Search Results (3,296)

Advancements in genomic technologies have transformed prenatal genetic testing, offering more accurate, comprehensive, and noninvasive approaches to reproductive care. This review provides an in-depth overview of current methodologies and emerging innovations, including expanded carrier screening (ECS), cell-free DNA (cfDNA) testing, chromosomal microarray analysis (CMA), and sequencing-based diagnostics. We highlight how next-generation sequencing (NGS) technologies have revolutionized carrier screening and fetal genome analysis, enabling detection of a broad spectrum of genetic conditions. The clinical implementation of cfDNA has expanded from common aneuploidies to include copy number variants (CNVs), and single-gene disorders. Diagnostic testing has similarly evolved, with genome sequencing outperforming traditional CMA and exome sequencing through its ability to detect both sequence and structural variants in a single assay. Emerging tools such as optical genome mapping, RNA sequencing, and long-read sequencing further enhance diagnostic yield and variant interpretation. This review summarizes major technological advancements, assesses their clinical utility and limitations, and outlines future directions in prenatal genomics. Full article

Background/Objectives: Cerebral palsy (CP) is a leading cause of motor disability in children and is commonly associated with spasticity. Treatment with radial extracorporeal shock waves (rESWs) is an established non-invasive therapy for spasticity, although its underlying mechanisms remain poorly understood. Caenorhabditis elegans (C. elegans) represents a powerful model for neuromuscular research due to its fully mapped nervous system, conserved cholinergic pathways and suitability for high-throughput behavioral analysis. This study aimed to test whether rESWs modulate cholinergic signaling at the neuromuscular junction (NMJ) in C. elegans. Methods: Wild-type and acr-16 mutant C. elegans were exposed in liquid to varying doses of rESWs, nicotine and carbachol in different combinations. Locomotor behavior was recorded using high-resolution video tracking, and parameters including peristaltic speed, body wavelength, reversals and omega bends were quantified. Results: Exposure to rESWs transiently altered locomotion, most notably by reducing forward speed and increasing the frequency of reversals. However, rESWs did not consistently modify behavioral responses to nicotine or carbachol, and these effects were not clearly dependent on NMJ-associated nicotinic receptors. Conclusions: Exploring C. elegans as a model for rESW effects on spasticity proved informative but also revealed important limitations. Results indicate that rESWs act on the nervous system more broadly, extending beyond neuromuscular structures. This contrasts with the clinical situation, where rESWs primarily target muscles and connective tissues. While this precludes C. elegans as a direct model for CP-related spasticity, the observation that rESWs influence nervous-system function at a systemic level points to potential therapeutic avenues for neurological diseases. Full article

Background: Deep learning (DL) models using Holter-ECG may enhance risk stratification after heart failure (HF) or myocardial infarction (MI). Objective: To evaluate the prognostic performance of a Holter-based DL model for predicting major adverse cardiac events (MACE), compared with conventional noninvasive markers. Methods: In the K-REDEFINE study, 1108 patients with acute MI or HF underwent 24 h Holter monitoring. A DL model was trained using raw Holter-ECG data and tested for predicting a composite of cardiac death and ventricular arrhythmias. Its performance was compared with heart rate turbulence (HRT), T-wave alternans (TWA), and ejection fraction (EF). Results: During follow-up, 56 adjudicated cardiac deaths (1.18%/yr) and 21 ventricular arrhythmias (0.44%/yr) occurred. The DL model showed an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI, 0.70–0.77) for the composite outcome, improving to 0.77 (0.74–0.81) when combined with EF. In comparison, HRT and TWA showed lower AUROCs of 0.62 and 0.55, respectively. For cardiac death alone, the AUROC reached 0.79, further improving to 0.82 with EF. Model-derived risk stratification revealed a seven-fold increase in cardiac death risk in the high-risk group compared to the low-risk group (HR 7.47, 95% CI 2.24–24.96, p < 0.001). This stratification remained particularly effective in patients with EF > 40%. Conclusions: A DL algorithm trained on single-lead Holter-ECG data effectively predicted cardiac death and ventricular arrhythmia. Its performance surpassed conventional markers and was further enhanced when integrated with EF, supporting its potential for noninvasive, scalable risk stratification. Full article

Background/Objectives: Ischemia with non-obstructive coronary arteries (INOCA) remains an underdiagnosed and undertreated condition due to the extensive diagnostic testing required and heterogeneous pathophysiology of different endotypes, each of which require tailored treatment. This study aimed to explore the effect of intracoronary physiology testing-based endotype-specific medical therapy on quality of life in patients with INOCA. Methods: Intracoronary physiology testing was performed in patients presenting with cardiac symptoms, evidence of significant ischemia on non-invasive testing, and non-obstructive epicardial coronary arteries. Microvascular angina (MVA) was defined as coronary flow reserve ≤ 2.5 and an index of microvascular resistance ≥ 25. Vasospastic angina (VSA) was defined as a >90% vasoconstriction of an epicardial artery during acetylcholine provocation test in the presence of ischemic electrocardiogram changes and chest pain. Quality of life was evaluated using the Seattle Angina Questionnaire 7 (SAQ-7) before the start of new treatment and at the three months follow-up. Results: The total study population consisted of 35 patients (80% women), of whom MVA was observed in 19 (54.3%), VSA in 9 (25.7%), and the combination of MVA and VSA in 3 (8.6%) cases. Four patients (11.4%) had no pathology on intracoronary physiology testing detected. High rates of dyslipidemia (100%), arterial hypertension (85.7%), diabetes (17.1%), and depression and anxiety (34.3%) were documented. In the isolated MVA and VSA groups, adjustment of medical therapy resulted in an improvement in the SAQ-7 summary score at 3 months (p < 0.001 and p = 0.007, respectively). There was no change of SAQ-7 summary score in the mixed endotype group (p = 0.11). Conclusions: Adjustment of medical therapy according to intracoronary physiology testing-based phenotype resulted in improved quality of life as assessed by the SAQ-7. Our findings highlight the importance of invasive testing in patients with clinically suspected INOCA. Full article

Obstructive sleep apnea (OSA) is a commonly underdiagnosed condition that not only increases the risk of accidents but also significantly contributes to a wide range of health complications, including heightened perioperative morbidity and mortality risks during surgeries under general anesthesia. Polysomnography (PSG), which is the diagnostic gold standard, is costly, requires skilled technicians, is time-consuming, and is not always accessible. This study presents a fast, objective, and non-invasive method for detecting OSA severity by analyzing tracheal breathing sounds (TBS) recorded during wakefulness in supine position. Features were extracted from six binary (1-vs-1) severity comparisons—Non-OSA, Mild, Moderate, and Severe—and combined with anthropometric characteristics for classification. The data of 199 subjects (74 Non-OSA, 35 Mild, 50 Moderate, and 40 Severe) were analyzed, the data of 169 and 30 was used for training and blind testing, respectively, and the training dataset was shuffled 10 times to avoid any bias during training. Multiple machine learning models were evaluated, and the best-performing model for each was saved. Across six experimental models comparing OSA severity levels, the most balanced performance was achieved by the Base Model of Non-OSA vs. Severe-OSA using the support vector machine algorithm, with 88.2% accuracy, 83.3% sensitivity, and 90.9% specificity. While Random Forests in the Base Model of Non-OSA vs. Mild-OSA achieved 100% sensitivity, its accuracy was lower (81.2%). The results confirm the reliability and robustness of the proposed approach, providing a basis for OSA severity screening in under 10 min during wakefulness. Full article

Background/Objectives: High-frequency ultrasonography (HFUS) has gained increasing attention in dermatology as a non-invasive imaging technique capable of visualizing cutaneous structures with high resolution. In cutaneous T-cell lymphomas (CTCL), including mycosis fungoides (MF)/Sézary syndrome (SS), HFUS may provide an objective method for assessing disease activity and monitoring treatment response. This study aimed to evaluate the clinical utility of HFUS in detecting therapy-induced changes in subepidermal low-echogenic band (SLEB) thickness. Methods: We conducted a prospective, single-center study between May 2021 and May 2025. Thirty-three patients with histologically confirmed MF (n = 31) or SS (n = 2) underwent HFUS at baseline and after 4–8 weeks of treatment. SLEB thickness was measured before (E1) and after early treatment (E2). Patients received systemic agents, phototherapy, or topical regimens. Statistical analysis included mixed-model ANOVA with repeated measures to assess SLEB changes, and post hoc tests were applied to explore the influence of therapy type, age, and gender. Results: Among 31 evaluable patients with MF, HFUS revealed a significant reduction in SLEB thickness after treatment (0.90 ± 1.10 mm vs. 0.69 ± 0.89 mm; F(1,29) = 8.88, p = 0.006, η² = 0.23). The type of early therapy (systemic vs. topical) did not significantly affect outcomes (p = 0.452). Age emerged as a relevant factor: patients ≥ 66 years exhibited higher baseline SLEB values and a significant reduction post-treatment (p < 0.001), whereas no comparable effect was observed in younger patients. Gender did not significantly influence SLEB changes. Conclusions: HFUS is a sensitive and clinically applicable imaging tool for monitoring treatment response in MF/SS. Reductions in SLEB thickness were observed across therapeutic modalities and aligned with early clinical improvement. HFUS may serve as a valuable adjunct to standard clinical and histopathological evaluation in the routine management of MF/SS. Full article

Objectives: To identify factors correlated with post-surgery residue in cases of breast cancer incidentally found via vacuum-assisted excision (VAE). Methods: A total of 6083 patients were enrolled in a retrospective study. Ultrasound evaluation and ultrasound-guided VAE were performed on these patients. According to the pathology of VAE, 53 patients with incidentally found breast cancer were included in the final analysis. Either breast-conserving surgery or mastectomy was performed. The maximal diameter, depth, location, BIRADS category, and Adler’s grade of all lesions before VAE was reviewed and recorded. VAE and post-surgery pathologies were used as gold standards. Either Pearson’s chi-square test or Fisher’s exact test was used for comparison of categorical variables. Results: The mean age of the enrolled patients was 49 years (IQR: 43–55 years). The mean maximal diameter of the lesions was 11.3 mm (IQR: 7–15 mm). There were twenty-eight ductal carcinomas in situ, twelve invasive ductal carcinomas, five lobular carcinomas in situ, two invasive lobular carcinomas, four intraductal papillary carcinomas, and two mucinous carcinomas. Post-surgery pathology showed 15 cases with residual cancer and 38 cases with no residual cancer. The maximal diameter, depth, and pathology derived via VAE were statistically correlated with post-surgery residue (p < 0.05). Conclusions: Small incidentally found noninvasive carcinomas located comparatively deep in the breast could be totally excised by ultrasound-guided vacuum-assisted excision. Both large and superficially invasive carcinomas were more likely to be associated with residue. Full article

Objective: This study aimed to validate the clinical utility of a salivary molecular platform (Oral Predict^®) for periodontal pathogen detection across preventive, therapeutic, and maintenance settings. Methods: A longitudinal randomized study was conducted involving 78 adults who provided saliva samples at baseline, one month, and three months after professional dental hygiene. Participants were randomized into two groups: control group (n = 39) and probiotic group with Oral Predict^® probiotic supplementation (n = 39). Crude saliva was processed directly without nucleic acid extraction and analyzed by multiplex real-time PCR using either the compact Real-time PCR system or standard thermocyclers. Results: At baseline, Fusobacterium nucleatum was the most prevalent pathogen (84.6%), followed by Tannerella forsythia (53.8%) and Porphyromonas gingivalis (46.2%). The Total Pathogen Burden Score (TPBS) showed progressive increases with age, smoking, and poor oral hygiene, and was significantly higher in participants with gingival bleeding. Among individual pathogens, no significant associations were observed with periodontitis staging or grading. Professional hygiene induced mean reductions of 1–2 logs across all pathogens, with TPBS decreasing from 8.7 ± 3.2 to 4.1 ± 2.8 (p < 0.001). At three months, 69.2% of the control group experienced bacterial rebound, whereas 85% of probiotic users sustained or improved bacterial reductions. Conclusions: Salivary molecular testing provides a robust, non-invasive approach for periodontal pathogen detection, treatment monitoring, and long-term maintenance assessment. The flexibility of the Oral Predict^® platform across point-of-care and laboratory settings, combined with automated interpretation, supports integration into preventive protocols and personalized periodontal care. These findings demonstrate the potential of saliva-based molecular diagnostics to shift periodontal management from reactive to predictive and precision-based strategies. Full article

Background/Objectives: Radiomics enables extraction of quantitative imaging features to support non-invasive classification of prostate cancer (PCa). Accurate detection of clinically significant PCa (csPCa; Gleason score ≥ 3 + 4) is crucial for guiding treatment decisions. However, many studies explore limited feature selection, classifier, and harmonization combinations, and lack external validation. We aimed to systematically benchmark modeling pipelines and evaluate whether combining radiomics with the lesion-to-normal ADC ratio improves classification robustness and generalizability in multicenter datasets. Methods: Radiomic features were extracted from ADC maps using IBSI-compliant pipelines. Over 100 model configurations were tested, combining eight feature selection methods, fifteen classifiers, and two harmonization strategies across two scenarios: (1) repeated cross-validation on a multicenter dataset and (2) nested cross-validation with external testing on the PROSTATEx dataset. The ADC ratio was defined as the mean lesion ADC divided by contralateral normal tissue ADC, by placing two identical ROIs in each side, enabling patient-specific normalization. Results: In Scenario 1, the best model combined radiomics, ADC ratio, LASSO, and Naïve Bayes (AUC-PR = 0.844 ± 0.040). In Scenario 2, the top-performing configuration used Recursive Feature Elimination (RFE) and Boosted GLM (a generalized linear model trained with boosting), generalizing well to the external set (AUC-PR = 0.722; F1 = 0.741). ComBat harmonization improved calibration but not external discrimination. Frequently selected features were texture-based (GLCM, GLSZM) from wavelet- and LoG-filtered ADC maps. Conclusions: Integrating radiomics with the ADC ratio improves csPCa classification and enhances generalizability, supporting its potential role as a robust, clinically interpretable imaging biomarker in multicenter MRI studies. Full article

Background: A thorough post-myocardial infarction (MI) evaluation is essential for prognosis and rehabilitation. While cardiopulmonary exercise testing (CPET) is the standard for assessing functional capacity, combining it with dynamic stress echocardiography (DSE) may offer a more comprehensive assessment. Aim: This study examined the role of stress echocardiography (SE) in male post-MI patients by evaluating left ventricular function with conventional indices and the change in global longitudinal strain (ΔGLS) at rest and during maximal treadmill CPET. A secondary aim was to determine whether ΔGLS could provide additional value to traditional measures in post-MI care. Methods: Eighteen men with a recent MI [15 ST-elevation MI, three non-ST-elevation MI; mean age 53.2 ± 5.9 years, mean body mass index (BMI) 27.9 ± 2.2, 44.4% with a smoking history) and 18 age-matched male controls (mean age 50.1 ± 10.8 years, mean BMI 26.5 ± 2.4, 39.0% with smoking history) were enrolled. All MI patients were under optimal medical therapy, including β-blockers, which were withheld on the test day. Most underwent percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG) n = 2, or PCI for non-ST-elevation MI (NSTEMI) n = 3. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) were measured at rest and at peak effort and correlated with CPET parameters. Results: Post-MI patients had lower LVEF (50.6% vs. 60.7% at rest; 55.3% vs. 67.4% at peak, both p < 0.001), impaired GLS (–14.7% vs. –20.2% at rest, p = 0.003; –15.8% vs. –22.7% at peak, p = 0.001), and reduced VO₂peak (29.2 vs. 41.9 mL/kg/min, p < 0.001) compared with controls. In the MI group, ΔGLS correlated with VO₂peak (r = –0.645, p = 0.003) and VE/VCO₂ (r = 0.539, p = 0.020), indicating its potential as a marker of functional reserve. Conclusions: Combined CPET and SE offered comprehensive insights into functional and myocardial performance, identifying ΔGLS as a useful non-invasive index for risk stratification and rehabilitation after MI, with high feasibility and safety. Full article

Advances in smart animal husbandry necessitate efficient pig behavior monitoring, yet traditional approaches suffer from operational inefficiency and animal stress. We address these limitations through a lightweight YOLOv8n architecture enhanced with SPD-Conv for feature preservation during downsampling, LSKBlock attention for contextual feature fusion, and a dedicated small-target detection head. Experimental validation demonstrates superior performance: the optimized model achieves a 92.4% mean average precision (mAP@0.5) and 87.4% recall, significantly outperforming baseline YOLOv8n by 3.7% in AP while maintaining minimal parameter growth (3.34M). Controlled illumination tests confirm enhanced robustness under strong and warm lighting conditions, with performance gains of 1.5% and 0.7% in AP, respectively. This high-precision framework enables real-time recognition of standing, prone lying, lateral lying, and feeding behaviors in commercial piggeries, supporting early health anomaly detection through non-invasive monitoring. Full article

The aim of our study is to determine the changes in the biomarkers CXCL-16, CCL-20, GDF-15, and CD8a, which play an immunological role in CHB patients according to viral load to determine their diagnostic potential and to investigate their relationships with hematological parameters and non-invasive fibrosis indices. Our study included 96 chronic hepatitis B patients and 30 healthy individuals as a control group. The patients were divided into three groups based on their serum HBV DNA levels: mild (0–10² IU/mL), moderate (10³–10⁵ IU/mL), and severe viral load (10⁶–10⁸ IU/mL). HBV DNA levels were determined by the real-time PCR (Anatolia, Istanbul, Turkey) method. CXCL-16, GDF-15, and CD8a levels in patient serum were quantitatively determined by the ELISA method (Elabscience, Wuhan, China), and CCL-20 levels were determined by the ELISA method BT LAB, Shanghai, China). ROC (Receiver Operating Characteristics) and HUM (Hypervolume Under Manifold) analyses were used to determine the diagnostic efficacy of the biomarkers. ROC analyses showed that GDF-15 (AUC = 0.920) and CCL-20 (AUC = 0.751) had “very good” and “good” diagnostic values, respectively, in predicting hepatitis B disease. HUM analyses revealed that all biomarkers have good potential when it comes to distinguishing the severity of the disease. This study has shown that the biomarkers GDF-15 and CCL-20 may be potential diagnostic biomarkers in detecting the presence of chronic hepatitis B, and the biomarkers CXCL-16, CCL-20, GDF-15, and CD8a may be potential diagnostic biomarkers in determining the severity of the disease. These findings suggest that these biomarkers, which can be measured by the simpler and more economical ELISA method, could be a supportive tool for the HBV DNA test. The clinical use of these biomarkers can be expanded with future prospective studies. Full article

Background: Despite technological advancements in cataract surgery, including Femtosecond Laser-Assisted Cataract Surgery (FLACS), postoperative dry eye disease (DED) remains a challenge, impacting patients’ quality of life. Identifying preoperative predictors of ocular discomfort could improve patient management. Methods: This exploratory prospective study compared the onset of DED symptoms and ocular surface changes after FLACS and standard cataract surgery (SCS). Twenty eyes were evaluated preoperatively and postoperatively, using Ocular Surface Disease Index (OSDI), Non-Invasive Break-Up Time (NI-BUT), Schirmer I Test, and Oxford Score. One-week OSDI was analyzed as the dependent variable using multivariable quantile regression (τ = 0.5), with baseline parameters (OSDI, Oxford score, Schirmer test, NI-BUT), age, BCVA, surgical technique, and cumulative dissipated energy (CDE) as predictors. Results: FLACS was associated with a transient worsening of OSDI at one week, which resolved by three months, whereas SCS showed a milder but more gradual increase. In multivariable analysis, baseline OSDI (β = 0.61, p < 0.001) and Oxford score (β = 5.42, p = 0.045) were independent predictors, while surgical technique and perioperative parameters were not significant. In a reduced model, both predictors confirmed their association. Subgroup analyses showed baseline OSDI as predictive only in FLACS. Conclusions: Preoperative ocular surface status emerges as the main determinant of early postoperative DED symptoms. Routine assessment of OSDI and Oxford scores may help identify at-risk patients and guide preventive strategies. Full article

Background: Since the introduction of the hepatitis B virus (HBV) vaccination program in Oman in 1990, the HBV prevalence has markedly decreased. However, hepatitis D virus (HDV) infection, which is associated with progressive liver disease in patients with chronic HBV, remains understudied in the Omani population. This study aimed to estimate HDV’s seroprevalence, characterize its virological and clinical features, and identify factors associated with anti-HDV positivity among adult Omani patients with chronic HBV infection. Methods: We conducted a multicenter cross-sectional study in 2024 at two referral hospitals and two polyclinics in Oman. Adult Omani patients with chronic HBV (HBsAg-positive for >6 months) were enrolled. Demographic, clinical, laboratory, imaging, and elastography data were collected. The total anti-HDV antibodies were tested using an ELISA; HDV RNA was tested for anti-HDV-positive or equivocal results. Liver Fibrosis was assessed non-invasively through liver stiffness measurement (LSM) using vibration-controlled transient elastography (VCTE); FibroScan^® and clinical evaluation. Ridge (penalized) logistic regression identified predictors independently associated with anti-HDV positivity. Results: Among 639 patients (59.3% male; mean age of 46.6 ± 8.8 years), 36 patients were anti-HDV-positive, resulting in an HDV seroprevalence of 5.6% (95% CI: Exact 3.98–7.71; Wilson 4.10–7.70). Only one anti-HDV-positive patient had detectable HDV RNA, which became undetectable on follow-up without HDV treatment. The anti-HDV-positive patients were more frequently female and had a higher frequency of prior blood transfusions. In a penalized multivariable analysis, blood transfusions were independently associated with anti-HDV positivity (OR of 19.94), whereas male sex was associated with lower odds of being anti-HDV-positive (OR of 0.15). All the anti-HDV-positive patients had mild fibrosis (F0–F1). Conclusions: Our study demonstrated an anti-HDV prevalence of 5.63% among adult Omani patients with chronic HBV infection, while active viremia appeared to be rare. Blood transfusions were the main identified risk factor. Given the very low HDV viremia, targeted screening of higher-risk groups may be efficient. Full article

This study tested whether classic and specific bioelectrical impedance vector analysis (BIVA) parameters could explain metabolic and mechanical performance in endurance-trained trail runners. Fifteen males ($\dot{\mathrm{V}}$O₂max 61.04 ± 6.91 mL·kg⁻¹·min⁻¹) completed a 60-min treadmill protocol at 70% $\dot{\mathrm{V}}$O₂max across randomized slopes (−7% to +7%), with continuous gas-exchange, heart-rate, and running-power recording; whole-body BIVA was obtained immediately pre- and post-exercise. Post-test, impedance and resistance increased (+2.73%, +2.84%), while reactance (Xc) and phase angle decreased (−2.36%, −4.91%); all were significant and mirrored by both classic and specific indices, consistent with acute fluid loss and altered cellular status. After Benjamini–Hochberg adjustment, baseline Xc/height correlated inversely with $\dot{\mathrm{V}}$CO₂peak and $\dot{\mathrm{V}}$CO₂mean, whereas exercise-induced changes in ΔXc/height and ΔXcspecific correlated positively with both metabolic variables and mean power. Stepwise regression retained ΔXc/h or ΔXcspecific as the only BIVA predictors for $\dot{\mathrm{V}}$CO₂peak, $\dot{\mathrm{V}}$CO₂mean, and mean power output, explaining ~31–36% and ~22–23% of the variance, respectively; classic and specific approaches performed similarly. No bioelectrical variable predicted $\dot{\mathrm{V}}$O₂max. These preliminary findings suggest that acute reactance shifts may provide a modest yet sensitive, non-invasive index of exercise-induced physiological responses, warranting confirmation in larger and more diverse cohorts. Full article