Synthetic wastewaters treatment by electrocoagulation to remove silver nanoparticles produced by different routes

International audienceNanoscience is a field that has stood out in recent years. The accurate long-term health and environmental risks associated with these emerging materials are unknown. Therefore, this work investigated how to eliminate silver nanoparticles (AgNPs) from synthetic effluents by electrocoagulation (EC) due to the widespread use of this type of nanoparticle (NP) in industry and its potential inhibition power over microorganisms responsible for biological treatment in effluent treatment plants. Synthesized AgNPs were studied via four different routes by chemical reduction in aqueous solutions to simulate the chemical variations of a hypothetical industrial effluent, and efficiency conditions of the EC treatment were determined. All routes used silver nitrate as the source of silver ions, and two synthesis routes were studied with sodium citrate as a stabilizer. In route I, sodium citrate functioned simultaneously as the reducing agent and stabilizing agent, whereas route II used sodium borohydride as a reducing agent. Route III used d-glucose as the reducing agent and sodium pyrophosphate as the stabilizer; route IV used sodium pyrophosphate as the stabilizing agent and sodium borohydride as the reducing agent. The efficiency of the EC process of the different synthesized solutions was studied. For route I, after 85 min of treatment, a significant decrease in the plasmon resonance peak of the sample was observed, which reflects the efficiency in the mass reduction of AgNPs in the solution by 98.6%. In route II, after 12 min of EC, the absorbance results reached the detection limit of the measurement instrument, which indicates a minimum reduction of 99.9% of AgNPs in the solution. During the 4 min of treatment in route III, the absorbance intensities again reached the detection limit, which indicates a minimum reduction of 99.8%. In route IV, after 10 min of treatment, a minimum AgNP reduction of 99.9% was observed. Based on these results, it was possible to verify that the solutions containing citrate considerably increased the necessary times required to eliminate AgNPs from the synthesized effluent, whereas solutions free of this reagent showed better results on floc formation and, therefore, are best for the treatment. The elimination of AgNPs from effluents by EC proved effective for the studied routes

Methyl (2E)-2-[(2,4-dioxo-1,3-thia­zolidin-3-yl)meth­yl]-3-phenyl­prop-2-enoate

In the title compound, C14H13NO4S, the thia­zolidine ring is essentially planar [maximum deviation = 0.010 (2) Å for the carbonyl C atom between the N and S atoms] and is oriented at a dihedral angle of 60.1 (1)° with respect to the benzene ring. In the crystal, mol­ecules are linked into zigzag chains running along the c axis by C—H⋯O hydrogen bonds. The crystal packing is further stabilized by C—H⋯π inter­actions involving the benzene ring

Methyl (Z)-2-[(2,4-dioxothia­zolidin-3-yl)meth­yl]-3-(2-methyl­phen­yl)prop-2-enoate

The C=C bond in the title compound, C15H15NO4S, has a Z configuration. The thia­zolidine ring is essentially planar [maximum deviation = 0.008 (1) Å for the N atom] and is oriented at a dihedral angle of 59.1 (1)° with respect to the benzene ring. In the crystal, pairs of C—H⋯O hydrogen bonds link centrosymmetrically related mol­ecules into dimers, generating R 2 2(18) ring motifs. The crystal packing is further stabilized by C—H⋯π and C—O⋯π [O⋯centroid = 3.412 (2) Å and C—O⋯centroid = 115.0 (1)°] inter­actions

Transperineal versus transrectal prostate biopsy for predicting the final laterality of prostate cancer : are they reliable enough to select patients for focal therapy? Results from a multicenter international study

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Impact of Mutation Density and Heterogeneity on Papillary Thyroid Cancer Clinical Features and Remission Probability

BACKGROUND: The need to integrate the classification of cancer with information on the genetic pattern has emerged in recent years for several tumors. METHODS: The genomic background of a large series of 208 papillary thyroid cancers (PTC) followed at a single center was analyzed by a custom MassARRAY genotyping platform, which allows the simultaneous detection of 19 common genetic alterations, including point mutations and fusions. RESULTS: Of the PTCs investigated, 71% were found to have pathognomonic genetic findings, with BRAFV600E and TERT promoter mutations being the most frequent monoallelic alterations (42% and 23.5%, respectively), followed by RET/PTC fusions. In 19.2% of cases, two or more point mutations were found, and the co-occurrence of a fusion with one or more point mutation(s) was also observed. Coexisting BRAFV600E and TERT promoter mutations were detected in a subgroup of aggressive PTCs (12%). A correlation between several aggressive features and mutation density was found, regardless of the type of association (i.e., only point mutations, or point mutations and fusions). Importantly, Kaplan-Meier curves demonstrated that mutation density significantly correlated with a higher risk of persistent disease. In most cases, the evaluation of the allelic frequencies normalized for the cancer cell content indicated the presence of the monoallelic mutation in virtually all tumor cells. A minority of cases was found to harbor low allelic frequencies, consistent with the presence of the mutations in a small subset of cancer cells, thus indicating tumor heterogeneity. Consistently, the presence of coexisting genetic alterations with different allelic frequencies in some tumors suggests that PTC can be formed by clones/subclones with different mutational profiles. CONCLUSIONS: A large mono-institutional series of PTCs was fully genotyped by means of a cost- and time-effective customized panel, revealing a strong impact of mutation density and genetic heterogeneity on the clinical features and on disease outcomes, indicating that an accurate risk stratification of thyroid cancer cannot rely on the analysis of a single genetic event. Finally, the heterogeneity found in some tumors warrants attention, since the occurrence of this phenomenon is likely to affect response to targeted therapies

Asymmetric Fluid Criticality I: Scaling with Pressure Mixing

The thermodynamic behavior of a fluid near a vapor-liquid and, hence, asymmetric critical point is discussed within a general ``complete'' scaling theory incorporating pressure mixing in the nonlinear scaling fields as well as corrections to scaling. This theory allows for a Yang-Yang anomaly in which \mu_{\sigma}^{\prime\prime}(T), the second temperature derivative of the chemical potential along the phase boundary, diverges like the specific heat when T\to T_{\scriptsize c}; it also generates a leading singular term, |t|^{2\beta}, in the coexistence curve diameter, where t\equiv (T-T_{\scriptsize c}) /T_{\scriptsize c}. The behavior of various special loci, such as the critical isochore, the critical isotherm, the k-inflection loci, on which \chi^{(k)}\equiv \chi(\rho,T)/\rho^{k} (with \chi = \rho^{2} k_{\scriptsize B}TK_{T}) and C_{V}^{(k)}\equiv C_{V}(\rho,T)/\rho^{k} are maximal at fixed T, is carefully elucidated. These results are useful for analyzing simulations and experiments, since particular, nonuniversal values of k specify loci that approach the critical density most rapidly and reflect the pressure-mixing coefficient. Concrete illustrations are presented for the hard-core square-well fluid and for the restricted primitive model electrolyte. For comparison, a discussion of the classical (or Landau) theory is presented briefly and various interesting loci are determined explicitly and illustrated quantitatively for a van der Waals fluid.Comment: 21 pages in two-column format including 8 figure

A cross-sectional study of SARS-CoV-2 seropositivity among healthcare workers and residents of long-term facilities in Italy, January 2021

Long‐term care facilities (LTCFs) are high‐risk settings for SARS‐CoV‐2 infection. This study aimed to describe SARS‐CoV‐2 seropositivity among residents of LTCFs and health‐care workers (HCWs). Subjects were recruited in January 2021 among unvaccinated HCWs of LTCFs and hospitals and residents of LTCFs in Northern Italy. Information concerning previous SARS‐CoV‐2 infections and a sample of peripheral blood were collected. Anti‐S SARS‐CoV‐2 IgG antibodies were measured using the EUROIMMUN Anti‐SARS‐CoV‐2 QuantiVac ELISA kit (EUROIMMUN Medizinische Labordiagnostika AG). For subjects with previous COVID‐19 infection, gender, age, type of subject (HCW or resident), and time between last positive swab and blood draw were considered as possible determinants of two outcomes: the probability to obtain a positive serological result and antibody titer. Six hundred and fifty‐eight subjects were enrolled. 56.1% of all subjects and 65% of residents presented positive results (overall median antibody titer: 31.0 RU/ml). Multivariable models identified a statistically significant 4% decrease in the estimated antibody level for each 30‐day increase from the last positive swab. HCWs were associated with significant odds for seroreversion over time (OR: 0.926 for every 30 days, 95% CI: 0.860–0.998), contrary to residents (OR: 1.059, 95% CI: 0.919–1.22). Age and gender were not factors predicting seropositivity over time. Residents could have a higher probability of maintaining a seropositive status over time compared to HCWs

Aerobiology of the Wheat Blast Pathogen - Inoculum Monitoring and Detection of Fungicide Resistance Alleles

Wheat blast, caused by the ascomycetous fungus Pyricularia oryzae Triticum lineage (PoTl), is mainly controlled by fungicide use, but resistance to the main fungicide groups—sterol demethylase (DMI), quinone outside (QoI), and succinate dehydrogenase inhibitors (SDHI)—has been reported in Brazil. In order to rationalize fungicide inputs (e.g., choice, timing, dose-rate, spray number, and mixing/alternation) for managing wheat blast, we describe a new monitoring tool, enabling the quantitative measurement of pathogen’s inoculum levels and detection of fungicide resistance alleles. Wheat blast airborne spores (aerosol populations) were monitored at Londrina in Paraná State, a major wheat cropping region in Brazil, using an automated high-volume cyclone coupled with a lab-based quantitative real-time PCR (qPCR) assay. The objectives of our study were as follows: (1) to monitor the amount of PoTl airborne conidia during 2019–2021 based on DNA detection, (2) to reveal the prevalence of QoI resistant (QoI-R) cytochrome b alleles in aerosol populations of wheat blast, and (3) to determine the impact of weather on the dynamics of wheat blast aerosol populations and spread of QoI resistant alleles. PoTl inoculum was consistently detected in aerosols during the wheat cropping seasons from 2019 to 2021, but amounts varied significantly between seasons, with highest amounts detected in 2019. High peaks of PoTl DNA were also continuously detected during the off-season in 2020 and 2021. The prevalence of QoI resistant (QoI-R) cytochrome b G143A alleles in aerosol populations was also determined for a subset of 10 PoTl positive DNA samples with frequencies varying between 10 and 91% using a combination of PCR-amplification and SNP detection pyrosequencing. Statistically significant but low correlations were found between the levels of pathogen and the weather variables. In conclusion, for wheat blast, this system provided prior detection of airborne spore levels of the pathogen and of the prevalence of fungicide resistance alleles

NetKet: A machine learning toolkit for many-body quantum systems

We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and flexible implementation of neural-network quantum states, which are used as a variational ansatz for quantum wavefunctions. NetKet provides algorithms for several key tasks in quantum many-body physics and quantum technology, namely quantum state tomography, supervised learning from wavefunction data, and ground state searches for a wide range of customizable lattice models. Our aim is to provide a common platform for open research and to stimulate the collaborative development of computational methods at the interface of machine learning and many-body physics