Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring Process Barriers and Enablers Towards Universal Health Coverage Within the Sustainable Development Goals: A Systematic Review and Content Analysis

Background This study builds on previous successes of using tracer indicators in tracking progress towards Universal Health Coverage (UHC) and complements them by offering a more detailed tool that would allow us to identify potential process barriers and enablers towards such progress. Purpose This tool was designed accounting for possibly available data in low- and middle-income counties. Methodology A systematic review of relevant studies was carried out using PubMed, ISI Web of Science, Embase, Scopus, and ProQuest databases with no time restriction. The search was complemented by a scoping review of grey literature, using the World Bank and the World Health Organization (WHO) official reports depositories. Next, an inductive content analysis identified determinants influencing the progress towards UHC and its relevant indicators. The conceptual proximity between indicators and categorized themes was explored through three focus group discussion with 18 experts in UHC. Finally, a comprehensive list of indicators was converted into an assessment tool and refined following three consecutive expert panel discussions and two rounds of email surveys. Results A total of 416 themes (including indicators and determinants factors) were extracted from 166 eligible articles and documents. Based on conceptual proximity, the number of factors was reduced to 119. These were grouped into eight domains: social infrastructure and social sustainability, financial and economic infrastructures, population health status, service delivery, coverage, stewardship/governance, and global movements. The final assessment tool included 20 identified subcategories and 88 relevant indicators. Conclusion Identified factors in progress towards UHC are interrelated. The developed tool can be adapted and used in whole or in part in any country. Periodical use of the tool is recommended to understand potential factors that impede or advance progress towards UHC.
Electroacupuncture Attenuates Inflammation after Ischemic Stroke by Inhibiting NF-κB-Mediated Activation of Microglia

Microglial activation and microglia-mediated inflammation play an important role in the occurrence, development, and outcome of stroke. Brain injury induces the activation and release of proinflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin- (IL-) 1β, and IL-6. Many studies have confirmed that acupuncture is effective in treating ischemic stroke. However, its protective mechanism against ischemic brain injury is complex and multifactorial. In this study, we observed the effects of electroacupuncture at Baihui (GV20) and Dazhui (GV14) on microglial activation and inflammation in the cortical ischemic penumbra (IP) of permanent middle cerebral artery occlusion (pMCAO) rats. It was found that electroacupuncture inhibited the degeneration and necrosis of microglia in the cortical IP and ameliorated mitochondrial damage. Immunofluorescence and western blot analysis showed that microglia were in a resting state or weakly activated in the normal brain. After cerebral ischemia, the expression of microglial markers (Iba-1 and CD11b) increased, and NF-κB p65, IL-1β, and TNF-α expression gradually increased. The dynamic changes were generally temporally consistent. Electroacupuncture downregulated the expressions of Iba-1 and CD11b. Additionally, it inhibited the expression of NF-κB p65, IL-1β, and TNF-α and reduced the conversion of microglia to the M1 phenotype after ischemia. Electroacupuncture regulated the activation of microglia and microglia-mediated inflammation after cerebral ischemia, confirming the relevant theories regarding the effect of acupuncture treatment on cerebral ischemia and guiding clinical practice.
Adaptive Evolution of Feline Coronavirus Genes Based on Selection Analysis

Purpose We investigated sequences of the feline coronaviruses (FCoV), which include feline enteric coronavirus (FECV) and feline infectious peritonitis virus (FIPV), from China and other countries to gain insight into the adaptive evolution of this virus. Methods Ascites samples from 31 cats with suspected FIP and feces samples from 8 healthy cats were screened for the presence of FCoV. Partial viral genome sequences, including parts of the nsp12-nsp14, S, N, and 7b genes, were obtained and aligned with additional sequences obtained from the GenBank database. Bayesian phylogenetic analysis was conducted, and the possibility of recombination within these sequences was assessed. Analysis of the levels of selection pressure experienced by these sequences was assessed using methods on both the PAML and Datamonkey platforms. Results Of the 31 cats investigated, two suspected FIP cats and one healthy cat tested positive for FCoV. Phylogenetic analysis showed that all of the sequences from mainland China cluster together with a few sequences from the Netherlands as a distinct clade when analyzed with FCoV sequences from other countries. Fewer than 3 recombination breakpoints were detected in the nsp12-nsp14, S, N, and 7b genes, suggesting that analyses for positive selection could be conducted. A total of 4, 12, 4, and 4 positively selected sites were detected in the nsp12-nsp14, S, N, and 7b genes, respectively, with the previously described site 245 of the S gene, which distinguishes FIPV from FECV, being a positive selection site. Conversely, 106, 168, 25, and 17 negative selection sites in the nsp12-14, S, N, and 7b genes, respectively, were identified. Conclusion Our study provides evidence that the FCoV genes encoding replicative, entry, and virulence proteins potentially experienced adaptive evolution. A greater number of sites in each gene experienced negative rather than positive selection, which suggests that most of the protein sequence must be conservatively maintained for virus survival. A few of the sites showing evidence of positive selection might be associated with the more severe pathology of FIPV or help these viruses survive other harmful conditions.
The metabolic enzyme arginase-2 is a potential target for novel immune modulatory vaccines

ABSTRACT One way that tumors evade immune destruction is through tumor and stromal cell expression of arginine-degrading enzyme arginase-2 (ARG2). Here we describe the existence of pro-inflammatory effector T-cells that recognize ARG2 and can directly target tumor and tumor-infiltrating cells. Using a library of 34 peptides covering the entire ARG2 sequence, we examined reactivity toward these peptides in peripheral blood mononuclear cells from cancer patients and healthy individuals. Interferon-γ ELISPOT revealed frequent immune responses against several of the peptides, indicating that ARG2–specific self-reactive T-cells are natural components of the human T-cell repertoire. Based on this, the most immunogenic ARG2 protein region was further characterized. By identifying conditions in the microenvironment that induce ARG2 expression in myeloid cells, we showed that ARG2-specific CD4T-cells isolated and expanded from a peripheral pool from a prostate cancer patient could recognize target cells in an ARG2-dependent manner. In the ‘cold’ in vivo tumor model Lewis lung carcinoma, we found that activation of ARG2-specific T-cells by vaccination significantly inhibited tumor growth. Immune-modulatory vaccines targeting ARG2 thus are a candidate strategy for cancer immunotherapy.
Is “Busy” Always Better? Time-Use Activities and Depressive Symptoms Among Older Mexican Adults

Abstract Background and Objectives Depression among older Mexican adults is underrecognized and of increasing concern due to its association with comorbidities including cognitive and functional impairments. Prior studies have found an association between low involvement levels in social activities and depression. We aimed to examine the association of time-use activities and depressive symptomatology by sex. Research Design and Methods We used data from the 2012 and 2015 waves of the Mexican Health and Aging Study. Participants aged 60 and older who had low or no depressive symptoms in 2012 were included in these analyses (N = 4,309). Factor analysis was used to group activities and logistic regression models were used to assess the association of baseline time use with depressive symptomatology in 2015. Results Among those with low or no depressive symptomatology in 2012, 21.0% reported elevated symptoms (5+) in 2015. Those with elevated depressive symptoms were more likely to be women, older, lower educated, and with at least one activity of daily living limitation. Four time-use domains emerged from the factor analysis including hobbies and indoor activities, volunteering, caregiving, and working. The hobbies and indoor activities domain was associated with lower odds of elevated symptoms for men and women (odds ratio [OR]: 0.76, 95% confidence interval [CI]: 0.61–0.96; and OR: 0.75, 95% CI: 0.61–0.91, respectively). Additionally, the volunteer and community activities domain was associated with lower odds of depressive symptoms for women (OR: 0.72, 95% CI: 0.58–0.89) and men (OR: 0.77, 95% CI: 0.60–0.99). Discussion and Implications Understanding how older Mexicans distribute their time among different activities and its associations with depressive symptoms can help guide policy and sex-specific interventions for psychological well-being. Certain domains had lower odds for elevated depressive symptomatology; future work should examine this association in other countries as well as the context of the built environment.
Three-Dimensional, MultiScale, and Interconnected Trabecular Bone Mimic Porous Tantalum Scaffold for Bone Tissue Engineering

To investigate the biocompatibility and bone ingrowth properties of a novel trabecular bone mimic porous tantalum scaffold which holds potential for bone tissue engineering, a novel three-dimensional, multiscale interconnected porous tantalum scaffold was designed and manufactured. The morphology of the novel scaffold was observed with the use of scanning electron microscopy (SEM) and industrial computerized tomography. Mesenchymal stem cells (MSCs) were cultured with novel porous tantalum powder, SEM was carried out for the observation of cell morphology and adhesion, and cytotoxicity was evaluated by the MTT assay. Canine femoral shaft bone defect models were established, and novel porous tantalum rods were used to repair the bone defect. Repair effects and bone integration were evaluated by hard tissue slice examination and push-out tests at the indicated time. We found that the novel porous tantalum scaffold is a trabecular bone mimic, having the characteristics of being three-dimensional, multiscaled, and interconnected. The MSCs adhered to the surface of tantalum and proliferated with time, the tantalum extract did not have a cytotoxic effect on MSCs. In the bone defect model, porous tantalum rods integrated tightly with the host bone, and new bone formation was found on the scaffold-host bone interface both 3 and 6 months after the implantation. Favorable bone ingrowth was observed in the center of the tantalum rod. The push-out test showed that the strength needed to push out the tantalum rod is comparable for both 3 and 6 months when compared with the normal femoral shaft bone tissue. These findings suggested that the novel trabecular bone mimic porous tantalum scaffold is biocompatible and osteoinductive, which holds potential for bone tissue engineering application.
Evaluation of transdermal drug delivery using terahertz pulsed imaging

Transdermal drug delivery (TDD) is widely used for painless dosing due to its minimally invasive nature compared to hypodermic needle injection and its avoidance of the gastrointestinal tract. However, the stratum corneum obstructs the permeation of drugs into skin. Microneedle and nanoneedle patches are ways to enhance this permeation. In this work, terahertz (THz) imaging is utilized to compare the efficacy of different TDD methods including topical application and via a needle patch. Our work shows the feasibility and potential of using THz imaging to quantify and evaluate different transdermal application methods.
Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (Mpro) through docking, molecular mechanic & dynamic, and ADMET profiling

Abstract Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 Mpro have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral Mpro. Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected Mpro proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2. Communicated by Ramaswamy H. Sarma
Drink bleach or do what now? Covid-HeRA: A dataset for risk-informed health decision making in the presence of COVID19 misinformation

Given the wide spread of inaccurate medical advice related to the 2019 coronavirus pandemic (COVID-19), such as fake remedies, treatments and prevention suggestions, misinformation detection has emerged as an open problem of high importance and interest for the NLP community. To combat potential harm of COVID19-related misinformation, we release Covid-HeRA, a dataset for health risk assessment of COVID-19-related social media posts. More specifically, we study the severity of each misinformation story, i.e., how harmful a message believed by the audience can be and what type of signals can be used to discover high malicious fake news and detect refuted claims. We present a detailed analysis, evaluate several simple and advanced classification models, and conclude with our experimental analysis that presents open challenges and future directions.
Asymmetric Instability of Thin-Film Flow on a Fiber

The flow of a thin film down a vertical fiber is valuable for many industrial applications, such as fiber coating, microfluidics, heat exchangers, and desalination processes. It is well known that such flows give rise to a number of instabilities that define the bead-on-fiber morphology including Plateau-Rayleigh breakup, isolated bead formation, and convective instabilities, all of which leave the interface shape axisymmetric. A new asymmetric instability in the flow of liquid on a fiber is observed and its dependence upon liquid properties, flow rate, and fiber diameter is documented. The transition between symmetric and asymmetric morphology depends critically upon the fiber diameter and surface tension. The instability dynamics are described by the bead spacing and bead velocity/frequency and are used to contrast the behavior of the symmetric and asymmetric morphologies. The asymmetric morphology displays more regular dynamics than the symmetric morphology. For example, in the asymmetric morphology the transition from the Plateau-Rayleigh to convective regime occurs when the nozzle velocity is equal to the bead velocity and this dimensionless velocity scales with the capillary number. This prediction, in addition to a full description of the instability dynamics of thin film flows down fibers, can be used as a design tool for novel desalination processes.
Extensive Numerical Results for Integrable Case of Standard Map

In recent years, conservative dynamical systems have become a vivid area of research from the statistical mechanical characterization viewpoint. With this respect, several areapreserving maps have been studied. It has been numerically shown that the probability distribution of the sum of the suitable random variable of these systems can be well approximated by a Gaussian (q-Gaussian) when the initial conditions are randomly selected from the chaotic sea (region of stability islands) in the available phase space. In this study, we will summarize these results and discuss a special case for the standard map, a paradigmatic example of area-preserving maps, for which the map is totally integrable.
Antibiofilm Activity of Kefir Probiotic Lactobacilli Against Uropathogenic Escherichia coli (UPEC)

Background: Inhibition of biofilm formation is essential for the prevention and treatment of urinary tract infection. This study was aimed to identify the probiotic potential of Lactobacillus strains isolated from kefir and evaluate their antimicrobial and antibiofilm activities against Uropathogenic Escherichia coli (UPEC). Methods: Twelve Lactobacillus strains were evaluated. Antimicrobial and antibiofilm activities of Cell Free Supernatant (CFS) of the Lactobacillus strains against UPEC isolates were evaluated by agar well diffusion method and crystal violet assay, respectively. Probiotic potential of selected isolates was assessed by analyzing their tolerance to acidic pH and bile salts, auto-aggregation ability, co-aggregation with Escherichia coli (E. coli) and hemolytic activity. The isolates were identified by phenotypic and 16S rRNA gene sequencing. Results: The CFS of all lactobacilli strains was able to inhibit UPEC isolates even after neutralization. Four out of 12 isolates inhibited the biofilm formation by UPEC in the range 62–75%. The viability under acidic condition varied among the isolates ranging from 6–89.8%. All the isolates could tolerate the 0.3% bile and eight isolates showed the adaptation time of less than 1 hr. All the strains exhibited co-aggregation with E. coli. Auto-aggregation was highly correlated with co-aggregation of all lactobacilli strains with E. coli (r=0.889, p<0.001). The isolates with satisfactory probiotic potential and higher ability of biofilm inhibition and antibacterial activity belonged to the species Lactobacillus rhamnosus and Lactobacillus paracasei. Conclusion: All four selected probiotic strains exhibited antimicrobial and antibiofilm activities, which suggest potential applications for controlling or preventing infections caused by UPEC.
Regulation of antimicrobial peptide genes in the tobacco hornworm Manduca sexta

The innate immune system, also known as natural or non-specific immune system, is conserved from insects to humans. The insect innate immune system is composed of humoral and cellular components. Insect humoral responses mainly include synthesis of antimicrobial peptides (AMPs) and activation of the prophenoloxidase (PPO) system. Expression of AMPs is regulated by two signaling pathways, the Toll-Spätzle (Spz) and immune deficiency (IMD) pathways, in Drosophila melanogaster. My research has been focusing on pattern recognition receptors (PRRs) and regulation of AMP genes in the tobacco hornworm, Manduca sexta. In chapter 2, I showed direct interaction between M. sexta MsToll and MsSpzC108 by Co-immunoprecipitation (Co-IP), and demonstrated that co-expression of MsToll and MsSpz-C108 can activate AMP gene promoters in S2 cells by dual luciferase assays. My results confirm a Toll-Spz pathway in an insect other than Drosophila. In chapter 3, a Toll-ML (MD2 (myeloid differentiation protein 2) related lipidrecognition)-LPS signaling pathway was identified in M. sexta. The Co-IP assay showed that MsToll, MsML-1 and lipopolysaccharide (LPS) could form a receptor complex. More importantly, I showed that co-expression of MsToll and MsML-1 could up-regulate
NFSv4 Test Project

This paper presents the testing effort done around NFSv4 1 by the Linux NFSv4 community. As an introduction, we explain the rationale for such a heavy testing activity, why NFSv4 was needed, the current status of NFSv4, and some Use Cases. Chapter 3 describes the tools used for testing integral features of NFSv4 in the areas of functionality, interoperability, robustness, performance, and security: where they come from, and which parts of NFSv4 they are aimed to test. We also describe some tools used for analyzing problems and loads. Chapter 4 ﬁrst explains the goals of the NFSv4 testing team and how contributors are working together. Major events for NFSv4 since January 2004 are displayed in a
COVID-CAM: A Method of Detection COVID using Active Map Classification, CNN and Deep Learning

The Novel Corona Virus (COVID'19) spread rapidly around the world and become pandemic.it has caused more than 6.1 million cases (end of May 2020) of corona disease and effect on both people's daily lives, public health, and the main issue of the global economy. It has critical to detect the COVID'19 from the people and give the quick treatment of affected people due to no accurate toolkit available. They see many researcher-made detection methods using CT images this method is time-consuming and also not give that much accuracy therefore for the early detection and accuracy we develop one model of AI system using computer vision and deep learning which can detect CORONA using chest X-ray (CXR) images that is open source and available to the general public. However model divide into the two modules, the first module detects the COVID'19 using Chest X-ray images and the second module with help of active classification map method gives results with high accuracy.
Implementing a foveal-pit inspired filter in a Spiking Convolutional Neural Network: a preliminary study

We have presented a Spiking Convolutional Neural Network (SCNN) that incorporates retinal foveal-pit inspired Difference of Gaussian filters and rank-order encoding. The model is trained using a variant of the backpropagation algorithm adapted to work with spiking neurons, as implemented in the Nengo library. We have evaluated the performance of our model on two publicly available datasets — one for digit recognition task, and the other for vehicle recognition task. The network has achieved up to 90% accuracy, where loss is calculated using the cross-entropy function. This is an improvement over around 57% accuracy obtained with the alternate approach of performing the classification without any kind of neural filtering. Overall, our proof-of-concept study indicates that introducing biologically plausible filtering in existing SCNN architecture will work well with noisy input images such as those in our vehicle recognition task. Based on our results, we plan to enhance our SCNN by integrating lateral inhibition-based redundancy reduction prior to rank-ordering, which will further improve the classification accuracy by the network.