Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Analysis of Natural Free Estrogens and Their Sulfate Conjugates in Wastewater

Natural estrogens from humans increasingly attract attention because of their strong endocrine disrupting potency. The discharge of sewage water is considered as the most important source of these endocrine disrupting chemicals (EDCs) in the environment. Therefore, a GC-MS method was developed for the simultaneous analysis of six natural free estrogens and their sulfate conjugates in municipal wastewater, in which natural free estrogens and sulfate conjugates were successfully separated from an Oasis HLB solid phase extraction (SPE) cartridge with two different eluents, and the sulfate conjugates were then transformed to their corresponding free estrogens by acid solvolysis. Before the analysis with GC-MS, samples were derivatized by N,O-bis (trimethylsilyl) trifluoroacetamide (BSTFA) plus 1% trimethylchlorosilane (TMCS) at 80°C for 40 min. Satisfactory recoveries ranging from 64 to 112.3% were obtained by spiking ultra-purified water, raw, and treated municipal wastewater with the six estrogens at 50, 100, and 50 ng/L, respectively. The method was successfully applied to wastewater samples from one WWTP, which suggested that E1 was the dominant natural estrogens in effluent and E3-3S was one of the conjugates possibly occurring in the effluent.
The facile synthesis of hierarchical porous flower-like NiCo2O4 with superior lithium storage properties

In this work, we demonstrate the facile fabrication of 3-dimensional (3D) hierarchical porous flower-like NiCo2O4 and its application as an anode material in high-performance lithium ion batteries (LIBs). The uniform flower-like NiCo2O4 is built from porous nanoplates with thicknesses of approximately 25 nm. A detailed investigation reveals that PVP plays an important role, not only in controlling the formation of the delicate hierarchical flower-like structure, but also in creating the uniform pores of each nanoplate. Furthermore, a possible formation mechanism for this unique structure is proposed based on the experimental results. As a virtue of its beneficial structural features, the as-prepared NiCo2O4 exhibits an enhanced lithium storage capacity and excellent cycling stability (∼939 mA h g−1 at 100 mA g−1 after 60 cycles). This remarkable electrochemical performance can be attributed to the hierarchical structure and sufficient void space within the surface of the nanoplates, which effectively increases the contact area between the active materials and the electrolyte, reducing the Li+ diffusion pathway and buffering the volume change during cycling.
Meningioma Segmentation in T1-Weighted MRI Leveraging Global Context and Attention Mechanisms

Purpose: Meningiomas are the most common type of primary brain tumor, accounting for ~30% of all brain tumors. A substantial number of these tumors are never surgically removed but rather monitored over time. Automatic and precise meningioma segmentation is, therefore, beneficial to enable reliable growth estimation and patient-specific treatment planning. Methods: In this study, we propose the inclusion of attention mechanisms on top of a U-Net architecture used as backbone: (i) Attention-gated U-Net (AGUNet) and (ii) Dual Attention U-Net (DAUNet), using a three-dimensional (3D) magnetic resonance imaging (MRI) volume as input. Attention has the potential to leverage the global context and identify features' relationships across the entire volume. To limit spatial resolution degradation and loss of detail inherent to encoder–decoder architectures, we studied the impact of multi-scale input and deep supervision components. The proposed architectures are trainable end-to-end and each concept can be seamlessly disabled for ablation studies. Results: The validation studies were performed using a five-fold cross-validation over 600 T1-weighted MRI volumes from St. Olavs Hospital, Trondheim University Hospital, Norway. Models were evaluated based on segmentation, detection, and speed performances, and results are reported patient-wise after averaging across all folds. For the best-performing architecture, an average Dice score of 81.6% was reached for an F1-score of 95.6%. With an almost perfect precision of 98%, meningiomas smaller than 3 ml were occasionally missed hence reaching an overall recall of 93%. Conclusion: Leveraging global context from a 3D MRI volume provided the best performances, even if the native volume resolution could not be processed directly due to current GPU memory limitations. Overall, near-perfect detection was achieved for meningiomas larger than 3 ml, which is relevant for clinical use. In the future, the use of multi-scale designs and refinement networks should be further investigated. A larger number of cases with meningiomas below 3 ml might also be needed to improve the performance for the smallest tumors.
The Source Locations of Major Flares and CMEs in Emerging Active Regions

Major flares and coronal mass ejections (CMEs) tend to originate from compact polarity inversion lines (PILs) in solar active regions (ARs). Recently, a scenario named “collisional shearing” was proposed by Chintzoglou et al. to explain the phenomenon, which suggests that the collision between different emerging bipoles is able to form a compact PIL, driving the shearing and flux cancellation that are responsible for the subsequent large activities. In this work, by tracking the evolution of 19 emerging ARs from their birth until they produce the first major flares or CMEs, we investigated the source PILs of the activities, i.e., the active PILs, to explore the generality of “collisional shearing. ” We find that none of the active PILs is the self PIL (sPIL) of a single bipole. We further find that 11 eruptions originate from the collisional PILs (cPILs) formed due to the collision between different bipoles, six from the conjoined systems of sPIL and cPIL, and two from the conjoined systems of sPIL and ePIL (external PIL between the AR and the nearby pre-existing polarities). Collision accompanied by shearing and flux cancellation is found to develop at all PILs prior to the eruptions, with 84% (16/19) cases having collisional length longer than 18 Mm. Moreover, we find that the magnitude of the flares is positively correlated with the collisional length of the active PILs, indicating that the more intense activities tend to originate from PILs with more severe collisions. The results suggest that “collisional shearing,” i.e., bipole–bipole interaction during the flux emergence, is a common process in driving the major activities in emerging ARs.
A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations

Semi-supervised learning on graphs is a widely applicable problem in network science and machine learning. Two standard algorithms -- label propagation and graph neural networks -- both operate by repeatedly passing information along edges, the former by passing labels and the latter by passing node features, modulated by neural networks. These two types of algorithms have largely developed separately, and there is little understanding about the structure of network data that would make one of these approaches work particularly well compared to the other or when the approaches can be meaningfully combined. Here, we develop a Markov random field model for the data generation process of node attributes, based on correlations of attributes on and between vertices, that motivates and unifies these algorithmic approaches. We show that label propagation, a linearized graph convolutional network, and their combination can all be derived as conditional expectations under our model, when conditioning on different attributes. In addition, the data model highlights deficiencies in existing graph neural networks (while producing new algorithmic solutions), serves as a rigorous statistical framework for understanding graph learning issues such as over-smoothing, creates a testbed for evaluating inductive learning performance, and provides a way to sample graphs attributes that resemble empirical data. We also find that a new algorithm derived from our data generation model, which we call a Linear Graph Convolution, performs extremely well in practice on empirical data, and provide theoretical justification for why this is the case.
The properties of clusters, and the orientation of magnetic fields relative to filaments, in magnetohydrodynamic simulations of colliding clouds

We have performed Smoothed Particle Magneto-Hydrodynamics (SPMHD) calculations of colliding clouds to investigate the formation of massive stellar clusters, adopting a timestep criterion to prevent large divergence errors. We find that magnetic fields do not impede the formation of young massive clusters (YMCs), and the development of high star formation rates, although we do see a strong dependence of our results on the direction of the magnetic field. If the field is initially perpendicular to the collision, and sufficiently strong, we find that star formation is delayed, and the morphology of the resulting clusters is significantly altered. We relate this to the large amplification of the field with this initial orientation. We also see that filaments formed with this configuration are less dense. When the field is parallel to the collision, there is much less amplification of the field, dense filaments form, and the formation of clusters is similar to the purely hydrodynamical case. Our simulations reproduce the observed tendency for magnetic fields to be aligned perpendicularly to dense filaments, and parallel to low density filaments. Overall our results are in broad agreement with past work in this area using grid codes.
Preparation and Characterization of Tacrolimus-Loaded SLNs in situ Gel for Ocular Drug Delivery for the Treatment of Immune Conjunctivitis

Background The aim of this study is to develop a novel in situ gel of tacrolimus-loaded SLNs (solid lipid nanoparticles) for ocular drug delivery. Methods The optimal formulation was characterized by surface morphology, particle size, zeta potential, entrapment efficiency, drug loading and in vitro release behavior. In vivo studies were also conducted to evaluate the pharmacokinetic and pharmacodynamic results. Results In this study, TAC-SLNs ISG were prepared using homogenization followed by probe sonication method. The average particle size of TAC-SLNs ISG was observed to be 122.3±4.3 nm. Compared with TAC-SLNs, in situ gel did not increase particle size, and there was no significant difference between them. The results of viscosity measurement showed that TAC SLNs-ISG were typical of pseudo plastic systems and showed a marked increase in viscosity as temperature increased and ultimately formed a rigid gel (32°C). In vitro and in vivo studies illustrated the sustained release model of the drug from TAC-SLNs ISG. Animal model showed that TAC-SLNs ISG had good pharmacodynamics when compared with eye drops and SLNs. Conclusion Our results demonstrated that TAC SLNs-ISG had the potential for being an ideal ocular drug delivery system.
Antiviral activity of Brazilian Green Propolis extract against SARS-CoV-2 (Severe Acute Respiratory Syndrome - Coronavirus 2) infection: case report and review

Neurociencia Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de Sao Joao del-Rei (UFSJ), Minas Gerais, MG, BR. Departamento de Ginecologia. Nucleo de Avaliacao de Tecnologias em Saude. Escola Paulista de Medicina / Universidade Federal de Sao Paulo (EPM/UNIFESP), Sao Paulo, SP, BR. Krankenanstalt Rudolfstiftung, Messerli Institute, Vienna, Austria. Departamento de Patologia e Analises Clinicas, Programa de Pos-graduacao em Ciencias da Saude da FMABC, Santo André, SP, BR. Departamento de Ciencias Farmaceuticas. Universidade
The Effects of Fear and Knowledge of COVID-19 on Preventive Practice Among Pregnant Women Who Attend Antenatal Care in Northwest Ethiopia, 2020: Institution-Based Cross-Sectional Study

Background The novel coronavirus disease 2019 (COVID-19) pandemic has infected over one million individuals with almost 50,000 deaths worldwide. COVID-19 is currently a global health threat and a public health emergency. Therefore, accurate and up-to-date information regarding prevention and control methods is essential. Objective The aim of the study was to assess the effects of fear and knowledge of COVID-19 on preventive practices among pregnant women who attend antenatal care in northwest Ethiopia, 2020. Methods An institution-based cross-sectional study was conducted between July and August 2020. The systematic random sampling technique was used to select 422 participants. Data collected by a face to face interview on pretested and structured questions were entered using Epi-Info version 7 and it was analyzed using SPSS version 22 software. The bivariate and multivariable logistic regression model was used to assess factors associated with COVID-19 preventive practices. Adjusted odds ratio (OR) with a 95% confidence interval (CI) was used to determine the association between covariates and the outcome variable. The p-value less than 0.05 was considered statically significant. Results According to this study, good preventive practice of COVID-19 among pregnant women was found to be (47.4%). Fear of COVID-19 was (50.9%). The majority (55.0%) of the respondents had good knowledge. Fear [AOR: 2.485, 95% CI: (1.664–3.711)] and having good knowledge [AOR: 2.308, 95% CI: (1.541–3.457)] were significantly associated with good prevention practices among the women. Conclusion and Recommendation Only half of the pregnant women had good preventive practice. The findings suggest that healthcare bodies should consider these findings to develop strategies for preventive practice against COVID-19.
Prognostic Significance of Preoperative Lymphocyte-to-C-Reactive Protein Ratio in Patients with Non-Metastatic Colorectal Cancer

Background The inflammatory indexes are attracting increasing attention as a prognostic predictor for colorectal cancer (CRC). However, the prognostic value of the preoperative lymphocyte-to-C-reactive protein ratio (LCR) in patients with non-metastatic CRC remains to be established. Methods A total of 955 patients from 2010 to 2014 at a single center were included. Receiver operating characteristic curves (ROC) were generated to define the optimal cutoff value of the inflammatory indexes, and the areas under the curve (AUC) were calculated to compare the predictive value among the inflammatory indexes. The Fine and Gray competing risk regression model and Cox proportional hazard model were used to determine the prognostic factors for cancer-specific survival (CSS) and overall survival (OS) by using sub-distribution hazard ratio (SHR) and hazard ratio (HR) as size effects, respectively. Results A ratio of 6500 was defined as the optimal cutoff value for LCR for dividing CRC patients into the high (> 6500, n = 528) and low (≤ 6500, n = 427) LCR groups. The LCR had the highest value of prognostic prediction among all inflammation-based scores. Low LCR was significant correlated with several clinicopathological features of tumor invasion and development. The patients with low LCR had poorer CSS and OS as compared to those with high LCR. Multivariate analyses showed that low LCR was independently associated with worse OS (HR = 0.61, 95% CI: 0.53–0.70) and CSS (SHR = 0.55, 95% CI: 0.43–0.71). Conclusion Preoperative LCR can be a useful biomarker for prognostic prediction in non-metastatic CRC patients with a better predictive value than other inflammatory indexes.
The Role of Regulatory B Cells in Health and Diseases: A Systemic Review

Abstract Equivalent to regulatory T cells, a novel B cell populace, called regulatory B cells (Bregs), has been found to exert a negative immune regulatory role. These subsets of cells account for 0.5% of human B cells from the periphery that expand after activation upon certain stimuli depending on the nature of the microenvironment and provide a variety of Breg cell phenotypes. The increasing number of suppressive mechanisms attributed to Bregs suggests that these immune cells play many roles in immune regulation. Bregs have been confirmed to play a role in host defense mechanisms of healthy individuals as well as they play pathologic and protective roles in diseases or other conditions. Accumulating evidence reported that Bregs have a role in autoimmune and infectious diseases to lower inflammation, and in cancer to attenuate antitumor immune responses, thereby to promote cancer growth and metastasis. More recently, Bregs are also found to be involved in conditions like transplantation for transplant tolerance, during pregnancy to create an immune-privileged uterine environment and during early neonate life. Herein, the review summarizes recent findings aimed to provide understanding on the Breg cells, in the hope to gain insight on the general overview, development, mechanism of activation, and action of Bregs as well as their potential roles in health and diseases.
Presence of pyrroloquinazoline alkaloid in Adhatoda vasica attenuates inflammatory response through the downregulation of pro-inflammatory mediators in LPS stimulated RAW 264.7 macrophages

Introduction: Inflammation is the primary response caused due to harmful stimuli which are followed by the increased draining of plasma and immune cells from the body into the site of the injured tissue. A signaling cascade of growth factors and cytokines propagates and eventually matures in the inflammatory site involving the blood vessels and immune markers within the injured tissue in order to promote the renewal of the degenerated tissue. During a chronic disorder like diabetic foot ulcer, there is an obstinate inflammation which may act as a prime factor for limb amputation and upon persistent prevalence may even lead to death. Methods: This study focuses on the mode of action of ALK-F (alkaloid fraction) isolated from Adhatoda vasica in attenuating the nitric oxide production which was estimated by Griess assay, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) expression was analyzed by ELISA and expression of COX-2 and iNOS by RT-PCR and western blotting in LPS stimulated RAW 264.7 macrophages. Total intracellular ROS was analyzed by DCFH-DA probing and the presence of quinazoline alkaloid (vasicine) in the ALK-F was evidenced by high performance liquid chromatography (HPLC). Results: The ALK-F of A. vasica exhibited a significant inhibitory effect on LPS elicited nitrite production (13.2 ± 1.06 µM), iNOS, and COX-2 (2.6 and 3.3 fold) in a dose-dependent manner. There was a significant decrease in the generation of these pro-inflammatory cytokines TNF-α (1102 ± 1.02 pg/mL) and IL-6 (18 ± 0.87 ng/mL) and total intracellular ROS in the highest tested concentrations (1 µg and 10 µg) of ALK-F of A. vasica. HPLC analysis by the gradient elution method revealed the presence of 12% of quinazoline alkaloid vasicine in the crude alkaloid fraction. Conclusion: Thus this study communally suggests that attenuation of nitric oxide and the dysregulation of genes responsible for inflammation which deliberates A. vasica to conflict against inflammation and provide remedial benefits in diabetic wound care.
Association Between Systemic Immune-Inflammation Index and Diabetic Depression

Background Depression is highly prevalent in patients with diabetes mellitus (DM). Diabetic depression has been shown to be associated with low-grade systemic inflammation. In recent years, the systemic immune-inflammation (SII) index has been developed as an integrated and novel inflammatory indicator. The aims of this study were to investigate the relationship between diabetic depression and SII levels, adjusting for a wide range of potential confounding factors, to examine the potential of SII in predicting diabetic depression. Methods The present cross-sectional study was conducted among adults with DM in the National Health and Nutrition Examination Survey between 2009 and 2016, the SII level was calculated as the platelet counts × neutrophil counts/lymphocyte counts. Patient Health Questionnaire‐9 was used to measure depression in patients with DM. Multivariable logistic regression and propensity score-matched analysis were used to analyze the association between SII levels and depression. Results A total of 2566 patients with DM were included in the study, of which 370 (13.3%) were diagnosed with depression. Multivariable logistic regression showed that high SII level was an independent risk factor for diabetic depression (OR = 1.347, 95% CI: 1.031–1.760, P = 0.02882) after adjusting for covariates. The relationship between SII and diabetic depression was further verified by propensity score-matched analysis. Conclusion Our data suggest that SII is a risk factor for depression in patients with DM. The SII may be an easily accessible and cost-effective strategy for identifying depression in patients with DM. More studies are warranted to further analyze the role of SII in depression in diabetic patients.
Cobalt ion-doped polyaniline, poly(N-methylaniline), and poly(N-ethylaniline): electrosynthesis and characterisation using electrochemical methods in acidic solutions

Cobalt ion (Co2+)-doped polyaniline (PANI-Co), poly(N-methylaniline) (PNMA-Co), and poly(N-ethylaniline) (PNEA-Co) films were synthesised electrochemically on a pencil graphite electrode (PGE) and their electrochemical properties were investigated for supercapacitor applications. The polymer film-coated electrodes (PGE/PANI-Co, PGE/PNMA-Co, and PGE/PNEA-Co) thus obtained were characterised by scanning electron microscopy (SEM) and different electrochemical methods. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements were employed in 0.1 M H2SO4 solution to calculate the specific capacitance (CS) values of the electrodes. The maximum CS of 192.94 F g−1, 139.83 F g−1, and 47.12 F g−1 were achieved for PGE/PANI-Co, PGE/PNMA-Co, and PGE/PNEA-Co at 1 mV s−1, respectively. On the other hand, the charge/discharge stability of the electrodes was analysed using the repeating chronopotentiometry (RCP) method. The RCP measurements indicate that the electrodes could be used as an electrode active material for low voltage supercapacitor applications.