A New Strategy for Efficient Retrospective Data Analyses for Designer Benzodiazepines in Large LC-HRMS Datasets

The expanding and dynamic market of new psychoactive substances (NPSs) poses challenges for laboratories worldwide. The retrospective data analysis (RDA) of previously analyzed samples for new targets can be used to investigate analytes missed in the first data analysis. However, RDA has historically been unsuitable for routine evaluation because reprocessing and reevaluating large numbers of forensic samples are highly work- and time-consuming. In this project, we developed an efficient and scalable retrospective data analysis workflow that can easily be tailored and optimized for groups of NPSs. The objectives of the study were to establish a retrospective data analysis workflow for benzodiazepines in whole blood samples and apply it on previously analyzed driving-under-the-influence-of-drugs (DUID) cases. The RDA workflow was based on a training set of hits in ultrahigh-performance liquid chromatography–quadrupole time-of-flight–mass spectrometry (UHPLC-QTOF-MS) data files, corresponding to common benzodiazepines that also had been analyzed with a complementary UHPLC–tandem mass spectrometry (MS/MS) method. Quantitative results in the training set were used as the true condition to evaluate whether a hit in the UHPLC-QTOF-MS data file was true or false positive. The training set was used to evaluate and set filters. The RDA was used to extract information from 47 DBZDs in 13,514 UHPLC-QTOF-MS data files from DUID cases analyzed from 2014 to 2020, with filters on the retention time window, count level, and mass error. Sixteen designer and uncommon benzodiazepines (DBZDs) were detected, where 47 identifications had been confirmed by using complementary methods when the case was open (confirmed positive finding), and 43 targets were not reported when the case was open (tentative positive finding). The most common tentative and confirmed findings were etizolam (n = 26), phenazepam (n = 13), lorazepam (n = 9), and flualprazolam (n = 8). This method efficiently found DBZDs in previously acquired UHPLC-QTOF-MS data files, with only nine false-positive hits. When the standard of an emerging DBZD becomes available, all previously acquired DUID data files can be screened in less than 1 min. Being able to perform a fast and accurate retrospective data analysis across previously acquired data files is a major technological advancement in monitoring NPS abuse

Pyramiding of gn1a, gs3, and ipa1 Exhibits Complementary and Additive Effects on Rice Yield

Pyramiding of quantitative trait loci (QTLs) is a powerful approach in breeding super-high-yield varieties. However, the performance of QTLs in improving rice yield varies with specific genetic backgrounds. In a previous study, we employed the CRISPR/Cas9 system to target three yield-related genes, gn1a, gs3, and ipa1 in japonica ‘Zhonghua 11’, mutants of which featured large panicle, big grain, few sterile tillers, and thicker culm, respectively. In this paper, four pyramided lines, including gn1a-gs3, gn1a-ipa1, gs3-ipa1, and gn1a-gs3-ipa1, were further generated by conventional cross-breeding to be tested. Agronomic traits analysis showed that: (1) the stacking lines carried large panicles with an increased spikelet number in the main panicle or panicle; (2) the grain weight of the stacking lines, especially gs3-ipa1 and gn1a-gs3-ipa1, were heavier than those in single mutants; (3) both gn1a-gs3 and gs3-ipa1 produced more grain yield per plant than single mutant lines; (4) pyramided lines were higher than single mutants and transcriptome analysis found improved expression levels of genes related to lipid, amino acid, and carbohydrate transport and metabolism in lines pyramiding three mutant alleles, possibly as a result of complementary and additive effects. Accordingly, the alteration of gene-expression patterns relating to hormone signaling, plant growth, and seed size control was characterized in pyramided lines. The present study not only investigates the effects of pyramiding genes, but also may provide an efficient strategy for breeding super-high-yield rice by reducing the time cost of developing pyramided lines

Myo‐inositol‐1‐phosphate synthase (Ino‐1) functions as a protection mechanism in Corynebacterium glutamicum under oxidative stress

Abstract Reactive oxygen species (ROS) generated in aerobic metabolism and oxidative stress lead to macromolecules damage, such as to proteins, lipids, and DNA, which can be eliminated by the redox buffer mycothiol (AcCys‐GlcN‐Ins, MSH). Myo‐inositol‐phosphate synthase (Ino‐1) catalyzes the first committed step in the synthesis of MSH, thus playing a critical role in the growth of the organism. Although Ino‐1s have been systematically studied in eukaryotes, their physiological and biochemical functions remain largely unknown in bacteria. In this study, we report that Ino‐1 plays an important role in oxidative stress resistance in the gram‐positive Actinobacteria Corynebacterium glutamicum. Deletion of the ino‐1 gene resulted in a decrease in cell viability, an increase in ROS production, and the aggravation of protein carbonylation levels under various stress conditions. The physiological roles of Ino‐1 in the resistance to oxidative stresses were corroborated by the absence of MSH in the Δino‐1 mutant. In addition, we found that the homologous expression of Ino‐1 in C. glutamicum yielded a functionally active protein, while when expressed in Escherichia coliBL21(DE3), it lacked measurable activity. An examination of the molecular mass (Mr) suggested that Ino‐1 expressed in E. coliBL21(DE3) was not folded in a catalytically competent conformation. Together, the results unequivocally showed that Ino‐1 was important for the mediation of oxidative resistance by C. glutamicum

Dexmedetomidine combined with ropivacaine in ultrasound-guided tranversus abdominis plane block improves postoperative analgesia and recovery following laparoscopic colectomy.

The present prospective, double blind, randomized clinical study was designed to evaluate whether dexmedetomidine (Dex) combined with ropivacaine for tranversus abdominis plane (TAP) block could improve analgesic quality and duration, and promote recovery following laparoscopic colectomy. Following induction of anesthesia, ultrasound-guided bilateral TAP block was performed in 60 patients scheduled for elective laparoscopic colectomy with either 20 ml of 0.375% ropivacaine plus 2 ml normal saline 0.9% (R group), or 20 ml of 0.375% ropivacaine plus 2 ml Dex (0.5 µg/kg) (RD group). Visual analogue scale (VAS) score for pain, sedation level, length of hospital stay (LOS), and bowel function recovery time and associated complications were recorded. Overall patient satisfaction with postoperative pain management was also assessed. The hemodynamic variables were not significantly different between the two groups during the surgery. However, the duration of analgesia was significantly longer in the RD group compared with the R group (P<0.05). VAS scores at 1, 2, 6 and 12 h following surgery were significantly decreased in the RD group compared with those in the R group (P<0.05). There was no significant difference in sedation level between the two groups. Notably, postoperative nausea and vomiting in the RD group was significantly decreased compared with those in the R group in the first 24 h (P<0.05). There were no serious adverse events in any group. Furthermore, 90.0 and 66.7% patients were satisfied with the postoperative pain management in the RD group and R group, respectively. The postoperative first bowel movement time was significantly shorter in the RD group compared with the R group (P<0.05). However, the LOS was not significantly different between the two groups. In conlusion, the addition of Dex to ropivacaine could significantly improve the analgesic quality and duration of TAP block, which in turn promotes recovery following laparoscopic colectomy

Calculation of Carbon Emissions and Study of the Emission Reduction Path of Conventional Public Transportation in Harbin City

As the northernmost megacity in China, the long winters, large population size, and unsustainable transport structure in Harbin determine that the city will produce relatively large carbon emissions. The transportation industry is one of the three greenhouse gas emission sources; therefore, the development of low-carbon transportation is imperative. This work compares commonly used carbon emission measurement methods and chooses a mileage method to classify the carbon emissions of conventional buses of different energy types used in Harbin in 2020. A multi-factor grey prediction model was constructed to predict the population size of Harbin and the number of conventional buses. After that, a scenario analysis method was used to analyze the fuel structure of buses in Harbin from three perspectives: a pessimistic scenario, a baseline scenario, and an optimistic scenario. The carbon emissions of conventional buses were calculated for Harbin from 2023 to 2030. Finally, by combining the prediction results and factors influencing carbon emission, a regular bus path to minimize carbon emissions is proposed. The outcome of this study shows that the carbon emission environment in Harbin will be improved by reducing vehicle energy consumption, optimizing energy structure, standardizing driving behavior, building intelligent transportation, giving priority to public transportation, and improving the road network structure

A New Strategy for Efficient Retrospective Data Analyses for Designer Benzodiazepines in Large LC-HRMS Datasets

The expanding and dynamic market of new psychoactive substances (NPSs) poses challenges for laboratories worldwide. The retrospective data analysis (RDA) of previously analyzed samples for new targets can be used to investigate analytes missed in the first data analysis. However, RDA has historically been unsuitable for routine evaluation because reprocessing and reevaluating large numbers of forensic samples are highly work- and time-consuming. In this project, we developed an efficient and scalable retrospective data analysis workflow that can easily be tailored and optimized for groups of NPSs. The objectives of the study were to establish a retrospective data analysis workflow for benzodiazepines in whole blood samples and apply it on previously analyzed driving-under-the-influence-of-drugs (DUID) cases. The RDA workflow was based on a training set of hits in ultrahigh-performance liquid chromatography–quadrupole time-of-flight–mass spectrometry (UHPLC-QTOF-MS) data files, corresponding to common benzodiazepines that also had been analyzed with a complementary UHPLC–tandem mass spectrometry (MS/MS) method. Quantitative results in the training set were used as the true condition to evaluate whether a hit in the UHPLC-QTOF-MS data file was true or false positive. The training set was used to evaluate and set filters. The RDA was used to extract information from 47 DBZDs in 13,514 UHPLC-QTOF-MS data files from DUID cases analyzed from 2014 to 2020, with filters on the retention time window, count level, and mass error. Sixteen designer and uncommon benzodiazepines (DBZDs) were detected, where 47 identifications had been confirmed by using complementary methods when the case was open (confirmed positive finding), and 43 targets were not reported when the case was open (tentative positive finding). The most common tentative and confirmed findings were etizolam (n = 26), phenazepam (n = 13), lorazepam (n = 9), and flualprazolam (n = 8). This method efficiently found DBZDs in previously acquired UHPLC-QTOF-MS data files, with only nine false-positive hits. When the standard of an emerging DBZD becomes available, all previously acquired DUID data files can be screened in less than 1 min. Being able to perform a fast and accurate retrospective data analysis across previously acquired data files is a major technological advancement in monitoring NPS abuse

The minimum inhibitory concentrations (MICs) of various antibiotics for <i>C</i>. <i>glutamicum</i> strains.

<p>**<i>P</i>≤0.01 versus wild type for the mutants.</p>a<p>The values are mean±SD for three independent determinations.</p><p>The minimum inhibitory concentrations (MICs) of various antibiotics for <i>C</i>. <i>glutamicum</i> strains.</p

Effects of divalent metal cations and pH on <i>C. glutamicum</i> Mca activity.

<p><b>A–E.</b> Catalytic activity of Mca in the presence of Co²⁺(A), Mn²⁺(B), Ni²⁺(C), Zn²⁺(D) and Fe²⁺(E), respectively, was analyzed with GlcNAc or MSmB as substrates. Apo-Mca was incubated with stoichiometric amounts of metal ions. After 30 min, the enzyme was diluted into assay buffer containing the substrate GlcNAc (5 mM) or MSmB (1 mM). The amidase activity (Left Y axis) and deacetylase activity (Right Y axis) were measured as described in “Materials and Methods”. <b>F.</b> Deacetylation of GlcNAc and amidase activity of MSmB by Zn²⁺-Mca at different pH levels. The <i>V/K</i> values were measured with 5 mM GlcNAc as substrate for deacetylase activity (Left Y axis) or 1 mM MSmB as substrate for amidase activity (Right Y axis) under six different pH values. <i>pK</i>_a values of 6.5 and 9.5 were determined by fitting <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115075#pone.0115075.e001" target="_blank">Equation 1</a> to the data (bars represent standard error of the mean).</p

Michaelis-Menten parameters of Mca for <i>N</i>-deacetylation of GlcNAc and for amidase activity of MSmB.

a<p>Assays were performed using 10 µM enzyme and 0–10 mM MSmB in 50 mM HEPES (pH 7.5) at 37°C.</p>b<p>Assays were performed in the presence of 10 µM enzyme and 0–5.0 mM GlcNAc in 50 mM HEPES (pH 7.5) at 30°C.</p><p>Michaelis-Menten parameters of Mca for <i>N</i>-deacetylation of GlcNAc and for amidase activity of MSmB.</p