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In vitro assays of ion transport are an essential tool for understanding molecular mechanisms associated with ATP-dependent pumps. Because ion transport is generally electrogenic, principles of electrophysiology are applicable, but conventional tools like patch-clamp are ineffective due to relatively low turnover rates of the pumps. Instead, assays have been developed to measure either voltage or current generated by transport activity of a population of molecules either in cell-derived membrane fragments or after reconstituting purified protein into proteoliposomes. In order to understand the nuances of these assays and to characterize effects of various operational parameters, we have developed a numerical model to simulate data produced by two relevant assays: fluorescence from voltage-sensitive dyes and current recorded by capacitive coupling on solid supported membranes. Parameters of the model, which has been implemented in Python, are described along with underlying principles of the computational algorithm. Experimental data from KdpFABC, a K+ pump associated with P-type ATPases, are presented, and model parameters have been adjusted to mimic these data. In addition, effects of key parameters such as nonselective leak conductance and turnover rate are demonstrated. Finally, simulated data are used to illustrate the effects of capacitive coupling on measured current and to compare alternative methods for quantification of raw data.

YiiP from Shewanella oneidensis is a prokaryotic Zn2+/H+ antiporter that serves as a model for the Cation Diffusion Facilitator (CDF) superfamily, members of which are generally responsible for homeostasis of transition metal ions. Previous studies of YiiP as well as related CDF transporters have established a homodimeric architecture and the presence of three distinct Zn2+ binding sites named A, B, and C. In this study, we use cryo-EM, microscale thermophoresis and molecular dynamics simulations to address the structural and functional roles of individual sites as well as the interplay between Zn2+ binding and protonation. Structural studies indicate that site C in the cytoplasmic domain is primarily responsible for stabilizing the dimer and that site B at the cytoplasmic membrane surface controls the structural transition from an inward facing conformation to an occluded conformation. Binding data show that intramembrane site A, which is directly responsible for transport, has a dramatic pH dependence consistent with coupling to the proton motive force. A comprehensive thermodynamic model encompassing Zn2+ binding and protonation states of individual residues indicates a transport stoichiometry of 1 Zn2+ to 2–3 H+ depending on the external pH. This stoichiometry would be favorable in a physiological context, allowing the cell to use the proton gradient as well as the membrane potential to drive the export of Zn2+.

Abstract Since the detection of phosphine in the wastewater treatment plants in 1988, more and more investigations revealed that phosphine is closely related to ecological activities on a global scale. Here, we present perspectives on the whole dynamic cycles of phosphorus, particularly in terms of phosphine and its interactions with natural ecosystems, as well as the impacts from human activities. It may conclude that the phosphine-driving cycles of phosphorus depend on the coordination of human activities with natural ecosystems. Most importantly, the extensive recovery of phosphorus in numerous urban wastewater treatment plants may seriously obstruct its global cycles to catch up with the ecological needs in natural ecosystems. Phosphine gas plays an important role in the biogeochemical phosphorus cycle. Phosphorus might be one of the important elements participating in the global climate change together with carbon and nitrogen.

In recent years, antibiotics have been widely used in the treatment of human and animal diseases due to their effectiveness. Most antibiotics enter the environment in the form of primitive or metabolites, making them new environmental pollutants, destroying the ecological environment, and endangering human health. The Fenton method is one of the advanced oxidation technologies including the traditional Fenton method and various Fenton methods. It has a good effect on the degradation of antibiotics in wastewater. Among them, the Fenton-like method has been widely studied by scholars because of its wide pH reaction conditions and better degradation efficiency. This article takes the Fenton-like reaction as the research object to study the catalytic and promotion effect of iron oxide as a catalyst on the degradation of antibiotics in the Fenton-like reaction. The experimental results show that the iron oxide catalytic system is much better than the traditional ferrous ion-catalyzed Fenton system to degrade antibiotics. Under certain experimental conditions, the degradation rate of ofloxacin in the Fe3O4-H2O2 reaction system for 72 hours reached 79.3%.

KdpFABC is an ATP-dependent K+ pump that ensures bacterial survival in K+-deficient environments. Whereas transcriptional activation of kdpFABC expression is well studied, a mechanism for down-regulation when K+ levels are restored has not been described. Here, we show that KdpFABC is inhibited when cells return to a K+-rich environment. The mechanism of inhibition involves phosphorylation of Ser162 on KdpB, which can be reversed in vitro by treatment with serine phosphatase. Mutating Ser162 to Alanine produces constitutive activity, whereas the phosphomimetic Ser162Asp mutation inactivates the pump. Analyses of the transport cycle show that serine phosphorylation abolishes the K+-dependence of ATP hydrolysis and blocks the catalytic cycle after formation of the aspartyl phosphate intermediate (E1~P). This regulatory mechanism is unique amongst P-type pumps and this study furthers our understanding of how bacteria control potassium homeostasis to maintain cell volume and osmotic potential.

Abstract Background DNA methylation in CpG context is fundamental to the epigenetic regulation of gene expression in higher eukaryotes. Changes in methylation patterns are implicated in many diseases, cellular differentiation, imprinting, and other biological processes. Techniques that enrich for biologically relevant genomic regions with high CpG content are desired, since, depending on the size of an organism’s methylome, the depth of sequencing required to cover all CpGs can be prohibitively expensive. Currently, restriction enzyme-based reduced representation bisulfite sequencing and its modified protocols are widely used to study methylation differences. Recently, Agilent Technologies, Roche NimbleGen, and Illumina have ventured to both reduce sequencing costs and capture CpGs of known biological relevance by marketing in-solution custom-capture hybridization platforms. We aimed to evaluate the similarities and differences of these four methods considering each platform targets approximately 10–13% of the human methylome. Results Overall, the regions covered per platform were as expected: targeted capture-based methods covered > 95% of their designed regions, whereas the restriction enzyme-based method covered > 70% of the expected fragments. While the total number of CpG loci shared by all methods was low, ~ 24% of any platform, the methylation levels of CpGs covered by all platforms were concordant. Annotation of CpG loci with genomic features revealed roughly the same proportions of feature annotations across the four platforms. Targeted capture methods comprise similar types and coverage of annotations and, relative to the targeted methods, the restriction enzyme method covers fewer promoters (~ 9%), CpG shores (~ 8%) and unannotated loci (~ 11%). Conclusions Although all methods are largely consistent in terms of covered CpG loci, the commercially available capture methods result in covering nearly all CpG sites in their target regions with few off-target loci and covering similar proportions of annotated CpG loci, the restriction-based enrichment results in more off-target and unannotated CpG loci. Quality of DNA is very important for restriction-based enrichment and starting material can be low. Conversely, quality of the starting material is less important for capture methods, and at least twice the amount of starting material is required. Pricing is marginally less for restriction-based enrichment, and the number of samples that can be prepared is not restricted to the number of capture reactions a kit supports. However, the advantage of capture libraries is the ability to custom design areas of interest. The choice of the technique would be decided by the number of samples, the quality and quantity of DNA available and the biological areas of interest since comparable data are obtained from all platforms.

This work presents an effective approach for manganese-doped Al2O3 ceramic membrane (Mn-doped membrane) fouling control by in-situ confined H2O2 cleaning in wastewater treatment. An Mn-doped membrane with 0.7 atomic percent Mn doping in the membrane layer was used in a membrane bioreactor with the aim to improve the catalytic activity toward oxidation of foulants by H2O2. Backwashing with 1 mM H2O2 solution at a flux of 120 L/m2/h (LMH) for 1 min was determined to be the optimal mode for in-situ H2O2 cleaning, with confined H2O2 decomposition inside the membrane. The Mn-doped membrane with in-situ H2O2 cleaning demonstrated much better fouling mitigation efficiency than a pristine Al2O3 ceramic membrane (pristine membrane). With in-situ H2O2 cleaning, the transmembrane pressure increase (ΔTMP) of the Mn-doped membrane was 22.2 kPa after 24-h filtration, which was 40.5% lower than that of the pristine membrane (37.3 kPa). The enhanced fouling mitigation was attributed to Mn doping, in the Mn-doped membrane layer, that improved the membrane surface properties and confined the catalytic oxidation of foulants by H2O2 inside the membrane. Mn3+/Mn4+ redox couples in the Mn-doped membrane catalyzed H2O2 decomposition continuously to generate reactive oxygen species (ROS) (i.e., HO• and O21), which were likely to be confined in membrane pores and efficiently degraded organic foulants.

Phased-array antennas are known for their capability to electronically steer a beam with high effectiveness, but beam steering is fixed in an angle for all range cells. Different from that, frequency diverse array (FDA) offers a range-angle-dependent beam-pattern. The use of a small frequency increment across its array elements to generate an array factor that is a function of the angle, time, and range, allowing the FDA antenna to form focusing beampattern to the desired range and angle region. Aiming to resolve the problem that traditional phased-array radars can be easy detected and localised by undesired reconnaissance receiver, the use of FDA instead of phased-array provides potential radio frequency (RF) stealth capability. Here, the authors analyse the RF localisation deception performance under interferometry reconnaissance for undesired receivers, which RF stealth capability is validated by the numerical results.

Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.

In 2021, the University of North Alabama decided to invest $2.5 million per year in scholarships for the next 10 years supporting students pursuing computing degrees. This paper will tell the story of why the university officials decided to make this major investment, how the computing department developed a process to screen and award scholarships and examine the initial findings during the first three years of this initiative. Post-implementation data reveals a consistent increase in enrollments, alongside notable findings from qualitative survey responses. The research demonstrates that well-designed scholarship programs can significantly enhance enrollments, draw talented students, and offer transformative opportunities for financially disadvantaged individuals. [ABSTRACT FROM AUTHOR]

According to the 2021 Film and Video Global Market Report, the global film and video market is expected to reach $318.2 billion by 2025 and $410.6 billion by 2030. The financial success of a movie, though, is largely uncertain due to many pertinent factors. Understanding which factors influence the financial success of a movie is crucial for the industry. The online movie rating is often used to measure a movie's success and has been investigated in many IS studies. The factors influencing online movie ratings can be classified into two major types: internal and external. Internal factors, such as actors, actresses, directors, and "stars," influence movie ratings and are related to the movie cast and crew. External factors, such as economics, motivations for moviegoing, and advertising effects, are movie rating influencers from the outside environment. Few studies focus on both the effect of individual and team characteristics on online movie ratings. Our research question is: How do team patterns, such as actors/actresses, experienced crew, and collaboration among team members, influence movie ratings? Using both decision tree model and neural network machine learning (ML) techniques, this research investigates the effects of movie team patterns on movie ratings. We make comparisons using OLS (ordinary least squares) regression for each ML technique. The results indicate that some crews and casts of a movie, especially experienced directors, play a critical role in determining the online movie rating. The results also demonstrate the power of the decision tree model and neural network in predicting online movie ratings. [ABSTRACT FROM AUTHOR]

The tech industry is experiencing a growing demand for skilled professionals, leading to the emergence of accelerated courses as a potential solution to the talent shortage. To address the increasing number of vacant information technology (IT) and cybersecurity positions, educational institutions have begun offering accelerated courses and programs aimed at reducing the time needed to obtain an IT degree. This qualitative research study aims to examine student perceptions of accelerated (8-week) courses compared to regular (16-week) courses. The study surveyed 82 students from three universities in New Mexico, Alabama, and Florida. The findings highlight unique concerns such as scheduling, focus, stress, workload, and content coverage in accelerated courses, while course difficulty favored regular courses with longer durations. Common themes favorable to both course types include retention, learning, preference, and pace. [ABSTRACT FROM AUTHOR]