwent LDLT. A logistic regression model was constructed using these variables, and a receiver-operating characteristic (ROC) curve analysis was performed to evaluate its discriminative performance. Predicted probabilities of each patient were calculated, and the optimal cutoff value was determined based on the Youden Index. Results: The multivariate logistic regression model demonstrated a statistically significant association between liver function markers and the ambulation status of a cohort of 63 patients. The ROC curve analysis yielded an area under the ROC curve (AUC) of 0.8416 (95% confidence interval [CI]: 0.715–0.968), indicating strong predictive performance. The optimal cutoff value was 0.865, with sensitivity and specificity of 74.1% and 88.9%, respectively. The bootstrap CI for sensitivity at this threshold ranged from 0.6111 to 0.8519. The Hosmer–Lemeshow test indicated good model fit (p = 0.363), and the correct classification rate was 87.3%. Conclusions: Liver function test results may be indicators of hepatic dysfunction as well as functional biomarkers that could predict ambulatory outcomes following LDLT. This predictive model may enhance early clinical decision-making regarding rehabilitation and discharge planning. Future prospective studies should be performed to validate the generalizability of these results to broader clinical contexts. Full article

Hepatocellular carcinoma (HCC) remains a global health challenge due to molecular heterogeneity and frequent delayed diagnosis. This comprehensive review synthesizes recent immunohistochemistry (IHC) advancements for HCC diagnosis, prognostication, and therapeutic prediction. We systematically evaluate conventional markers, such as hepatocyte paraffin 1 (HepPar1), arginase-1 (Arg-1), and glypican-3 (GPC3), as well as emerging biomarkers, detailing their diagnostic sensitivities and specificities in HCC with varied tumor differentiation. Prognostic immunostaining markers, such as Ki-67 proliferation index and vascular endothelial growth factor (VEGF) overexpression, correlate with reduced 5-year survival, while novel immune checkpoint IHC markers (PD-L1 and CTLA-4) predict response to immunotherapy, particularly in advanced HCC. This work provides evidence-based recommendations for optimizing IHC utilization in clinical practice while identifying knowledge gaps in biomarker validation and standardization. Full article

Background and Objectives: Anhedonia, a core symptom of major depressive disorder (MDD), is a known predictor of treatment response. It has been linked to heart rate variability (HRV), a physiological marker implicated in both MDD and cardiovascular disease. Agomelatine, a melatonergic antidepressant, has shown positive effects on both anhedonia and HRV. But little is known about the relationship between anhedonia improvement and HRV changes. This study aimed to investigate whether early changes in HRV predict anhedonia improvement following 8 weeks of agomelatine monotherapy. Materials and Methods: We enrolled 84 unmedicated patients with MDD and 143 age- and sex-matched healthy controls (HCs). Resting-state HRV, indexed by the standard deviation of NN intervals (SDNN), was recorded at baseline for all participants and after 1, 4, and 8 weeks of agomelatine treatment in patients. Anhedonia was assessed using the Snaith–Hamilton Pleasure Scale (SHAPS). Results: At baseline, patients exhibited significantly lower SDNN than HCs. After 8 weeks, SDNN levels in patients no longer differed significantly from HCs. SDNN decreased after one week of treatment but increased by week eight. Notably, a smaller reduction in SDNN after one week predicted greater improvement in anhedonia at week eight, filling the gap in the literature needed to facilitate treatment outcome prediction by integrating HRV assessment. Conclusions: Here we demonstrate that early reductions in HRV may serve as a predictive biomarker for anhedonia response to agomelatine in MDD. These findings support the potential utility of HRV monitoring to guide personalized treatment strategies. Full article

Background: Hereditary transthyretin amyloidosis (ATTRv) is a rare, autosomal dominant multisystem disease caused by pathogenic variants in the transthyretin (TTR) gene. Although ATTRv is classically categorized into “cardiac” and “neurologic” phenotypes, recent evidence suggests a more complex and overlapping disease spectrum. Objectives: This study investigates the relationship between neurological staging and cardiac involvement through an integrated assessment of patients with confirmed TTR mutations. Methods and Results: Fifty-eight patients with genetically confirmed ATTRv (41% female, mean age 60 ± 15 years) were evaluated. Genotypes included Phe64Leu, Val30Met, Val122Ile, and others. Patients were stratified by neurological stage: G0 (asymptomatic carriers), G1 (symptomatic but ambulatory), and G2 (requiring walking support). Cardiac assessment included clinical evaluation, echocardiography with tissue Doppler, global longitudinal strain (GLS), and NT-proBNP levels. Cardiac markers worsened with neurological stage. NT-proBNP, left ventricular mass index, maximal wall thickness, and E/E′ ratio increased progressively, while GLS declined (G0: –19%, G1: –14%, G2: –13%; p < 0.001), indicating a progressive structural and functional myocardial disease. Ejection fraction remained preserved. Neurological stage independently predicted cardiac dysfunction after age adjustment. Conclusions: This is the first study to assess cardiac abnormalities across neurological stages in a well-characterized cohort of ATTRv patients. Cardiac involvement in ATTRv begins early, even in asymptomatic carriers, and progresses with neurological deterioration. GLS and diastolic parameters are sensitive indicators of early myocardial dysfunction, highlighting the need for integrated neurologic and cardiac monitoring in all patients with ATTRv, regardless of initial phenotype. Full article

Borderline Personality Disorder (BPD) is marked by emotional dysregulation, instability in self-image and relationships, and high impulsivity. While functional magnetic resonance imaging (fMRI) studies have provided valuable insights into the disorder’s neural correlates, electroencephalography (EEG) may capture real-time brain activity changes relevant to BPD’s rapid emotional shifts. This review summarizes findings from studies investigating resting state and task-based EEG in individuals with BPD, highlighting common neurophysiological markers and their clinical implications. A targeted literature search (1980–2025) was conducted across databases, including PubMed, Google Scholar, and Cochrane. The search terms combined “EEG” or “electroencephalography” with “borderline personality disorder” or “BPD”. Clinical trials and case reports published in English were included if they recorded and analyzed EEG activity in BPD. A total of 24 studies met the inclusion criteria. Findings indicate that individuals with BPD often show patterns consistent with chronic hyperarousal (e.g., reduced alpha power and increased slow-wave activity) and difficulties shifting between vigilance states. Studies examining frontal EEG asymmetry reported varying results—some linked left-frontal activity to heightened hostility, while others found correlations between right-frontal shifts and dissociation. Childhood trauma, mentalization deficits, and dissociative symptoms were frequently predicted or correlated with EEG anomalies, underscoring the impact of adverse experiences on neural regulation—however, substantial heterogeneity in methods, small sample sizes, and comorbid conditions limited study comparability. Overall, EEG research supports the notion of altered arousal and emotion regulation circuits in BPD. While no single EEG marker uniformly defines the disorder, patterns such as reduced alpha power, increased theta/delta activity, and shifting frontal asymmetries converge with core BPD features of emotional lability and interpersonal hypersensitivity. More extensive, standardized, and multimodal investigations are needed to establish more reliable EEG biomarkers and elucidate how early trauma and dissociation shape BPD’s neurophysiological profile. Full article

Background and Objectives: Otitis media with effusion (OME), frequently associated with obstructive adenoid hypertrophy (OAH), is a leading cause of paediatric hearing loss. Clinically distinguishing effusion types (serous vs. mucoid) and predicting postoperative hearing recovery are unresolved challenges. This study evaluated the utility of preoperative blood inflammatory markers in predicting effusion characteristics and short-term hearing outcomes following adenoidectomy with tympanostomy tube (TT) insertion. Materials and Methods: In this retrospective cohort study, 232 children under 12 years old in 2024 and undergoing adenoidectomy (with or without TT insertion) were categorised into serous OME (n = 42), mucoid OME (n = 78), and non-effusion (n = 112) groups. Preoperative blood sample analyses assessed neutrophil, lymphocyte, eosinophil, basophil, and platelet counts, along with derived indices, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-basophil ratio (EBR), mean platelet volume (MPV), and systemic immune–inflammation index (SII). Hearing was evaluated at 2 weeks and 1 month postoperatively. Statistical analyses used SPSS v.28, with significance set at p < 0.05. Result: Mucoid OME patients exhibited significantly elevated neutrophil counts, platelet counts, eosinophils, NLR, and SII compared to those in serous OME and non-effusion groups (p < 0.05). All serous OME children achieved normal hearing by the first follow-up, whereas 15.4% of mucoid OME cases had transient mild hearing loss persisting after 2 weeks (p = 0.008; OR=15.97) but resolving by 1 month. Preoperative neutrophil count independently predicted delayed hearing recovery (p = 0.021). Conclusions: Systemic inflammatory markers, particularly neutrophil count, NLR, and SII, effectively differentiate mucoid OME from other effusion types and correlate with short-term hearing recovery. Neutrophil count may serve as a prognostic tool for surgical planning and patient counselling. Prospective studies are warranted to validate these findings in broader paediatric populations. Full article

Cardiovascular disease remains the world’s leading cause of mortality, yet everyday care still relies on episodic, symptom-driven interventions that detect ischemia, arrhythmias, and remodeling only after tissue damage has begun, limiting the effectiveness of therapy. A narrative review synthesized 183 studies published between 2016 and 2025 that were located through PubMed, MDPI, Scopus, IEEE Xplore, and Web of Science. This review examines CVD diagnostics using innovative technologies such as digital cardiovascular twins, which involve the collection of data from wearable IoT devices (electrocardiography (ECG), photoplethysmography (PPG), and mechanocardiography), clinical records, laboratory biomarkers, and genetic markers, as well as their integration with artificial intelligence (AI), including machine learning and deep learning, graph and transformer networks for interpreting multi-dimensional data streams and creating prognostic models, as well as generative AI, medical large language models (LLMs), and autonomous agents for decision support, personalized alerts, and treatment scenario modeling, and with cloud and edge computing for data processing. This multi-layered architecture enables the detection of silent pathologies long before clinical manifestations, transforming continuous observations into actionable recommendations and shifting cardiology from reactive treatment to predictive and preventive care. Evidence converges on four layers: sensors streaming multimodal clinical and environmental data; hybrid analytics that integrate hemodynamic models with deep-, graph- and transformer learning while Bayesian and Kalman filters manage uncertainty; decision support delivered by domain-tuned medical LLMs and autonomous agents; and prospective simulations that trial pacing or pharmacotherapy before bedside use, closing the prediction-intervention loop. This stack flags silent pathology weeks in advance and steers proactive personalized prevention. It also lays the groundwork for software-as-a-medical-device ecosystems and new regulatory guidance for trustworthy AI-enabled cardiovascular care. Full article

Background and Objectives: This study evaluated the correlation between hyperferritinemia and markers of liver steatosis, fibrosis, and risk of liver-related events in patients with type 2 diabetes mellitus (T2DM) and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). Material and Methods: This study included 271 patients that underwent a comprehensive medical evaluation. Hyperferritinemia was defined by values >200 ng/mL (females) and >300 ng/mL (males). Liver fibrosis and steatosis were evaluated by several non-invasive indexes, and Liver Risk Score (LRS) was calculated to determine the risk of liver-related events. Their correlation with serum ferritin was investigated by bivariate and multiple regression analyses. Receiver Operating Characteristic (ROC) analyses were used to assess the accuracy to predict advanced fibrosis and increased LRS. Statistical significance was set at p < 0.05. Results: The median serum ferritin level was 94.4 [128.1] ng/mL. Metabolic hyperferritinemia was present in 12.54% of patients. Patients with hyperferritinemia had higher liver enzymes, HbA1c, HOMA-IR, and increased markers of liver steatosis and fibrosis, with a higher prevalence of advanced fibrosis (OR = 3.744 [1.481, 9.460], p = 0.0081). LRS was highest in patients with hyperferritinemia (7.99 ± 2.01 vs. 7.12 ± 1.32 vs. 6.54 ± 1.06, p < 0.0001). Serum ferritin levels were correlated with LRS (β = 0.190 [0.001; 0.003], p < 0.001), liver fibrosis (Fibrotic NASH Index) (β = 0.198 [0.000; 0.001], p < 0.001), and steatosis, while haptoglobin concentrations were correlated negatively with them. Serum ferritin predicted the moderate risk of liver-related outcomes with an acceptable performance (area under the ROC curve = 0.726 [0.590; 0.862], p = 0.001). Conclusions: Hyperferritinemia is associated with liver fibrosis and steatosis and a higher risk of liver-related events in patients with T2DM and MASLD. Full article

Accurate genomic prediction of complex phenotypes is crucial for accelerating genetic progress in swine breeding. However, conventional methods like Genomic Best Linear Unbiased Prediction (GBLUP) face limitations in capturing complex non-additive effects that contribute significantly to phenotypic variation, restricting the potential accuracy of phenotype prediction. To address this challenge, we introduce a novel framework based on a self-supervised, pre-trained encoder-only Transformer model. Its core novelty lies in tokenizing SNP sequences into non-overlapping 6-mers (sequences of 6 SNPs), enabling the model to directly learn local haplotype patterns instead of treating SNPs as independent markers. The model first undergoes self-supervised pre-training on the unlabeled version of the same SNP dataset used for subsequent fine-tuning, learning intrinsic genomic representations through a masked 6-mer prediction task. Subsequently, the pre-trained model is fine-tuned on labeled data to predict phenotypic values for specific economic traits. Experimental validation demonstrates that our proposed model consistently outperforms baseline methods, including GBLUP and a Transformer of the same architecture trained from scratch (without pre-training), in prediction accuracy across key economic traits. This outperformance suggests the model’s capacity to capture non-linear genetic signals missed by linear models. This research contributes not only a new, more accurate methodology for genomic phenotype prediction but also validates the potential of self-supervised learning to decipher complex genomic patterns for direct application in breeding programs. Ultimately, this approach offers a powerful new tool to enhance the rate of genetic gain in swine production by enabling more precise selection based on predicted phenotypes. Full article

A comprehensive UPLC-MS/MS method was developed and validated for the simultaneous separation and quantification of atenolol, propranolol, quinidine, and verapamil, using established intestinal permeability standards in the Caco-2 cell monolayer model. This in vitro model is widely accepted for predicting intestinal drug permeability and is formally recognized by global regulatory agencies, including the FDA, EMA, and WHO, as a surrogate for assessing drug permeability in biowaiver applications under the Biopharmaceutics Classification System (BCS) framework. Despite its regulatory importance, standardized methods for the simultaneous quantification of key permeability markers remain scarce. The selected compounds represent distinct transport pathways: paracellular (atenolol), passive transcellular (propranolol, verapamil), and P-glycoprotein-mediated efflux (quinidine). Method validation followed FDA guidelines and demonstrated high selectivity, linearity (r² > 0.998), precision, and accuracy. Solid-phase extraction enhanced recovery and reduced matrix effects. Application to Caco-2 permeability assays confirmed expected transport profiles, including P-gp inhibition effects with verapamil. By integrating multiple analytes in a single workflow, the method improves analytical throughput, supports mechanistic interpretation, and ensures consistency across assays. This advanced separation strategy, combined with sensitive mass spectrometric detection, supports regulatory and BCS-based classification studies, contributing to the standardization of permeability assessments in drug development. Full article

Ulcerative colitis (UC) is associated with an elevated risk of colorectal cancer (CRC), driven by chronic inflammation and a distinct inflammation–dysplasia–carcinoma pathway. Conventional surveillance relies on colonoscopy and histologic assessment, but flat, multifocal dysplasia and sampling limitations challenge early detection. Tissue-based biomarkers offer promise in improving risk stratification and identifying patients at high risk for UC-associated CRC (UC-CRC). This review explores key categories of tissue biomarkers with potential clinical utility, including genetic mutations, epigenetic alterations, microRNA expression profiles, and markers of genomic instability such as telomere shortening, copy number variants, and aneuploidy. Many of these molecular alterations precede histologic dysplasia and reflect a “field effect,” suggesting their potential role in early cancer detection. Despite compelling associations between these biomarkers and neoplastic progression, most lack prospective validation and are not yet ready for routine clinical use. Future research should prioritize the development of integrated biomarker panels and validate their predictive accuracy in longitudinal UC cohorts. Molecular profiling may ultimately enable personalized, risk-adapted surveillance strategies that improve early detection while minimizing unnecessary interventions. Full article

Background/Objectives: We report on the association of clinical, demographic, and peri- and intraoperative factors with patient outcomes in large- and, separately, medium-vessel acute ischemic stroke (AIS) occlusions treated with mechanical thrombectomy or medical thrombolysis. Increasingly, neuroimaging, particularly novel markers of collateral status, has become useful in predicting response to endovascular treatment (EVT) among AIS patients. However, the relationship between these neuroimaging markers, documented predictors of stroke outcomes, and post-EVT functional status in anterior circulation large-vessel occlusions (LVOs) as compared to medium-vessel occlusions (MeVOs) remains unclear. We evaluated whether shared predictors of 90-day post-EVT functional outcomes in LVO compared to MeVO AIS patients within our institution exist. Methods: We retrospectively evaluated AIS patients treated at our institution between 9 January 2017 and 10 January 2023. The following were the inclusion criteria were applied: (i) CTA confirmed anterior circulation large or medium vessel occlusion; (ii) diagnostic CT perfusion was performed; (iii) mechanical thrombectomy was performed. A low modified Rankin score (mRS) indicating good functional outcomes (i.e., functional independence) was defined as less than or equal to 2, in accordance with prior studies. Univariate and multivariate logistic regression analyses were conducted to determine associations between demographic, clinical, and radiologic factors and mRS ≤ 2. Results: A total of 249 LVO (mean age 65.3 ± 16.2, 53.8% female) and 91 MeVO (mean age 68.9 ± 13.3, 46.2% female) patients met the inclusion criteria. Upon multivariate regression adjusted for race, age, hypertension, diabetes mellitus, radiologic features, IV alteplase, admission NIHSS, and reperfusion status, young age (p = 0.004), low admission NIHSS (p = 0.0001), and good reperfusion status (p = 0.007) were associated with good functional outcomes in LVO stroke. By contrast, no factors were significantly associated with good functional outcomes in MeVO stroke. Conclusions: Known factors, including young age, low admission stroke severity, and successful reperfusion predict EVT outcomes in LVO stroke but not necessarily in MeVO stroke. Further studies regarding predictors of MeVO outcomes in nonsurgical cases, including collateral status, may guide optimal medical management for this population. Full article

Background: Indigofera pseudotinctoria, a traditional Chinese forage and medicine widely used in East Asia, holds significant economic and agricultural value. Despite this, genomic information regarding I. pseudotinctoria remains conspicuously lacking. Methods: In this study, we utilized genome survey sequencing to elucidate the complete genome sequence of this species. Results: The genome size of I. pseudotinctoria to be around 637–920 Mb with a heterozygosity rate of 0.98% and a repeat rate of 66.3%. A total of 240,659 simple sequence repeat (SSR) markers were predicted in the genome of I. pseudotinctoria. Substantial differences were observed among nucleotide repeat types, for instance, mononucleotide repeats were found to be predominant (62.47%), whereas pentanucleotide repeats were notably scarce (0.24%). Furthermore, among dinucleotide and trinucleotide repeats, sequence motifs AT/AT (66.57%) and AAT/ATT (54.15%) were found to be particularly abundant. Among the identified unigenes, 58,790 exhibited alignment with known genes in established databases, including 33,218 genes within the Gene Ontology (GO) database and 10,893 genes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Conclusions: This study marks the first attempt to both sequence and delineate the genomic landscape of I. pseudotinctoria. Importantly, it will serve as a foundational reference for subsequent comprehensive genome-wide deep sequencing and the development of SSR molecular markers within the scope of I. pseudotinctoria research. Full article

As the leading cause of global mortality, cardiovascular diseases demand improved and innovative strategies for early detection and risk assessment to enhance prevention and timely treatment. This comprehensive review examines the potential of combining high-sensitivity cardiac troponins (hs-cTns) and homocysteine (Hcy) as complementary biomarkers for enhanced cardiovascular risk prediction. hs-cTn assays have revolutionized cardiovascular diagnostics by enabling the detection of minimal myocardial injury, improving early diagnosis of acute coronary syndrome, and providing robust prognostic information in both symptomatic and asymptomatic populations. Hcy, while established as a marker of vascular dysfunction, presents an interpretative challenge due to multiple confounding factors and inconsistent therapeutic responses. Emerging evidence demonstrates significant correlations between elevated Hcy and troponins across various clinical conditions, suggesting that their combined assessment—reflecting both myocardial injury and vascular dysfunction—may improve cardiovascular risk stratification. While initial findings are promising, additional studies are required to validate the clinical value of the combined marker approach. Future development of personalized interpretation algorithms, and multi-marker panels incorporating these biomarkers, may significantly advance cardiovascular medicine and enable more effective population-specific risk management strategies. Full article

Background/Objectives: Proteinuria, a marker of renal dysfunction, has been implicated in cancer risk, yet its role in gastric carcinogenesis remains underexplored in high-incidence populations. This study evaluated the association between urine dipstick proteinuria severity and gastric cancer incidence in a nationwide Korean cohort. Methods: We analyzed data from the Korean National Health Insurance Service–National Sample Cohort, including 220,941 adults aged > 40 years, without a diagnosis of cancer, who received health examinations in 2009. Proteinuria was classified by single dipstick testing as negative, 1+, or ≥2+. Participants were followed for a mean of 4.37 ± 0.49 years (965,601.2 person-years). Multivariable Cox proportional hazards models adjusted for age, sex, body mass index, systolic blood pressure, fasting glucose, LDL cholesterol, estimated glomerular filtration rate, smoking status, alcohol intake, and physical activity were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: During follow-up, 1934 participants (0.88%) developed gastric cancer. A significant dose–response relationship emerged (p for trend = 0.037). In fully adjusted models, 1+ proteinuria conferred no significant risk increase (HR 1.10; 95% CI, 0.80–1.51), whereas ≥2+ proteinuria was associated with a 42% higher gastric cancer risk (HR 1.42; 95% CI, 1.00–2.02). Conclusions: Severe dipstick proteinuria independently predicts elevated gastric cancer risk in Korean adults. Integration of urine dipstick testing into gastric cancer screening protocols may offer a simple, cost-effective strategy for risk stratification, particularly in high-incidence settings. Full article