Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes.

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno and Aytan-Aktug), an ML baseline and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amoxicillin/clavulanic acid, cefoxitin, ceftazidime and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, Campylobacter jejuni and Enterococcus faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

Stable Isotope Ratios Trace the Rice Uptake of Cadmium from Atmospheric Deposition via Leaves and Roots.

Cadmium (Cd) stable isotopes provide a novel technique to investigate the fate of Cd in the environment, but challenges exist for tracing the sources in the plants. We performed individual rice leaf and root exposures to dry and wet deposition using customized open-top chambers (OTCs) in the greenhouse and in the field next to a smelter, respectively. The field experiment also included a control without Cd deposition and a "full" treatment. The exposure experiments and isotope signatures showed that leaves can directly take up atmospheric Cd and then translocate within rice plants to other tissues, contributing 52-70% of Cd in grains, which exceeded the contribution (30-48%) by root exposure. The Cd isotopes in leaves, nodes, internodes, and grains demonstrate that roots preferentially take up Cd from wet deposition, but leaves favor uptake of Cd from dry deposition. The Cd uptake by leaves is redistributed via nodes, allowing for upward transport to the grains but preventing downward transport to the roots. Leaves favor uptake of heavy isotopes from atmospheric deposition (ΔCd114/110Leaf-Dust: 0.10 ± 0.02‰) but retain light isotopes and transport heavy isotopes to the nodes and further to grains. These findings highlight the contribution of atmospheric deposition to rice and Cd isotopes as a useful tracer for quantifying sources in plants when different isotopic compositions are in sources.

Machine learning-based nomogram for 30-day mortality prediction for patients with unresectable malignant biliary obstruction after ERCP with metal stent: a retrospective observational cohort study.

BACKGROUND: This study aimed to investigate the risk factors for 30-day mortality in patients with malignant biliary obstruction (MBO) after endoscopic retrograde cholangiopancreatography (ERCP) with endobiliary metal stent placement. Furthermore, we aimed to construct and visualize a prediction model based on LASSO-logistic regression. METHODS: Data were collected from 245 patients who underwent their first ERCP with endobiliary metal stent placement for unresectable MBO between June 1, 2013, and August 31, 2021. Univariable and multivariable logistic regression analyses were conducted to identify the risk factors for 30-day mortality. We subsequently developed a logistic regression model that incorporated multiple parameters identified by LASSO regression. The model was visualized and the nomogram was plotted. Risk stratification was performed based on nomogram-derived scores. RESULTS: The 30-day mortality rate was 10.7% (23/245 patients). Distant metastasis, total bilirubin, post-ERCP complications, and successful drainage were independent risk factors of 30-day mortality. The variables screened by LASSO regression, including distant metastasis, total bilirubin, post-ERCP complications, and successful drainage, were incorporated into the logistic model. The results were visualized through a nomogram based on the model. To assess the model's performance, discrimination was evaluated using the area-under-the-curve values obtained from receiver operating characteristic analyses with 10-fold cross-validation in the training group and validated in the testing group. The calibration curve showed the good predictive ability of the model. Decision curve analysis is used to evaluate the clinical application of nomogram. Finally, we performed risk stratification based on the risk calculated using the nomogram. Patients were assigned to the low-, moderate-, and high-risk groups based on their probability scores. The Kaplan-Meier survival curves for the different nomogram-based groups were significantly different (p < 0.001). CONCLUSIONS: We developed a nomogram using the LASSO-logistic regression model to forecast the 30-day mortality rate in patients who had undergone ERCP with endobiliary metal stent placement due to MBO. This nomogram can assist in identifying individuals at high-risk of 30-day mortality following ERCP.

Impacts of atmospheric deposition on the heavy metal mobilization and bioavailability in soils amended by lime.

Atmospheric deposition is an important source of heavy metal in agricultural soils, but there is limited research on the mobility of these metals in soil and their impact on soil amendment. Here, we performed a dust incubation experiment in soils in the laboratory and a factorial transplant experiment at three field sites with a gradient of atmospheric deposition to examine the impacts of atmospherically deposited heavy metals (Cu, Cd, and Pb) on the mobility and bioavailability in soils with and without lime applications. Results showed that the atmospherically deposited heavy metals showed high mobility and were primarily presented in the soluble ionic fractions in the wet part and acid-exchangeable and reducible fractions in the dry part of atmospheric deposition. Atmospheric dust addition caused the 2p3/2 and 2p1/2 electrons of Cu atoms in uncontaminated soils to transition the 3d vacant states, resulting in similar copper absorption peaks as atmospheric particles by the observation of X-ray absorption near-edge spectroscopy (XANES). In the field, atmospheric deposition can only increase the mobile fractions in the surface soils, but not in the deeper layers. However, the deposition can increase the soluble and diffusive gradients in thin films (DGT)-measured bioavailable fractions in profile along with the soil depth. Lime applications cannot significantly reduce the mobile fractions of heavy metals in the surface soils exposed to atmospheric deposition, but significantly reduce the heavy metal concentrations in soil solutions and the DGT-measured bioavailable concentrations, particularly in the deeper layer (6-10 cm). The major implication is that atmospherically deposited heavy metals can significantly increase their bioavailable concentrations in the plough horizon of soil and constrain the effects of soil amendments on heavy metal immobilization, thereby increasing the risks of crop uptake.

Chiral carbon dots derived from tryptophan and threonine for enantioselective sensing of L/D-Lysine.

Presently, most fluorescent probes for amino acid enantiomers detection require metal ions participation, which greatly increases the detection steps and costs, and affects the accuracy of detection results. To solve this problem, a dual pattern recognition sensor of chiral carbon dots (L-Try-Thr-CDs) with a quantum yield of 36.23 % was prepared by a one-step solvothermal method for the highly selective detection of lysine (Lys) enantiomers. Under optimal experimental conditions, the fluorescence and circular dichroism (CD) signals of the obtained L-Try-Thr-CDs could rapidly and effectively responded to L-Lys with limits of detection (LOD) of 16.51 nM and 24.38 nM, respectively, much lower than previously reported sensors. Importantly, the L-Try-Thr-CDs as a dual-mode sensor could not only detect amino acid enantiomers and simplify the steps, but also avoid inaccurate detection results due to unstable metal ions. Furthermore, the L-Try-Thr-CDs could detect L-Lys in living cells via a fluorescence microscope because of their excellent fluorescence characteristics and low toxicity. These results indicated that the dual-mode sensor not only provided a practical strategy for the design of new fluorescent probes, but also possessed outstanding application prospects in the accurate detection of lysine enantiomers.

Effect of Initial Surface Scratches on the Cavitation Erosion Behavior of 316L Stainless Steel Substrates and 316L Stainless Steel Coatings.

Rough surfaces have been widely considered as negative factors affecting cavitation erosion resistance. However, this study presented the opposite result. Here, 316L stainless steel substrates and the arc-sprayed 316L stainless steel coatings were subjected to a specific grinding process that introduced scratches on the surfaces. The surface hardness values of these ground specimens were measured to evaluate the influence of the grinding-induced strain hardening. The cavitation erosion performance of the specimens was evaluated. The results showed that rough surfaces with scratches could enhance the cavitation erosion resistance, particularly at the early stage of cavitation erosion. The scratches had a greater effect on the cavitation erosion resistance of the coatings than on the substrates. Moreover, rough surfaces with initial surface scratches could extend the incubation period of the 316L stainless steel substrates due to the inhibition of the plastic deformation. The SEM observation showed that the scratch structure of the coating surface inhibited the growth of cracks and the propagation of cavitation pits. This study could also serve as a reference for investigating the cavitation erosion behaviors of materials with a particular surface feature.

Impacts of atmospheric copper and cadmium deposition on the metal accumulation of camphor leaves and rings around a large smelter.

The atmospheric deposition of copper (Cu) and cadmium (Cd) was monitored in eight sites around a Cu smelter with similar distance to verify whether tree leaf and ring can be used as bio-indicators to track spatial pollution record. Results showed that total atmospheric deposition of Cu (103-1215 mg/m2/year) and Cd (3.57-11.2 mg/m2/year) were 4.73-66.6 and 3.15-12.2 times higher than those in background site (164 mg/m2/year and 0.93 mg/m2/year). The frequencies of wind directions significantly influenced the atmospheric deposition of Cu and Cd, and the highest atmospheric deposition of Cu and Cd were at the prevalent northeastern wind (JN), and low frequency south (WJ) and north (SW) winds for the lowest deposition fluxes. Since the bioavailability of Cd was higher than that of Cu, the atmospheric deposition of Cd was more easily adsorbed by tree leaf and ring, resulting in only significant relation between atmospheric Cd deposition and Cinnamomum camphora leaves and tree ring Cd. Although tree rings cannot correctly record the atmospheric Cu and Cd deposition, higher concentrations in the indigenous tree rings than the transplanted tree rings suggested that tree rings can reflect to some extent the variations of atmospheric deposition. Generally, spatial pollution of atmospheric deposition of heavy metals cannot reflect the distribution of soil total and available metals around the smelter, and only camphor leaf and tree ring can bio-indicate Cd deposition. A major implication of these findings is that leaf and tree ring can serve for biomonitoring purposes to assess the spatial distribution of atmospheric deposition metal with high bioavailability around a pollution source with similar distance.

TcpC Inhibits M1 but Promotes M2 Macrophage Polarization via Regulation of the MAPK/NF-κB and Akt/STAT6 Pathways in Urinary Tract Infection.

TcpC is a multifunctional virulence factor of Uropathogenic Escherichia coli (UPEC). Macrophages can differentiate into two different subsets M1 and M2 that play distinct roles in anti-infection immunity. Here, we investigate the influence of TcpC on M1/M2 polarization and the potential mechanisms. Our data showed that M1 markers CD86 and iNOS were significantly inhibited, while the M2 markers CD163, CD206 and Arg-1 were enhanced in macrophages in kidneys from the TcpC-secreting wild-type CFT073 (CFT073wt)-infected pyelonephritis mouse model, compared with those in macrophages in kidneys from TcpC knockout CFT073 mutant (CFT073Δtcpc)-infected mice. CFT073wt or recombinant TcpC (rTcpC) treatment inhibits LPS + IFN-γ-induced CD80, CD86, TNF-α and iNOS expression, but promotes IL-4-induced CD163, CD206, Arg-1 and IL-10 expression in both human and mouse macrophage cell lines THP-1 and J774A.1. Moreover, rTcpC significantly attenuated LPS + IFN-γ-induced phosphorylation of p38, ERK, p50 and p65 but enhanced IL-4-induced phosphorylation of Akt and STAT6. These data suggest that TcpC inhibits M1 but promotes M2 macrophage polarization by down-regulation of p38, ERK/NF-κB and up-regulation of the Akt/STAT6 signaling pathway, respectively. Our findings not only illuminate the regulatory effects of TcpC on macrophage M1/M2 polarization and its related signaling pathways, but also provide a novel mechanism underlying TcpC-mediated immune evasion of macrophage-mediated innate immunity.