Publications by authors named "Ali Behmanesh"

Article Synopsis
  • The study focuses on improving early detection and treatment of osteosarcoma (OS) by examining circulating miRNAs as a non-invasive diagnostic tool.
  • Utilizing RNAseq and PCR Array data, researchers identified 43 significantly expressed miRNAs and developed a diagnostic model based on four specific miRNAs, showing high accuracy in distinguishing OS patients from healthy individuals.
  • The research reveals that the down-regulation of these miRNAs is linked to poor prognosis and lower survival rates, indicating their potential role as tumor suppressors and establishing connections to key cancer-related signaling pathways, paving the way for future therapeutic strategies.
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Article Synopsis
  • Osteosarcoma is a highly invasive and metastatic bone cancer with poor prognosis, prompting research into early diagnostic biomarkers using miRNA expression profiles.
  • The study employed RNA sequencing and microarray data to identify key miRNAs associated with metastatic osteosarcoma, leading to the development of diagnostic models powered by machine learning algorithms.
  • The findings highlight miR-34c-3p and miR-154-3p as potential biomarkers for early diagnosis, demonstrating high diagnostic accuracy and revealing significant correlations with tumor grade and metastasis detection.
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This systematic review and meta-analysis focused on the effectiveness of biomaterials integrated with specific microRNAs (miRNAs) for bone fracture repair treatment. We conducted a comprehensive search of the PubMed, Web of Science, and Scopus databases, identifying 42 relevant papers up to March 2022. Hydrogel-based scaffolds were the most commonly used, incorporating miRNAs like miR-26a, miR-21, and miR-222, with miR-26a being the most prevalent.

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  • Telemedicine emerged as a critical tool for delivering cancer healthcare during the COVID-19 pandemic, facilitating remote services for patients.
  • A systematic review analyzed 1331 articles mainly from the U.S., identifying that breast cancer received the most telemedicine support, with teleconsultation being the predominant application.
  • While telemedicine is popular for its cost-effective, high-quality healthcare, it currently lacks comprehensive service offerings for all cancer patients globally during the pandemic.
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Objectives: There are several challenges in providing healthcare services for lung cancer patients. Using teleoncology is an effective solution to meet such challenges. Given this, we in this study aimed to identify the features of teleoncology in lung cancer.

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Background: The aim of this study was to perform a bibliometric analysis to assess the number of articles published by Iranian researchers in the field of hand and microsurgery over the last four decades.

Materials And Methods: An online search was conducted using 685 keywords in the abstract/title sections of articles, including carpal tunnel syndrome, wrist fractures, nerve injury and repair, skin flap and graft in the hand, congenital disorders in the hand and forearm, tumor in the hand and wrist, and infection in the hand and wrist. From February 1976 to May 2021, EndNote software version 8.

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The coronavirus disease 2019 (COVID-19) pandemic has negatively affected the medical services, particularly cancer diagnosis and treatment, for vulnerable cancer patients. Although lung cancer has a high mortality rate, monitoring and following up of these patients can help to improve disease management during the pandemic. Telemedicine has proven to be an effective method of providing health care to these patients.

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Article Synopsis
  • * The study analyzed 303 clinical records and utilized 26 features to compare the performance of various ML algorithms, including SVM, Random Forest, and KNN, for their effectiveness in identifying CAD.
  • * Results showed that SVM and Random Forest were the most effective algorithms, suggesting that ML can provide valuable support to doctors and enhance clinical decision-making in diagnosing CAD.
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MicroRNA (miRNA) expression dysregulations in pancreatic ductal adenocarcinoma (PDAC) have been studied widely for their diagnostic and prognostic utility. By the use of bioinformatics-based methods, in our previous study, we identified some potential miRNA panels for diagnosis of pancreatic cancer patients from noncancerous controls (the screening stage). In this report, we used 142 plasma samples from people with and without pancreatic cancer (PC) to conduct RT-qPCR differential expression analysis to assess the strength of the first previously proposed diagnostic panel (consisting of miR-125a-3p, miR-4530, and miR-92a-2-5p).

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Virtual Reality (VR) as an emerging and developing technology has received much attention in healthcare and trained different medical groups. Implementing specialized training in cardiac surgery is one of the riskiest and most sensitive issues related to clinical training. Studies have been conducted to train cardiac residents using this technology.

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Helicobacter pylori (H. pylori) is a major human pathogenic bacterium that survives in the gastric mucosa. The aim of this study is to evaluate the expression of the target gene network of miR-155-5p in H.

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The most common technique of orthopedic surgical procedure for the correction of deformities is bone lengthening by "distraction osteogenesis," which requires periodic and ongoing bone assessment following surgery. Bone impedance is a noninvasive, quantitative method of assessing bone fracture healing. The purpose of this study was to monitor bone healing and determine when fixation devices should be removed.

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Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of surgery and consequently leads to a high mortality rate. Pivotal improvements in circulating microRNA expression levels in PC patients make it possible to diagnose and treat patients at earlier stages. A list of circulating miRNAs was identified in this study using bioinformatics methods in association with pancreatic cancer through analyzing four GEO microarray datasets.

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The impact of smoking on male fertility has been extensively acknowledged. Many studies have shown that smoking reduces sperm production, motility and fertilizing capacity by increasing seminal oxidative stress and DNA damage. In this study, expression profiles of miRNAs and their predicted target genes, showing dysregulation in smokers and associated with male infertility, were obtained, using Gene Expression Omnibus (GEO) datasets.

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Introduction: The use of telemedicine in orthopaedics can provide high-quality orthopaedic services to patients in remote areas. Tele-orthopaedics is widely acknowledged for decreasing travel, time and cost, increasing accessibility and quality of care. In the absence of a comprehensive review on tele-orthopaedics applications and services, here, we systematically identify and classify the tele-orthopaedic applications and services, and provide an overview of the trends in the field.

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Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies and a major health problem worldwide. There were no major advances in conventional treatments in inhibiting tumor progression and increasing patient survival time. In order to suppress mechanisms responsible for tumor cell development such as those with oncogenic roles, more advanced therapeutic strategies should be sought.

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Context: The current studies on IoT in healthcare have reviewed the uses of this technology in a combination of healthcare domains, including nursing, rehabilitation sciences, ambient assisted living (AAL), medicine, etc. However, no review study has scrutinized IoT advances exclusively in medicine irrespective of other healthcare domains.

Objectives: The purpose of the current study was to identify and map the current IoT developments in medicine through providing graphical/tabular classifications on the current experimental and practical IoT information in medicine, the involved medical sub-fields, the locations of IoT use in medicine, and the bibliometric information about IoT research articles.

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Introduction: Sleep scoring is an important step in the treatment of sleep disorders. Manual annotation of sleep stages is time-consuming and experience-relevant and, therefore, needs to be done using machine learning techniques.

Methods: Sleep-EDF polysomnography was used in this study as a dataset.

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