bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-inflammatory properties of curcumin and silver (I) nanocomplexes in inflammatory bowel diseases: in vitro and in vivo examination
Authors: Piotrowska Marta , Krajewska Julia , Talar Marcin , Długosz Olga , Banach Marcin , Fichna Jakub 
Published: July 2022

Abstract

Purpose
Inflammatory bowel disease (IBD) is characterized by chronic and relapsing inflammation of the gastrointestinal tract. Current treatment strategies of IBD are insufficient, expensive and connected with high toxicity. In search for alternatives that could help in the management of IBD without causing serious side effects, natural compounds attracted much attention recently. Curcumin is a natural, inexpensive compound with anti-inflammatory properties derived from rhizomes of Curcuma longa L. Concurrently, silver can suppress microbial activity and promote wound healing. Taking into consideration properties of both compounds, we decided to combine, with the use of nanotechnology, silver and curcumin to synergistically enhance their activity.
Methods
We obtained two formulations: curcumin and silver (I) nanoparticles complex (curcumin + nAg) and curcumin nanoparticles and silver (I) nanoparticles complex (ncurcumin + nAg). We assessed the anti-inflammatory effect of formulations in vitro in the LPS-stimulated RAW264.7 macrophages and in vivo in the mouse model of dextran sulfate sodium (DSS)-induced colitis.
Results
In vitro, both formulations inhibited nitric oxide (NO) release and in vivo complexes alleviated colitis.
Conclusion
In conclusion, our research showed that combination of curcumin with nAg improves curcumin’s anti-inflammatory properties and that using nanocurcumin instead of curcumin further enhanced this effect. Curcumin and silver (I) nanocomplexes may become a new treatment option in inflammatory bowel diseases.
La Culebra stream, a hydrological relic in the Guadalajara Metropolitan Area (Mexico)
Authors: Carrillo-González Karen Aidé , Zavala-Aguirre José Luis 
Published: July 2022

Abstract
In urban environments the existence of streams with ecological functionality, with an assembly of producers, consumers and degraders, with abundance governed by environmental variations and by the flow of nutrients, maintaining an aerobic process is becoming less frequent. La Culebra stream originates in Los Colomos Urban Forest (LCUF) within the Guadalajara Metropolitan Area (GMA), which is preserved almost naturally with few human interventions in the studied section. The stream flows from springs that emerge within the Urban Forest. But its waters are discharged into an urban channel that carries drainage water and stormwater runoff. In addition, there are no records of the water quality of La Culebra stream. It is of great interest to know its characteristics to propose management alternatives or a better use. Through the use of physicochemical techniques and test organisms, the behavior of macronutrients in the water, the existence of inhibition factors and the presence of coliforms were investigated during six months representative of the seasonality of the year 2018. In the last month of the study, it was implemented the analysis of sediment quality with the use of a specific test organism for the soil-water interface. In general, the stream was found without an excessive load of nutrients and with a variability in its physicochemistry and biology depending on the seasonal cycle. The system maintains adequate levels of dissolved oxygen to support the respiration of organisms in the water column and in particular the upper layer of the sediment with the highest demand for this gas. It was found that the oscillation of the annual temperature in the stream presents a delay of one to two months in relation to the atmospheric temperature. The finding of the inverse behavior between temperature and pH facilitated the interpretation of the availability of nutrients that maintain a production, based on photosynthesis, proportional to their availability. Through the use of EDTA as a chelating agent of metal cations, the increase in the production of the plants was determined and in this way the presence of an inhibition factor was revealed. Although coliform levels were high in all samples, we conclude that their presence is not from human origin, but of ducks and small mammals that normally inhabit the urban forest. We recommend conducting microbiological studies of groundwater to confirm the natural origin of coliforms. Likewise, it is recommended that studies be implemented to characterize the nature of the inhibiting agent that we have detected. Finally, it is recommended that the administrative authority of the Urban Forest manage funds for the dissemination and preservation of La Culebra stream as a subject of high environmental and cultural value in the GMA.
The Suppressive role of Nanoencapsulated Chia oil against DMBA-induced breast cancer through oxidative stress repression and tumor genes expression modulation in rats
Authors: makawy Aida El , Mabrouk Dalia M , Mohammed Shaimaa E , Abdel-Aziem Sekena H , Kader Heba A M Abd EL , Sharaf Hafiza A , Youssef Dalia A , Ibrahim Faten M 
Published: July 2022

Abstract
Chia oil is high in omega-3 fatty acids, which have been linked to a lower risk of many diseases, including cancer. Oil encapsulation is a promising method for preserving oil content and improving solubility and stability. This study aims to prepare nano-encapsulated Chia oil and explore its suppressive role against chemically induced breast cancer in rats. The oil was extracted from commercial Chia seeds and their fatty acids were analyzed using Gas Chromatography-Mass Spectrometry (GC/MS). The Chia oil nanocapsules were prepared by using sodium alginate as a loading agent. The ability of oil nanocapsules to scavenge free radicals was determined using the DPPH radical scavenging assay. Breast cancer was induced via a single-dose subcutaneous injection of 80 mg/kg dimethylbenz(a)anthracene (DMBA). Breast cancer models were orally treated with Chia oil nanocapsules at doses of 100 & 200mg/kg for one month. The suppressive effect of Chia oil nanocapsules was investigated through estimation of intracellular reactive oxygen species (ROS) and protein carbonyl, gene expression of tumor suppressor genes (BRCA 1 & 2, TP53) evaluation, and histopathological analysis. The administration of Chia oil nanocapsules significantly reduced the increase in ROS and PC levels induced in DMBA groups. On the molecular level, the mRNA expression levels of BRCA1, BRCA2, and TP53 were modulated in tumor tissue of rats given Chia oil nanocapsules. According to the histopathological analysis, nanocapsules improved the tissue architecture of breast tumors. These findings demonstrate the ability of Chia oil nanocapsules to inhibit cancer cells in the rat breast.
A Hybrid Visualizing Approach Based on Adaptive Neuro-fuzzy Inference System, Decision Tree, and K-means for Intrusion Detection
Authors: Liu Jia , Yinchai Wang , Siong Teh Chee , Li Xinjin , Zhao Liping , Wei Fengrui 
Published: July 2022

Abstract
Intrusion detection is a fuzzy classification problem. Intrusion detection can detect the attack behaviors of hackers in advance. For generating a visualizing architecture for identifying intrusions, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System), DT (Decision Tree), and K-means clustering algorithm for visualizing the deep pattern of intrusion detection. The ANFIS generates complex and fuzzy combinations of selected attributes. To reduce the rules generation of ANFIS, Pearson Correlation analysis is used to select attributes that highly relate to the target. Meanwhile, standard deviation analysis and a proposed adaptive K-means algorithm are used for determining the interval division of selected attributes. Then, the CART (classification and regression tree) is used to identify the deep mode in generated rules and selected attributes. The architecture of the proposed algorithm is a hybrid visualizing approach. The architecture can identify deep and hybrid features in intrusion detection. The proposed algorithm was trained, validated, and tested on the NSL-KDD dataset. Using 22 attributes that highly relate to the target, the performance of the proposed method achieved a 99.86% detection rate and 0.14% false alarm rate, which is better than many classifiers. Besides, the visualizing model can help us visually identify the complex pattern of intrusions and analyze the pattern of various intrusions.
Nighttime Vehicle Detection using Improved CycleGAN
Authors: V Sathananthavathi , K Kandasamy , D Rajamanickam 
Published: July 2022

Abstract
Nighttime Vehicle Detection is the challenging task to be addressed properly in the Automatic Driving System. Detection of oncoming vehicles in time is essential for safe driving in the Automatic Driving System and this task is critical when the lighting condition is deprived. Detecting vehicle in nighttime is based on the high-level features by the automotive system. In order to address the problem of nighttime vehicle detection effectively, image translation by improved Cycle Generative Adversarial Network (GAN) architecture is proposed in this paper. The Cycle Generative Adversarial Network (CycleGAN) is the deep convolution neural network trained in the form of image-to-image translation tasks. Cycle GAN contains two GANs, first GAN is used for night to day translation and second GAN for day to night translation. The proposed improved Cycle GAN architecture is enriched with shallow Unet Generator in the first image translator GAN. Using this architecture, the input night time image is getting translated into day time image and hence supporting to extract high level of features for the vehicle detection module to detect the vehicles with high confidence probability. The proposed architecture is compared with the conventional cycle GAN architecture in terms of the vehicle detection accuracy. From the experimental results, it is observed that proposed improved Cycle GAN can able to detect vehicles in the perplex view condition.
Screening of GDM during COVID pandemic in an Italian setting: comparison between IADPSG and WHO ‘99 criteria
Authors: D'anna Rosario , Benedetto Antonio Di , Palella Stefania , Miceli Alessia , Romeo Paola , Corrado Francesco 
Published: July 2022

Abstract
Background: During pandemic period, a single fast glycemia value (≥ 92 mg/dl) performed within the recommended time windows for the risk level defined by the Italian guidelines, was considered an acceptable surrogate for GDM diagnosis following Italian Diabetes Association recomendations.Methods: All pregnant women who performed an OGTT following Italian Guidelines from march 2020 to september 2021 and then delivered at our University Hospital were prospectively enrolled in this study. Primary outcome of the study was the number of women to whom was diagnosed GDM with only the fasting glucose value (≥ 92 mg/dl), following Italian Diabetes Societies recommendations for COVID 19 pandemic period. In the same time, the data of women who became diabetic following the criteria of WHO 1999 was collected too. Secondary outcome was the comparison of risk factors and clinical outcomes between women diagnosed with IADPSG criteria and those diagnosed with WHO ’99 criteria.Results: The number of women with a diagnosis of GDM following Italian guidelines in the 18-month period considered was 161. Only 109 (67.7%) had a fast glucose value ≥ 92 mg/dl. No difference between IADPSG and WHO ’99 groups in relation to risk factors, with the exception for overweight and obesity, and clinical outcomes,Conclusion: Recommendations of Italian Diabetes Societies for COVID 19 pandemic failed to recognize one third of GDM diagnosis.CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, www.clinicaltrials.gov, NCT 05026840, August 30, 2021, 'retrospectively registered'.
Protective effect of rosiglitazone on microscopic and oxidative stress parameters of ram sperm after freeze-thawing
Authors: Mehdipour Mahdieh , Daghigh-Kia Hossein , Najafi Abouzar , Mehdipour Zohreh , Mohammadi Hossein 
Published: July 2022

Abstract
The purpose of this study was to investigate the effects of rosiglitazone on ram semen after cryopreservation on the quality of thawed sperm. Sperm motility (CASA), membrane integrity (HOS test), viability, total abnormality, PSA, mitochondrial activity (Rhodamine 123), reactive oxygen species production, ATP content and apoptotic features (Annexin V/Propidium iodide) were assessed after thawing. Rosiglitazone at concentration of 60 µM resulted in the highest (P < 0.05) total motility, progressive motility and VSL. The percentage of VAP and VCL was greater in the 60 µM group. Different concentrations of rosiglitazone did not have significant effects on ALH, LIN and STR. The highest amount of membrane functionality and mitochondrial activity after freeze-thawing were observed in groups containing 60 µM. The lowest ROS concentration was recorded in 60 µM rosiglitazone group (P<0.05). The percentage of viable sperm was significantly the highest in 60 µM rosiglitazone (P < 0.05). The group containing 60 µM rosiglitazone also produced the lowest significant percentage of apoptosis-like changes and dead sperm. A greater (P ≤ 0.05) percentage of acrosome integrity in frozen-thawed spermatozoa was observed in the 60 µM rosiglitazone group. The result showed that supplementation in ram semen extender with rosiglitazone had a positive role in the regulation of ram sperm motility and had strong protective effect on the sperm membrane and acrosome integrity
Histologic evaluation of the healing potentiality of the human treated dentin matrix scaffold as direct pulp capping material
Authors: Saeed Mahmoud , Grawish Mohammed E. 
Published: July 2022

Abstract
Aim
Find a reasonable substitution for current DPC materials.
Methods
The hTDM properties were evaluated by assessing its alkalinity, antibacterial activity, and potentiality to induce cell migration compared to MTA. The acute inflammatory response was evaluated 3 days after iatrogenic pulp exposure by histological examination. However, both chronic inflammatory response and dentin-pulp complex regeneration were evaluated after 3 months.
Results
The results of in vitro assessment revealed high alkalinity of MTA while hTDM exhibited optimum alkalinity. Moreover, the higher antibacterial activity and potentiality of inducing cell migration than MTA. The in vivo assessment ensured the ability of hTDM in optimizing the inflammatory response and dentin-pulp complex regeneration. However, MTA prolonged the inflammatory response and induced the formation of a thick calcific bridge toward the pulp tissue.
Conclusion
hTDM semi-rigid scaffold is a promising novel DPC material.
Exploring race and gender as a conduit to STEM disciplines via decolonial intersectionality theory
Authors: Bayaga Anass 
Published: July 2022

Abstract
In the past decade, motivational pathways influencing all disciplines or career choices through various theories/models is on the rise. Regardless, race and gender within the domain of science, technology, engineering, and mathematics (STEM) is disproportionately researched. The disproportionality is particularly true in comparison with other races and gender. Undoubtedly, whilst there is the need to bridge the disparity, ongoing research is leaning towards under-examining the extent to which the intersection of race and gender identities influence the experiences of various racial and genders’ access, opportunity, and success to STEM disciplines. In reaction to such crucial discourse, the current study is in part motivated by the dearth of scholarship. Consequently, and through case study by sampling 15 respondents, the aim was to examine the multifaceted marginalisation of various racial and genders’ experiences in STEM disciplines. Using decolonial intersectionality as a theoretical lens, the data from the participants’ exposed not only academic challenges but concurrently one that reflects a social and institutional barrier. The study revealed persistent presence of race and gender challenges in the pursuit of STEM discipline. While previous studies established the increase of racism in primary, secondary, and postsecondary education, the current study however, illustrates uncontrolled position of the racialised and gendered experiences of STEM aspirants. However, the theoretical contribution following the application of intersectionality provides the grounds for further examination of identity among underrepresented groups. The data from the current study reinforces the correlation between career interests and the possibility of pursuing STEM career.
Identification of essential genes and drug discovery in bladder cancer and inflammatory bowel disease via text mining and bioinformatics analysis
Authors: Zheng Qingyuan , Guo Liantao , Yang Rui , Ni Xinmiao , Yang Song , Wang Lei , Chen Zhiyuan , Liu Xiuheng 
Published: July 2022

Abstract
Background: Bladder cancer (BCa) is the most common malignancy of the urinary system. Inflammation is critical in the occurrence and development of BCa. The purpose of this study was to identify key genes and pathways of inflammatory bowel disease in BCa through text mining technology and bioinformatics technology, and to explore potential therapeutic drugs for BCa.Methods: Genes associated with BCa and Crohn's disease (CD) were detected using the text mining tool GenClip3, and analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape, and modular analysis was performed using the Molecular Complex Detection plugin (MCODE). Finally, the genes clustered in the first two modules were selected as core genes, and the drug-gene interaction database was used to discover potential therapeutic drugs.Results: We identified 796 genes shared by "Bladder cancer" and " Crohn's disease " by text mining. Gene function enrichment analysis yielded 18 enriched GO terms and the 6 most relevant KEGG pathways. A PPI network with 758 nodes and 4014 edges was constructed, and 20 gene modules were obtained using MCODE. We selected the top two gene clusters as core candidate genes. We found that 3 out of 55 selected core genes could be targeted by 26 existing drugs.Conclusions: The results indicated that CXCL12, FGF2 and FSCN1 are potential key genes involved in CD with BCa. Additionally, 26 drugs were identified as potential therapeutics for BCa treatment and management.
Machine Learning Models and New Computational Tool for the Discovery of Insect Repellents that Interfere with Olfaction
Authors: Pulgar-Sánchez Mary , Marrero-Ponce Yovani , Hernández-Lambraño Ricardo , García-Jacas César R. , Martinez-Rios Felix 
Published: July 2022

Abstract
Disease vector insects rely on chemosensors to locate hosts, find mates and choose where to lay their eggs. Currently, the most efficient method of preventing and controlling the outbreak of insect-borne diseases is the use of Insect Repellents (IRs). However, current IRs have significant drawbacks and do not meet the necessary conditions, such as protecting a broad spectrum of mosquitoes; many have unpleasant odors or produce unpleasant sensations on the skin. Some of them are even carcinogens. Therefore, the need for new, more effective, safer, and longer-lasting broad-spectrum IRs than conventional IRs is evident. Here, classifiers for predicting IRs will be developed using QuBiLS-MIDAS 3D-molecular descriptors and shallow machine learning techniques. We intend to introduce, the ability of QSAR (Quantitative Structure-Activity Relationships) models to describe the interaction of IRs with the olfactory response of the six sensilla of the mosquito Culex quinquefasciatus as well as with repellent activities by using four datasets that take into consideration the two most relevant IR scaffolds: carboxamides and plant-derived compounds with repellent effect on A. aegypti and also A. gambiae and the two most common species of cockroach (Blattella germanica and Periplaneta americana). A non-commercial and cross-platform software, named “SiliS-PAPACS” is developed for the IRs-prediction (http://tomocomd.com/apps), in which all the best models developed are implemented. This software is used to screen datasets containing diverse chemotypes like chemicals and/or FDA-approved drugs, like Malaria box library. From that virtual screening, we report 28 novel virtual leads (new IR chemical scaffold) that may have potential IR activity. The results suggest that the proposed method will be an excellent computer-assisted system that could increase the chance of finding new insect control agents and assist those researchers in screening and/or designing new chemotype IRs.
Pyramidal-Relative Entropy Based Temporal Signature for Video Transition Detection using LSTM
Authors: .A Sasithradevi , Roomi Mohamed Mansoor , Gupta{} Saurav 
Published: July 2022

Abstract
Video transition detection (VTD) is a significant topic in the field of video analytics, owing to its useful applications in video indexing, video surveillance, and video understanding. The challenge in VTD is to extract the complex temporal variations caused by the change in illumination, rapid motion of object and camera. To address these challenges, a pyramidal-relative en-tropy based long-short term memory (LSTM) framework is proposed. Initially, the uncompressed video frame is modeled using pyramidal attributes. Then, the temporal signature is generated based on forward-backward ratio of relative entropy measure. The LSTM network is trained to detect the transitions through temporal signature and categorizes them as no transition, abrupt transition and gradual transition. Benchmarks namely TRECVID 2001, TRECVID 2007, VIDEO-SEG2004, RAI and BBC data-sets have been used in evaluation assessments. The simulation results illustrate the efficacy of the proposed framework to achieve an average F 1 score of 95.5±0.06%, 98.51±0.79%, 97.5 ±2.6%, 93.54±5.03%, and 97.58±1.89% on TRECVID 2001, TRECVID 2007 VIDEOSEG 2004, RAI and BBC data-sets, respectively.
Whole-tissue Mapping of &gt;5000 proteins by Micro-scaffold Assisted Spatial Proteomics(MASP)
Authors: Ma Min , Huo Shihan , Zhang Ming , Qian Shuo , Zhu Xiaoyu , Pu Jie , Rasam Sailee , Xue Chao , Shen Shichen , An Bo , Wang Jianmin , Qu Jun 
Published: July 2022

Abstract
Quantitative protein mapping on whole-tissue levels provides important insights into the spatially-organized regulatory processes/networks related to diseases and therapy, but remains a tremendous challenge. We describe a micro-scaffold assisted spatial proteomics(MASP) method, based on precise tissue spatial-compartmentalization using a 3D-printed micro-scaffold, capable of mapping thousands of proteins across a whole-tissue slice with excellent quantitative quality. The mapping accuracy was validated and applied in mapping > 5,000 cerebral proteins in mouse brain.