bluuebunny/crossref_metadata_2025 huggingface dataset:
Observations on 25 Years of Cannabis Law Reforms and Their Implications for the Psychedelic Renaissance in the United States
Authors: Mikos Robert A.
Published: April 2022

Interest in psychedelics is booming, heralding a possible psychedelic renaissance in the United States. But policy makers interested in expanding access to psychedelic substances would be wise to heed lessons gleaned from the past 25 years of marijuana law reforms. That experience suggests that it may prove impossible to repeal or narrow the federal ban on psychedelics in the near term, but that states provide an alternative pathway to reform. Still, to blunt the risk of a federal crackdown, policy makers may need to sacrifice certain policy goals. Furthermore, until the public warms to a broader psychedelic renaissance, policy makers may pursue narrow reforms. Policy makers will also need to address thorny questions over how psychedelics will be supplied once legalized.
Brittle Solids: From Physics and Chemistry to Materials Applications
Authors: Lawn Brian R. , Marshall David B.
Published: April 2022

Hard solids with predominantly covalent–ionic bonding are finding rapidly increasing usage in many modern technologies. However, this class of solids is severely limited by their intrinsic brittleness—they break easily. It is in this context that a fundamental knowledge of brittle fracture mechanisms is of practical importance. This review covers the essential features of crack behavior in characteristically brittle solids, starting with fundamental physical and chemical models, with distinctions between equilibrium and kinetic states, stability and instability, and crack propagation and initiation. Means of imparting higher strength and toughness to otherwise brittle materials are then explored along with their pros and cons. Select technological areas where fracture properties constitute a vital facet of material function—windows and display panels, structural ceramics, biomaterials, layer structures, manufacturing, and nanomechanics—are then presented as illustrative case studies. The balance between factors such as strength and toughness, scaling and threshold effects, and crack containment and crack avoidance, as well as structure at the atomic and microstructural scales, emerge as critical factors in materials design.
The Postoperative Effects of Patellar Eversion in Total Knee Arthroplasty: An Updated Systematic Review and Meta‐Analysis
Authors: Wang Jun , Guo Jian-Bin , Wen Peng-Fei , Zhang Yu-Min , Song Wei , Wang Tao , Ma Tao , Cheng Qian-Yue , Zhang Bin-Fei
Published: April 2022

Background. During total knee arthroplasty (TKA), surgeons mobilize the patella to facilitate clear visualization of the articular surfaces and allow better prosthesis placement. According to the manipulation, this manipulation can be divided into patellar eversion and noneversion. However, the effect of patellar eversion in TKA is controversial, with substantial variability in clinical practice. This systematic review is aimed at assessing the adverse effects of patellar eversion and patellar noneversion duration in TKA. Methods. This updated systematic literature review identified randomized controlled trials comparing patellar eversion and noneversion durations in TKA. Two investigators independently extracted data and evaluated the quality of the studies. A meta‐analysis was performed using RevMan version 5.3. Results. Nine studies with a total of 608 patients (730 knees) were included. Of these, 374 knees were classified in the eversion group and 356 knees in the noneversion group. The quality of the studies was high. The results showed that patellar eversion could increase the postoperative complication rate (relative risk [RR] = 1.67; 95% confidence interval [CI], 1.09–2.54; P = 0.02) and postoperative pain before discharge (mean deviation [MD] = 0.19; 95% CI, 0.04–0.34; P = 0.01), compared to noneversion. Additionally, patellar eversion could prolong the time until the patient is able to raise the leg while straightened (MD = 0.42; 95% CI, 0.24–0.59; P < 0.00001) and increase the length of stay (MD = 0.65; 95% CI, 0.05–1.25; P = 0.03). However, patellar eversion did not influence postoperative pain at 1 year (MD = 0.02; 95% CI, ‐0.23–0.28; P = 0.85), operative time (MD = −2.66; 95% CI, ‐8.84–3.52; P = 0.40), recovery of quadriceps force throughout the follow‐up period, and Insall–Salvati ratio (MD = −0.04; 95% CI, [‐0.11–0.02]; P = 0.23). Conclusions. The patellar eversion could increase the postoperative complication rate and postoperative pain. Current evidence supports the avoidance of patellar eversion in TKA. Further large‐sample and long‐term trials are required to validate these results.
Evaluation Model of English Diagnostic Intelligence Based on Organizational Evolutionary Information Entropy
Authors: Zhang Fuzhuang , Shen Jun
Published: April 2022

We show how to optimize English diagnostic Q matrix based on cognitive diagnostic model fitting method. Firstly, attribute annotation verifies the reliability of existing Q matrix and fitting analysis, as researchers found that they still have the original Q matrix optimization space; secondly, this paper proposes a classification algorithm based on organization evolution and the information entropy of English in the diagnosis of intelligent evaluation algorithm, the running mechanism of the existing evolutionary algorithm, and the evolution of its direct effects on operation data rather than the rule. After the end of evolution, rules can be extracted from each organization to avoid meaningless rules in the process of evolution. According to the characteristics of the classification problem, we put forward three kinds of evolutionary operators and a selection mechanism, which is presented based on the information office of the evolution of the way of attribute importance. Based on this definition, the organizational fitness function, and finally the algorithm used in six test data sets and compared with the existing two classification methods, the experimental results show that the method obtained the higher forecast accuracy, and smaller rule sets are produced. Finally, a matching combination and quantitative fitting screening based on G-DINA measurement model were decomposed and analyzed, and a better fitting model was optimized based on the original Q matrix model. The results show that, first, the optimized new model is better than the original model in relative data fitting value and interpretation and diagnosis of fractional variation; second, the new model has a higher correlation with the results of self-evaluation, indicating that the probability of the new model is closer to the results of self-evaluation.
Design and Implementation of Obstetric Central Monitoring System Based on Medical Image Segmentation Algorithm
Authors: Zhang Yuanyuan , Nie Hua
Published: April 2022

At present, the incidence of emergencies in obstetric care environment is gradually increasing, and different obstetric wards often have a variety of situations. Therefore, it can provide great help in clinical medicine to give early warning and plan coping plans according to different situations. This paper studied an obstetrics central surveillance system based on a medical image segmentation algorithm. Images obtained by central obstetrics monitoring are segmented, magnified in detail, and image features are extracted, collated, and trained. The normal distribution rule is used to classify the features, which are included in the feature library of the obstetric central monitoring system. In the gray space of the medical image, the statistical distribution of gray features of the medical image is described by the mixture model of Rayleigh distribution and Gaussian distribution. In the gray space of the medical image, Taylor series expansion is used to describe the linear geometric structure of medicine. The eigenvalues of Hessian matrix are introduced to obtain high-order multiscale features of medicine. The multiscale feature energy function is introduced into Markov random energy objective function to realize medical image segmentation. Compared with other segmentation algorithms, the accuracy and sensitivity of the proposed algorithm are 87.98% and 86.58%, respectively, which can clearly segment small medical features.
Research on Automatic Intelligent Coloring of Animation Sketch Based on Enhanced Deep Learning
Authors: Wang Zhe
Published: April 2022

An automatic intelligent coloring model of animation sketch based on enhanced deep learning is proposed. In the proposed model, generative adversarial networks (GANS) are adopted. The U-net network based on the Swish function residual enhancement is used in the generative model, and the ResNet network is used in the discriminant model. The U-net embedded with the Swish Gate module is adopted to transmit feature map information. The perceptual network on the discriminator is used to perceive the perceptual features of the generated image and the actual image and calculate the perceptual loss. Experiment results show that perceptual loss can better capture the difference between black-and-white images and color images, so as to better train the network end-to-end. After comparative analysis, it can be concluded that compared with the existing methods, the proposed model has greater advantages in processing animation sketches. The color images it generates have higher visual quality and richer color diversity and matching.
The Effects of Ticagrelor Combined with Tirofiban on Coagulation Function, Serum Myocardial Injury Markers, and Inflammatory Factor Levels in Patients with Acute Myocardial Infarction after Percutaneous Coronary Intervention
Authors: Li Fang , Wang Shuhui , Wang Lei , Liu Feng , Meng Zhen , Liu Jia
Published: April 2022

Background. Acute myocardial infarction (AMI) refers to the acute necrosis of part of the myocardium caused by persistent and severe myocardial ischemia. This study is aimed at investigating the efficacy of tirofiban combined with ticagrelor in AMI patients after percutaneous coronary intervention (PCI) and its effects on plasma activated partial thromboplastin time (APTT), fibrinogen (FIB), D-dimer (D-D) levels, myocardial injury markers, and inflammatory factors. Methods. 68 AMI patients with AMI who received PCI were divided into control group and observation group (n =34) according to postoperative treatment methods. Both groups received ticagrelor tablets (90 mg). The observation group was additionally given tirofiban (10 μg/kg). APTT, FIB, D-D, serum myoglobin (MB), cardiac troponin I (cTnI), serum C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and IL-6, myeloperoxidase (MPO) levels and the peak time in both groups were detected. The incidence of cardiovascular events and drug safety were compared. Results. After treatment, APTT was increased, and FIB and D-D levels were decreased in both groups. After treatment, the APTT in the observation group was longer, and FIB and D-D levels were lower than those in the control group. The peak time of serum MB and cTnI in the observation group was earlier than that in the control group. The levels of serum MB and cTnI in the observation group were lower than those in the control group. After treatment, serum CRP, TNF-α, IL-6, and MPO levels were decreased. And the incidence of cardiovascular events was reduced. Conclusion. Tirofiban combined with ticagrelor can improve coagulation function, protect myocardium, relieve inflammation, and reduce the risk of cardiovascular events in patients with AMI after PCI.
Harmful Consequences of Proton Pump Inhibitors on Male Fertility: An Evidence from Subchronic Toxicity Study of Esomeprazole and Lansoprazole in Wistar Rats
Authors: Mumtaz Namra , Akhtar Muhammad Furqan , Saleem Ammara , Riaz Amjad
Published: April 2022

Proton pump inhibitors (PPIs) are frequently prescribed as gastric acid-suppressing agents. Nevertheless, there is limited evidence supporting the risk of detrimental effects of PPIs on male fertility. The purpose of the current study was to evaluate the effect of subchronic use of proton pump inhibitors on male fertility. Seventy adult male Wistar rats were assigned into seven groups. The normal control group orally received solvent only. Groups 2, 3, and 4 were orally given esomeprazole while groups 5, 6, and 7 received lansoprazole at 2.5, 5, and 10 mg/kg/day, respectively. After 45 days of treatment, blood samples, epididymis, and testis were collected. Sperm count, motility, and morphology were determined. The level of hormones such as testosterone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) and oxidative status of testis tissue, such as superoxide dismutase, catalase, reduced glutathione, malondialdehyde (MDA), and nitric oxide (NO) were estimated. Results demonstrated a significant decline in sperm count, motility, morphology, testosterone, and catalase at 10 mg/kg/day and GSH at 2.5 mg/kg/day. A significant increase in FSH, LH, and MDA at 10 mg/kg/day and NO at 2.5 mg/kg/day was found as compared to the control group. The pathological alterations specifically dilation of Leydig cells, vacuolization, and degeneration of the seminiferous tubules were also evident. It is concluded that PPIs had caused male reproductive toxicity in Wistar rats due to altered levels of hormones such as testosterone, FSH, and LH, elevated levels of NO, and oxidative stress.
A Pest Intrusion Detection in Chinese Beehive Culture Using Deep Learning
Authors: Liu Chao , Lin Shouying
Published: April 2022

At present, the quality of material life and richness of the Chinese residents have been improved. Some people have high requirements for quality of their personal lives and put forward the problem of health preservation. Honey, as a nutritious food, is deeply loved by people. There are a large number of trace elements in honey, such as VC, VA, VD, VB1, and VB2. The honey from the Chinese honeybee has a very high nutritional value and plays an important role in the pollination and reproduction of some plants. Therefore, the Chinese honeybee plays a very significant role in the ecological environment. Moreover, it is protected as the main species resource of the country, which also fully proves the importance of the Chinese honeybee. Chinese bees can survive in various ecological and geographical environments in China and have strong heat as well as cold resistance. They can survive in the hot environment in the south and withstand the dynamics of severe cold in the north. At the same time, they can make full use of a small number of honey sources and have strong resistance to a variety of diseases and pests. In fact, there will be a variety of insect invasion problems in the beehive culture of Chinese bees, and it is necessary to accurately detect various diseases and pests during the breeding of Chinese bees. However, there are a large amount of insect invasion and various disease sources in the breeding stage of the Chinese bees. Therefore, in this paper, we use a deep learning algorithm to detect the insect invasion of the Chinese beehive culture and analyze the bee colonies in six bee farms in the province of Sichuan. In addition, we measure the common insect and disease indexes of the Chinese bee and analyze the parasitism rate, microsporidia infection rate, virus infection rate, and virus infection titer of bee colonies in overwintering and spring breeding. The experimental results show that the anti-insect invasion situation of bees in the six bee farms is significantly different; however, the antimite ability is basically the same.
Construction and Application of Enterprise Internal Audit Data Analysis Model Based on Decision Tree Algorithm
Authors: Si Yuna
Published: April 2022

With the systematization, informatization, and intelligence of the management and operation of communication enterprises, the amount of audit content and business data is increasing. The traditional audit work is mainly offline audit, the task is heavy and temporary, there are few auditors, and there is a lack of unified data mart and analysis model support. In order to solve many problems in traditional auditing, this paper realizes the interface of data dictionary attributes through effective domain management of multisystem data, so as to achieve the purpose of system support and effective management to improve data quality. Furthermore, the platform is extensible, which can gradually expand the data coverage and support more management fields and business systems. A method of obtaining continuous attribute clustering center points by K‐means algorithm and using triangular fuzzy numbers to fuzzify process continuous data is proposed. At the same time, a visual fuzzy decision‐making system based on Fuzzy ID3 and Min‐Ambiguity algorithm was designed. Adding the C4.5 and CART algorithms implemented in the Weka open source data mining software, through experimental analysis, the differences in the classification accuracy and the number of rules generated by the four decision tree algorithms are compared. The experiment found that the Fuzzy ID3 algorithm has a high accuracy rate on each dataset and the number of rules is large. The number of rules generated by the CART algorithm is the least because of the model characteristics of its binary tree and the characteristics of using the Gini index as the criterion for the selection of splitting attributes. Comparing Fuzzy ID3 and Min‐Ambiguity fuzzy decision tree algorithms, it is found that the overall performance of the former is better than that of the latter, and the effect of authenticity on the two algorithms is analyzed experimentally. This paper constructs the internal audit flowchart in the big data environment and studies the optimization of the internal audit process in the big data environment. We evaluate traditional internal audit processes using process optimization theory. The internal audit process in this paper refers to the internal audit process under the risk‐oriented model that is widely used at this stage. The optimization research on the internal audit process in this paper is mainly aimed at the internal audit process of general enterprises with a certain level of informatization, at a large scale, and certain foundation and requirements for the analysis and use of data. The optimization of internal audit process is feasible in research and practical application and has universal applicability and reference value.
Recognition of Immune Cell Markers of COVID‐19 Severity with Machine Learning Methods
Authors: Chen Lei , Mei Zi , Guo Wei , Ding ShiJian , Huang Tao , Cai Yu-Dong
Published: April 2022

COVID‐19 is hypothesized to be linked to the host’s excessive inflammatory immunological response to SARS‐CoV‐2 infection, which is regarded to be a major factor in disease severity and mortality. Numerous immune cells play a key role in immune response regulation, and gene expression analysis in these cells could be a useful method for studying disease states, assessing immunological responses, and detecting biomarkers. Here, we developed a machine learning procedure to find biomarkers that discriminate disease severity in individual immune cells (B cell, CD4+ cell, CD8+ cell, monocyte, and NK cell) using single‐cell gene expression profiles of COVID‐19. The gene features of each profile were first filtered and ranked using the Boruta feature selection method and mRMR, and the resulting ranked feature lists were then fed into the incremental feature selection method to determine the optimal number of features with decision tree and random forest algorithms. Meanwhile, we extracted the classification rules in each cell type from the optimal decision tree classifiers. The best gene sets discovered in this study were analyzed by GO and KEGG pathway enrichment, and some important biomarkers like TLR2, ITK, CX3CR1, IL1B, and PRDM1 were validated by recent literature. The findings reveal that the optimal gene sets for each cell type can accurately classify COVID‐19 disease severity and provide insight into the molecular mechanisms involved in disease progression.
Depression Identification of Students Based on Campus Social Platform Data and Deep Learning
Authors: Zhao Guang Feng , Sun Lin Fang
Published: April 2022

Depression is one of the most common psychological problems faced by human society. Because of less social experience, low psychological endurance, and the multiple responsibilities of future families and society, college students have become one of the most vulnerable groups to suffer from depression. This paper explores an automatic identification method to identify patients with early depression tendency through deep mining of online information of campus social platform users. First, we comprehensively analyze the common characteristics of emotion and behavior on the campus social platform for depression. Secondly, the experimental corpus is formed by preprocessing operations such as deprivation, word segmentation, and denoising of the original data. Finally, the depression recognition is transformed into a text classification problem, and a shallow support vector machine and a deep convolutional neural network model are, respectively, constructed based on the experimental corpus. Combined with the features of depression blog, the algorithm was further improved, and a dual-input convolutional neural network algorithm compatible with multiple features was proposed. The experiments showed that the recognition rate was effectively improved.
Study on the Antifatigue Effect of Compound Amino Acid Capsules
Authors: Huang Wen , Hui Huaqiang , Xu Jiping , Guo Honglei , Wang Yunfeng , Zhu Wei
Published: April 2022

Supplementing amino acids was proven to relieve fatigue caused by exercise. This study explored the antifatigue effects of compound amino acid capsules (CAAC) on rats undergoing the forced swimming test (FST). CAAC augmented the endurance of FST in rats and alleviated the damage of skeletal muscle tissue and reduced the content of biochemical indicators in the serum. Furthermore, CAAC prevented skeletal muscle dysfunction in FST rats by modulating inflammation and oxidation reactions. After the treatment with CAAC, apoptosis and apoptosis-related protein and p-p65 were weakened, while the levels of SIRT1 and SIRT1/PGC-1α/Nrf2 pathway-related proteins were enhanced. The antifatigue properties of CAAC were associated with its antioxidant and anti-inflammatory capabilities, which were realized by activating the SIRT1/PGC-1α/Nrf2 pathway.
Post-Veraison Water Stress and Pruning Level on Merlot Grapevine (Vitis vinifera L.): Effects on Berry Development and Composition
Authors: Berhe Dargie Tsegay
Published: April 2022

The grapevine berry development and composition at harvest are major determinant of productivity and wine quality. The increase in grapevine productivity by applying proper pruning and watering may affect fruit traits of the grapevine development notably berry size, weight, and volume as well as the berry composition mainly the total soluble solids (TSSs), titratable acidity (TA), pH of the grapes, total anthocyanins, and phenolic content and concentration. In this context, this study aimed to explore the response of berry development and composition to the interactive effect of pruning level and post-veraison water stress. Four pruning levels (severe, standard, light, and minimal) in combination with four post-veraison water stresses (none, light, moderate, and intense) were tested. The interactive effect of pruning level and post-veraison water stress has significantly altered all parameters, except berry weight which was influenced by the main effect of the two factors. Generally, post-veraison water stress reduced berry volume, weight, yield, and TA, but increased the TSS, pH, total anthocyanins, and phenols. Increasing in the pruning level also reduced berry yield per vine, TSS, and pH, but increased the berry volume, weight, TA, total anthocyanins, and phenols. Specifically, the highest berry volume, weight, and TA were registered in severely pruned grapevines with adequate water supply. Conversely, the minimally pruned grapevines with intense water stress had the highest TSS and pH of grape juice. The total anthocyanins and phenols were advanced by the increment from minimal to severe pruning levels but depressed when the water stress extended from none to an intense level. In the other hand, the maximum total anthocyanins and phenols in terms of concentration and content were observed in severely pruned grapevines under intense water stress. Interestingly, higher berry yield per grapevine was scored in minimally pruned grapevines with adequate water supply, possibly due to the increased number of nodes per vine. TSS had a strong negative relationship with berry volume, weight, yield, and TA, while pH had a strong positive relationship with TSS. Total anthocyanins and phenols were also inversely correlated with berry yield per grapevine. The results showed that the combined effect of pruning levels and water stress is a powerful tool to balance berry development and composition. As Merlot is a typical red wine grapevine, it is important to increase the berry composition even though there could be a reduction in its berry development variables including berry yield per vine.
Synchronous Gastric Adenocarcinoma and Diffuse Large B-Cell Lymphoma in the Pelvis: A Rare Case Presentation
Authors: Pliakou Evangelia , Lampropoulou Dimitra-Ioanna , Soupos Nikolaos , Aravantinos Gerasimos
Published: April 2022

Multiple primary cancer (MPC) is defined as more than one primary tumour diagnosed at the same patient, either simultaneously or sequentially. Its incidence is low and varies in reporting among medical centers. Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) while gastric cancer (GC) is the fifth most frequently diagnosed malignancy. The aim of this article is to present a rare case of a female patient who was diagnosed with two synchronous malignancies, an adenocarcinoma of the stomach (SRCC) and an aggressive extranodal NH lymphoma (DLBCL) within 2 months. Given the fact that there is an expanding availability of more sensitive diagnostic and screening methods, we aim to increase surveillance amongst medical doctors and provide valuable information for further systematic analysis and identification of such rare cases of concurrent malignancies.
Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater
Authors: Alhothali Areej , Khurshid Hifsa , Mustafa Muhammad Raza Ul , Moria Kawthar Mostafa , Rashid Umer , Bamasag Omaimah Omar
Published: April 2022

This study was aimed at evaluating the artificial neural network (ANN), genetic algorithm (GA), adaptive neurofuzzy interference (ANFIS), and the response surface methodology (RSM) approaches for modeling and optimizing the simultaneous adsorptive removal of chemical oxygen demand (COD) and total organic carbon (TOC) in produced water (PW) using tea waste biochar (TWBC). Comparative analysis of RSM, ANN, and ANFIS models showed mean square error (MSE) as 5.29809, 1.49937, and 0.24164 for adsorption of COD and MSE of 0.11726, 0.10241, and 0.08747 for prediction of TOC adsorption, respectively. The study showed that ANFIS outperformed the ANN and RSM in terms of fast convergence, minimum MSE, and sum of square error for prediction of adsorption data. The adsorption parameters were optimized using ANFIS-surface plots, ANN-GA hybrid, RSM-GA hybrid, and RSM optimization tool in design expert (DE) software. Maximum COD (88.9%) and TOC (98.8%) removal were predicted at pH of 7, a dosage of 300 mg/L, and contact time of 60 mins using ANFIS-surface plots. The optimization approaches showed the performance in the following order: ANFIS-surface plots>ANN-GA>RSM-GA>RSM.
lncRNA STAT4-AS1 Inhibited TH17 Cell Differentiation by Targeting RORγt Protein
Authors: He Hanlin , Qiu Xiangjie , Qi Mingming , Bajinka Ousman , Qin Ling , Tan Yurong
Published: April 2022

Objective. From our previous study, we obtained long noncoding RNA (lncRNA) STAT4-AS1, which is related to asthma through high-throughput screening. However, we could not determine the specific mechanism involved and in response to this. We further designed this study. Results. First, we found that lncRNA STAT4-AS1 was downregulated in T cells from patients with asthma when compared to healthy controls. Next, we confirmed that lncRNA STAT4-AS1 was significantly negatively correlated with T helper 17 (TH17) differentiation in vitro experiments. The decreases of STAT4-AS1 promoted TH17 differentiation, while the increases of STAT4-AS1 inhibited TH17 differentiation. Subsequently, through RNA pull-down, RNA-binding protein immunoprecipitation (RIP), and dual luciferase reporter assay, we found that STAT4-AS1 could inhibit the binding of retinoid-related orphan receptor-γt (RORγt) protein with an IL-17A promoter after binding with RORγt protein. Fluorescence in situ hybridization (FISH) and nuclear-cytoplasmic separation assay showed that STAT4-AS1 is bonded to RORγt in the cytoplasm, preventing RORγt from entering the nucleus. Conclusion. Overall, STAT4-AS1 directly targets RORγt protein, inhibits the mutual binding of RORγt and IL-17 gene promoter, and eventually inhibits TH17 differentiation. To this end, STAT4-AS1 as a potential target may confer applications in the clinical treatment and diagnosis of TH17-related diseases.
Green Synthesis of Zinc Oxide Nanoparticles from Coriandrum sativum and Their Use as Fertilizer on Bengal Gram, Turkish Gram, and Green Gram Plant Growth
Authors: Ukidave Varada V. , Ingale Lalit T.
Published: April 2022

Plant growth and development rely on various factors, including mineral nutrients. Some are macronutrients like nitrogen, phosphorus, and potassium, whereas some are micronutrients like iron, magnesium, zinc, and a few vitamins. This experimental attempt was to check the stimulatory effect of zinc nanoparticles on pulse plant growth. The study was conducted on the green synthesis of zinc oxide nanoparticles using Coriandrum sativum leaves extract. The characterization of zinc oxide nanoparticles was studied using the X-ray diffraction (XRD), scanning electron microscope (SEM), and transmission electron microscope technique (TEM). The effect of zinc oxide nanoparticles as a fertilizer on pulses plant (Bengal gram, Turkish gram, and green grams) was studied in vitro. The seed germination rate, length of root and shoot, fresh weight, dry weight, and protein and chlorophyll content were measured in different media for assessment of zinc oxide nanoparticle’s growth stimulatory effects. The green synthesis of zinc oxide nanoparticles was confirmed with a size around 100 nm by transmission microscope technique. The germination rate of plants was 100% in MS media and MS media + nanoparticles. The present study found that the root length, shoot length, and weight were higher in MS media + nanoparticles followed by MS media, MS media only with nanoparticles, and MS media without zinc, respectively. It is found that the zinc oxide nanoparticles support seed germination and plant growth and also increase the protein and chlorophyll content. Significantly enhanced growth and development were evident in green gram and Turkish gram compared to that in Bengal gram in media treated with zinc oxide nanoparticles. The protein estimation results showed that the content was higher after 7 days in plants of Bengal gram (1.23 mg/ml), Turkish gram (1.19 mg/ml), and green gram (1.26 mg/ml) than that in roots and shoots. The application of MS media + ZnO nanoparticles results showed that chlorophyll content 12.6 mg/l was observed in other applications in the plant’s seedlings. In contrast, the absence of zinc decreases the germination rate, plant growth, chlorophyll, and protein content. This study confirms that the green synthesis of zinc oxide nanoparticles assessed from Coriandrum sativum leaves holds implication and should function as an active biofertilizer.
Fault Classification with Convolutional Neural Networks for Microgrid Systems
Authors: Pan Prateem , Mandal Rajib Kumar , Rahman Redoy Akanda Md. Mojibur
Published: April 2022

The microgrid (MG) networks require adaptive and rapid fault classification mechanisms due to their insufficient kinetic energy reserve and dynamic response of power electronic converters of distributed generation (DG) systems. To achieve this requirement, this study explores the issues in standalone (SA) and grid-connected (GC) operating modes of MG and develops a near-real-time intelligent disturbance detection and protective solutions for their stable operation. In the proposed approach, an intelligent fault classification mechanism is developed using the advantages of wavelet transform and convolutional neural networks (CNNs). Initially, the voltage and current outcomes for each and every possible fault in the MG network are identified and the wavelet transforms are applied for preprocessing and image conversion. The converted images are identified as scalograms which are further trained with the CNNs. To assess the development of the proposed approach, the IEEE 13 bus system is considered for data gathering. To replicate the real-time behavior of the MG network, the additive white Gaussian noise (AWGN) and additive impulsive Gaussian noise (AIGN) are injected at various levels during the classifier development process. The trained classifier has an average training accuracy of 99.1% for SA MG and 97.7% for GC MG, and the average testing accuracies are 98.9% for SA MG and 97.1% for GC MG.
The Diagnostic and Predictive Significance of Immune-Related Genes and Immune Characteristics in the Occurrence and Progression of IgA Nephropathy
Authors: Qing Jian-Bo , Song Wen-Zhu , Li Chang-Qun , Li Ya-Feng
Published: April 2022

Objective. To investigate the potential diagnostic and predictive significance of immune-related genes in IgA nephropathy (IgAN) and discover the abnormal glomerular inflammation in IgAN. Methods. GSE116626 was used as a training set to identify different immune-related genes (DIRGs) and establish machine learning models for the diagnosis of IgAN; then, a nomogram model was generated based on GSE116626, and GSE115857 was used as a test set to evaluate its clinical value. Short Time-Series Expression Miner (STEM) analysis was also performed to explore the changing trend of DIRGs with the progression of IgAN lesions. GSE141344 was used with DIRGs to establish the ceRNA network associated with IgAN progression. Finally, ssGSEA analysis was performed on the GSE141295 dataset to discover the abnormal inflammation in IgAN. Results. Machine learning (ML) performed excellently in diagnosing IgAN using six DIRGs. A nomogram model was constructed to predict IgAN based on the six DIRGs. Three trends related to IgAN lesions were identified using STEM analysis. A ceRNA network associated with IgAN progression which contained 8 miRNAs, 14 lncRNAs, and 3 mRNAs was established. A higher macrophage ratio and lower CD4+ T cell ratio in IgAN compared to controls were observed, and the correlation between macrophages and monocytes in the glomeruli of IgAN patients was inverse compared to controls. Conclusion. This study reveals the diagnostic and predictive significance of DIRGs in IgAN and finds that the imbalance between macrophages and CD4+ immune cells may be an important pathomechanism of IgAN. These results provide potential directions for the treatment and prevention of IgAN.
Interest of a Kidney Biopsy to Rule out ANCA-Associated Renal Vasculitis in Glomerulonephritis Patients with a Positive ANCA
Authors: Garo Florian , Aglae Cédric , Perrochia Hélène , Ahmadpoor Pedram , Daniel Laurent , Moranne Olivier
Published: April 2022

Kidney biopsy is the gold standard for diagnosing glomerular kidney disease. Some authors debate the necessity of systematically performing kidney biopsies in ANCA-associated vasculitis (AAV) to confirm the diagnosis and assess the severity of renal damage. Nevertheless, kidney involvement is considered an organ-threatening disease requiring an aggressive immunosuppressive regimen. We present a series of 4 cases with a high clinical suspicion of ANCA-associated crescentic glomerulonephritis based on rising serum creatinine, presence of proteinuria and/or hematuria, and presence of ANCA with specificity against PR-3 or MPO. The main diagnosis, however, was arterionephrosclerosis without renal AAV. Certain comorbidities, such as diabetes and/or high blood pressure, can quickly mimic progressive glomerulonephritis. In addition, some patients with AAV do not have high creatinine, proteinuria, or hematuria levels. ANCA alone is not specific to AAV and has a poor positive predictive value. The main concern is to prevent the unnecessary, inappropriate complications of heavy immunosuppression, i.e., serious infections or risk of future malignancies. Kidney pathological confirmation is important in patients with no compatible extra-renal manifestations of AAV or any other possible renal diagnosis such as may be found in polyvascular disease or diabetic patients.
Micropapillary Variant of Urothelial Carcinoma in a Hemodialysis Patient
Authors: Fukuta Kyotaro , Iihara Kiyotaka , Moriyama Takahiro , Nakanishi Ryoichi , Izaki Hirofumi , Kanda Kazuya , Inai Tohru , Kudo Eiji , Fukawa Tomoya , Yamaguchi Kunihisa , Yamamoto Yasuyo , Takahashi Masayuki , Sutou Yasushi , Kanayama Hiro-Omi
Published: April 2022

The micropapillary variant of urothelial carcinoma (MPUC) is an aggressive form of urothelial carcinoma with high metastatic potential and a poor prognosis. Although various therapies have been reported, there is still no established treatment strategy for MPUC due to its rarity. The incidence of urinary tract malignancies is higher in patients undergoing hemodialysis (HD) than in healthy individuals. Here, we report the case of an 82-year-old man on HD with end-stage kidney disease who visited our hospital for macrohematuria. Cystoscopy followed by computed tomography and urine cytology revealed a sessile papillary tumor around the left bladder wall. We performed transurethral resection of the bladder tumor. Based on histopathological and imaging findings indicative of clinical-stage T3N0M0 MPUC, we performed radical cystectomy. Histopathology revealed a pathological stage T4aN0M0 MPUC. Two months after the cystectomy, the patient complained of constipation and painful defecation due to local recurrence and rectal invasion. While colostomy was performed to improve defecation 3 months after cystectomy, he did not receive any chemotherapy due to his progressively worsening general condition. Six months after cystectomy, he died following rapid metastases. Our findings, in this case, confirm that bladder cancer in HD patients tends to be pathologically more advanced. Therefore, regular screening is recommended for its early detection in HD patients.
INHIBITORY EFFECT OF ULIN WOOD LIQUID SMOKE AND GOGO RICE ENDOPHYTIC FUNGI AGAINST PATHOGEN Pyricularia oryzae
Authors: Imaningsih Witiyasti , Mariana  , Junaidi Ahmad Budi , Adventaria Della
Published: April 2022

Diseases in rice plants (paddy) caused by microorganisms such as Pyricularia oryzae lead to a decrease in rice production. Therefore, it is essential to find out biological agents for protecting paddy and plants in general, against plant diseases. Liquid smoke and endophytic fungi have been known as biological agents to enhance the protection of plants against disease. The purpose of this study was to determine the ability of liquid smoke, endophytic fungi and the concentrations combinations to suppress the growth of P. oryzae. The results showed that liquid smoke concentrations of 0.17% to 1.75% and endophytic fungi filtrate of 2% to 10% showed significant ability against pathogen P. oryzae. However, the combination of liquid smoke and endophytic fungi filtrate at selected concentrations (0.17% liquid smoke combined with 2% endophytic fungi filtrate and 0.34% liquid smoke combined with 2% endophytic fungi filtrate) showed no significant inhibition percentage against  P. oryzae compared to control. In conclusion, this study showed that the respective applications of liquid smoke and endophytic fungi filtrate inhibit the growth of P. oryzae.
 
Keywords: endophytic fungi, inhibition ability, liquid smoke, P. oryzae
BIOLOGICAL CHARACTERISTIC OF INDONESIAN GAYO HORSE
Authors: Melia Juli , Amrozi Amrozi , Agil Muhammad , Supriatna Iman
Published: April 2022

This study aims to find out the characteristic of gayo horse and to identify the population of gayo horse. Data collection was conducted through selection process over 100 local horse distributed in Central Aceh Sub-districts, Gayo Lues and Bener Meriah. The result was 30 gayo horses with varying age distribution. Detail observation was performed on six gayo horses of male (n=3) and female (n=3). The observation consisted of morphological observation and morphometry. Data collection of gayo horse population was based on annual report from local Animal Husbandry and Fishery Official over the last 5 years. Result showed that gayo horse has straight cranial shape similar to thoroughbred with smaller size, thick and stiff mane, and ears akin to donkey. Gayo horse body height ranges between 113-120 with body weight ranging around 215-280 kg. Gayo horse is agile despite living in mountain and able to carry heavy weight. There has been drastic decline of population in year 2010-2014. In conclusion, gayo horse is included as large pony category, and without any rescue effort, gayo horse is predicted to be extinct in 2037.
Ceticismo e dogmatismo em Pascal
Authors: Oliva Luís César Guimarães
Published: April 2022

O objetivo deste artigo é comparar a maneira como Pascal trata das relações entre ceticismo e dogmatismo em duas de suas principais obras, os Pensamentos e Conversa com o Senhor de Sacy, as quais, embora não conflitantes, trazem uma relevante mudança de pontos de vista. A Conversa aborda o debate ceticismo/dogmatismo diretamente pelo ângulo moral, de modo que os riscos morais (e as paixões correspondentes de orgulho e preguiça) para os leitores serão o critério fundamental de avaliação das duas filosofias. É igualmente do ponto de vista moral que Epiteto e Montaigne, representantes do dogmatismo e do ceticismo, serão considerados inconciliáveis, visto que a aniquilação recíproca de vícios e virtudes impossibilita a constituição de uma moral perfeita. Nos Pensamentos, o ponto de vista assumido é o da teoria do conhecimento, ainda que se termine o embate no mesmo impasse moral da Conversa. A diferença mais importante, porém, é que os Pensamentos trazem o embate para o interior da natureza humana. Ambas as obras concordam em apontar ao apontar a religião cristã como fonte de explicação para os paradoxos da condição humana.
Myeloid LXR (Liver X Receptor) Deficiency Induces Inflammatory Gene Expression in Foamy Macrophages and Accelerates Atherosclerosis
Authors: Endo-Umeda Kaori , Kim Eunyoung , Thomas David G. , Liu Wenli , Dou Huijuan , Yalcinkaya Mustafa , Abramowicz Sandra , Xiao Tong , Antonson Per , Gustafsson Jan-Åke , Makishima Makoto , Reilly Muredach P. , Wang Nan , Tall Alan R.
Published: April 2022

Background:

Cholesterol loaded macrophage foam cells are a prominent feature of atherosclerotic plaques. Single-cell RNA sequencing has identified foam cells as TREM2 (triggering receptor expressed on myeloid cells 2) positive populations with low expression of inflammatory genes, resembling the TREM2 positive microglia of neurodegenerative diseases. Cholesterol loading of macrophages in vitro results in activation of LXR (liver X receptor) transcription factors and suppression of inflammatory genes.

Methods:

To test the hypothesis that LXRs mediate anti-inflammatory effects in
Trem2
expressing atherosclerotic plaque foam cells, we performed RNA profiling on plaque cells from hypercholesterolemic mice with myeloid LXR deficiency.

Results:

Myeloid LXR deficiency led to a dramatic increase in atherosclerosis with increased monocyte entry, foam cell formation, and plaque inflammation. Bulk cell-RNA profiling of plaque myeloid cells showed prominent upregulation of inflammatory mediators including oxidative, chemokine, and chemotactic genes. Single-cell RNA sequencing revealed increased numbers of foamy TREM2-expressing macrophages; however, these cells had reduced expression of the
Trem2
gene expression module, including phagocytic and cholesterol efflux genes, and had switched to a proinflammatory and proliferative phenotype. Expression of
Trem2
was suppressed by inflammatory signals but not directly affected by LXR activation in bone marrow-derived macrophages.

Conclusions:

Our current studies reveal the key role of macrophage LXRs in promoting the
Trem2
gene expression program and in suppressing inflammation in foam cells of atherosclerotic plaques.
Abstract 12015: Inflammation of SARS-CoV2-infected Human Pluripotent Stem Cell-Derived Cardiomyocytes and the Effects and Side Effects of Remdesivir
Authors: Kim Sangsung , Kim Minwoo , Park In Ho , Bae SeongHo , Keivan Zandi , Yang Eun-Jeong , Cho Kyuwon , Cho Sung-Rae , Kohler James , Kim Baek , Schinazi Raymond F , Oh Jong-Won , Shin Jeon-Soo , Yoon Young-sup
Published: April 2022

Introduction:
The global pandemic of the coronavirus 2019 disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In addition to respiratory failures, COVID-19 patients exhibited cardiac complications. Studies observed the direct infection and replication of SARS-CoV2 in human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) accompanied by cytopathic effects. However, the underlying mechanisms of SARS-CoV-2-mediated CM death remain poorly understood. In addition, the therapeutic potential of remdesivir (RDV) on CMs has yet to be answered.

Methods and Results:
We confirmed that SARS-CoV-2 is infectious to and effectively replicates in hPSC-CMs and is cytopathic to hPSC-CMs. We also found that RDV effectively inhibited viral replication at a concentration of 50 nM. RNA-seq analyses demonstrated that expression of immune responsive genes was elevated in SARS-CoV-2 infected hPSC-CMs. Immunostaining and an ELISA assay further revealed formation of inflammasomes and secretion of inflammasome-mediated cytokines, such as IL-1β, IL-18, and IL-6 in SARS-CoV-2 infected hPSC-CMs. RNA-seq analyses showed gene profile changes in SARS-CoV-2 infected hPSC-CMs corroborating with activation of inflammatory signals and cell death pathways. While gene profiles of 0.1 μM RDV-treated SARS-CoV-2-infected hPSC-CMs showed reversal of such changes, a high dose (10 μM) RDV-treated CoV-2-infected hPSC-CMs showed changes in 44% of genes expressed compared to non-RDV-treated CoV2-infected hPSC-CMs. Among those, expression of protein stability related genes, such as genes associated with autophagy and protein ubiquitination increased while expression of antiviral responsive genes decreased. In addition, a high dose of RDV inhibited expression of mitochondrial genes, particularly MitoComplex I and V compositions, which are related to energy production.

Conclusions:
This study demonstrates that SARS-CoV2 induced inflammasome in hPSC-CMs, which can underlie cardiac damage in addition to direct cytopathic effects. In addition, RDV can reduce inflammasome when introduced early after SARS-CoV2 infection while a high-dose can aggravate cytopathic effects by potential toxicity to mitochondria.