Removal of Antibiotic-Resistant Bacteria and Antibiotic Resistance Genes Affected by Varying Degrees of Fouling on Anaerobic Microfiltration Membranes

An anaerobic membrane bioreactor was retrofitted with polyvinylidene fluoride (PVDF) microfiltration membrane units, each of which was fouled to a different extent. The membranes with different degrees of fouling were evaluated for their efficiencies in removing three antibiotic-resistant bacteria (ARB), namely, <i>bla</i>_NDM‑1-positive <i>Escherichia coli</i> PI-7, <i>bla</i>_CTX‑M‑15<i>-</i>positive <i>Klebsiella pneumoniae</i> L7, and <i>bla</i>_OXA‑48-positive <i>E. coli</i> UPEC-RIY-4, as well as their associated plasmid-borne antibiotic resistance genes (ARGs). The results showed that the log removal values (LRVs) of ARGs correlated positively with the extent of membrane fouling and ranged from 1.9 to 3.9. New membranes with a minimal foulant layer could remove more than 5 log units of ARB. However, as the membranes progressed to subcritical fouling, the LRVs of ARB decreased at increasing operating transmembrane pressures (TMPs). The LRV recovered back to 5 when the membrane was critically fouled, and the achieved LRV remained stable at different operating TMPs. Furthermore, characterization of the surface attributed the removal of both the ARB and ARGs to adsorption, which was facilitated by an increasing hydrophobicity and a decreasing surface ζ potential as the membranes fouled. Our results indicate that both the TMP and the foulant layer synergistically affected ARB removal, but the foulant layer was the main factor that contributed to ARG removal

Additional file 1: of Application of hierarchical oligonucleotide primer extension (HOPE) to assess relative abundances of ammonia- and nitrite-oxidizing bacteria

Target coverage for the different primers used in this study. (PDF 1668 kb

Dual-Stimulus-Responsive Fluorescent Supramolecular Prodrug for Antitumor Drug Delivery

To achieve higher bioavailability by taking advantage of the complex biological environment, the development of drug delivery systems (DDSs) keeps progressing. Through supramolecular technology, building blocks with different properties and functions could be combined in a controlled manner, realizing programmable drug delivery with high efficiency. In this study, we constructed a supramolecular DDS (SDDS) with charge-reversal polyanions and fluorescent polycations with reduction cleavable camptothecin (CPT) attached. During the supramolecular assembly process, the prodrug exhibited a morphological change from cubelike to rodlike and its fluorescence was significantly enhanced. Programmed drug delivery was achieved by a dual response of the extracellular acid and intracellular reductive environment. <i>In vitro</i> studies of the SDDS made it possible to visualize faster cellular uptake at pH 6.8 than at pH 7.4 because of the re-exposure of cationic charges and subsequent successful delivery of CPT to the cell nucleus. In the <i>in vivo</i> studies, SDDS treatment through tail vein injection showed enhanced tumor suppression compared with that of the cationic prodrug and free CPT treatment at a low concentration (1.5 mg/kg of CPT equivalents). Altogether, we developed a novel fluorescent supramolecular system as a tumor microenvironment-responsive carrier of hydrophobic drugs for programmed drug delivery, which could be used in future cancer therapy

Ultrafast Hydrogen Exchange Reveals Specific Structural Events during the Initial Stages of Folding of Cytochrome <i>c</i>

Many proteins undergo a sharp decrease in chain dimensions during early stages of folding, prior to the rate-limiting step in folding. However, it remains unclear whether compact states are the result of specific folding events or a general hydrophobic collapse of the poly peptide chain driven by the change in solvent conditions. To address this fundamental question, we extended the temporal resolution of NMR-detected H/D exchange labeling experiments into the microsecond regime by adopting a microfluidics approach. By observing the competition between H/D exchange and folding as a function of labeling pH, coupled with direct measurement of exchange rates in the unfolded state, we were able to monitor hydrogen-bond formation for over 50 individual backbone NH groups within the initial 140 microseconds of folding of horse cytochrome <i>c</i>. Clusters of solvent-shielded amide protons were observed in two α-helical segments in the C-terminal half of the protein, while the N-terminal helix remained largely unstructured, suggesting that proximity in the primary structure is a major factor in promoting helix formation and association at early stages of folding, while the entropically more costly long-range contacts between the N- and C-terminal helices are established only during later stages. Our findings clearly indicate that the initial chain condensation in cytochrome <i>c</i> is driven by specific interactions among a subset of α-helical segments rather than a general hydrophobic collapse

DataSheet_1_Deep learning architectures for diagnosing the severity of apple frog-eye leaf spot disease in complex backgrounds.pdf

IntroductionIn precision agriculture, accurately diagnosing apple frog-eye leaf spot disease is critical for effective disease management. Traditional methods, predominantly relying on labor-intensive and subjective visual evaluations, are often inefficient and unreliable.MethodsTo tackle these challenges in complex orchard environments, we develop a specialized deep learning architecture. This architecture consists of a two-stage multi-network model. The first stage features an enhanced Pyramid Scene Parsing Network (L-DPNet) with deformable convolutions for improved apple leaf segmentation. The second stage utilizes an improved U-Net (D-UNet), optimized with bilinear upsampling and batch normalization, for precise disease spot segmentation.ResultsOur model sets new benchmarks in performance, achieving a mean Intersection over Union (mIoU) of 91.27% for segmentation of both apple leaves and disease spots, and a mean Pixel Accuracy (mPA) of 94.32%. It also excels in classifying disease severity across five levels, achieving an overall precision of 94.81%.DiscussionThis approach represents a significant advancement in automated disease quantification, enhancing disease management in precision agriculture through data-driven decision-making.</p

DataSheet1_Healthcare professionals’ knowledge, attitude and practice towards National Centralized Drug Procurement policy in central China: A cross-sectional study.pdf

Background: National Centralized Drug Procurement (NCDP), an ongoing government-led policy starting in 2019 in China, aimed at reducing drug costs. During the implementation of NCDP, healthcare professionals (HCPs) still have a certain degree of concern about the policy, which affects the clinical use of related drugs.Objective: This study aims to assess the level of knowledge, attitude and practice (KAP) of HCPs towards NCDP policy, together with the associated factors that determine their KAP.Methods: A cross-sectional study was conducted between September and November of 2021 in 30 hospitals in Hubei province in Central China. A self-designed online questionnaire including KAP towards NCDP policy was administered to HCPs. Logistic regression analysis was adopted to identify the factors associated with KAP.Results: A Total of, 742 HCPs completed the questionnaires. 43.4% of HCPs had good knowledge, 24.7% had a positive attitude, and 23.7% held good practice. Through multivariate logistic regression analysis, HCPs who are males, pharmacists, with senior professional titles and 6–10 years of professional working experience contributed to a higher knowledge level. Pharmacists and HCPs with good knowledge were more likely to have positive attitudes, while HCPs with higher education were less likely to have positive attitudes. Pharmacists, HCPs who had 11–20 years of professional working experience, worked in medium-size urban areas or had good knowledge were more likely to have good practice. Good practice is also associated with the positive attitude towards the efficacy of centralized-purchased medicines and impacts of NCDP policy.Conclusion: Only a small percentage of HCPs had good KAP towards NCDP policy. Pharmacists showed better KAP than physicians. The positive attitude towards the efficacy of centralized-purchased medicines and impacts of NCDP policy contributed to better practice. High-quality clinical evidence on the therapeutic effects and safety of the centralized-purchased drugs is needed.</p

A trust network.

<p>A circle denotes a node, an arrow represents a trust relationship between two nodes, and the associated weight denotes the trust score.</p

Summary of the datasets.

<p>Kaitiaki is a unsigned trust network dataset, while Epinions, Slashdot1, Slashdot2, and Slashdot3 are signed trust network datasets.</p

Bias scores by the -MAX algorithm.

<p>The table shows the bias scores by the -MAX algorithm in the trust network given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050843#pone-0050843-g001" target="_blank">Figure 1</a>. The -MAX algorithm converges in 5 iterations, and node 5 achieves the highest bias score.</p

Dong_et_al_2004_datamatrix

Cladistic data matri