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.

Radiotherapy remains one of the essential treatment modalities for brain gliomas, brain metastases, pediatric neuroblastomas, and primary central nervous system lymphomas. With continuous advancements in modern radiotherapy techniques, patients have achieved significantly improved local control rates and prolonged survival. However, the long-term complications associated with radiotherapy have become increasingly evident. Radiation-induced brain injury (RIBI) is a clinical syndrome characterized primarily by neurological dysfunction following focal or whole-brain radiotherapy. It negatively impacts patients’ quality of life and imposes a considerable burden on families and society. With the rapid development of medical imaging and artificial intelligence technologies, multimodal imaging techniques, including structural magnetic resonance imaging, diffusion-weighted imaging, functional magnetic resonance imaging, perfusion imaging, positron emission tomography-computed tomography metabolic imaging, and radiomics, have demonstrated significant potential for early detection, dynamic monitoring, and quantitative evaluation of RIBI. Meanwhile, treatment strategies for RIBI are shifting from traditional symptomatic and supportive care toward multidimensional interventions aimed at protecting the blood-brain barrier, modulating neuroinflammation, and implementing precise targeted therapies. Additionally, emerging studies have explored neuromodulation techniques and gut-brain axis regulation, offering new directions for the prevention and treatment of RIBI. Although conventional imaging methods remain valuable for diagnosing RIBI, they exhibit notable limitations in the early stages of the disease and in differentiating RIBI from tumor recurrence. This review focuses on the current state of technological development, key findings, and existing limitations, with the aim of providing a theoretical foundation and technical support for the early identification and precise intervention of RIBI.

The COVID-19 pandemic profoundly impacted university students, presenting multifaceted challenges including the abrupt transition to virtual learning and significant disruptions to emotional well-being and dietary habits. This study aimed to investigate the dietary and nutritional characteristics associated with academic stress among Mexican university students during the COVID-19 lockdown.

This cross-sectional study was conducted with a sample of 114 university students in Mexico. Participants completed a self-reported questionnaire assessing dietary patterns, nutritional intake, and academic stress levels. Informed consent was obtained from all participants prior to data collection.

Among study participants (n = 114), 57.8% experienced moderate academic stress, while 25.7% reported high academic stress during the COVID-19 lockdown. Notably, 13.5% of students demonstrated food cravings that were significantly associated with increased consumption of red and fatty meats (P = 0.030) and sausages (P = 0.017). A negative virtual education experience was associated with food cravings towards high-calorie and saturated-fat foods (P = 0.014), as well as elevated academic stress levels (P = 0.009). Furthermore, high academic stress levels were positively associated with food cravings (P = 0.020), particularly towards carbohydrate-rich foods (P = 0.037).

The COVID-19 lockdown substantially disrupted the dietary habits and nutritional status of university students, with academic stress serving as a significant mediating factor.

Micro- and nanoplastics (MNPs) are plastic particles smaller than 5 mm and 1 µm, respectively, and are emerging environmental pollutants with growing implications for human health. These particles stem from either ‘primary sources’, such as intentionally manufactured microbeads and industrial abrasives, or ‘secondary sources’, where larger plastic items break down into smaller fragments over time. Human exposure primarily occurs through ingestion and inhalation, with contaminated seafood and plastic-laden food packaging representing key routes of entry. Once ingested, MNPs can cross the intestinal barrier, accumulate in gastrointestinal (GI) tissues, and trigger biological responses. Mechanistic studies reveal that MNPs induce oxidative stress, DNA damage, chronic inflammation, and endocrine disruption, all of which are hallmarks of carcinogenic pathways. They also alter gut microbiota, potentially promoting dysbiosis and immune dysregulation. The GI tract is particularly vulnerable to these effects due to direct luminal mucosal contact and high epithelial turnover. Epidemiological data remain limited, but early evidence supports a plausible link between MNPs exposure and GI malignancies. Such findings are particularly concerning given the increasing global incidence and early age presentation of colorectal and esophageal cancers. Given that MNPs may represent a modifiable environmental risk factor in GI cancer prevention, public health strategies must prioritize reducing plastic exposure, promoting antioxidant-rich diets, and improving environmental monitoring. This review explores the potential carcinogenic effects of microplastics while also examining their emerging roles in cancer therapeutics. It highlights critical avenues for future investigation and underscores the importance of cross-disciplinary efforts to tackle this growing global health concern.

Prognostic scores are valuable tools for predicting survival in patients with chronic liver disease. Recently, the albumin-bilirubin (ALBI) score has emerged as a potential prognostic indicator in liver-related conditions. This study aimed to compare the prognostic efficacy of the ALBI score with the Model for End-stage Liver Disease (MELD), MELD-Na+, and Child-Turcotte-Pugh (CTP) scores in predicting survival among patients with alcohol-associated liver disease (ALD).

This study included consecutive ALD patients admitted to the Medicine and Gastroenterology wards of MKCG Medical College and Hospital, Berhampur, Odisha, India, between November 2019 and November 2022. Upon hospitalization, baseline characteristics, clinical and laboratory parameters, ALBI, MELD, MELD-Na+, and CTP scores were recorded. The accuracy of these scores in predicting survival up to three years was compared.

A total of 490 ALD patients were included. Higher ALBI scores were observed in patients who died during hospitalization (p < 0.001), at 28 days (p < 0.001), 90 days (p < 0.001), six months (p < 0.001), one year (p < 0.001), two years (p < 0.001), and three years (p < 0.001), compared to those who survived. However, the area under the receiver operating characteristic (AUROC) curves showed that the ALBI score was inferior to MELD, MELD-Na+, and CTP scores in predicting survival at admission [AUROC: ALBI (0.719), MELD-Na+ (0.823), MELD (0.817), CTP (0.770)] and at three years [AUROC: ALBI (0.755), MELD-Na+ (0.787), MELD (0.758), CTP (0.784)]. Furthermore, Cox regression analysis revealed that components used in the MELD, MELD-Na+, and CTP scores—such as serum creatinine, serum sodium, and hepatic encephalopathy—were independent predictors of mortality, whereas the components of the ALBI score (serum albumin and serum bilirubin) were not.

All hospitalized ALD patients had a grade 3 ALBI score, with significantly higher scores observed among non-survivors compared to survivors. However, MELD, MELD-Na+, and CTP scores were superior to the ALBI score in predicting survival both during hospitalization and over a three-year follow-up period.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has become one of the leading causes of chronic liver diseases in China, imposing a substantial and growing burden on the healthcare system. Considering the large number of individuals affected by MAFLD and the gap in disease management capacity at the primary care level, standardized guidance tailored to primary healthcare settings is urgently needed. In response, the Chronic Disease Management Branch of the China Medical Biotechnology Association convened a multidisciplinary working group incorporating hepatologists, general practitioners, and other specialists to initiate the first China national Guidelines for Diagnosis and Management of Metabolic Dysfunction-associated Fatty Liver Disease in Primary Care (2025). These guidelines provide recommendations and suggestions covering screening, risk assessment, diagnosis, treatment, referral pathways, and follow-up tailored for primary care institutions, thereby improving the long-term outcomes for the population with MAFLD and comprehensively strengthening the role of primary healthcare in chronic liver disease management.

Parenteral nutrition (PN)-associated cholestasis (PNAC) is frequently diagnosed in premature infants; however, not all PN-exposed infants develop PNAC. We propose that, in premature infants receiving PN and varying amounts of enteral feeds, differences in the gut microbiome and fecal bile acid content are associated with PNAC development. This study aimed to examine the fecal microbiome and bile acid content of premature infants on PN to determine if there is a relationship with the development of PNAC.

Twenty-two preterm infants had serial bilirubin measurements and fecal samples collected during their neonatal intensive care unit admission. Fecal samples underwent 16S rRNA gene sequencing and bile acid analysis. Binomial regression, adjusting for postmenstrual age with feed amount as a moderator, was used to assess the impact of the fecal microbiome and bile acids on PNAC development.

Cholestatic patients (n = 11) had greater PN and antibiotic exposure (p = 0.020; p = 0.010) and longer neonatal intensive care unit stays (p = 0.0038) than non-cholestatic patients. Microbiome richness was higher in non-cholestatic infants (p < 2E-16), with no difference in β diversity (p = 1.0). Cholestatic infants had a significantly higher abundance of Proteobacteria and Fusobacteriota and a lower abundance of Bacteroidota (p < 2E-16). Akkermansia was abundant in all infants on low feeds; as feed volume increased, Akkermansia abundance significantly increased in non-cholestatic infants (p < 2E-16). Bile acid analysis demonstrated significantly lower deoxycholic acid concentrations in cholestatic infants (p < 2E-16). Metagenomic analysis revealed an increase in Proteobacteria requiring augmented stress responses in non-cholestatic infants.

This is the first study to directly explore the relationship between PNAC susceptibility, the microbiome, and fecal bile acids in preterm infants. The microbiome and bile acid patterns identified here may inform the development of targeted therapeutics for this vulnerable population.

Chronic diabetes mellitus is marked by hyperglycemia and metabolic dysfunction, increasing the risk of complications such as nephropathy. This study aimed to evaluate key biochemical parameters among participants with diabetic nephropathy (DNp), diabetes control (DC), nephropathy control (NC), and healthy control groups.

A prospective case-control study was conducted with 200 participants categorized into four groups: DNp, NC, DC, and healthy controls. Biochemical parameters, including glucose, glycated hemoglobin, waste metabolites, proteins, enzymes, electrolytes, and lipids, were analyzed using an Advia 1800 chemical system analyzer (Siemens, Germany) with standard kits.

Among the four investigated groups, the DNp group exhibited augmented fasting glucose (178.75 ± 61 mg/dL), glycated hemoglobin (8.13 ± 1.7%), creatinine (5.67 ± 1.8 mg/dL), and blood urea nitrogen (72.02 ± 22.8 mg/dL), indicating poor glycemic control and impaired kidney function. In contrast, the DC group showed elevated random glucose levels (280 ± 3.1 mg/dL). Elevated inflammatory markers (C-reactive protein, 6.35 ± 6.3 mg/L; lactate dehydrogenase, 1,216.43 ± 634 U/L) were observed in the NC group. Compared to the other groups, the DC group demonstrated augmented lipid profiles, including elevated triglycerides (230.67 ± 59 mg/dL), very low-density lipoprotein (48.5 ± 16.5 mg/dL), low-density lipoprotein (107.41 ± 16 mg/dL), and cholesterol (169 ± 19 mg/dL). Statistical analysis was performed using one-way analysis of variance followed by a t-test to investigate differences among groups at P < 0.05.

Altered biochemical variations were noted among groups. The DNp group showed renal dysfunction and poor glycemic control, the DC group had dyslipidemia and hyperglycemia, and the NC group showed elevated inflammatory markers. Early testing is indispensable for the timely diagnosis and management of diabetic complications.

Endometrial polyp (EMP) is one of the most common diagnoses in the evaluation of women with abnormal uterine bleeding. Understanding the malignancy risk associated with EMPs and related risk factors is essential for guiding both pathology practice and clinical management. This study aimed to explore risk factors for malignancy in EMPs.

The pathology database was searched for women diagnosed with EMP between 2021 and 2022. Patient age, polyp size, background endometrium, recurrence, and (if applicable) cancer types were recorded. Immunohistochemistry (IHC) for p53 and p16 was performed on selected cases. Risk factors for malignancy were analyzed using Chi-square and analysis of variance tests.

Among the 740 EMP cases analyzed, 94% were benign, 2% were premalignant, and 4% were malignant. The median patient age was 54 years (range: 19–92). Minimal serous carcinoma (n = 14, 2%) was the most prevalent cancer. Among the 52 cases with p53 IHC, 38 were diagnosed as benign, supported by a wild-type p53 pattern, while 14 were diagnosed as serous carcinoma, supported by a mutant p53 pattern. Malignant polyps were found to be significantly associated with advanced age and malignant background endometrium (p < 0.001). Large size and recurrence were not identified as significant risk factors.

EMPs carry a low risk of malignancy, which is not significantly influenced by the polyp’s size or its recurrence. Our findings highlight the significantly elevated risk of malignancy in elderly patients and the importance of p53 IHC in improving diagnostic accuracy.