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Over the past few years, breast cancer has become the most prevalent type of cancer globally, with the primary cause of death from the disease being metastatic cancer. This has led to the development of early detection techniques, mainly using non-invasive biomarkers in a range of body fluids. Exosomes are unique extracellular vesicles (EVs) transmitting cellular signals over great distances via various cargo. They are readily apparent in physiological fluids due to release by breast cancer cells or breast cancer-tumor microenvironment (TME) cells. In light of this, numerous biological and functional facets of human tumours, such as breast cancer, are intimately associated with exosomal noncoding RNAs (ncRNAs), containing miRNAs (microRNAs), lncRNAs (long noncoding RNAs), and circRNAs (circular RNAs). Exosomal ncRNAs serve a critical role in various steps of breast cancer development, enabling the exchange of genetic information between cancer cells and other cells (e.g., immune cells), thus regulating tumour angiogenesis, growth, metastasis, immune responses and drug resistance. They interact with multiple regulatory complexes with dissimilar enzymatic actions, which, in turn, modify the chromatin sceneries, including nucleosome modifications, DNA methylation, and histone modifications. Herein, we look into the exosomes' underlying regulatory mechanisms in breast cancer. Furthermore, we inspect the existing understanding of the functions of exosomal miRNAs, lncRNAs, and circRNAs in breast cancer to authenticate their possible significance in identifying biomarkers, deciphering their role in immune escape and drug resistance, and finally, analyzing treatment practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Conventional cancer therapies can have significant adverse effects as they are not targeted to cancer cells and may damage healthy cells. Single-stranded oligonucleotides assembled in a particular architecture, known as aptamers, enable them to attach selectively to target areas. Usually, they are created by Systematic Evolution of Ligand by Exponential enrichment (SELEX), and they go through a rigorous pharmacological revision process to change their therapeutic half-life, affinity, and specificity. They could thus offer a viable substitute for antibodies in the targeted cancer treatment market. Although aptamers can be a better choice in some situations, antibodies are still appropriate for many other uses. The technique of delivering aptamers is simple and reasonable, and the time needed to manufacture them is relatively brief. Aptamers do not require animals or an immune response to be produced, in contrast to antibodies. When used as a medication, aptamers can directly suppress tumor cells. As an alternative, they can be included in systems for targeted drug delivery that administer medications specifically to tumor cells while reducing toxicity to healthy cells. The most recent and cutting-edge methods for treating gastrointestinal (GI) tract cancer with aptamers will be covered in this review, with a focus on targeted therapy as a means of conquering resistance to traditional medicines., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In recent decades, analytical techniques have increasingly focused on the precise quantification. Achieving this goal has been accomplished with conventional analytical approaches that typically require extensive pretreatment methods, significant reagent usage, and expensive instruments. The need for rapid, simple, and highly selective identification platforms has become increasingly pronounced. Molecularly imprinted polymer (MIP) has emerged as a promising avenue for developing advanced sensors that can potentially surpass the limitations of conventional detection methods. In recent years, the application of MIP-silica materials-based sensors has garnered significant attention owing to their distinctive characteristics. These types of probes hold a distinct advantage in their remarkable stability and durability, all of which provide a suitable sensing platform in severe environments. Moreover, the substrate composed of silica materials offers a vast surface area for binding, thereby facilitating the efficient detection of even minuscule concentrations of targets. As a result, sensors based on MIP-silica materials have the potential to be widely applied in various industries, including medical diagnosis, and food safety. In the present review, we have conducted an in-depth analysis of the latest research developments in the field of MIPs-silica materials based sensors, with a focus on succinctly summarizing and elucidating the most crucial findings. This is the first comprehensive review of integration MIPs with silica materials in electrochemical (EC) and optical probes for biomedical analysis and food safety., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Machine learning could be used for prognosis/diagnosis of maternal and neonates' diseases by analyzing the data sets and profiles obtained from a pregnant mother., Purpose: We aimed to develop a prediction model based on machine learning algorithms to determine important maternal characteristics and neonates' anthropometric profiles as the predictors of neonates' health status., Methods: This study was conducted among 1280 pregnant women referred to healthcare centers to receive antenatal care. We evaluated several machine learning methods, including support vector machine (SVM), Ensemble, K-Nearest Neighbor (KNN), Naïve Bayes (NB), and Decision tree classifiers, to predict newborn health state., Results: The minimum redundancy-maximum relevance (MRMR) algorithm revealed that variables, including head circumference of neonates, pregnancy intention, and drug consumption history during pregnancy, were top-scored features for classifying normal and unhealthy infants. Among the different classification methods, the SVM classifier had the best performance. The average values of accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) in the test group were 75%, 75%, 76%, 76%, and 65%, respectively, for SVM model., Conclusion: Machine learning methods can efficiently forecast the neonate's health status among pregnant women. This study proposed a new approach toward the integration of maternal data and neonate profiles to facilitate the prediction of neonates' health status., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

According to estimates, cancer will be the leading cause of death globally in 2022, accounting for 9.6 million deaths. At present, the three main therapeutic modalities utilized to treat cancer are radiation therapy, chemotherapy, and surgery. However, during treatment, tumor cells resistant to chemotherapy may arise. Drug resistance remains a major oppose since it often leads to therapeutic failure. Furthermore, the term "acquired drug resistance" describes the situation where tumor cells already display drug resistance before undergoing chemotherapy. However, little is still known about the basic mechanisms underlying chemotherapy-induced drug resistance. The development of new technologies and bioinformatics has led to the discovery of additional genes associated with drug resistance. Long noncoding RNA plasmacytoma variant translocation 1 (PVT1) has been linked to an increased risk of cancer, according to a growing body of research. Apart from biological functions associated with cell division, development, pluripotency, and cell cycle, lncRNA PVT1 contributes significantly to the regulation of various aspects of genome function, such as transcription, splicing, and epigenetics. The article will address the mechanism by which lncRNA PVT1 influences drug resistance in cancer cells., Competing Interests: Declaration of Competing Interest I declare that there is no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier GmbH.)

During the radiotherapeutic treatment of pediatric oncology patients, they would be at a latent risk of developing ionizing radiation-induced ototoxicity when the cochlea or auditory nerve is located within the radiation field. Sensorineural hearing loss (SNHL) is an irreversible late complication of radiotherapy, and its incidence depends on various factors such as the patient's hearing sensitivity, total radiation dose to the cochlea, radiotherapy fractionation regimen, age and chemoradiation. Importantly, this complication exhibits serious challenges to adult survivors of childhood cancer, as it has been linked to impairments in academic achievement, psychosocial development, independent living skills, and employment in the survivor population. Therefore, early detection and proper management can alleviate academic, speech, language, social, and psychological morbidity arising from hearing deficits. In the present review, we have addressed issues such as underlying mechanisms of radiation-induced SNHL, audiometric findings of pediatric cancer patients treated with radiotherapy, and management and protection measures against radiation-induced ototoxicity., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Since cancer is one of the world's top causes of death, early diagnosis is critical to improving patient outcomes. Artificial intelligence (AI) has become a viable technique for cancer diagnosis by using machine learning algorithms to examine large volumes of data for accurate and efficient diagnosis. AI has the potential to alter the way cancer is detected fundamentally. Still, it has several disadvantages, such as requiring a large amount of data, technological limitations, and ethical concerns. This overview looks at the possibilities and restrictions of AI in cancer detection, as well as current applications and possible future developments. We can better understand how to use AI to improve patient outcomes and reduce cancer mortality rates by looking at its potential for cancer detection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier GmbH.)

Eagle's syndrome, or ES, is associated with the elongation of the styloid process and partial or complete mineralization of the stylohyoid ligament. Clinically, the symptoms of ES are characterized by sore throat, neck pain radiating to the ear, dysphagia, and a foreign body sensation when swallowing, resulting from disruption of the neck or pharyngeal region. This report describes 3 male patients (40, 60, and 43 years old) with neck discomfort. These patients were inadvertently diagnosed with ES using multidetector computer tomography and 3-dimensional volumetric computed tomography (MDCT-3D CT). The length of the left styloid process in the first case was 42 mm. In the second case, the size of the right styloid process was 53 mm. In the last case, the length of the right styloid process was 41 mm, while the left side was 43 mm. This syndrome should always be suspected when pain is unilateral and unresponsive to analgesics, mainly in women. Diagnosis requires appropriate examination through radiological examination, special techniques, and experiences. We aim to present and re-emphasize the consideration of a differential diagnosis of ES for diagnosticians., (© 2023 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)

One of the primary indicators of plaque vulnerability is the lipid composition of atherosclerotic plaques. Therefore, the medical industry requires a method to evaluate necrotic nuclei in atherosclerosis imaging with sensitivity. In this regard, photoacoustic imaging is a plaque detection method that provides chemical information on lipids and cholesterol thickness in the arterial walls of the patient. This aspect aims to increase the low-frequency axial resolution by developing a new photoacoustic-based system. A photoacoustic system has been developed to detect the cholesterol thickness of the blood vessels to observe the progression of plaque in the heart's blood vessels. The application of the coherent photoacoustic discontinuous correlation tomography technique, which is based on a novel signal processing, significantly increased the cholesterol oleate's sensitivity to plaque necrosis. By enhancing the quality of thickness detection, the system for measuring the thickness of cholesterol in blood vessels has been reduced to approximately 23 microns. The results show that the phase spectrum peaked at 100 Hz at 58.66 degrees, and at 400 Hz, the phase spectrum was 46.37 degrees. The minimum amplitude is 1.95 at 100 Hz and 17.67 at 400 Hz. In conclusion, it can be stated that photoacoustic imaging as a method based on new technologies is of great importance in medical research, which is based on the use of nonionizing radiation to perform diagnostic processes and measure different types of body tissues., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Alaa Kassar Salih et al.)

Necrotizing pneumonia is a rare, serious complication of pneumonia in children. We present a case of a 20-month-old girl presenting with respiratory distress which later be diagnosed with necrotizing pneumonia. In this paper, we highlight the role of imaging such as chest X-ray, chest CT, and lung ultrasonography for diagnosis and the importance of intravenous antibiotic therapy for better outcome., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2020 Herlina Uinarni et al.)

Duplication of ureter is one of the most common anomalies of the urinary tract. Early detection has dramatically increased due to advance in technology of imaging to detect the anomalies during antenatal period; however, numbers of undiagnosed adult still exist. It may remain asymptomatic, but may cause repeated urinary tract infections or calculi. This case report presents a case of a 7-year-old female who had duplex collecting systems. This patient has repeating symptoms throughout the years, referred to several medical specialties. Then ultrasonography and computed tomography showed that she had complete duplex collecting system on her left kidney. She was then undergone left partial nephrectomy surgery and removal of dilated left ureter. Congenital anomaly of the urogenital system should be considered in patients with chronic infection. Multimodal imaging technique such as ultrasonography, computed tomography, or magnetic resonance imaging should be done to confirm the diagnosis especially before surgical management., (© 2020 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)