Bioimpacts最新文献

{"title":"The synergistic impact of sleep duration and obesity on metabolic syndrome risk: exploring the role of microRNAs.","authors":"Atefeh Ansarin, Dariush Shanehbandi, Habib Zarredar, Alireza Ostadrahimi, Neda Gilani, Khalil Ansarin","doi":"10.34172/bi.30593","DOIUrl":"https://doi.org/10.34172/bi.30593","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Given the well-established association between metabolic syndrome (MetS) and obesity, this study elucidates the influences of sleep duration and weight on MetS risk and explores the potential role of miRNAs as underlying mechanisms.</p><p><strong>Methods: </strong>According to sleep logs and biochemistry tests, this study investigated the association between MetS and its components, sleep duration, and weight in four subgroups: A: normal sleepers with normal weight (N = 145), B: normal sleepers with obesity (N = 140), C: short sleepers with normal weight (N = 130), and D: short sleepers with obesity (N = 142). Chi-square, one-way ANOVA, and Tukey's post hoc tests were used for statistical analysis. Furthermore, following total RNA isolation by TRIzol from blood samples, cDNA was synthesized using stem-loop technique. Quantitative real-time polymerase chain reaction (qRT-PCR) was then employed to evaluate the expression levels of miR-33a, miR-378a, miR-132-3p, and miR-181d. The data were analyzed using one-way ANOVA.</p><p><strong>Results: </strong>Our findings revealed the strongest association between MetS prevalence and individuals in group D (short sleepers with obesity; Cramer's V = 0.649, <i>P</i> < 0.001). This observation underscores the synergistic effect of short sleep and obesity on MetS risk. Furthermore, there was an independent association between short sleep duration and elevated triglyceride levels (<i>P</i> < 0.05). MicroRNA expression analysis revealed downregulation of miR-33a and miR-181d in B, C, and D groups compared to the normal group. Conversely, miR-132-3p expression was upregulated in the B, C, and D groups.</p><p><strong>Conclusion: </strong>Short sleep and obesity synergistically elevate MetS risk, potentially via miR-33a and miR-181d downregulation and miR-132-3p upregulation, impacting triglyceride metabolism.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30593"},"PeriodicalIF":2.2,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient hybrid filter-wrapper method based on improved Harris Hawks optimization for feature selection.","authors":"Jamshid Pirgazi, Mohammad Mehdi Pourhashem Kallehbasti, Ali Ghanbari Sorkhi, Ali Kermani","doi":"10.34172/bi.30340","DOIUrl":"https://doi.org/10.34172/bi.30340","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>High-dimensional datasets often contain an abundance of features, many of which are irrelevant to the subject of interest. This issue is compounded by the frequently low number of samples and imbalanced class samples. These factors can negatively impact the performance of classification algorithms, necessitating feature selection before classification. The primary objective of feature selection algorithms is to identify a minimal subset of features that enables accurate classification.</p><p><strong>Methods: </strong>In this paper, we propose a two-stage hybrid method for the optimal selection of relevant features. In the first stage, a filter method is employed to assign weights to the features, facilitating the removal of redundant and irrelevant features and reducing the computational cost of classification algorithms. A subset of high-weight features is retained for further processing in the second stage. In this stage, an enhanced Harris Hawks Optimization algorithm and GRASP, augmented with crossover and mutation operators from genetic algorithms, are utilized based on the weights calculated in the first stage to identify the optimal feature set.</p><p><strong>Results: </strong>Experimental results demonstrate that the proposed algorithm successfully identifies the optimal subset of features.</p><p><strong>Conclusion: </strong>The two-stage hybrid method effectively selects the optimal subset of features, improving the performance of classification algorithms on high-dimensional datasets. This approach addresses the challenges posed by the abundance of features, low number of samples, and imbalanced class samples, demonstrating its potential for application in various fields.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30340"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the function and targeting of MET protein as an oncogene kinase in pancreatic ductal adenocarcinoma: A microarray data integration.","authors":"Nahid Askari, Morteza Hadizadeh, Mohammad Sina, Sepideh Parvizpour, Seyedeh Zahra Mousavi, Mohd Shahir Shamsir","doi":"10.34172/bi.30187","DOIUrl":"10.34172/bi.30187","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with a poor prognosis. Kinase proteins are essential regulators of cellular processes and potential targets for drug development.</p><p><strong>Methods: </strong>Integration of multiple microarray datasets was screened to find differentially expressed kinases (DE-Kinases) across adjacent normal and tumor tissue samples in PDAC. The most effective kinase for drug design and docking in this study was selected by investigating biological mechanisms and survival analyses. Forty phytochemicals were extracted from the yellow sweet clover, <i>Melilotus officinalis</i> (Linn.) Pall, and were then subjected to in silico screening and molecular docking studies against a specific potent kinase.</p><p><strong>Results: </strong>MET, PAK3, and PDK4 were identified as the DE-Kinases. After examining the pathways and biological processes, up-regulated MET had the most significant survival analysis and became our primary kinase for drug design and docking in this study. Four of the extracted phytocompounds of <i>Melilotus officinalis</i> (Linn.) Pall that exhibited high binding affinities with MET and were selected for toxicity analysis. Finally, the stability and mobility of the two nontoxic compounds that passed the toxicity test (dicumarol PubChem CID: 54676038 and melilotigenin PubChem CID: 14059499) were studied by molecular dynamics simulation.</p><p><strong>Conclusion: </strong>This study's results identified two phytochemicals in yellow sweet clover that could be used to develop an anticancer drug, but experimental evaluation is necessary to confirm their efficacy.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30187"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Safety and efficacy of extracellular vesicles in individuals with cancer; A systematic review.","authors":"Hila Asham, Negin Jafari, Elham Mohamadrezapour, Hossein Bannazadeh Baghi, Hosein Eslami, Taher Entezari-Maleki","doi":"10.34172/bi.30501","DOIUrl":"https://doi.org/10.34172/bi.30501","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Extracellular vesicles (EVs) are crucial in intercellular signaling pathways. Since cancer has had a significant impact on global health as the second leading cause of death, this study aimed to systematically review the literature on the efficacy and safety of EVs in this setting.</p><p><strong>Methods: </strong>A systematic literature review was performed on MEDLINE, Embase, the Cochrane Library, and ClinicalTrials.gov from database inception until August 10th, 2023. Based on PICOS, the inclusion criteria were: individuals with cancer treated with EVs compared to control among clinical studies.</p><p><strong>Results: </strong>EVs administered to 46 individuals with cancer. Most studies revealed significant clinical benefits after treatment. Results also demonstrated that EVs are safe without major adverse events (AEs).</p><p><strong>Conclusion: </strong>The use of EVs may provide potential therapeutic benefits for treating cancer. Further, well-designed randomized clinical trials (RCTs) are needed to provide robust evidence for supporting the clinical use of EVs in this setting.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30501"},"PeriodicalIF":2.2,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144035401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic classification of <i>Giardia</i> infection from stool microscopic images using deep neural networks.","authors":"Pezhman Yarahmadi, Ehsan Ahmadpour, Parham Moradi, Nasser Samadzadehaghdam","doi":"10.34172/bi.30272","DOIUrl":"10.34172/bi.30272","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Giardiasis is a common intestinal infection caused by the <i>Giardia</i> lamblia parasite, and its rapid and accurate diagnosis is crucial for effective treatment. The automatic classification of <i>Giardia</i> infection from stool microscopic images plays a vital role in this diagnosis process. In this study, we applied deep learning-based models to automatically classify stool microscopic images into three categories, namely, normal, cyst, and trophozoite.</p><p><strong>Methods: </strong>Unlike previous studies focused on images acquired from drinking water samples, we specifically targeted stool samples. In this regard, we collected a dataset of 1610 microscopic digital images captured by a smartphone with a resolution of 2340 × 1080 pixels from stool samples under the Nikon YS100 microscope. First, we applied CLAHE (Contrast Limited Adaptive Histogram Equalization) histogram equalization a method to enhance the image quality and contrast. We employed three deep learning models, namely Xception, ResNet-50, and EfficientNet-B0, to evaluate their classification performance. Each model was trained on the dataset of microscopic images and fine-tuned using transfer learning techniques.</p><p><strong>Results: </strong>Among the three deep learning models, EfficientNet-B0 demonstrated superior performance in classifying <i>Giardia</i> lamblia parasites from stool microscopic images. The model achieved precision, accuracy, recall, specificity, and F1-score values of 0.9599, 0.9629, 0.9619, 0.9821, and 0.9607, respectively.</p><p><strong>Conclusion: </strong>The EfficientNet-B0 showed promising results in accurately identifying normal, cyst, and trophozoite forms of <i>Giardia</i> lamblia parasites. This automated classification approach can provide valuable assistance to laboratory science experts and parasitologists in the rapid and accurate diagnosis of giardiasis, ultimately improving patient care and treatment outcomes.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30272"},"PeriodicalIF":2.2,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>In-silico</i> based discovery of potential Keap1 inhibitors using the strategies of pharmacophore screening, molecular docking, and MD simulation studies.","authors":"Ekta Singh, Gurubasavaraja Swamy Purawarga Matada, Prasad Sanjay Dhiwar, Rajesh B Patil, Rohit Pal","doi":"10.34172/bi.30335","DOIUrl":"https://doi.org/10.34172/bi.30335","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>The main objective of this research is to identify potential leads for developing potent Keap1 inhibitors.</p><p><strong>Methods: </strong>In the current research article, <i>in-silico</i> methods have been employed to discover potential Keap1 inhibitors. 3D-QSAR was generated using the ChemBL database of Keap1 inhibitors with IC₅₀. The best pharmacophore was selected for the screening of three different libraries namely Asinex, MiniMaybridge, and Zinc. The molecules screened from the databases were filtered through druggability rules and molecular docking studies. The best binding molecules obtained after docking studies were subjected to physicochemical properties toxicity determination by <i>in-silico</i> methods. The best hits were studied for stability in the cavity of Keap1 by molecular dynamic simulations.</p><p><strong>Results: </strong>The virtual screening of different databases was carried out separately and three leads, were obtained. These lead molecules ASINEX 508, MiniMaybridgeHTS_01719, and ZINC 0000952883 showed the best binding in the Keap1 cavity. The molecular dynamic simulations of the binding complexes of the leads support the docking analysis. The leads (ASINEX 508, MiniMaybridgeHTS_01719, and ZINC 0000952883) were stabilized in the Keap1 binding cavity throughout 100 ns simulation, with average RMSD values of 0.100, 0.114, and 0.106 nm, respectively.</p><p><strong>Conclusion: </strong>This research proposes three lead molecules as potential Keap1 inhibitors based on high throughput screening, docking, and MD simulation studies. These hit molecules can be used for further design and development of Keap1 inhibitors. This research provides the preliminary data for discovering novel Keap1 inhibitors. It opens new avenues for medicinal chemists to explore antioxidant-stimulating molecules targeting the Keap1-Nrf2 pathway.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30335"},"PeriodicalIF":2.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008509/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting hypoxia-inducible factor 1 alpha augments synergistic effects of chemo/immunotherapy via modulating tumor microenvironment in a breast cancer mouse model.","authors":"Mohsen Rashid, Mina Ramezani, Ommoleila Molavi, Zeinab Ghesmati, Behzad Baradaran, Mehdi Sabzichi, Fatemeh Ramezani","doi":"10.34172/bi.30424","DOIUrl":"https://doi.org/10.34172/bi.30424","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>The immunosuppressive context of the tumor microenvironment (TME) is a significant hurdle in breast cancer (BC) treatment. Combinational therapies targeting cancer core signaling pathways involved in the induction of TME immunosuppressive milieu have emerged as a potent strategy to overcome immunosuppression in TME and enhance patient therapeutic outcomes. This study presents compelling evidence that targeting hypoxia-inducible-factor-1 alpha (Hif-1α) alongside chemotherapy and immune-inducing factors leads to substantial anticancer effects through modulation of TME.</p><p><strong>Methods: </strong>Chitosan (Cs)/Hif-1alpha siRNA nano-complex was synthesized by siRNA adsorption methods. Nanoparticles were fully characterized using dynamic light scattering and scanning electron microscope. Cs/Hif-1α siRNA cytotoxicity was measured by MTT assay. The anticancer effects of the combinational therapy were assessed in BALB/c bearing 4T1 tumors. qPCR and western blotting were applied to assess the expression of some key genes and proteins involved in the induction of immunosuppression in TME.</p><p><strong>Results: </strong>Hif-1α siRNA was successfully loaded in chitosan nanoparticles. Hif-1α siRNA nanocomplexes significantly inhibited the expression of <i>Hif-1α</i>. Triple combination therapy (Paclitaxel (Ptx) + Imiquimod (Imq) + Cs/Hif-1α siRNA) inhibited tumor growth and downregulated cancer progression genes while upregulating cellular-immune-related cytokines. Mice without Cs/Hif-1α siRNA treatments revealed fewer cancer inhibitory effects and more TME immunosuppressive factors. These results suggest that the inhibition of <i>Hif-1α</i> effects synergize with Ptx and Imq to inhibit cancer progression more significantly than other combinational treatments.</p><p><strong>Conclusion: </strong>Combining Hif-1α siRNA with Ptx and Imq is promising as a multimodality treatment. It has the potential to attenuate TME inhibitory effects and significantly enhance the immune system's ability to combat tumor cell growth, offering an inspiration of hope in the fight against BC.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30424"},"PeriodicalIF":2.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking the potential of lumateperone and novel anti-psychotics for schizophrenia.","authors":"S Rehan Ahmad, Md Zeyaullah, Abdullah M AlShahrani, Mohammad Suhail Khan, Adam Dawria, Ali Mohieldin, Haroon Ali, Abdelrhman Ag Altijani, Mohammad Shane Alam, Munzila Mehdi, Sabika Akram, Ejaz Rizvi Hussain, Mohammad Amjad Kamal","doi":"10.34172/bi.30259","DOIUrl":"10.34172/bi.30259","url":null,"abstract":"<p><p>Schizophrenia is a devastating chronic mental health illness which includes a complex set of symptoms like hallucination, illusion and delusion, and to manage, lifelong antipsychotic medications are needed. Schizophrenia affects 1% of the population worldwide, and to date, two different classes of antipsychotics, i.e., typical and atypical antipsychotics, are available in the market, and there is an urgent need for promising antipsychotic drugs. In this review, we focus on recently approved antipsychotics and then focus on different antipsychotic drugs under clinical trials. In this review, we first focus on lumateperone in detail, which was approved in December 2019 by the Food and Drug Administration (FDA) and simultaneously modulates serotonin, glutamate and dopamine neurotransmitters and is used at doses of 10.5-, 21- and 42 mg, which show mild adverse effects like constipation, sedation, somnolence and fatigue. This review also focuses on a few more emerging antipsychotics like brexpiprazole, brilaroxazine, roluperidone, F17464, pimavanserin (ACP-103), xanomeline, BI 409306, BI 425809 and MK-8189 which are under different phase of clinical trials and might get approved soon. Brexpiprazole and brilaroxazine act on dopamine receptors, whereas xanomeline, pimavanserin and roluperidone do not act on D2 receptors and manage the symptoms. All the antipsychotic drugs covered did not show any other severe adverse effects except gastrointestinal issues and cardiometabolic risk factors. However, still rigorous clinical trials and modifications are needed to manage adverse effects, and we can expect a few antipsychotics to be on the market soon.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30259"},"PeriodicalIF":2.2,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Annexin A1, calreticulin and high mobility group box 1 are elevated in secondary progressive multiple sclerosis: Does immunogenic cell death occur in multiple sclerosis?","authors":"Mohammad Saeid Hejazi, Sevda Jafari, Soheila Montazersaheb, Ommoleila Molavi, Vahid Hosseini, Mahnaz Talebi, Masoud Nikanfar","doi":"10.34172/bi.30264","DOIUrl":"10.34172/bi.30264","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Multiple sclerosis (MS) is a chronic neuroinflammatory diseases characterized by demyelination of the nerve fibers. Immunogenic cell death (ICD) is a process, during which damaged and stressed cells release danger-associated molecular patterns (DAMPs) activating immune responses. This study aimed to elucidate the induction of ICD in MS diseases.</p><p><strong>Methods: </strong>To achieve this goal, the level of DAMPs including Annexin A1 (ANXA1), calreticulin and HMGB1 was measured in the cerebrospinal fluid (CSF) of a secondary progressive multiple sclerosis (SPMS) patient in comparison to control group.</p><p><strong>Results: </strong>Results showed significant upregulation (more than two-fold) of ANXA1, calreticulin (CRT) and HMGB1 in the CSF of the patient.</p><p><strong>Conclusion: </strong>Although further studies are suggested in this regard, this data could imply induction of ICD in MS. The proposed ICD might trigger immune response against neural cells resulting in neuroinflammation and demyelination in CNS in MS. Our observation could suggest inclusion of ICD interfering treatments in routine MS therapy.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30264"},"PeriodicalIF":2.2,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new method for early diagnosis and treatment of meniscus injury of knee joint in student physical fitness tests based on deep learning method.","authors":"Yan Fang, Lu Liu, Qingyu Yang, Shuang Hao, Zhihai Luo","doi":"10.34172/bi.30419","DOIUrl":"https://doi.org/10.34172/bi.30419","url":null,"abstract":"<p><p></p><p><strong>Introduction: </strong>Meniscus injuries in athletes' knee joints not only hinder performance but also pose substantial challenges in timely diagnosis and effective treatment. Delayed or inaccurate diagnosis often leads to prolonged recovery periods, exacerbating athletes' discomfort and compromising their ability to return to peak performance levels. Therefore, the accurate and timely diagnosis of meniscus injuries is crucial for athletes to receive appropriate treatment promptly and resume their training regimen effectively.</p><p><strong>Methods: </strong>This paper presents a multi-step approach for diagnosing meniscus injuries through segmentation of images into lesions regions, followed by a combined classification method. The present study employs a method whereby image noise is first reduced, followed by the implementation of an enhanced iteration of the U-Net algorithm to perform image segmentation and identify regions of interest for potential injury detection.</p><p><strong>Results: </strong>In the context of diagnosing injury images, the extraction of features was accomplished through the utilization of the contour line method. Furthermore, the identification of injury types was facilitated through the application of the ensemble method, employing the principles of basic category-based voting. The method under consideration has been subjected to evaluation using a well-recognized dataset comprising MRI images knee joint injuries.</p><p><strong>Conclusion: </strong>The findings reveal that the efficacy of the proposed approach exhibits a significant enhancement in contrast to the newly developed techniques.</p>","PeriodicalId":48614,"journal":{"name":"Bioimpacts","volume":"15 ","pages":"30419"},"PeriodicalIF":2.2,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008252/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}