Echinacoside ameliorates hepatic fibrosis and tumor invasion in rats with thioacetamide-induced hepatocellular carcinoma

Hepatocellular carcinoma (HCC) affects approximately 800,000 individuals globally each year. Despite advancements in HCC treatments, there is still a pressing need to identify new drugs that can combat resistance. One potential option is echinacoside, a natural caffeic acid glycoside with antioxidant, anti-inflammatory, antidepressant, and antidiabetic properties. Therefore, we aimed to investigate the ability of echinacoside to exhibit antitumor activity against HCC in rats through ameliorating hepatic fibrosis and tumor invasion. Rats were given thioacetamide to induce HCC, and some were given 30 mg/kg of echinacoside twice a week for 16 weeks. The liver impairment was assessed by measuring serum α-fetoprotein (AFP) and examining liver sections stained with Masson trichrome or anti-transforming growth factor (TGF)-β1 antibodies. The hepatic expression of mRNA and protein levels of TGF-β1, β-catenin, SMAD4, matrix metalloproteinase-9 (MMP9), phosphoinositide 3-kinases (PI3K), mammalian target of rapamycin (mTOR), connective tissue growth factor 2 (CCN2), E-Cadherin, platelets derived growth factor (PDGF)-B and fascin were also analyzed. Echinacoside improved the survival rate of rats by decreasing serum AFP and the number of hepatic nodules. Examination of micro-images indicated that echinacoside can reduce fibrosis. It also significantly decreased the expression of TGF-β1, β-catenin, SMAD4, MMP9, PI3K, mTOR, CCN2, PDGF-B, and fascin while enhancing the expression of E-Cadherin. In conclusion, echinacoside exhibits a protective effect against HCC by increasing survival rates and decreasing tumor growth. It also acts as an inhibitor of the hepatic tissue fibrosis pathway by reducing the expression of TGF-β1, β-catenin, SMAD4, PI3K, CCN2, PDGF-B and mTOR. Additionally, it prevents tumor invasion by suppressing MMP9 and fascin, and increasing the expression of E-Cadherin

AI-Driven livestock identification and insurance management system

Cattle identification is pivotal for many reasons. Animal health management, traceability, bread classification, and verification of insurance claims are largely depended on the accurate identification of the animals. Conventionally, animals have been identified by various means such as ear tags, tattoos, rumen implants, and hot brands. Being non-scientific approaches, these controls can be easily circumvented. The emerging technologies of biometric identification are extensively applied for Human recognition via thumb impression, face features, or eye retina patterns. The application of biometric recognition technology has now moved towards animals. Cattle identification with the help of muzzle patterns has shown tremendous results. For precise identification, nature has awarded a unique Muzzle pattern that can be utilized as a primary biometric feature. Muzzle pattern image scanning for biometric identification has now been extensively applied for identification. Animal recognition via Muzzle pattern image for different applications has been proliferating gradually. One of those applications includes the identification of fake insurance claims under livestock insurance. Fraudulent animal owners tend to lodge fake claims against livestock insurance with proxy animals. In this paper, we proposed the solution to avoid and/or discard fraudulent claims of livestock insurance by intelligently identifying the proxy animals. Data collection of animal muzzle patterns remained challenging. Key aspects of the proposed system include: (1) the Animal face will be detected through visual using YOLO v7 object detector. (2) After face detection, the same procedures will apply to detect muzzle point (3) the muzzle pattern is extracted and then stored in the database. The System has a mean average precision of 100% for the face and 99.43% for the nose/muzzle point of the animal. Once the animal is registered in the database, the identification process is initiated by extracting unique nose pattern features with ORB and/or SIFT. Then it is matched using the pattern matchers like BFMatcher and/or FLANNMatcher for animal identification. The proposed model is more efficient and accurate as compared to concurrent approaches. The results extracted from this research study show 100% accurate identification

Use of image-enhanced endoscopy in the characterization of colorectal polyps: Still some ways to go

Background/Aim: Instrument-based image-enhanced endoscopy (IEE) is of benefit in detecting and characterizing lesions during colonoscopy. We aimed to study the ability of community-based gastroenterologists to differentiate between neoplastic and non-neoplastic lesions using IEE modalities and to identify predictors of correct classification and the confidence of the optical diagnosis made. Materials and Methods: An electronic survey was sent to practicing gastroenterologists using electronic tablets during a gastroenterology meeting. Demographic and professional information was gathered and endoscopic images of various colonic lesions were shown and they were requested to classify the images based in white light, flexible spectral imaging color enhancement (FICE), iScan, and narrow band imaging (NBI). Results: Overall, 71 gastroenterologists responded to the survey, 76% were males and the majority were aged between 36 and 45 years (44%). Most of the respondents practiced both hepatology and gastroenterology (56%) and most of them had never received any training on IEE (66%). Correct identification of lesions using regular white light endoscopy was low (range 28%–84%). None of the IEE modalities increased the percentage of correct diagnoses apart from one NBI image where it increased from 28% (95%CI: 17%–38%) to 56% (95%CI: 44%–68%) (P < 0.01). Those who identified themselves as practicing mainly luminal gastroenterology were more confident 72% (95%CI: 60%–84%) compared with hepatologists 36% (95%CI: 25%–48%), or those who practiced both 48% (95%CI: 39%–56%) despite no difference in the percentage in correct answers. Conclusion: There remain areas of improvement in the performance of endoscopists in practice and would recommend more dedicated training programs, which could make use of asynchronous technological platforms

Efficacy of curcumin for recurrent aphthous stomatitis: a systematic review

Background Recurrent aphthous stomatitis (RAS) is the most common ulcerative lesion of the oral mucosa. The management of RAS is quite challenging with no definitive cure. Objective The present systematic review aimed to summarize the available evidence regarding the efficacy of curcumin in the management of RAS. Methods PubMed, Scopus and Web of Science databases were searched in June 2020 for all relevant studies. Clinical trials that assessed the efficacy of curcumin for the management of RAS were included. The primary outcomes were pain and/or clinical improvement. Results Eight studies involving 439 subjects were included. The efficacy of curcumin was compared with 1% triamcinolone in four studies, glycerin vehicle in one study, placebo in one study, and honey in one study. Overall, the included studies reported a good efficacy of curcumin in reducing pain and ulcers size in patients with RAS. Four studies found curcumin as effective as triamcinolone in relieving signs and symptoms of RAS. Three studies reported superior results with curcumin as compared with control groups. Conclusion The limited available evidence suggests that curcumin have potential benefits in alleviating pain and accelerating healing in patients with RAS. Further well-designed clinical trials with standardized curcumin formulations are highly recommended

Fuzzy-Based Fusion Model for β-Thalassemia Carriers Prediction Using Machine Learning Technique

The abnormality of haemoglobin in the human body is the fundamental cause of thalassemia disease. Thalassemia is considered a common genetic blood condition that has received extensive investigation in medical research globally. Likely, inherited disorders will be passed down to children from their parents. If both parents are beta Thalassemia carriers, 25% of their children will have intermediate or major beta thalassemia, which is fatal. An efficient method of beta thalassemia is prenatal screening after couples have received counselling. Identifying Thalassemia carriers involves a costly, time-consuming, and specialized test using quantifiable blood features. However, cost-effective and speedy screening methods must be developed to address this issue. The demise rate due to thalassemia development is outstandingly high around the globe. The passing rate due to thalassemia development can be reduced by following the proper procedure early; otherwise, it significantly impacts the body. A machine learning-based late fusion model proposes the detection of beta-thalassemia carriers by analyzing red blood cells. This study applied the late fusion technique to employ four machine learning algorithms. For identifying the beta thalassemia carriers, Logistics Regression, Naïve Bayes, Decision Tree, and Neural Network, they have achieved an accuracy of 94.01%, 93.15%, 97.93%, and 98.07%, respectively, by using the features-based dataset. The late fusion-based ML model achieved an overall accuracy of 96% for detecting beta-thalassemia carriers. The proposed late fusion model performs better than previously published approaches regarding efficiency, reliability, and precision

Seasonal Variation and Geographical Distribution of COVID-19 across Nigeria (March 2020–July 2021)

Globally, the novel corona virus infection has continued to witness a growing number of cases since December 2019 when the outbreak was discovered and noted in China. Despite this has not been well studied for the case of COVID-19, human contact, public moveableness and environmental variables could have an impact onairborne’spropagation and virus continuance, such as influenza virus. This study aimed to determine the seasonal variation and geographical distribution of COVID-19 across Nigeria. An internet based archival research design was employed for this study on the seasonal variation and geographical distribution of COVID-19 across Nigeria. This involved the use of goggle mobility data and world map on Corona Virus Infection (COVID-19). The search strategy for getting information for this research was done electronically. The keywords in the case search using the goggle mobility software was “COVID-19 Update”, “COVID-19 Update in Nigeria”, ‘COVID-19 Winter Report’, “COVID-19 Case Fatality March 2020–July 2021”, “COVID-19 Case Fatality in Nigeria”. The data gotten from the goggle motor updates were entered into Statistical Package for the Social Sciences (SPSS) which was used in the analysis of the study. Results from the study, reported that official COVID-19 cases number was significantly higher in the Dry season (October 2020–April 2021) with 59.0% (127,213) compared to 41.0% (85,176) in the wet/rainy season (May–September) it revealed that the dry and rainy seasons had a COVID-19 prevalence of 0.063 and 0.041 respectively. Further results from the study showed that the prevalence of COVID-19 was 0.07% in the North-Central, 0.04% in both the North-East and North-West, 0.03% in the South-West, 0.09% in the South-South, and the highest prevalence of 0.16% in the South-East. Considering the case Fatality rate of COVID-19 during the Dry and Wet Seasons. The study revealed that North-Central had a death toll of 196 (10.4%) out of 9457 confirmed COVID-19 cases hence a fatality of 2.07. Fatality rate of 1.49% in South western Nigeria, South-South Nigeria, 1.49%, South-East accounted to a fatality rate of 1.25%. Nigeria based on the finding of this study records increased fatality in Dry season over wet seasons. The study concluded that prevalence of COVID-19 varies in seasons in Nigeria Hence; further Data and Meteorological analysis on weather variations towards the SARS-CoV-2 Virus spread should be evaluated by future researchers. It is imperative to ensure strict and controlled application of social measures, such as social distancing, mandatory wearing of non-medical masks to prevent droplets from entering the respiratory tract, screening of affected patients along with quarantine is essential to defeat and improve infection control

Seasonal Variation and Geographical Distribution of COVID-19 across Nigeria (March 2020&ndash;July 2021)

Globally, the novel corona virus infection has continued to witness a growing number of cases since December 2019 when the outbreak was discovered and noted in China. Despite this has not been well studied for the case of COVID-19, human contact, public moveableness and environmental variables could have an impact onairborne&rsquo;spropagation and virus continuance, such as influenza virus. This study aimed to determine the seasonal variation and geographical distribution of COVID-19 across Nigeria. An internet based archival research design was employed for this study on the seasonal variation and geographical distribution of COVID-19 across Nigeria. This involved the use of goggle mobility data and world map on Corona Virus Infection (COVID-19). The search strategy for getting information for this research was done electronically. The keywords in the case search using the goggle mobility software was &ldquo;COVID-19 Update&rdquo;, &ldquo;COVID-19 Update in Nigeria&rdquo;, &lsquo;COVID-19 Winter Report&rsquo;, &ldquo;COVID-19 Case Fatality March 2020&ndash;July 2021&rdquo;, &ldquo;COVID-19 Case Fatality in Nigeria&rdquo;. The data gotten from the goggle motor updates were entered into Statistical Package for the Social Sciences (SPSS) which was used in the analysis of the study. Results from the study, reported that official COVID-19 cases number was significantly higher in the Dry season (October 2020&ndash;April 2021) with 59.0% (127,213) compared to 41.0% (85,176) in the wet/rainy season (May&ndash;September) it revealed that the dry and rainy seasons had a COVID-19 prevalence of 0.063 and 0.041 respectively. Further results from the study showed that the prevalence of COVID-19 was 0.07% in the North-Central, 0.04% in both the North-East and North-West, 0.03% in the South-West, 0.09% in the South-South, and the highest prevalence of 0.16% in the South-East. Considering the case Fatality rate of COVID-19 during the Dry and Wet Seasons. The study revealed that North-Central had a death toll of 196 (10.4%) out of 9457 confirmed COVID-19 cases hence a fatality of 2.07. Fatality rate of 1.49% in South western Nigeria, South-South Nigeria, 1.49%, South-East accounted to a fatality rate of 1.25%. Nigeria based on the finding of this study records increased fatality in Dry season over wet seasons. The study concluded that prevalence of COVID-19 varies in seasons in Nigeria Hence; further Data and Meteorological analysis on weather variations towards the SARS-CoV-2 Virus spread should be evaluated by future researchers. It is imperative to ensure strict and controlled application of social measures, such as social distancing, mandatory wearing of non-medical masks to prevent droplets from entering the respiratory tract, screening of affected patients along with quarantine is essential to defeat and improve infection control

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7