Search results for: liver segmentation

Authors: Elidrissi Laila, El Rhaoussi Fatima-Zahra, Haddad Fouad, Tahiri Mohamed, Hliwa Wafaa, Bellabah Ahmed, Badre Wafaa

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Introduction: Metabolic Dysfunction Associated with Non-Alcoholic Fatty Liver Disease (MASLD), formerly known as Non-Alcoholic Fatty Liver Disease (NAFLD), is the leading cause of chronic liver disease. The cardiometabolic risk factors associated with MASLD represent common health issues and significant public health challenges. Medical students, being active participants in the healthcare system and a young demographic, are particularly relevant for understanding this entity to prevent its occurrence on a personal and collective level. The objective of our study is to assess the level of knowledge among medical students regarding MASLD, its risk factors, and its long-term consequences. Materials and Methods: We conducted a descriptive cross-sectional study using an anonymous questionnaire distributed through social media over a period of 2 weeks. Medical students from various faculties in Morocco answered 22 questions about MASLD, its etiological factors, diagnosis, complications, and principles of treatment. All responses were analyzed using the Jamovi software. Results: A total of 124 students voluntarily provided complete responses. 59% of our participants were in their 3rd year, with a median age of 21 years. Among the respondents, 27% were overweight, obese, or diabetic. 83% correctly answered more than half of the questions, and 77% believed they knew about MASLD. However, 84% of students were unaware that MASLD is the leading cause of chronic liver disease, and 12% even considered it a rare condition. Regarding etiological factors, overweight and obesity were mentioned in 93% of responses, and type 2 diabetes in 84%. 62% of participants believed that type 1 diabetes could not be implicated in MASLD. For 83 students, MASLD was considered a diagnosis of exclusion, while 41 students believed that a biopsy was mandatory for diagnosis. 12% believed that MASLD did not lead to long-term complications, and 44% were unaware that MASLD could progress to hepatocellular carcinoma. Regarding treatment, 85% included weight loss, and 19% did not consider diabetes management as a therapeutic approach for MASLD. At the end of the questionnaire, 89% of the students expressed a desire to learn more about MASLD and were invited to access an informative sheet through a hyperlink. Conclusion: MASLD represents a significant public health concern due to the prevalence of its risk factors, notably the obesity pandemic, which is widespread among the young population. There is a need for awareness about the seriousness of this emerging and long-underestimated condition among young future physicians.

Keywords: MASLD, medical students, obesity, diabetes

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Shahriar Sepahvand, Mohammad Ali Davarpanah

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Infections caused by Acinetobacter baumannii are among the common hospital-acquired infections that have seen an increase in antibiotic resistance in recent years. Colistin is the last treatment option against this pathogen. The aim of this study is to investigate the histopathology of BALB/C mice receiving sensitive and resistant strains of Acinetobacter baumannii to colistin. A total of 68 female laboratory mice weighing 30 to 40 grams of the BALB/C breed were studied in this research for three weeks under appropriate laboratory conditions in terms of food and environment. The experimental groups included: control group, second group, third group, fourth group. Lung, liver, spleen, and kidney tissues were removed from anesthetized mice and, after washing in physiological serum, were fixed in 10% formalin for 14 days. For dehydration, alcohol with ascending degrees of 70, 80, 90, and 100 was used. After clearing and soaking in paraffin, the samples were embedded in paraffin. Then, sections with a thickness of 5 microns were prepared and, after staining by hematoxylin-eosin, the samples were ready for study with a light microscope. In liver, spleen, lung, and kidney tissues of mice receiving the colistin-sensitive strain of Acinetobacter baumannii, infiltration of inflammatory cells and hyperemia were observed compared to control group mice. Liver and lung tissues of mice receiving strains of Acinetobacter baumannii resistant to colistin showed tissue destruction in addition to infiltration of inflammatory cells and hyperemia, with more destruction observed in lung tissue.

Keywords: acinetobacter baumannii, colistin antibiotic, histopathological examination, resistant

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Authors: Ali Bagherpour, Masoud Soltanialvar

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Campylobacter species are common bacterial pathogens associated with human gastroenteritis which are generally transmitted through foods of animal origin. This study was carried out to determine the prevalence of Campylobacter species in poultry meat and by products in the city of Dezful in Iran. Since April 2012 to July 2013, a total of 400 samples including meat (n = 100), liver (n = 100), gizzard (n = 100), and poultry heart (n = 100), were randomly collected from Dezful industrial poultry abattoir and were experimented in order to investigate presence of Campylobacter species. According to culture test, 251 samples out of 400 samples under study (69%) were contaminated with Campylobacter species. The highest prevalence of Campylobacter species was observed in poultry's liver (78.3%) and then in gizzard (75.8%), heart (65%) and meat (56.7%). The most common isolated Campylobacter were C. jejuni (90.9%) and the rest were C. coli (9.1%). There was a significant difference (P < 0.05) in the prevalence of Campylobacter species between the meat samples taken in the summer (86.7%). The results of this study indicate the importance of edible offal of poultries as the potential source of Campylobacter infections.

Keywords: Campylobacter jejuni, Campylobacter coli, poultry, meat, products

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Authors: Michael R. Shurin, Galina Shurin, Vladimir A. Kirichenko

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Background. Visibility of hepatic malignancies is poor on non-contrast imaging for daily verification of liver malignancies prior to radiation therapy on MRI-guided Linear Accelerators (MR-Linac). Ferumoxytol® (Feraheme, AMAG Pharmaceuticals, Waltham, MA) is a SPION agent that is increasingly utilized off-label as hepatic MRI contrast. This agent has the advantage of providing a functional assessment of the liver based upon its uptake by hepatic Kupffer cells proportionate to vascular perfusion, resulting in strong T1, T2 and T2* relaxation effects and enhanced contrast of malignant tumors, which lack Kupffer cells. The latter characteristic has been recently utilized for MRI-guided radiotherapy planning with precision targeting of liver malignancies. However potential radiotoxicity of SPION has never been addressed for its safe use as an MRI-contrast agent during liver radiotherapy on MRI-Linac. This study defines the radiomodulating properties of SPIONs in vitro on human monocyte and macrophage cell lines exposed to 60Go gamma-rays within clinical radiotherapy dose range. Methods. Human monocyte and macrophages cell line in cultures were loaded with a clinically relevant concentration of Ferumoxytol (30µg/ml) for 2 and 24 h and irradiated to 3Gy, 5Gy and 10Gy. Cells were washed and cultured for additional 24 and 48 h prior to assessing their phenotypic activation by flow cytometry and function, including viability (Annexin V/PI assay), proliferation (MTT assay) and cytokine expression (Luminex assay). Results. Our results reveled that SPION affected both human monocytes and macrophages in vitro. Specifically, iron oxide nanoparticles decreased radiation-induced apoptosis and prevented radiation-induced inhibition of human monocyte proliferative activity. Furthermore, Ferumoxytol protected monocytes from radiation-induced modulation of phenotype. For instance, while irradiation decreased polarization of monocytes to CD11b+CD14+ and CD11bnegCD14neg phenotype, Ferumoxytol prevented these effects. In macrophages, Ferumoxytol counteracted the ability of radiation to up-regulate cell polarization to CD11b+CD14+ phenotype and prevented radiation-induced down-regulation of expression of HLA-DR and CD86 molecules. Finally, Ferumoxytol uptake by human monocytes down-regulated expression of pro-inflammatory chemokines MIP-1α (Macrophage inflammatory protein 1α), MIP-1β (CCL4) and RANTES (CCL5). In macrophages, Ferumoxytol reversed the expression of IL-1RA, IL-8, IP-10 (CXCL10) and TNF-α, and up-regulates expression of MCP-1 (CCL2) and MIP-1α in irradiated macrophages. Conclusion. SPION agent Ferumoxytol increases resistance of human monocytes to radiation-induced cell death in vitro and supports anti-inflammatory phenotype of human macrophages under radiation. The effect is radiation dose-dependent and depends on the duration of Feraheme uptake. This study also finds strong evidence that SPIONs reversed the effect of radiation on the expression of pro-inflammatory cytokines involved in initiation and development of radiation-induced liver damage. Correlative translational work at our institution will directly assess the cyto-protective effects of Ferumoxytol on human Kupfer cells in vitro and ex vivo analysis of explanted liver specimens in a subset of patients receiving Feraheme-enhanced MRI-guided radiotherapy to the primary liver tumors as a bridge to liver transplant.

Keywords: superparamagnetic iron oxide nanoparticles, radioprotection, magnetic resonance imaging, liver

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Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

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The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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Authors: Mohammad K. Parvez, Ahmed H. Arbab, Mohammed S. Al-Dosari, Adnan J. Al-Rehaily

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We investigated ex vivo and in vivo antioxidative and hepatoprotective effect of Aerva javanica. Total ethanol extract of A. javanica aerial parts was prepared, and tested on DCFH-toxicated HepG2 cell in CCl4-injured Wistar rats. MTT-assay was used to determine cell viability, and serum biochemical markers of liver injury as well as histopathology were performed. In vitro DPPH and β-carotene free-radical scavenging assay and phytochemical screening of the extract was done. Furthermore, A. javanica total extract was standardized and validated by HPTLC method. While DCFH-injured cells were recovered to about 56.7% by 100 microg/ml of the extract, a 200 microg/ml dose resulted in hepatocytes recovery by about 90.2%. Oral administration of the extract (100 and 200 mg/kg.bw/day) significantly normalized the serum SGOT, SGPT, GGT, ALP, bilirubin, cholesterol, HDL, LDL, VLDL, TG and MDA levels, including tissue NP-SH and TP in CCl4-injured rats. In addition, the histopathology of dissected liver also revealed that A. javanica cured the tissue lesion compared to reference drug, Silymarin. In vitro assays revealed strong free-radical scavenging ability of the extract and presence of alkaloids, flavonoids, tannins, sterols and saponins where Rutin, a well-known antioxidant flavonoid was identified. Our finding therefore, suggests the therapeutic potential of A. javanica in various liver diseases. However, isolation of the active principles, their mechanism of action and other therapeutic contribution remain to be addressed.

Keywords: Aerva javanica, antioxidant, hepatoprotection, rutin

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Deepak Kumar Mittal, Alok Kumar Jena, Deepmala Joshi

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The present study was carried out to observe the hepatoprotective effect and antioxidant activity of the aqueous extract of the roots of Polygonum bistorta (PB) (200 mg/kg) and Zingiber roseum (ZR) (250 mg/kg) in rats treated with carbon tetrachloride (0.15 ml/kg, i.p.). Extract of PB and ZR at the tested doses restored the levels of liver homogenate enzymes, glutathione peroxidase, glutathione-S-transferase, superoxide dismutase and catalase enzymes, significantly. The activities of MTT assay significantly recovered the damage and supported the biochemical observations. This study suggests that Zingiber roseum has a higher protective effect on liver, compared to Polygonum bistorta, against carbon tetrachloride-induced hepatotoxicity and possesses antioxidant activities. Also, extracts exhibited moderate anticancer activity towards cell viability at higher concentration.

Keywords: Polygonum bistorta, Zingiber roseum, hepatoprotective effect, carbon tetrachloride, anti-cancerous

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Authors: M. Zehtabian, Z. Molaiemanesh, Z. Shafahi, M. Papie, M. Zahraie Moghaddam, M. Mehralizadeh, M. R. Vahidi, S. Sina

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The introduction of CT scans has been a great improvement in diagnosis of different diseases. However, this imaging modality can expose the patients to cumulative radiation doses which may increase the risks of some health problems like cancer. In this study, the dose delivered to different organs in lumbar-abdominal imaging was measured by putting the TLD-100, and TLD-100H chips inside the Alderson Rando phantom. The lumbar-abdominal image of the phantom was obtained, while TLD chips were inside the holes of the phantom. According to the results obtained in this study using TLD-100 chips, the average dose received by liver, bladder, rectum, kidneys, and uterus were found to be 12.9 mSv, 8.9 mSv, 10.1 mSv, 11.0 mSv, 11.2 mSv, and 10.5 mSv respectively, while the measurements performed by TLD-100H show that the average dose to liver, bladder, rectum, kidneys, and uterus were found to be 12.4 mSv, 9.2 mSv, 9.5 mSv, 10.5 mSv, 10.7 mSv, and 9.9 mSv respectively. The results of this study indicates that the dose measured by the TLD-100H chips are in close agreement with those obtained by TLD-100.

Keywords: CT scan, dose, TLD-100, diagnosis

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Authors: Awad G. Abdellatif, Huda M. Gargoum, Abdelkader A. Debani, Mudafara Bengleil, Salmin Alshalmani, N. El Zuki, Omran El Fitouri

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In this study, the administration of 660 mg/kg of the ethanolic extract of the Alhgigraecorum (camel thorn) to mice, showed a significant decrease in the level of transaminases in animals treated with a combination of CTE plus carbon tetrachloride (CCl4) or acetaminophen as compared to animals receiving CCl4 or acetaminophen alone. The histopathological investigation also confirmed that camel thorn extract protects the liver against damage-induced either by carbon tetrachloride or acetaminophen. On the other hand, the cardiac toxicity produced by adriamycin was significantly increased in the presence of the ethanolic extract of camel thorn. Our study suggested that camel thorn can protect the liver against the injury produced by carbon tetrachloride or acetaminophen, with an unexpected increase in the cardiac toxicity–induced by adriamycin in rodents.

Keywords: ethanolic, alhgigraecorum, tetrachloride, acetaminophen

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Authors: Muhammad Shahzad Tufail, Iram Liaqat

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Silver nanoparticles (AgNPs) have wider biomedical applications due to their intensive antimicrobial activities. However, toxicity and side effects of nanomaterials like AgNPs is a subject of great controversy towards the further studies in this direction. In this study, biogenically synthesized AgNPs, previously characterized via ultraviolet (UV) visible spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD) and fourier transform infrared spectroscopy (FTIR), were subjected to toxicity evaluation using mice model. Albino male mice (BALB/c) were administered with 50 mgkg-1, 100 mgkg-1 and 150 mgkg-1 of AgNPs, respectively, except for control for 30 days. Log-probit regression analysis was used to measure the dosage response to determine the median lethal dose (LD50). Exposure to AgNPs caused significant changes in the levels of serum AST (P ˂ 0.05) at the 100mgkg-1 and 150mgkg-1 of AgNPs exposure, while ALT and serum creatinine (P ˃ 0.05) levels remained normal. Histopathology of male albino mice liver and kidney was studied after 30 days experimental period. Results revealed that mice exposed to heavy dose (150 mgkg-1) of AgNPs showed cell distortion, necrosis and detachment of hepatocytes in the liver. Regarding kidney, at lower concentration, normal renal structure with normal glomeruli was observed. However, at higher concentration (150 mgkg-1), kidneys showed smooth surface and dark red colour with proliferation of podocytes. It can be concluded from present study that biologically synthesized AgNPs are small to be eliminated easily by kidney and therefore the liver and kidney did not show toxicity at low concentrations.

Keywords: silver nanoparticles, pseudomonas aeruginosa, male albino mice, toxicity assessment

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Khairy M. A. Zoheir, Nehma A. Ali, Ahmed M. Darwish, Mohamed S. Kishta, Ahmed A. Abd-Rabou, Mohamed A. Abdelhafez, Karima F. Mahrous

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The study comprehensively investigated the multifaceted therapeutic properties of the IQGAP1shRNA plasmid, encompassing its hepatoprotective, immunomodulatory, and anticancer activities. The study employed a Prednisolone-induced immunosuppressed rat model to assess the hepatoprotective and immunomodulatory effects of IQGAP1shRNA plasmid. Using this model, IQGAP1shRNA plasmid was found to modulate haematopoiesis, improving RBC, platelet, and WBC counts, underscoring its potential in hematopoietic homeostasis. Organ atrophy, a hallmark of immunosuppression in spleen, heart, liver, ovaries, and kidneys, was reversed with IQGAP1shRNA plasmid treatment, reinforcing its hepatotrophic and organotropic capabilities. Elevated hepatic biomarkers (ALT, AST, ALP, LPO) indicative of hepatocellular injury and oxidative stress were reduced with GST, highlighting its hepatoprotective and antioxidative effects. IQGAP1shRNA plasmid also restored depleted antioxidants (GSH and SOD), emphasizing its potent antioxidative and free radical scavenging capabilities. Molecular insights into immune dysregulation revealed downregulation of IQGAP1, IQGAP3 interleukin-2 (IL-2), and interleukin-4 (IL-4) mRNA expression in the liver of immunosuppressed rats. IL-2 and IL-4 play pivotal roles in immune regulation, T-cell activation, and B-cell differentiation. Notably, treatment with IQGAP1shRNA plasmid exhibited a significant upregulation of IL-2 and IL-4 mRNA expression, thereby accentuating its immunomodulatory potential in orchestrating immune homeostasis. Additionally, immune dysregulation was associated with increased levels of TNF-α. However, treatment with IQGAP1shRNA plasmid effectively decreased the levels of TNF-α, further underscoring its role in modulating inflammatory responses and restoring immune balance in immunosuppressed rats. Additionally, pharmacokinetics, bioavailability, drug-likeness, and toxicity risk assessment prediction suggest its potential as a pharmacologically favourable agent with no serious adverse effects. In conclusion, this study confirms the therapeutic potential of the IQGAP1shRNA plasmid, showcasing its effectiveness against hepatotoxicity, oxidative stress, immunosuppression, and its notable anticancer activity.

Keywords: IQGAP1, shRNA, cancer, liver, rat

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Authors: Abdul Soofi, Katherine Wolf, Egon Ranghini, Gregory Dressler

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Obesity and its associated complications, such as insulin resistance and non-alcoholic fatty liver disease, are reaching epidemic proportions. In mice, the TGF-β superfamily is implicated in the regulation of white and brown adipose tissues differentiation. The Kielin/Chordin-like Protein (KCP) is a secreted regulator of the TGF-β superfamily pathways that can inhibit both TGF-β and Activin signals while enhancing the Bone Morphogenetic protein (BMP) signaling. However, the effects of KCP on metabolism and obesity have not been studied in animal models. Thus, we examined the effects of KCP loss or gain of function in mice that were maintained on either a regular or a high fat diet. Loss of KCP sensitized mice to obesity and associated complications such as hepatic steatosis and glucose intolerance. In contrast, transgenic mice that expressed KCP in the kidney, liver and adipose tissues were resistant to developing high fat diet induced obesity and had significantly reduced white adipose tissue. KCP over-expression was able to shift the pattern of Smad signaling in vivo, to increase the levels of P-Smad1 and decrease P-Smad3, resulting in resistance to high fat diet induced hepatic steatosis and glucose intolerance. In aging mice, loss of KCP promoted liver pathology even when mice were fed a normal diet. The data demonstrate that shifting the TGF-β superfamily signaling with a secreted inhibitor or enhancer can alter the physiology of adipose tissue to reduce obesity and can inhibit the initiation and progression of hepatic steatosis to significantly reduce the effects of high fat diet induced metabolic disease.

Keywords: adipose tissue, KCP, obesity, TGF-β, BMP, hepatic steatosis, metabolic syndrome

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Authors: Soudeh Tabashi, Mohammadreza Moshari, Parisa Sezari

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Introduction: Postoperative analgesia in Orthotopic Liver Transplantation (OLT) surgery is challenging for anesthesiologists. Although OLT is one of the most extensive abdominal operations, it seems that patients don’t suffer from severe post operative pain. On the other hands drug metabolism is unpredictable due to unknown graft function. The aim of this study was to compare intraoperative infusion of remifentanil versus fentanyl in postoperative opioid demand in patients with OLT and evaluating the complications in two groups. Method: In this double-blind clinical trial 34 patients who had OLT were included. They divided randomly in two groups of Remifentanil (R) and Fentanyl (F). Patients in group R and F received infusion of Remifentanil 0.3-1 µg/Kg/min and Fentanyl 0.3-1 µg/Kg/min during maintenance of anesthesia. Post operative pain were measured in 6, 12, 18, 24 hours and second and third days after surgery with Numeric Rate Scale (NRS). Patients had received intravenous acetaminophen as rescue therapy with NRS of 3 or more. In addition to demographic information, post operative opioid consumption were recorded as the primary outcome. Intraoperative blood transfusion, intraoperative inotropic drugs consumption, weaning time and intensive care unit stay were also evaluated. Results: Total dose of acetaminophen consumption in first 3 days after surgery did not have significant difference between two groups (Pvalue=0.716). intraoperative inotrope consumption, blood transfusion and post operative weaning time and ICU stay were also similar in both groups. Conclusion: This study demonstrates that intraoperative infusion of remifentanil in OLT have the same effect on post operative pain management as fentanyl. Despite the complications of operation were not increased by remifentanil.

Keywords: liver transplantation, postoperative pain, remifentanil, fentanyl

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Faizah Asiri, Mohammed Fathy, Saeed Alghamdi, Nahlah Ayoub, Faisal Asiri

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Background: - The strategies for this study were based on the toxic effect of long-term inhalation of Benzene on hormones and liver enzymes and various parameters related to it. The following databases were searched: benzene, hepatotoxic, benzene metabolism, hormones, testosterone, hemotoxic, and prolonged exposure. A systematic strategy is designed to search the literature that links benzene with the multiplicity and different types of intoxication or the medical abbreviations of diseases relevant to benzene exposure. Evidence suggests that getting rid of inhaled gasoline is by exhalation. Absorbed benzene is metabolized by giving phenolic acid as well as meconic acid, followed by urinary excretion of conjugate sulfates and glucuronides. Materials and Methods :- This work was conducted in the Al-Khadra laboratory in Taif 2020/2021 and aimed to measure some of the possible endocrinal and liver toxicities associated with benzene's long-term exposure in Saudi Arabia at the station workers who are considered the most exposed category to gasoline. One hundred ten station workers were included in this study. They were divided into four patient groups according to the chronic exposure rate to benzene, one control group, and three other groups of exposures. As follows: patient Group 1 (controlled group), patient Group 2 (exposed less than 1y), patient Group 3 (exposed 1-5 y), patient Group 4 (more than 5). Each group is compared with blood sample parameters (ALT, FSH and Testosterone, TSH). Blood samples were drawn from the participants, and statistical tests were performed. Significant change (p≤0.05) was examined compared to the control group. Workers' exposure to benzene led to a significant change in hematological, hormonal, and hepatic factors compared to the control group. Results:- The results obtained a relationship between long-term exposure to benzene and a decrease in the level of testosterone and FSH hormones, including that it poses a toxic risk in the long term (p≤0.05) when compared to the control. We obtained results confirming that there is no significant coloration between years of exposure and TSH level (p≤0.05) when compared to the control. Conclusion:- We conclude that some hormones and liver enzymes are affected by chronic doses of benzene through inhalation after our study was on the group most exposed to benzene, which is gas station workers.

Keywords: toxicities, benzene, hormones, station workers

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Flaurence Benjamain, Michel Casperance

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We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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Authors: Yara Mohamed Taha, Mohamed Ali El Desouky, Heba Kamal Abdel Hakim, Maha Hanafy Mahmoud

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Hepatotoxicity due to drugs and toxic chemicals constitutes a crucial health problem nowadays. Medicinal plants are widely used recently for protecting against many liver disorders and inflammatory conditions. This study aims to evaluate hepatoprotective impact of green tea extract (GTE), rosemary extract (RE) and rosmarinic acid (RA) against hepatotoxins; ferric nitrilotriacetate (Fe-NTA) and diethylnitrosamine (DEN) in rats. Five groups of male Wistar rats were included; one control negative, while the other groups were treated intraperitoneally with DEN as 160 mg.kg-1 b.w. on 15th day and Fe-NTA as 5 mg.kg-1 b.w. on 33rd day. One of them was control positive. The other three groups were pre-administered with daily protective oral doses of either 200 mg.kg-1 b.w. of RE or 1 g.kg- 1 b.w. of GTE or 50 mg.kg-1 b.w. of RA two weeks prior to DEN exposure and continued till the end of the experimental period. The obtained data revealed a highly significant increase of MDA, 8-OHdG, DNA damage percent, a significant depletion of GSH and elevated Gr-1 protein expression in hepatocytes with liver tissue histopathological changes of rats exposed to DEN+Fe-NTA. Pre-administration of protective doses of RE, GTE and RA to DEN+Fe-NTA treated rats could normalize the altered biochemical, histopathological and immunohistochemical parameters. In conclusion, RE, GTE and RA showed a hepatoprotective effect against liver toxicity induced by DEN+Fe-NTA, with the best antioxidant and anti-inflammatory impact were for RA and GTE. Therefore, the current study declared that rosemary, green tea and products enriched with rosmarinic acid should be involved daily in diet of people who are exposed to chemicals and environmental toxins to protect themselves from hepatotoxicity.

Keywords: hepatotoxicity, diethylnitrosamine and ferric nitrilotriacetate, rosemary extract (RE), green tea extract (GTE), rosmarinic acid (RA)

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Authors: Hiba T. Allah ALtieb Gusm ALsied, Amna Beshir Medani Ahmed, Ikram Mohamed ELtayeb, Saad Mohamed Hussein Ayoub

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This study was carried out to determine the hepatoactivity and the antioxidant activity of Coiradrum sativum L. aerial part and fruit extracts against CCL4 induced acute liver damages in Wistar rats. The aerial parts and fruits part of the plant were extracted 96% ethanol with soxhlet apparatus. Hepatic injury was achieved by subcutaneous injection of 3 ml/kg of CCL4 diluted with olive oil with ratio 1:1. The extracts were mixed together 1:1 ratio and given in different doses 100,200,400 mg/kg/day for 5 days under CCL4 induction at 3rd day. The significance of differences between means by using T-test was compared among the groups. The mixture of the two extracts didn’t show any significant result in protecting liver injury (antagonistic effects), it shows high level of liver enzyme like alkaline phosphatase (ALP), glutamate oxaloacetate transaminase (SGOT) and glutamate pyruvate transaminase (SGPT). Serological studies further confirmed the results. The results obtained were compared with silymarin (70 mg/kg/day) orally, the standard drug for hepatoprotection which show recovery close to normalization almost like that of silymarin; therefore, further studies on this plant with different ratios especially in isolated tissue to spot more light on antagonistic effects of the two extracts. Antioxidant activity of the extracts was determined by the DPPH method. The results obtained show high anti-oxidant activity for fruits extract while slight or moderate antioxidant activity to aerial extracts.

Keywords: antioxidant, aerial part, Coriadrum sativum L., fruity, hepatoprotection, Silymarin, phytochemical screening

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

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Authors: Adegbegi Ademuyiwa Joshua, Onoagbe Iyare

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Medicinal plants have been recognized to have therapeutic effects and they may also have toxic side effects. The present study was undertaken to investigate the effect of extracts of Cymbopogon citratus on normal rats. Blood glucose levels of all animals were determined. Biochemical studies carried out to determine the oxidative status by measuring activities of superoxide dismutase (SOD) and catalase (CAT), and in the liver, kidney and pancrease. Oral administration of ethanolic and aqueous extract of C. citratus at a doses of 200 mg/kg body weight, for a period of 30 days, caused a significant (p<0.05) reduction in blood glucose levels. Effect on hormonal profile (TSH, T3, and T4) was also determined, and was found to be significantly higher in all the administered groups when compared with control. Lipid profiles levels; Total cholesterols, triglycerides, high density lipoprotein-cholesterol and low density lipoprotein-cholesterol were significantly (p>0.05) higher for all treated rats as compared against control. SOD, catalase, GSH and Vitamin C activities in the tissues (liver, kidney and pancrease) of the rats treated with the medicinal plants were generally higher or statistical slightly similar to control. Histopathology result showed that both ethanolic and aqueous extracts (200 mg/kg body weight) of C. citratus was safer as no adverse effects were observed in the organs examined. Findings in this study showed that this plant has hypoglycemic properties and did not exert oxidative damage; in some instances, particularly in the liver, kidney and pancreas as well as its relative safety and possible use for weight gain.

Keywords: medicinal plants, blood glucose, cymbopogon citratus, hypoglycaemic, oxidative status

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

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Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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