African-Americans and Latinos suffer the highest cervical cancer burden compared to other populations and have sub-optimal HPV vaccination rates.
To condense research findings of studies conducted ...with African-Americans and Latinos on factors associated with HPV vaccine acceptability and uptake.
Standards for conducting an integrative review were used. PubMed, Cumulative Index to Nursing and Allied Health Literature, and PsycINFO databases were searched.
Awareness about HPV and the HPV vaccine varied by demographics of parents. For Latino parents, acculturation and awareness were associated. However, findings were mixed regarding the association between acculturation and knowledge. Among African-Americans, higher socioeconomic status (SES) and awareness were associated. Sexuality-related concerns, concerns about safety and low perceived risk of daughter’s acquiring HPV emerged as barriers to vaccination among Latinos and African-Americans. Among Latinos, vaccine acceptability was associated with the vaccine’s cancer prevention benefits and a provider’s recommendation. Among African-Americans, acceptability was associated with awareness, perceived risk of acquiring HPV, religion, and a provider’s recommendation. Few interventions have been developed to increase HPV vaccine acceptance. Importantly, few studies assessed the influence of culture on vaccine acceptance and uptake.
Future research should be informed by culture-centered theories as this is the first step to inform the development of culturally-grounded interventions.
•Few studies assess reasons for African-Americans’ low HPV vaccine completion rate.•Few studies examine how acculturation may affect U.S. Latinos’ HPV vaccine acceptance.•Few studies assessed beliefs and attitudes that underpin barriers to acceptance.•African-Americans’ HPV vaccine acceptance is linked with socio-demographic factors.•Few studies assessed the potential influence of culture-related variables.
Aqueous Zn-ion batteries have attracted increasing research interest; however, the development of these batteries has been hindered by several challenges, including dendrite growth, Zn corrosion, ...cathode material degradation, limited temperature adaptability and electrochemical stability window, which are associated with water activity and the solvation structure of electrolytes. Here we report that water activity is suppressed by increasing the electron density of the water protons through interactions with highly polar dimethylacetamide and trimethyl phosphate molecules. Meanwhile, the Zn corrosion in the hybrid electrolyte is mitigated, and the electrochemical stability window and the operating temperature of the electrolyte are extended. The dimethylacetamide alters the surface energy of Zn, guiding the (002) plane dominated deposition of Zn. Molecular dynamics simulation evidences Zn
ions are solvated with fewer water molecules, resulting in lower lattice strain in the NaV
O
·1.5H
O cathode during the insertion of hydrated Zn
ions, boosting the lifespan of Zn|| NaV
O
·1.5H
O cell to 3000 cycles.
Molecular recognition between proteins and their interacting partners underlies the biochemistry of living organisms. Specificity in this recognition is thought to be essential, whereas promiscuity ...is often associated with unwanted side effects, poor catalytic properties and errors in biological function. Recent experimental evidence suggests that promiscuity, not only in interactions but also in the actual function of proteins, is not as rare as was previously thought. This has implications not only for our fundamental understanding of molecular recognition and how protein function has evolved over time but also in the realm of biotechnology. Understanding protein promiscuity is becoming increasingly important not only to optimize protein engineering applications in areas as diverse as synthetic biology and metagenomics but also to lower attrition rates in drug discovery programs, identify drug interaction surfaces less susceptible to escape mutations and potentiate the power of polypharmacology.
Altered metabolism in pulmonary artery smooth muscle cells (PASMCs) and endothelial cells (PAECs) contributes to the pathology of pulmonary hypertension (PH), but changes in substrate uptake and how ...substrates are utilized have not been fully characterized. We hypothesized stable isotope metabolomics would identify increased glucose, glutamine and fatty acid uptake and utilization in human PASMCs and PAECs from PH versus control specimens, and that TGF-β treatment would phenocopy these metabolic changes. We used
C-labeled glucose, glutamine or a long-chain fatty acid mixture added to cell culture media, and mass spectrometry-based metabolomics to detect and quantify
C-labeled metabolites. We found PH PASMCs had increased glucose uptake and utilization by glycolysis and the pentose shunt, but no changes in glutamine or fatty acid uptake or utilization. Diseased PAECs had increased proximate glycolysis pathway intermediates, less pentose shunt flux, increased anaplerosis from glutamine, and decreased fatty acid β-oxidation. TGF-β treatment increased glycolysis in PASMCs, but did not recapitulate the PAEC disease phenotype. In TGF-β-treated PASMCs, glucose, glutamine and fatty acids all contributed carbons to the TCA cycle. In conclusion, PASMCs and PAECs collected from PH subjects have significant changes in metabolite uptake and utilization, partially recapitulated by TGF-β treatment.
SARS-CoV-2 is the new coronavirus responsible for COVID-19 disease. The first two cases of COVID-19 were detected in Venezuela on March 13, 2020. The aim of this study was the genetic ...characterization of Venezuelan SARS-CoV-2 isolates. A total of 7 full SARS-CoV-2 genome sequences were obtained by Sanger sequencing, from patients of different regions of Venezuela, mainly from the beginning of the epidemic. Ten out of 11 isolates (6 complete genomes and 4 partial spike genomic regions) belonged to lineage B, bearing the D614G mutation in the Spike protein. Isolates from the first outbreak that occurred in the Margarita Island harbored an in-frame deletion in its sequence, without amino acids 83-85 of the NSP1 of the ORF1. The search for deletions in 48,635 sequences showed that the NSP1 gene exhibit the highest frequency of deletions along the whole genome. Structural analysis suggests a change in the N-terminal domain with the presence of this deletion. In contrast, isolates circulating later in this island lacked the deletion, suggesting new introductions to the island after this first outbreak. In conclusion, a high diversity of SARS-CoV-2 isolates were found circulating in Venezuela, with predominance of the D614G mutation. The first small outbreak in Margarita Island seemed to be associated with a strain carrying a small deletion in the NSP1 protein, but these isolates do not seem to be responsible for the larger outbreak which started in July.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The ‘neurogenesis hypothesis of depression’ emphasizes the importance of upregulated hippocampal neurogenesis for the efficacy of antidepressant treatment. Neuromodulation is a promising therapeutic ...method that stimulates neural circuitries to treat neuropsychiatric illnesses. We conducted a scoping review on the neurogenic and antidepressant outcomes of neuromodulation in animal models of depression. PubMed, Web of Science, and PsycInfo were comprehensively searched for full-text English articles from inception to October 5, 2021. Data screening and extraction were conducted independently by two researchers. Seventeen eligible studies were included in this review. The majority of studies used non-invasive neuromodulation (n = 14) and assessed neurogenesis using neural proliferation (n = 16) and differentiation markers (n = 9). Limited reports (n = 2) used neurogenic inhibitors to evaluate the role of neurogenesis on the depressive-like behavioral outcomes. Overall, neuromodulation substantially effectuated both hippocampal cell proliferation and antidepressant-like behavior in animal models of depression, with some providing evidence for enhanced neuronal differentiation and maturation. The proposed neurogenic-related mechanisms mediating the neuromodulation efficacies included neurotrophic processes, anti-apoptotic pathways, and normalization of HPA axis functions. Further research is warranted to explore the role of neuromodulation-induced neurogenic effects on treatment efficacies and to elucidate the underlying molecular mechanisms.
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•Neuromodulation are promising therapeutic tools for treating depression.•Studies show antidepressant effects of neuromodulation in depression models.•Upregulated hippocampal cell proliferation and differentiation were also observed.•There are neurogenesis-dependent and -independent effects of neuromodulation.•Further research is needed to explore underlying molecular mechanisms.
The increasing complexity of modern technical systems can exacerbate model uncertainty in model-based control, posing a great challenge to safe and effective system operation under closed loop. ...Online learning of model uncertainty can enhance control performance by reducing plant-model mismatch. This article presents a learning-based stochastic model predictive control (LB-SMPC) strategy for reference tracking of stochastic linear systems with additive state-dependent uncertainty. The LB-SMPC strategy adapts the state-dependent uncertainty model online to reduce plant-model mismatch for control performance optimization. Standard reachability and statistical tools are leveraged along with the state-dependent uncertainty model to develop a chance constraint-tightening approach, which ensures state constraint satisfaction in probability. The stability and recursive feasibility of the LB-SMPC strategy are established for tracking time-varying targets, without the need to redesign the controller every time the target is changed. The performance of the LB-SMPC strategy is experimentally demonstrated on an atmospheric pressure plasma jet (APPJ) testbed with prototypical applications in plasma medicine and materials processing. Real-time control comparisons with learning-based MPC with no uncertainty handling and offset-free MPC showcase the usefulness of LB-SMPC for predictive control of safety-critical systems with hard-to-model and/or time-varying dynamics.
Abstract
Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the ...recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.
In recent years, molecular dynamics simulations of proteins in explicit mixed solvents have been applied to various problems in protein biophysics and drug discovery, including protein folding, ...protein surface characterization, fragment screening, allostery, and druggability assessment. In this study, we perform a systematic study on how mixtures of organic solvent probes in water can reveal cryptic ligand binding pockets that are not evident in crystal structures of apo proteins. We examine a diverse set of eight PDB proteins that show pocket opening induced by ligand binding and investigate whether solvent MD simulations on the apo structures can induce the binding site observed in the holo structures. The cosolvent simulations were found to induce conformational changes on the protein surface, which were characterized and compared with the holo structures. Analyses of the biological systems, choice of probes and concentrations, druggability of the resulting induced pockets, and application to drug discovery are discussed here.
Cases of Alzheimer's disease (AD) are rising exponentially due to increasing global life expectancy. There are approximately 50 million sufferers worldwide, with prevalence rising most rapidly in ...low-income countries such as Africa and Asia. There is currently no definite diagnosis of AD until after death, thus an early biomarker for AD is urgently required in order to administer timelier and more effective interventions. Olfactory dysfunction (problems with the sense of smell) is one of the earliest, preclinical symptoms observed in AD. Olfaction is a promising early biomarker for use worldwide as it is easy, cheap to measure, and not reliant on specialist clinicians or laboratory analysis. We carried out a meta-analysis to determine the credibility of olfaction in diagnosing AD in the preclinical stages, by comparing olfaction in healthy controls against AD patients and patients with mild cognitive impairment (MCI). Data from 10 articles were subjected to two comparative meta-analyses. In the case of AD, the results illustrated that the overall magnitude of effect size was more apparent,
= -1.63, 95% CI -1.95, -1.31, in comparison to that of MCI,
= -0.81, 95% CI -1.08, -0.55. This shows that olfaction worsens progressively as patients progress from MCI to AD, highlighting the potential for olfactory dysfunction to identify AD in the preclinical stages prior to MCI.
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