Bacteria use quorum sensing (QS) and biofilm formation as essential adaptation and persistence strategies in harsh settings, which contribute to the development of antibiotic resistance and persistent infections. Through signaling molecules, QS allows bacteria to coordinate group behaviors, and biofilms improve microbial resistance and offer structural protection. A potentially effective physical intervention for interfering with QS signaling and biofilm integrity is ultrasound. The modulation of QS pathways by ultrasound, including signaling molecule degradation and interference with QS receptor binding, is examined in this article. The physical disruption of biofilm structures by ultrasonic via cavitation and shear stress is also investigated. Important discoveries demonstrate how well ultrasound attenuates QS and encourages biofilm disintegration, which in turn increases bacterial sensitivity to antimicrobial drugs. The possible uses of ultrasound in both medical and environmental contexts are discussed, emphasizing its role as a non-invasive, targeted strategy for controlling biofilm-related infections and microbial persistence. Despite its promise, the purpose of this review is to provide a brief background on biofilms, and implants, and advance approach for treatment. Further research is needed to refine ultrasound parameters and optimize its integration with other therapeutic approaches for broader clinical and industrial use.

Periodic Medical Examinations (PMEs) is a preventive healthcare strategy for early detection and management of medical conditions like hypertension and diabetes in order to mitigate potentially fatal outcomes. This is particularly relevant for individuals over 40, where annual PMEs are recommended for optimal health and productivity. A study was conducted in Apir community, Northcentral Nigeria, to investigate factors influencing PME uptake among adult residents. This community-based cross-sectional study, involving 420 participants, utilized questionnaires to assess knowledge, uptake, and associated factors. The study revealed a high level of PME knowledge (70%) and awareness (82.4%), primarily sourced from hospitals. However, awareness of existing PME policies was limited (57.6%), and actual uptake was low, at only 29.5%. Statistically significant associations were found between PME uptake and education level, occupation, and income (p<0.05). Knowledge regarding PME frequency and timing, coupled with awareness of hospital policies, also correlated with uptake (p<0.05). Furthermore, lifestyle factors, including cigarette smoking and sufficient sleep, exhibited significant associations with PME utilization (p<0.05). The conclusion highlights a disparity between PME knowledge and uptake, depicting trends observed in other studies. This underscores the need for targeted interventions. Government and stakeholders should leverage on these findings to develop policies promoting health education, lifestyle modifications, and financial empowerment, ultimately aiming to improve PME uptake and public health outcomes.

Background: This study aimed to assess the attitude of Jordanian healthcare workers (HCWs) toward modern assisted reproductive technologies (ARTs), including gamete donation and sex selection. Design and Methods: The HCWs from three municipalities in Jordan were randomly selected to participate in a self-administered, cross-sectional survey. The study settings included hospitals and clinics in the public and private health sectors. Logistic regression analysis was used to examine the association of demographic characteristics and fertility experience with the attitude toward modern ARTs. Results: A total of 382 HCWs were included in the study. Most participants did not support the donation of fertilized or unfertilized eggs for any purpose (86.4% and 75.4%, respectively). Overall, only 39.3% and 42.9% of the respondents supported the use of in vitro fertilization and intrauterine insemination for sex selection, respectively. Religious considerations were the main reason (71.1%) for the negative attitude toward ARTs. However, more supportive attitude was observed among male participants and medical doctors. Logistic regression analysis showed that none of the variables were significantly associated with the attitude toward sex selection and gamete donation. Conclusion: The use of ARTs was generally more acceptable for sex selection than for gamete donation. The attitude of HCWs was primarily driven by religious beliefs, which typically shape the cultural values and the acceptance of such technologies. Additionally, sex and profession seem to play a significant role in shaping the attitude of HCWs toward ARTs.

Psoriasis is a chronic inflammatory skin disease with a complex and multifactorial pathophysiology. Among the triggering factors, certain medications have been implicated as causing the appearance of new cases or exacerbations in previously diagnosed patients. This article reviews the latest evidence on medications associated with induced psoriasis, paradoxical eruptions, the pathophysiological mechanisms involved, and clinical implications. Strategies for its management and prevention are also discussed, highlighting the importance of pharmacovigilance in these patients.

Machine learning has emerged as a transformative tool in healthcare, enabling predictive analytics for disease progression, patient management, and clinical decision-making. This study integrates three critical areas: mortality trends in the USA, heart failure survival prediction using machine learning (ML) models, and hospital readmission forecasting with artificial intelligence (AI)-driven methodologies. Using datasets from national health statistics, clinical trial data, and electronic health records, this research applies Logistic Regression, Random Forest, Support Vector Machines (SVM), Neural Networks, and Gradient Boosting models to enhance prediction accuracy. Results indicate that SVM achieves the highest predictive accuracy for heart failure survival (88.41%), while Gradient Boosting performs best for readmission prediction. Findings highlight ML’s potential in improving risk stratification, resource allocation, and targeted interventions, contributing to a growing body of AI applications in healthcare analytics. This study provides a foundation for future research on personalized medicine and predictive healthcare models, with broader implications for disease prevention and healthcare efficiency.

Background: Magnetic resonance imaging (MRI) is the most sensitive technique for the detection of breast cancer in contemporary medical practice. Contrast-enhanced mammography (CEM), a novel technology, provides a contrast-enhanced imaging alternative to breast MRI. Objectives: to assess the diagnostic efficacy of CEM in the characterization of suspicious breast lesions, with histopathological results serving as the gold standard. Compare CEM with dynamic contrast enhanced MRI (DCE-MRI). Patients and Methods: 30 individuals with suspicious lesions identified using conventional mammography or ultrasonography underwent CEM and DCE-MRI examinations after receiving ethical approval. Proficient radiologists evaluated all discernible lesions using the Breast Imaging Reporting and Data System (BI-RADS) classifications (categories 1–6). Histopathological data were compared to the morphological descriptions of each lesion that were received from each modality. Results: 30 lesions were identified by the combination of breast MRI and CEM in the 30 patients who were enrolled in CEM/MRI investigations. Histopathology verified that 15 of the 30 lesions were malignant and 15 were benign. Twelve of the fifteen malignant lesions were invasive cancers, while three were in situ cancers. Both breast MRI and CEM demonstrated a sensitivity of 93.33%. The specificity of breast MRI was 93.33%, while CEM had a specificity of 80.00%. The breast MRI achieved an accuracy of 93.33%, while the CEM achieved an accuracy of 86.67%. Conclusions: Contrast-enhanced mammography (CEM) has the potential to replace dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a problem-solving instrument for the characterization of indeterminate breast lesions, particularly in situations where MRI is contraindicated or not promptly accessible. CEM provides a viable alternative for evaluating ambiguous lesions, as it utilizes similar principles of contrast enhancement and tumor vascularity. However, it has the additional benefit of being more broadly available, less expensive, and better tolerated by specific patient populations.

Hyperbilirubinemia refers to an elevated level of bilirubin in the blood. Bilirubin is a yellow pigment produced during the normal breakdown of red blood cells. It is processed by the liver and excreted in bile. When bilirubin levels rise above normal, it can cause jaundice, a condition characterized by yellowing of the skin, eyes, and mucous membranes. Hyperbilirubinemia is common in newborns due to immature liver function and is usually transient. However, untreated severe cases can lead to complications like kernicterus (brain damage).there are three types of Hyperbilirubinemia: Physological jaundice due to hemolysis of blood cell, pathological jaundice due to pathological disorders such as rubella, and bacterial septicemia, Breast Milk Jaundice resulting from a combination of genetic and environmental factors such as the components of breast milk , Hemolytic Jaundice due to many reasons : Rhesus hemolytic disease, Blood group incompatibility, Glucose-6 phosphate dehydrogenase deficiency and minor blood group incompatibility.