by increasing the students’ informational and media literacy, providing authentic and low-cost online resources of information and specialized TV programs, the damages rooted in using invalid information resources concerning fitness can be substantially diminished.Identification and quantification of plant flavonoids are critical to pharmacokinetic study and pharmaceutical quality control due to their distinct pharmacological functions. Here we report on a novel plant flavonoid electrochemical sensor for sensitive and selective detection of dihydromyricetin (DMY) based on double- layered membranes consisting of gold nanoparticles (Au) anchored on reduced graphene oxide (rGO) and molecularly imprinted polymers (MIPs) modified glassy carbon electrode (GCE). Both rGO-Au and MIPs membranes were directly formed on GCE via in-situ electrochemical reduction and polymerization processes step by step. The compositions, morphologies, and electrochemical properties of membranes were investigated with X-ray powder diffractometry (XRD), Fourier transform infrared spectrum (FTIR), Field emission scanning electron microscopy (FESEM) combined with various electrochemical methods. The fabricated electrochemical sensor labeled as GCE│rGO-Au/MIPs exhibited excellent performance in determining of DMY under optimal experimental conditions. A wide linear detection range (LDR) ranges from 2.0×10-8 to 1.0×10-4 M together with a low limit of detection (LOD) of 1.2×10-8 M (S/N = 3) were achieved. Moreover, the electrochemical sensor was employed to determine DMY in real samples with satisfactory results.Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer’s disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).The vertical distribution of radiocarbon (14C) was examined in the bottom sediment core, taken from Lake Drūkšiai, which has served as a cooling pond since 1983 for the 26 years of the Ignalina Nuclear Power Plant (INPP) operation using two RBMK-1500 reactors (Russian acronym for”Channelized Large Power Reactor”). 14C specific activity was measured in alkali-soluble and -insoluble fractions of the sediment layers. Complementary measurements of the 210Pb and 137Cs activity of the samples provided the possibility to evaluate the date of every layer formation, covering the 1947-2013 period. In addition, 14C distribution was examined in the scales of pelagic fish caught between 1980 and 2012. Our measurements reveal that, during the period 1947-1999, the radiocarbon specific activity in both fractions exhibits a parallel course with a difference of 5 ± 1 pMC (percent of modern carbon) being higher in alkali-soluble fraction, although 14C specific activity in both fractions increased by 11.4-13.6 pMC during the first 15 years of plant operation. However, during the 2000-2009 period, other than previously seen, a dissolved inorganic carbon (DIC) → aquatic primary producers → sediments 14C incorporation pattern occurred, as the radiocarbon specific activity difference between alkali-soluble and -insoluble fractions reached 94, 25, and 20 pMC in 2000, 2006, and 2008, respectively. Measurements in different sediment fractions allowed us to identify the unexpected organic nature of 14C contained in liquid effluences from the INPP in 2000-2009. The discrepancy between 14C specific activity in fish scales samples and DIC after 2000 also confirmed the possibility of organic 14C contamination. Possible reasons for this phenomenon might be industrial processes introduced at the INPP, such as the start of operation of the cementation facility for spent ion exchange resins, decontamination procedures, and various maintenance activities of reactor aging systems and equipment.In humans, most germline mutations are inherited from the father. This observation has been widely interpreted as reflecting the replication errors that accrue during spermatogenesis. If so, the male bias in mutation should be substantially lower in a closely related species with similar rates of spermatogonial stem cell divisions but a shorter mean age of reproduction. To test this hypothesis, we resequenced two 3-4 generation nuclear families (totaling 29 individuals) of olive baboons (Papio anubis), who reproduce at approximately 10 years of age on average, and analyzed the data in parallel with three 3-generation human pedigrees (26 individuals). We estimated a mutation rate per generation in baboons of 0.57×10-8 per base pair, approximately half that of humans. Strikingly, however, the degree of male bias in germline mutations is approximately 41, similar to that of humans-indeed, a similar male bias is seen across mammals that reproduce months, years, or decades after birth. These results mirror the finding in humans that the male mutation bias is stable with parental ages and cast further doubt on the assumption that germline mutations track cell divisions. Our mutation rate estimates for baboons raise a further puzzle, suggesting a divergence time between apes and Old World monkeys of 65 million years, too old to be consistent with the fossil record; reconciling them now requires not only a slowdown of the mutation rate per generation in humans but also in baboons.Understanding the behavior of emerging disease outbreaks in, or ahead of, real-time could help healthcare officials better design interventions to mitigate impacts on affected populations. Most healthcare-based disease surveillance systems, however, have significant inherent reporting delays due to data collection, aggregation, and distribution processes. Recent work has shown that machine learning methods leveraging a combination of traditionally collected epidemiological information and novel Internet-based data sources, such as disease-related Internet search activity, can produce meaningful „nowcasts” of disease incidence ahead of healthcare-based estimates, with most successful case studies focusing on endemic and seasonal diseases such as influenza and dengue. Here, we apply similar computational methods to emerging outbreaks in geographic regions where no historical presence of the disease of interest has been observed. By combining limited available historical epidemiological data available with disease-related Internet search activity, we retrospectively estimate disease activity in five recent outbreaks weeks ahead of traditional surveillance methods. We find that the proposed computational methods frequently provide useful real-time incidence estimates that can help fill temporal data gaps resulting from surveillance reporting delays. However, the proposed methods are limited by issues of sample bias and skew in search query volumes, perhaps as a result of media coverage.Genome editing is now widely used in plant science for both basic research and molecular crop breeding. The clustered regularly interspaced short palindromic repeats (CRISPR) technology, through its precision, high efficiency and versatility, allows for editing of many sites in plant genomes. This system has been highly successful to produce knock-out mutants through the introduction of frameshift mutations due to error-prone repair pathways. Nevertheless, recent new CRISPR-based technologies such as base editing and prime editing can generate precise and on demand nucleotide conversion, allowing for fine-tuning of protein function and generating gain-of-function mutants. However, genome editing through CRISPR systems still have some drawbacks and limitations, such as the PAM restriction and the need for more diversity in CRISPR tools to mediate different simultaneous catalytic activities. In this study, we successfully used the CRISPR-Cas9 system from Staphylococcus aureus (SaCas9) for the introduction of frameshift mutations in the tetraploid genome of the cultivated potato (Solanum tuberosum). We also developed a S. aureus-cytosine base editor that mediate nucleotide conversions, allowing for precise modification of specific residues or regulatory elements in potato. Our proof-of-concept in potato expand the plant dicot CRISPR toolbox for biotechnology and precision breeding applications.Congestive heart failure is characterized by suppressed cardiac output and arterial filling pressure, leading to renal retention of salt and water, contributing to further volume overload. Mathematical modeling provides a means to investigate the integrated function and dysfunction of heart and kidney in heart failure. This study updates our previously reported integrated model of cardiac and renal functions to account for the fluid exchange between the blood and interstitium across the capillary membrane, allowing the simulation of edema. A state of heart failure with reduced ejection fraction (HF-rEF) was then produced by altering cardiac parameters reflecting cardiac injury and cardiovascular disease, including heart contractility, myocyte hypertrophy, arterial stiffness, and systemic resistance. After matching baseline characteristics of the SOLVD clinical study, parameters governing rates of cardiac remodeling were calibrated to describe the progression of cardiac hemodynamic variables observed over one year in the placebo arm of the SOLVD clinical study. The model was then validated by reproducing improvements in cardiac function in the enalapril arm of SOLVD. The model was then applied to prospectively predict the response to the sodium-glucose co-transporter 2 (SGLT2) inhibitor dapagliflozin, which has been shown to reduce heart failure events in HF-rEF patients in the recent DAPAHF clinical trial by incompletely understood mechanisms. The simulations predict that dapagliflozin slows cardiac remodeling by reducing preload on the heart, and relieves congestion by clearing interstitial fluid without excessively reducing blood volume. This provides a quantitative mechanistic explanation for the observed benefits of SGLT2i in HF-rEF. The model also provides a tool for further investigation of heart failure drug therapies.