Environmental Drivers of Antimicrobial Resistance in Low and Middle-Income Countries: The Impacts of a Changing World

This letter highlights the impact of environmental drivers on antimicrobial resistance (AMR) in low and middle-income countries (LMICs) and highlights the need for a comprehensive approach to address this global health threat. Key factors, such as agricultural practices, wastewater treatment, and pollution, contribute to the development and spread of resistant pathogens. Utilizing the One Health approach, the paper emphasizes the importance of promoting responsible antimicrobial use, strengthening public health systems, investing in innovative research, and raising public awareness. By understanding and addressing these environmental drivers, we can work toward safeguarding global health and ensuring a sustainable future.

The role of hydrogels in the management of brain tumours: a narrative review

Conventional therapeutic techniques for brain tumours have limitations and side effects, necessitating the need for alternative treatment options. MRI-monitored therapeutic hydrogel systems show potential as a non-surgical approach for brain tumour treatment. Hydrogels have unique physical and chemical properties that make them promising for brain tumour treatment, including the ability to encapsulate therapeutic agents, provide sustained and controlled drug release, and overcome the blood-brain barrier for better penetration. By combining hydrogel systems with MRI techniques, it is possible to develop therapeutic approaches that provide real-time monitoring and controlled release of therapeutic agents. Surgical resection remains important, but there is a growing need for alternative approaches that can complement or replace traditional methods. The objective of this comprehensive narrative review is to evaluate the potential of MRI-monitored therapeutic hydrogel systems in non-surgical brain tumour treatment.

Recurrent bladder leiomyoma: a case report

BACKGROUND

Bladder leiomyomas are rare benign growths in the bladder, comprising less than 0.5% of bladder tumors with only 250 cases reported globally. They are more common in women. This case involves a 70-year-old woman with recurrent leiomyoma, presenting with lower urinary tract symptoms and painless hematuria. A recurrent bladder leiomyoma is rarely reported, making its presence exceptionally rare.

CASE PRESENTATION

A 70-year-old Pakistani woman with hypertension and diabetes presented with lower urinary tract symptoms (LUTS) and painless hematuria. She had a history of similar symptoms in 2010, leading to a diagnosis of bladder leiomyoma via cystoscopy and biopsy. Imaging studies revealed a substantial 3.7 × 4 × 4.0 cm isodense mass with calcifications at the bladder base, along with bladder wall thickening and diverticula. Pathological examination during Transurethral Resection of Bladder Tumor (TURBT) confirmed the presence of bladder tissue with smooth muscle, ruling out malignancy. Immunohistochemical studies supported the diagnosis. A successful TURBT was performed, and the patient recovered well.

DISCUSSION

Recurrent bladder leiomyoma is a rarely-discussed topic in medical literature. This article primarily aims to review existing studies and present a detailed case study, shedding light on this rare phenomenon.

Exploring the current and prospective role of artificial intelligence in disease diagnosis

Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems, providing assistance in a variety of patient care and health systems. The aim of this review is to contribute valuable insights to the ongoing discourse on the transformative potential of AI in healthcare, providing a nuanced understanding of its current applications, future possibilities, and associated challenges. The authors conducted a literature search on the current role of AI in disease diagnosis and its possible future applications using PubMed, Google Scholar, and ResearchGate within 10 years. Our investigation revealed that AI, encompassing machine-learning and deep-learning techniques, has become integral to healthcare, facilitating immediate access to evidence-based guidelines, the latest medical literature, and tools for generating differential diagnoses. However, our research also acknowledges the limitations of current AI methodologies in disease diagnosis and explores uncertainties and obstacles associated with the complete integration of AI into clinical practice. This review has highlighted the critical significance of integrating AI into the medical healthcare framework and meticulously examined the evolutionary trajectory of healthcare-oriented AI from its inception, delving into the current state of development and projecting the extent of reliance on AI in the future. The authors have found that central to this study is the exploration of how the strategic integration of AI can accelerate the diagnostic process, heighten diagnostic accuracy, and enhance overall operational efficiency, concurrently relieving the burdens faced by healthcare practitioners.

Cost-Effectiveness Analysis of Sacubitril/Valsartan for Reducing the Use of Implantable Cardioverter-Defibrillator (ICD) and the Risk of Death in ICD-Eligible Heart Failure Patients With Reduced Ejection Fraction

This critical review of Kaddoura et al.'s article on sacubitril/valsartan in heart failure patients underscores the importance of considering potential adverse effects, including renal failure, hyperkalemia, angioedema, and increased reports of sudden cardiac death. It highlights the need for rigorous monitoring and precise treatment regimens, especially in diabetic heart failure patients. Additionally, the review questions the generalizability of the study's results to diverse healthcare settings and emphasizes the importance of grounded patient follow-up data for accurate long-term assessment. These considerations are vital for informed decision-making regarding sacubitril/valsartan use in heart failure management.

Commentary on "Relationship between miRNA-21, miRNA-155, and miRNA-182 expression and inflammatory factors in cerebrospinal fluid from patients with multiple sclerosis"

This letter provides insightful perspectives on multiple sclerosis (MS) biomarkers, building upon Behrouz Shademan et al.'s study on miRNA-21, miRNA-155, and miRNA-182 [1]. Beyond these miRNAs, we delve into recent advancements, highlighting promising biomarkers such as ELTD1, CHI3L1, and Fecal Lcn-2. ELTD1 exhibits potential for MS diagnosis, CHI3L1 correlates with disability aspects, and Fecal Lcn-2 serves as a sensitive indicator for gut dysbiosis. Our exploration underscores the evolving landscape of MS biomarker research, urging further investigation for integrating these new markers into diagnostic and monitoring strategies.