Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of electrocardiogram (ECG) non-linear features and different topological medical features (heart rate, anthropometry, blood, glucose, and lipid profile, and heart rate variability) to discriminate between different Framingham Cardiovascular Risk Scale status groups in adult obesity using machine learning.

We conducted a cross-sectional study between November 2023 and May 2024 in Fortaleza, Ceará, Brazil. Based on the Framingham Cardiovascular Risk Scale, patients were categorized into three cardiovascular risk groups: Low (22 participants), Moderate (14 participants), and High (17 participants). From ECG signals at two different positions (ECG_Down and ECG_UP), 27 non-linear features were extracted using multi-band analysis. Additionally, 42 medical features provided by physicians were included. From a pool of 19 machine learning classifiers, models were trained and tested within a nested leave-one-out cross-validation procedure using information solely from ECG, solely from medical features, and combining both (multimodal), respectively, to distinguish between Low vs. Moderate, Low vs. High, Moderate vs. High, and All vs. All.

The multimodal model presented the best results for every comparison group, reaching (1) 88.89% Accuracy and 0.8831 area under the curve (AUC) for Low vs. Moderate; (2) 97.44% Accuracy and 0.9706 AUC for Low vs. High; (3) 93.55% Accuracy and an AUC of 0.9412 for Moderate vs. High; (4) 86.79% Accuracy and 0.9346 AUC for All vs. All.

The multimodal model outperformed single-source models in cardiovascular risk classification. ECG-derived non-linear features, especially from ECG_Down, were key drivers, with medical features adding complementary value. The results support its potential use in clinical triage and diagnosis.

Reporting quality in clinical research is critical for evidence-based medicine and reproducibility of clinical studies. Previous work has mostly focused on the reporting quality of clinical trials and observational longitudinal studies. However, few studies have examined the reporting quality of trend analyses. Moreover, the reporting of recommended statistical metrics in trend analyses remains largely unclear. Therefore, we assessed the reporting quality of trend analyses based on reporting of recommended statistical metrics. We systematically searched the PubMed for the trend-analysis articles published in 10 leading medicine and oncology journals over an 11-year period (2008–2018). Studies published after 2019 were excluded due to a sudden, significant increase in publication numbers during and immediately after the COVID-19 pandemic. Only original articles, research letters, and meta-analyses/systematic reviews were included. We scored the reporting quality of these articles based on whether they reported p-values, effect sizes, beta/coefficient/slope/annual-percentage-change (APC). 297 articles met the inclusion criteria. Among these, 193 (66.0%) reported p-values and 216 (72.7%) reported effect sizes. Only 13 (5.8%) analyses reported neither p-values/effect sizes nor beta/coefficient/slope/APC. In multivariable regression models, authors affiliated with epidemiology departments were less likely to report effect sizes, whereas those from statistics departments were more likely to do so. Interestingly, U.S.-based senior authors (versus non-U.S.) more likely reported p-values. No factors were independently associated with reporting APC. Overall, the reporting quality of trend analyses in leading medicine and oncology journals appears moderate and warrants improvement. We thus call for increased awareness and further research on reporting quality in trend analyses in oncology research and beyond.

Cirrhotic cardiomyopathy (CCM) is a significant complication of cirrhosis, but its progression and underlying mechanisms remain incompletely understood. This study aimed to investigate dynamic changes in cardiac function, pathology, inflammation, and mitochondrial damage in a mouse model of CCM, and to compare echocardiographic characteristics in patients with cirrhosis.

Bile duct ligation was performed in male C57BL/6J mice to induce cirrhosis. Longitudinal analyses were conducted over eight weeks. Cardiac function was assessed using serum biomarkers, echocardiography, and electrocardiography. Pathology was examined with hematoxylin and eosin, Masson’s trichrome, Sirius Red, and wheat germ agglutinin staining. Western blotting and immunohistochemistry were used to detect markers of inflammation, fibrosis, apoptosis, and mitochondrial function. Cardiac and liver function markers were also evaluated in patients with cirrhosis.

Mice subjected to bile duct ligation developed progressive cardiac dysfunction, including reduced cardiac output and diastolic dysfunction (end-diastolic interventricular septal thickness, left ventricular internal diameters, stroke volume, and left ventricular end-diastolic volume decreased, whereas ejection fraction and fractional shortening increased), as well as cardiac atrophy. Myocardial apoptosis, inflammation (elevated tumor necrosis factor, interleukin-6, and p65), and fibrosis worsened over time. Mitochondrial injury was characterized by reduced carnitine palmitoyltransferase 1A and peroxisome proliferator-activated receptor alpha, with increased hexokinase 2, pyruvate kinase M2, and lactate dehydrogenase A. In patients with cirrhosis, impaired cardiac function and elevated brain natriuretic peptide levels correlated with total bilirubin.

The progression of CCM is closely associated with cirrhosis severity and appears to be driven by myocardial atrophy, apoptosis, inflammation, fibrosis, and mitochondrial dysfunction.

Clove essential oil (CEO) derived from Syzygium aromaticum and miswak (Salvadora persica) contains bioactive compounds with antimicrobial properties. Due to the growing interest in alternatives to conventional antibiotics, this study aimed to evaluate the in vitro antimicrobial efficacy of CEO, miswak, and their combination against key peri-implantitis pathogens.

The antimicrobial activities of CEO, miswak, and their combinations were tested against Fusobacterium nucleatum, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Prevotella intermedia. Disc diffusion and serial dilution methods were used to measure the inhibition zones and minimum inhibitory concentrations, respectively. Doxycycline served as a standard antibiotic for comparison, while ethanol was used as a negative control. Data were analyzed using one-way analysis of variance and Tukey’s honestly significant difference test, with significance set at α = 0.05.

CEO exhibited inhibition zones of 10–16 mm, comparable to that of doxycycline (13–16 mm), whereas miswak (6–13 mm vs. 1–14 mm) and the CEO–miswak combination (8–14 mm vs. 0–14 mm) showed lower activity. Mean minimum inhibitory concentration values were lowest for doxycycline (1.73 ± 0.46 µg/mL), followed by CEO (2.37 ± 0.24 µg/mL) and CEO–miswak combination (2.92 ± 0.12 µg/mL). Statistical analysis showed that the CEO–miswak combination was less effective than CEO (p = 0.0326) and doxycycline (p = 0.0001), but not different from miswak (p = 0.9836). CEO showed slightly greater activity than miswak (p = 0.0605).

Among the natural extracts tested, CEO exhibited superior antimicrobial efficacy, whereas miswak was less effective. The combination of CEO with miswak did not enhance antimicrobial efficacy, suggesting antagonistic interactions between their bioactive compounds.

Celiac disease is a chronic, immune-mediated enteropathy precipitated by gluten exposure in genetically predisposed individuals, with a global prevalence of approximately 1%. Though diagnostic workflows incorporate serologic techniques with both histologic and genetic evaluation, each approach carries key pitfalls that contribute to diagnostic inaccuracy. Serology testing is limited by selective immunoglobulin A deficiency and low-titer antibodies, in addition to interlaboratory variability of calibration standards and specimen concentrations. While duodenal biopsy is considered the gold standard for celiac diagnosis, patchy villous atrophy (e.g., ultrashort celiac disease) mimics other enteropathies, and the inherent subjectivity of histologic interpretation can compromise accuracy. Furthermore, celiac predisposition is highly correlated with two human leukocyte antigen (HLA) alleles, HLA-DQ2 and HLA-DQ8. However, nearly 30–40% of the general population expresses one of these alleles, thus introducing the risk of overdiagnosis and limiting the practical implications of genetic testing. There exist special celiac presentations, such as seronegative or potential celiac disease, overlap syndromes, and enteropathy-associated T-cell lymphoma, that introduce additional challenges to diagnostic success. The serologic-histologic discordance and nonspecific symptoms associated with these cases may require divergence from the traditional workflow, as well as supplemental investigations, such as a gluten challenge or breath testing, to confirm a celiac diagnosis. These challenges in celiac diagnosis have driven research into novel biomarkers and molecular assays that can not only enable earlier, more accurate detection but also provide longitudinal disease monitoring. Such markers include intestinal fatty acid-binding proteins, specific microRNA expression, and microbiome signatures that are strongly linked to celiac disease, which may one day serve as adjunctive screening tools to optimize diagnostic yield. This narrative review identifies the key pitfalls in adult celiac disease diagnosis — from pre-analytic serology issues to patchy histology and overinterpretation of HLA — and proposes a guideline-aligned, stepwise algorithm (with emerging biomarkers) to enhance accuracy and reduce missed or delayed cases. Ultimately, continued refinement of a comprehensive, multimodal diagnostic strategy that can integrate with emerging molecular tools is necessary for overcoming the current limitations of individual approaches to celiac diagnosis.

Preclinical studies of the serotonin 2A (5-HT2A) antagonist deramciclane suggested an anxiolytic profile, which has not been unequivocally established in the clinic. The same receptor profile also indicated that the compound may exhibit antidepressant potential. However, evidence for these effects remains inconclusive. The present study examined the effect of the drug in two preclinical tests with predictive validity for antidepressant activity.

The antidepressant-like activity of deramciclane was assessed in male Sprague-Dawley rats by measuring immobility time in the forced swim test (doses: 1, 5 mg/kg) and ambulation scores in the bilateral olfactory bulbectomized (doses: 5, 10 mg/kg) rat model. In both tests, the clinically effective antidepressant imipramine served as the control condition.

In the forced swim test, there was a statistically significant effect of treatment on immobility time (F2,34 = 5.77; p < 0.01; analysis of variance), which was attributable to the effect of the 5 mg/kg dose (p < 0.01; Bonferroni post-hoc test). Deramciclane at 1 mg/kg was not significantly different from vehicle-treated animals. By contrast, neither dose of deramciclane (5 mg/kg or 10 mg/kg) reversed the hyperactivity of olfactory bulbectomized rats, whereas imipramine was active in both tests.

Deramciclane demonstrates contradictory evidence for antidepressant-like activity in two validated pharmacological tools that identify such potential. The agent is clearly active in the forced swim test but not in the bulbectomized rat model. Further evaluation of the antidepressant-like potential of deramciclane in pharmacological models with predictive validity is warranted, and a more detailed examination of the dose-response relationship may be informative.

5-methylcytosine RNA modification is a key regulator of neuroblastoma oncogenesis and differentiation. NSUN6, a 5-methylcytosine-specific messenger RNA methyltransferase, modulates messenger RNA methyltransferase activity and translation termination. Yet, its potential link to neuroblastoma risk has not been previously reported. The present study aimed to reveal the relationship between NSUN6 gene polymorphisms and the risk of neuroblastoma in children from Jiangsu province.

In this case-control study, we investigated three NSUN6 gene polymorphisms (rs3740102 A>C, rs12780826 T>A, and rs61842187 G>C) in 402 neuroblastoma cases and 473 controls, all of whom were children from Nanjing City, Jiangsu Province, China. DNA from these subjects was assessed using the TaqMan method. Multivariate logistic regression analysis was employed to examine the association between NSUN6 gene polymorphisms and neuroblastoma risk. Additionally, the Genotype-Tissue Expression database was utilized to elucidate the impact of these polymorphisms on NSUN6 and nearby gene expression. Kaplan-Meier analysis and the non-parametric test were conducted on the R2 platform to assess the relationship between gene expression, prognosis, and neuroblastoma risk.

Carriage of two to three protective genotypes (rs3740102 AA/AC, rs12780826 TT/TA, rs61842187 CC) was significantly associated with a lower risk of neuroblastoma (adjusted odds ratio = 0.41, 95% confidence interval = 0.23–0.73, P = 0.002), with consistent results across all subgroups. Expression quantitative trait locus analysis showed these single-nucleotide polymorphisms may upregulate the expression of NSUN6 and CACNB2. Furthermore, higher NSUN6 and CACNB2 expression was correlated with a potentially lower risk of neuroblastoma, improved overall survival (NSUN6: P = 2.54e-03; CACNB2: P = 6.35e-06) and event-free survival (NSUN6: P = 7.90e-04; CACNB2: P = 4.64e-06), as well as a lower likelihood of MYCN amplification.

NSUN6 rs3740102 AA/AC, rs12780826 TT/TA, and rs61842187 CC genotypes may be associated with a better prognosis of neuroblastoma. This association may be related to the potential upregulation of NSUN6 gene expression and a lower likelihood of MYCN amplification.