Miracle-dz/UniFAR-FTUs huggingface dataset:
The Diagnosis of Small Gastrointestinal Subepithelial Lesions by Endoscopic Ultrasound-Guided Fine Needle Aspiration and Biopsy

Endoscopic ultrasonography (EUS) has been widely accepted in the diagnosis of all types of tumors, especially pancreatic tumors, lymph nodes, and subepithelial lesions (SELs). One reason is that the examination can provide a detailed observation, with tissue samples being immediately obtained by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA). Many SELs are detected incidentally during endoscopic examinations without symptoms. Most SELs are mesenchymal tumors originating from the fourth layer, such as gastrointestinal stromal tumors (GISTs), leiomyomas, and schwannomas. GISTs are potentially malignant. Surgical treatment is recommended for localized GISTs of ≥20 mm. However, the indications for the diagnosis and follow-up of GISTs of <20 mm in size are controversial. There are several reports on the rapid progression or metastasis of small GISTs. Therefore, it is important to determine whether a SEL is a GIST or not. The main diagnostic method is EUS-FNA. Recently, endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) using a new biopsy needle has been reported to obtain larger tissue samples. Additionally, various biopsy methods have been reported to have a high diagnostic rate for small GISTs. In local gastric SELs, regardless of the tumor size, EUS can be performed first; then, EUS-FNA/B or various biopsy methods can be used to obtain tissue samples for decision-making in relation to therapy and the follow-up period.
Formulation of a novel anti-human oral squamous cell carcinoma supplement by gold nanoparticles-Kaolin nanocomposite

Abstract In this work, we have described the biogenic synthesized gold nanoparticles being supported over Kaolin mediated by Pomegranate peel extract as natural reducing and stabilizing agent under mild conditions without any toxic reagents. Pomegranate peel extract was used as a green reducing agent and an excellent stabilizer of the synthesized Au NPs. Physicochemical characterization of the as-synthesized Kaolin@extract/Au NPs nanocomposite was carried out through electron microscopy (SEM and TEM), energy dispersive X-ray spectroscopy (EDX), elemental mapping, X-ray diffraction (XRD) and inductively coupled plasma-optical emission spectroscopy (ICP-OES). In the cellular and molecular part of the recent study, the treated cells with Au NPs-Kaolin nanocomposite were assessed by MTT assay for 48 h about the cytotoxicity and anti-human oral squamous cell carcinoma properties on normal (HUVEC) and oral squamous cell carcinoma cell lines i.e. HSC-2, HSC-3, HSC-4 and Ca9-22. It has been observed that the Au NPs with spherical shape and size were dispersed homogeneously on the modified-Kaolin surface. The significance of this study is the novel initiative to combine the gold nanoparticle with inexpensive Kaolin clay and utilization of them as anticancer agent. The IC50 of Kaolin@extract/Au nanocomposite were 277, 367, 250 and 545 µg/mL against HSC-2, HSC-3, HSC-4 and Ca9–22 cell lines, respectively. The viability of malignant human oral cell lines reduced dose-dependently in the presence of Kaolin@extract/Au NPs nanocomposite.
Induction by Phenobarbital of Phase I and II Xenobiotic-Metabolizing Enzymes in Bovine Liver: An Overall Catalytic and Immunochemical Characterization

In cattle, phenobarbital (PB) upregulates target drug-metabolizing enzyme (DME) mRNA levels. However, few data about PB’s post-transcriptional effects are actually available. This work provides the first, and an almost complete, characterization of PB-dependent changes in DME catalytic activities in bovine liver using common probe substrates and confirmatory immunoblotting investigations. As expected, PB increased the total cytochrome P450 (CYP) content and the extent of metyrapone binding; moreover, an augmentation of protein amounts and related enzyme activities was observed for known PB targets such as CYP2B, 2C, and 3A, but also CYP2E1. However, contradictory results were obtained for CYP1A, while a decreased catalytic activity was observed for flavin-containing monooxygenases 1 and 3. The barbiturate had no effect on the chosen hydrolytic and conjugative DMEs. For the first time, we also measured the 26S proteasome activity, and the increase observed in PB-treated cattle would suggest this post-translational event might contribute to cattle DME regulation. Overall, this study increased the knowledge of cattle hepatic drug metabolism, and further confirmed the presence of species differences in DME expression and activity between cattle, humans, and rodents. This reinforced the need for an extensive characterization and understanding of comparative molecular mechanisms involved in expression, regulation, and function of DMEs.
Retraction: Dual role for an allelochemical: (±)‐catechin from Centaurea maculosa root exudates regulates conspecific seedling establishment

The Executive Editor and Managing Editor of the Journal of Ecology and authors Laura G. Perry, Ragan Callaway and Jorge Vivanco are retracting this article (Perry et al. 2005). A formal investigation by Colorado State University Research Integrity Office has found that ( )-catechin concentrations reported as being found in field soil samples in this article (Fig. 2) (Perry et al. 2005) were intentionally fabricated by a third party. The investigation therefore concluded that the results of this article are not reproducible and its scientific validity has been undermined.
The Dislocation- and Cracking-Mediated Deformation of Single Asperity GaAs during Plowing Using Molecular Dynamics Simulation

This work simulates the plowing process of a single asperity GaAs by diamond indenter using molecular dynamics simulations. The deformation mechanism of asperity GaAs is revealed by examining the topography evolution and stress state during the plowing. This work also investigates the origin of the influence of asperity size, indenter radius and plow depth on the deformation of the asperity GaAs. We observed the initiation and propagation of cracks up to the onset of fracture and the plastic activity near the indenter, obtaining more information usually not available from planar GaAs in normal velocity plowing compared to just plastic activity. The simulations demonstrated the direct evidence of cracking in GaAs induced by plowing at an atomic level and probed the origin and extension of cracking in asperity GaAs. This finding suggests that cracking appears to be a new deformation pattern of GaAs in plowing, together with dislocation-dominated plasticity modes dominating the plowing deformation process. This work offers new insights into understanding the deformation mechanism of an asperity GaAs. It aims to find scientific clues for understanding plastic removal performed in the presence of cracking.
Antioxidant Capacity of Potentilla paradoxa Nutt. and Its Beneficial Effects Related to Anti-Aging in HaCaT and B16F10 Cells

Skin aging is a natural process influenced by intrinsic and extrinsic factors, and many skin anti-aging strategies have been developed. Plants from the genus Potentilla has been used in Europe and Asia to treat various diseases. Potentilla paradoxa Nutt. has been used as a traditional medicinal herb in China and has recently been shown to have anti-inflammatory effects. Despite the biological and pharmacological potential of Potentilla paradoxa Nutt. , its skin anti-aging effects remain unclear. Therefore, this study evaluated the free radical scavenging, moisturizing, anti-melanogenic, and wound-healing effects of an ethanol extract of Potentilla paradoxa Nutt. (Pp-EE). Pp-EE was found to contain phenolics and flavonoids and exhibits in vitro antioxidant activities. α-Linolenic acid was found to be a major component of Pp-EE on gas chromatography-mass spectrometry. Pp-EE promoted the expression of hyaluronic acid (HA) synthesis-related enzymes and suppressed the expression of HA degradation-related enzymes in keratinocytes, so it may increase skin hydration. Pp-EE also showed inhibitory effects on the production and secretion of melanin in melanocytes. In a scratch assay, Pp-EE improved skin wound healing. Taken together, Pp-EE has several effects that may delay skin aging, suggesting its potential benefits as a natural ingredient in cosmetic or pharmaceutical products.
Development and Evaluation of a Paper-Based Microfluidic Device for Detection of Listeria monocytogenes on Food Contact and Non-Food Contact Surfaces

Listeria monocytogenes is the third most deadly foodborne pathogen in the United States. The bacterium is found in soil and water, contaminating raw food products and the processing environment, where it can persist for an extended period. Currently, testing of food contact and non-food contact surfaces is performed using an array of sampling devices and endpoint technologies, offering various levels of sensitivity, cost, user skill, and time to detection. Paper-based microfluidic devices (µPADs) are a rapid detection platform amenable to low-cost, user-friendly, and portable diagnostics. In this study, we developed and evaluated a µPAD platform specific for the colorimetric detection of the Listeria genus following recovery from food contact and non-food contact surfaces. For detection, four colorimetric substrates specific for the detection of β-glucosidase, two broths selective for the detection of Listeria spp. , and a nonselective broth were evaluated to facilitate detection of Listeria spp. The limit of detection and time to detection were determined by using pure bacterial cultures. After 8 h enrichment, L. monocytogenes (102 Colony Forming Units (CFU)/coupon) was detected on every surface. After 18 h enrichment, L. monocytogenes (102 CFU/coupon) was detected on all surfaces with all swabbing devices. This study demonstrated the ability of the µPAD-based method to detect potentially stressed cells at low levels of environmental contamination.
Prognose ved "Local Binary Pattern" teksturanalyse av cellekjerner fra prostata- og eggstokkreft

In the treatment of cancer, patients with the same type of cancer often react differently, even when the patients have the same age and medical history. Our wish is to predict how a patient diagnosed with cancer will react on a given treatment, and whether the patient will relapse after the treatment. The difficulty is that the majority of the cell nuclei of a patient with bad prognosis will behave like the cell nuclei of a patient with good prognosis [15]. In this thesis, we have applied local texture analysis on prostate and ovarian cancer to separate patients with good and bad prognosis. We have used Local Binary Pattern (LBP), local variance and combinations of the two mentioned operators on images of cell nuclei from prostate and ovary. In addition, we have created an image pyramid, to see whether reduction of the resolution of the cell nuclei images can improve the results. We have also used adaptive features based on occurrence matrices from LBP and three other operators. The other operators were entropy, local variance and gray level. At best, we achieved a correct classification rate of about 74 %. This result is 4 percentage points better than what Nielsen and Danielsen achieved in [50] on the same ovarian material. The best results were achieved by using LBP on images with reduced image resolution. In general, the best results where obtained by using LBP and local variance on images with reduced image resolution.
Pathophysiology and Treatment of Diabetic Cardiomyopathy and Heart Failure in Patients with Diabetes Mellitus

There is a close relationship between diabetes mellitus and heart failure, and diabetes is an independent risk factor for heart failure. Diabetes and heart failure are linked by not only the complication of ischemic heart disease, but also by metabolic disorders such as glucose toxicity and lipotoxicity based on insulin resistance. Cardiac dysfunction in the absence of coronary artery disease, hypertension, and valvular disease is called diabetic cardiomyopathy. Diabetes-induced hyperglycemia and hyperinsulinemia lead to capillary damage, myocardial fibrosis, and myocardial hypertrophy with mitochondrial dysfunction. Lipotoxicity with extensive fat deposits or lipid droplets is observed on cardiomyocytes. Furthermore, increased oxidative stress and inflammation cause cardiac fibrosis and hypertrophy. Treatment with a sodium glucose cotransporter 2 (SGLT2) inhibitor is currently one of the most effective treatments for heart failure associated with diabetes. However, an effective treatment for lipotoxicity of the myocardium has not yet been established, and the establishment of an effective treatment is needed in the future. This review provides an overview of heart failure in diabetic patients for the clinical practice of clinicians.
Pre-service teachers’ perceptions on integrating a social networking site for language learning into English classes

This paper aims to report on partial findings of a research study that intends to explore how Social Networking Sites for Language Learning (SNSLL) can be integrated into English classes of a BA program in the Teaching of Modern Languages. More specifically, this paper reports on the students' perceptions before and during the implementation of a SNSLL (Busuu). The data was gathered through two collection techniques: surveys and learning logs. Concerning the participants’ perceptions before the use of Busuu, the data analysis shows that, despite some concerns about communicative ability and personal privacy, they perceived this kind of virtual communities as effective platforms to learn EFL through genuine interaction with other users. Although the students’ perceptions during the use of Busuu involved some usability limitations and technical issues, they reiterated the potential of this SNSLL to not only facilitate language learning, but also foster intercultural development and metacognitive processes.
Advances in Nanostructures for Antimicrobial Therapy

Microbial infections caused by a variety of drug-resistant microorganisms are more common, but there are fewer and fewer approved new antimicrobial chemotherapeutics for systemic administration capable of acting against these resistant infectious pathogens. Formulation innovations of existing drugs are gaining prominence, while the application of nanotechnologies is a useful alternative for improving/increasing the effect of existing antimicrobial drugs. Nanomaterials represent one of the possible strategies to address this unfortunate situation. This review aims to summarize the most current results of nanoformulations of antibiotics and antibacterial active nanomaterials. Nanoformulations of antimicrobial peptides, synergistic combinations of antimicrobial-active agents with nitric oxide donors or combinations of small organic molecules or polymers with metals, metal oxides or metalloids are discussed as well. The mechanisms of actions of selected nanoformulations, including systems with magnetic, photothermal or photodynamic effects, are briefly described.
Tiny-UKSIE: An Optimized Lightweight Semantic Inference Engine for Reasoning Uncertain Knowledge

The application of semantic web technologies such as semantic inference to the field of the Internet of Things (IoT) can realize data semantic information enhancement and semantic knowledge discovery, which plays a key role in enhancing data value and application intelligence. However, Mainstream semantic inference engines cannot be applied to IoT computing devices with limited storage resources and weak computing power, and cannot reason about uncertain knowledge. To solve this problem, the authors propose a lightweight semantic inference engine, Tiny-UKSIE, based on the RETE algorithm. The genetic algorithm (GA) is adopted to optimize the Alpha network sequence, and the inference time can be reduced by 8.73% before and after optimization. Moreover, a four-tuple knowledge representation method with probability factors is proposed, and probabilistic inference rules are constructed to enable the inference engine to infer uncertain knowledge. Compared with mainstream inference engines, storage resource usage is reduced by up to 97.37%, and inference time is reduced by up to 24.55%.
Review on skin cancer detection using AI

Skin cancer is caused by reasons such as unhealthy life style, air pollution, UV radiation, etc. Various automated machine learning algorithmic solutions have been created in prevalent years to be used to detect such cancers before any major aggravation has taken place. In this paper there is a review on ways can detect disease and alert us before something becomes serious. The goal of this study is to look at how Artificial Intelligence can be used to diagnose skin cancer. With the use of Artificial Intelligence, people can learn what skin illness they have and what safeguards and steps they should take at an early stage, allowing them to treat the disease successfully. Machine learning will be utilized to determine the ailment and assist us in detecting the outcome. Support vector machine is the most prevalently used classification techniques. The findings of this study will aid doctors in treating disease at its onset, preventing future deterioration.
Perivascular Adipose Tissue Inflammation: The Anti-Inflammatory Role of Ghrelin in Atherosclerosis Progression

Perivascular adipose tissue (PVAT) and its adipokines engage in bidirectional crosstalk with the vascular wall. Atherosclerosis disrupts this interaction through inflammation, rupture-prone plaques, and subsequent thrombosis. The cardioprotective effects of ghrelin are in contradiction to its adipogenic properties. The concurrent research of anti-/pro-atherogenic mechanisms of ghrelin and PVAT-derived adipokines provides a better understanding of atherosclerosis progression in metabolic disorders. In-depth coverage of the characteristic features of PVAT concerning vascular dysfunction, with a survey of ghrelin-induced anti-inflammatory effects on adipose tissue macrophage infiltration and the inhibitory activity of ghrelin on the proinflammatory adipokine secretion, show that the impact of ghrelin on the endothelial function should be studied in relation to PVAT.
DISTANCE TRANSFORM BASED HAND GESTURES RECOGNITION FOR POWER POINT PRESENTATION NAVIGATION

Information conveyed in seminars, project presentation or even in class rooms can be effective when slideshow presentation is used. There are various means to control slides which require devices like mouse, keyboard, or laser pointer etc. The disadvantage is one must have prior knowledge about the devices in order to operate them. This paper proposes two methods to control the slides during a presentation using bare hands and compares their efficiencies. The proposed methods employ hand gestures given by the user as input. The gestures are identified by counting the number of active fingers and then slides are controlled. Unlike the conventional method for hand gesture recognition which makes use of gloves or markers or any other devices, this method does not require any additional devices and makes the user comfortable. The proposed method for gesture recognition does not require any database to identify a particular gesture. The experiment was tested under different kinds of light sources like incandescent bulb, fluorescent lamp and natural light .
A Survey on Knowledge, Attitude, and Practices of Large-Animal Farmers towards Antimicrobial Use, Resistance, and Residues in Mymensingh Division of Bangladesh

The widespread and indiscriminate use of antimicrobials in food animals is a key contributor to antimicrobial resistance and antimicrobial residue, which have become a growing public and animal health concern in developing countries such as Bangladesh. This study was aimed to assess the knowledge, attitude, and practices (KAP) of large-animal farmers towards antimicrobial use (AMU), antimicrobial resistance (AMR), and antimicrobial residue (AR) with their correlation. A cross-sectional survey was conducted with a structured and pretested questionnaire in the Mymensingh division of Bangladesh. A total of 212 large-animal farmers (dairy, beef fattening, buffalo, sheep, and goat farmers) were surveyed. Results showed that most of the farmers are male (85.8%) and belong to the 18–30 age group (37.3%). About 20.3% had no formal education, and nearly half of the participants (48.1%) received training regarding antibiotic use and resistance. Penicillin is the most common class of antibiotic used (61.8%) in the study area, followed by other antimicrobials. Only 37.7% of the farmers used antimicrobials on the recommendation of their veterinarian. Overall, 41.5%, 42.5%, and 21.7% of farmers possess adequate knowledge and a satisfactory attitude and perform desirable practices, respectively. Farmers in the 31–40 age group have adequate knowledge, attitude, and ability to implement desired practices compared to farmers in the 18–30 age group. Farmers having a graduate or post-graduate degree scored better in relation to knowledge, attitude, and practice than other farmers. Analysis revealed that farmers who received training on AMU and AMR had 10.014 times (OR = 10.014, 95% CIs: 5.252–19.094), 9.409 times (OR = 9.409, 95% CIs: 4.972–17.806), and 25.994 times (OR = 25.994, 95% CIs: 7.73–87.414) better knowledge, attitude, and performance, respectively, compared to their counterparts. A significant proportion of farmers (97.2%) dispose of leftover antibiotics inappropriately. The findings of the present study will be used to intervene in the education and training of the farmers, which will help to limit the indiscriminate and irrational use of antimicrobials, leading to reducing the chances of developing AMR.
Association Rule Mining: An Overview

Data mining is the process of discovering previou sly unknown, undiscovered and hidden patterns from large information repositories like relational databases and warehouses. It is of great importance in the re cent time where the amount of data has reached to gigabytes and even terabytes. Data mining makes use of various techniques such as Clustering, Classification, Association Rule Mining and Regression. Association Rule Mining finds association between the items in the database. This paper gives us a brief idea regardin g Association Rule Mining and applications of association rule mining in different areas for effective decision making.
AttentiveSDN: EndHost Awareness-Based Power-Optimized Software-Defined Networks

Internet users are increasing day by day due to its support for many applications and creation of innovative services. Along with this, energy consumption is also becoming an important concern in networking. Several researchers have investigated energy saving schemes for networks. Software-defined networking (SDN) is an excellent choice that improves network functionalities with flexible management aided by centralized control. Recent studies designed efficient algorithms for advancing SDN with overall energy savings. Shutting down idle links and switches are among numerous solutions available for SDN. In this paper, the authors proposed a novel algorithm named AttentiveSDN for reducing the energy consumption in SDNs. Here the controller collects the traffic and the link status from the switches involved in network operation and takes the decision to put which idle links and switches into sleep state. The authors evaluated the performance of the AttentiveSDN algorithm using Mininet. The result has shown that the proposed approach saves more power than existing solutions.