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The volatile components of honeysuckle were determined using hydro-distillation (HD), water extraction coupling rectification (WER), and water extraction coupling rectification with solvent extraction (WER-SE). Gas chromatography–mass spectrometry (GC–MS) and headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME/GC–MS) identified 127 compounds. There were 27 common compounds extracted by these methods. A heatmap of the 27 common compounds indicates that WER-SE and WER were complementary approaches. In addition, 59 compounds were detected for the first time in honeysuckle. The results of this study provide a reference for the determination of volatile components in plants. [ABSTRACT FROM AUTHOR]

Among the layered two-dimensional ferromagnetic materials (2D FMs), due to a relatively high TC, the van der Waals (vdW) Fe3GeTe2 (FGT) crystal is of great importance for investigating its distinct magnetic properties. Here, we have carried out static and dynamic magnetization measurements of the FGT crystal with a Curie temperature TC ≈ 204 K. The M–H hysteresis loops with in-plane and out-of-plane orientations show that FGT has a strong perpendicular magnetic anisotropy with the easy axis along its c-axis. Moreover, we have calculated the uniaxial magnetic anisotropy constant (K1) from the SQUID measurements. The dynamic magnetic properties of FGT have been probed by utilizing the high sensitivity electron-spin-resonance (ESR) spectrometer at cryogenic temperatures. Based on an approximation of single magnetic domain mode, the K1 and the effective damping constant (αeff) have also been determined from the out-of-plane angular dependence of ferromagnetic resonance (FMR) spectra obtained at the temperature range of 185 K to TC. We have found large magnetic damping with the effective damping constant αeff ∼ 0.58 along with a broad linewidth (Δ Hpp > 1000 Oe at 9.48 GHz, H ∥ c-axis). Our results provide useful dynamics information for the development of FGT-based spintronic devices. [ABSTRACT FROM AUTHOR]

Here, we have investigated the spin pumping effect of Y3Fe5O12 (YIG)/Cu (tCu nm)/Cr heterostructures at room temperature with the thickness of the Cu interlayer varying from 0.4 nm to 5.0 nm. A huge charge signal Ic = 0.239 μA is observed in a YIG/Cr bilayer with direct contact, whereas Ic drops dramatically by two orders of magnitude when thin Cu interlayers down to 0.4 nm are inserted between YIG and Cr. Meanwhile, the injected spin current Js stays almost invariant for all the heterostructures. The effective spin Hall angle "θSH" of the YIG/Cr interface is found to be three orders of magnitude larger than the spin Hall angle θSH of the bulk Cr layer in YIG/Cu/Cr. The huge spin-charge conversion efficiency at the YIG/Cr interface is attributed to the inverse Rashba–Edelstein effect. Our experimental results demonstrate the dominant role of the interfacial effect in the spin-charge conversion process of the YIG/Cr heterostructures. [ABSTRACT FROM AUTHOR]

Near-infrared spectroscopy (NIR) models built on a particular instrument are often invalid on other instruments due to spectral inconsistencies between the instruments. In the present work, global and robust NIR calibration models were constructed by partial least square (PLS) regression based on hybrid calibration sets, which are composed of both primary and secondary spectra. Three datasets were used as case studies. The first consisted of 72 radix scutellaria samples measured on two NIR spectrometers with known baicalin content. The second was composed of 80 corn samples measured on two instruments with known moisture, oil, and protein concentrations. The third dataset included 279 primary samples of tobacco with known nicotine content and 78 secondary samples of tobacco with known nicotine concentrations. The effect of the number of secondary spectra in the hybrid calibration sets and the methods for selecting secondary spectra on the PLS model performance were investigated by comparing the results obtained from different calibration sets. This study shows that the global and robust calibration models accurately predicted both primary and secondary samples as long as the ratios of the number of primary spectra to the number of secondary spectra were less than 22. The models performance was not influenced by the selection method of the secondary spectra. The hybrid calibration sets included the primary spectral information and also the secondary spectra; information, rendering the constructed global and robust models applicable to both primary and secondary instruments. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Danshen and Zidanshen are successfully classified by near infrared spectroscopy. • Their lipophilic component fingerprints are built by UHPLC and identified by LC–MS. • Lipophilic component fingerprints of Danshen are obviously different from Zidanshen. • Zidanshen has three lipophilic compounds that are not found in Danshen. • The contents of main common compounds are much lower in Zidanshen than in Danshen. Abstract Near infrared spectroscopy (NIR) was applied to discriminate the roots of salvia miltiorhiza Bunge (Danshen for short) and Salvia yunnanensis C. H. Wright (Zidanshen for short) by means of principal component analysis (PCA), improved and simplified K nearest neighbors (IS-KNN). Furthermore, an ultra-high performance liquid chromatographic (UHPLC) coupled with photodiode-array detector was developed for building fingerprints of lipophilic components of Danshen and Zidanshen, respectively. Basing on NIR information, both PCA and IS-KNN method classified the two kinds of Chinese medical herbs with 100% accuracy. The chromatographic fingerprints of the lipophilic components of Danshen and Zidanshen have 10 and 12 common peaks, respectively. Liquid chromatography coupled with mass spectroscopy (LC–MS-MS) was applied to identify these peaks. Among these, three small peaks in the fingerprints of Zidanshen are not found in Danshen, one of which was identified as α-lapachone, and the other two compounds were not yet identified; a small peak after tanshinone IIA in the fingerprints of Danshen was not found in Zidanshen, which was identified as miltirone. The two herbs have 10 common lipophilic components. The similarity between the two reference chromatograms of Zidanshen and Danshen is 0.902, but the mean similaritie between Zidanshen (or Danshen) fingerprints and its own reference chromatogram is 0.973 (or 0.976). The contents of main lipophilic components are significantly lower in Zidanshen than in Danshen (P < 0.01 or P < 0.05). The results indicate that the two Chinese medical materials are not only different in NIR spectra, but also different in species and quantities of lipophilic components. NIR spectra analysis can identify Danshen and Zidanshen rapidly and accurately. UHPLC coupled with MS analysis demonstrates the detail differences between the two herbs both in species and contents of their lipophilic components. [ABSTRACT FROM AUTHOR]

Abstract Measurement environmental changes and spectral signal differences among multi-spectrometers may lead to big error in the process of transferring the model of near infrared (NIR) spectra to secondary instruments. Basing on the common sense, NIR calibration models could be shared directily among multi-instruments, if they were built on the wavelengths at which the spectral signals of secondary instruments are stable and well consistent with the primary's. Present work advanced a method named as screening wavelengths with consistent and stable signals (SWCSS) to transfer NIR calibration models. It eliminates the wavelengths at which the standard deviation of difference spectra between the primary and secondary instruments (SDDSI) is much higher than the standard deviation of precision detection spectra (SDPDS) of a sample tested on the primary and the wavelengths with higher SDPDS values. So that the spectral signals of different instruments at these selected wavelengths are consistent well and stable. The NIR calibration model is built by partial least square regression (PLS) based on the screened wavelengths. Two datasets of corn and radix scutellariae samples measured with different NIR instruments are used to test the performance of the method. The results show that the overall prediction performance of the SWCSS-PLS models for samples measured on secondaries is much better than that of the full-wavelength PLS models. The root mean square of error prediction (RMSEP) of the SWCSS-PLS models for samples tested on secondaries is equivalent or superior to that of the piecewise direct standardization (PDS) correction. The SWCSS-PLS model is of fewer parameters, robust and can give good prediction results for samples of secondary instruments. Because standard samples are no longer needed during transferring the calibration models to secondary instruments, SWCSS-PLS models could be directly shared by multi-spectroscopy instruments. Graphical Abstract Unlabelled Image Highlights • A method named as SWCSS selecting wavelengths to build robust PLS models was advanced. • SWCSS selects consistent and stable spectral variables by analyzing spectra deviation. • The PLS models built by SWCSS are accurate for samples of host and slave instruments. • The SWCSS-PLS models have good transfer performance on multi-instruments. [ABSTRACT FROM AUTHOR]

As new information carriers, antiferromagnetic magnons have great potential in the fields of spintronics and quantum information. However, the strong exchange interaction between sublattice spins in conventional antiferromagnets results in their frequencies up to the terahertz (THz) range, hindering further exploration of related applications and physics. Recently, emerging van der Waals A‐type antiferromagnets with the weak exchange interaction may bring about a change. In this study, it demonstrates two distinct tunable ultrastrong magnon–magnon couplings in the gigahertz (GHz) band using this type of antiferromagnet, CrPS4, with a maximum normalized coupling strength (η) of 0.31. It establishes orthorhombic and monoclinic models for theoretical analyses, unambiguously showing that the ultrastrong coupling strength is caused by unique magnetocrystalline anisotropy rather than exchange enhancement. Furthermore, for the first time, it observes a continuous switching process of sublattice magnon chirality arising from the orthorhombic nature of anisotropy. These findings not only deepen the understanding of antiferromagnetic spin dynamics but also offer a powerful platform for building magnonic quantum systems and chirality‐based spintronics. [ABSTRACT FROM AUTHOR]

[Display omitted] • Scale invariant feature transform (SIFT) method is applied to select characteristic NIR variables. • SIFTur-stable and independent feature variables are screened from the variables selected by SIFT. • PLS models built on SIFTur at many nLVs work well for both master and slave samples. In order to realize calibration model transfer of near infrared (NIR) spectra without standards, scale invariant feature transform (SIFT) algorithm was applied to extract characteristic spectral points of NIR spectra in this study. Three sets of spectral points were selected by SIFT from the spectra of precision detection (SPD) of a radix scutellariae sample by continuously testing the sample three times. Aiming at obtaining high consistency of the three sets, the orthogonal table L9 (34) was used to optimize the parameters of SIFT. Basing on the NIR spectra of several representative radix scutellariae samples, a series of spectral point sets were screened by SIFT with the optimized parameters. Three methods of further treating the spectral points sets to optimize the combination of the spectral points and provided three spectral point sets, which were recorded as U i , U u and U ur , respectively. The partial least square (PLS) calibration models for predicting baicalin content of radix scutellariae were built on whole wavelengths, U i , U u and U ur at different number of latent variables (nLVs), respectively. Compared with other PLS models, the models of SIFTur-PLS built on U ur , which was obtained by taking union of the firstly selected spectral point sets, then eliminating the points with high deviance of SPD and those with high correlativity from the union, are most robust and always give lower or lowest prediction errors for both master and slave samples at many nLVs. It is a good way to filter stable, highly independent and characteristic spectral points to build robust PLS calibration models by combining SIFT algorithm with standard deviance analysis of SPD and correlative analysis. The models can be directly shared by the slave instrument, without needing transfer sets, and without requiring to correct the spectra of slave instruments or spectral calibration models. [ABSTRACT FROM AUTHOR]

Aiming at guiding agricultural producers to harvest crops at an appropriate time and ensuring the pesticide residue does not exceed the maximum limit, the present work proposed a method of detecting pesticide residue rapidly by analyzing near-infrared microscopic images of the leaves of Shanghaiqing (Brassica rapa), a type of Chinese cabbage with computer vision technology. After image pre-processing and feature extraction, the pattern recognition methods of K nearest neighbors (KNN), naïve Bayes, support vector machine (SVM), and back propagation artificial neural network (BP-ANN) were applied to assess whether Shanghaiqing is sprayed with pesticides. The SVM method with linear or RBF kernel provides the highest recognition accuracy of 96.96% for the samples sprayed with trichlorfon at a concentration of 1 g/L. The SVM method with RBF kernel has the highest recognition accuracy of 79.16~84.37% for the samples sprayed with cypermethrin at a concentration of 0.1 g/L. The investigation on the SVM classification models built on the samples sprayed with cypermethrin at different concentrations shows that the accuracy of the models increases with the pesticide concentrations. In addition, the relationship between the concentration of the cypermethrin sprayed and the image features was established by multiple regression to estimate the initial pesticide concentration on the Shanghaiqing leaves. A pesticide degradation equation was established on the basis of the first-order kinetic equation. The time for pesticides concentration to decrease to an acceptable level can be calculated on the basis of the degradation equation and the initial pesticide concentration. The present work provides a feasible way to rapidly detect pesticide residue on Shanghaiqing by means of NIR microscopic image technique. The methodology laid out in this research can be used as a reference for the pesticide detection of other types of vegetables. [ABSTRACT FROM AUTHOR]

Abstract: The first concise total syntheses of pyrroloquinoline natural products, Marinoquinolines A–C, have been achieved in six linear steps from commercially available starting materials. The key steps were a reaction between (p-tolylsulfonyl)methylisocyanide (TosMIC) and α, β-unsaturated ester under basic condition to prepare the pyrrole moiety and Morgen-Walls reaction to construct quinoline ring. [Copyright &y& Elsevier]

Abstract: A facile and environment-benign oxidation by dioxygen as the sole oxidant was applied for the conversion of 2-oxazolines to oxazoles. The substituent effect on 2-oxazoline ring was investigated. The use of this methodology for the synthesis of a key intermediate of a CDC25 phosphatase inhibitor (SC-ααδ9) as an anticancer agent was also described. [Copyright &y& Elsevier]

The efficacy of different echinocandins is assessed by evaluating the in vitro activity of a novel antifungal, rezafungin, against invasive fungal isolates in comparison with anidulafungin and caspofungin. Using the broth microdilution (BMD) method, the susceptibility of 1000 clinical Candida isolates (including 400 C. albicans, 200 C. glabrata, 200 C. parapsilosis, 150 C. tropicalis and 50 C. krusei) and 150 Aspergillus isolates (100 A. fumigatus and 50 A. flavus) from the Eastern China Invasive Fungi Infection Group (ECIFIG) was tested for the antifungals including anidulafungin, rezafungin, caspofungin and fluconazole. The echinocandins showed strong activity against C. albicans that was maintained against fluconazole-resistant isolates. The GM MIC (geometric mean minimum inhibitory concentration) value of rezafungin was found to be comparable to that of anidulafungin or caspofungin against the five tested common Candida species. C. tropicalis exhibited higher resistance rates (about 8.67–40.67% in different antifungals) than the other four Candida species. Through the sequencing of FKS genes, we searched for mutations in echinocandin-resistant C. tropicalis isolates and found that all displayed alterations in FKS1 S654P. The determined MEC (minimal effective concentration) values against A. fumigatus and A. flavus for rezafungin (0.116 μg/mL, 0.110 μg/mL) are comparable to those of caspofungin (0.122 μg/mL, 0.142 μg/mL) but higher than for anidulafungin (0.064 μg/mL, 0.059 μg/mL). Thus, the in vitro activity of rezafungin appears comparable to anidulafungin and caspofungin against most common Candida and Aspergillus species. Rezafungin showed higher susceptibility rates against C. glabrata. Rezafungin indicates its potent activity for potential clinical application. [ABSTRACT FROM AUTHOR]

Provides a model for composition prediction of petroleum fractions. Role of the American Society of Test and Material on standard testing method; Correlation between vaporization portion and temperature; State of vapor-liquid equilibrium.

Purpose: The objective of this multicenter study was to compare the diagnostic performance of lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) to detect the Dynamiker Aspergillus Galactomannan levels in serum and bronchoalveolar lavage fluid (BALF) samples for I. Methods: We registered 310 clinically suspected Aspergillus infection patients from December 2021 to February 2023 and classified them into subgroups as the "IA group" and "non-IA group" based on the latest EORTC/MSG guidelines. The immunoassays were analyzed by LFA and ELISA respectively. Results: Galactomannan was examined using LFA, and serum and BALF samples demonstrated sensitivities of 82.57% and 89.47%, specificities of 90.76% and 92.00%, PPVs of 89.11% and 96.23%, and NPVs of 85.04% and 79.31%, respectively. Galactomannan was observed using two assays in serum and BALF samples and showed PPAs of 95.11% and 93.33%, NPAs of 89.19% and 96.30%, and TPAs of 92.47% and 94.25%, respectively. The ROC curve demonstrated that LFA had optimum diagnostic value when the index value (I value) = 0.5, the sensitivity was 84.94%, and the specificity was 90.97%. Conclusion: Compared to the ELISA method, the LFA has shown excellent performance for the diagnosis of IA in serum and BALF sample and can be used as an assay for the early diagnosis of patients with IA. The dynamic change in galactomannan levels may be useful for assessing treatment response. [ABSTRACT FROM AUTHOR]

[Display omitted] • A robust NIR calibration model of TPA was built by a three-step wavelength selection method of SISCW. • The SISCW-PLS model of predicting TPA in tobacco leaves can be re-used by 6 NIR secondaries. • The SISCW-PLS model can serve on 4 NIR devices for 7 years from 2014 to 2020. • The transferability and service life of the SISCW-PLS are superior to other developed models. • SISCW realizes TPA model transfer without standards and improves the model's service life greatly. The rapid determination of total plant alkaloids (TPA) content in tobacco products by means of near infrared (NIR) spectroscopy is becoming conventional detection method in tobacco industry. An established NIR model of TPA is anticipated to be shared by other devices as long as possible not needing to update the model. Present study developed a three-step wavelength selection method SISCW (selecting important and stable characteristic wavelengths）to build a robust NIR calibration model of TPA to improve its transferability and to prolong its use period at many devices. For this, 292 flue-cured tobacco leaf samples from more than 10 regions of China, which were harvested in 2011–2013 and tested on the primary NIR device, were used to build the model. 77 samples harvested from 2011 to 2013 were applied to verify the transferability of the model on six secondary NIR devices. 180 samples harvested from 2014 to 2020 that were divided into 7 groups according to their growing years, were used to examine the long-term application capacity of the model on the seven NIR devices. The SISCW method integrates an image processing method of scale invariant feature transformation (SIFT) with analyzing standard deviation of the sample spectra (SDSS) and water absorption coefficients to select important and stable characteristic wavelengths (SISCW). The wavelengths selected by the SISCW were recorded as U isc. The results indicated that the partial least square (PLS) calibration model of TPA based on U isc (SISCW-PLS) performed well on both primary and the six secondary devices when it was employed to predict TPA of the 77 samples of 2011–2013. The model has run 7 years on the primary and 3 of the secondary devices from 2014 to 2020. This emphasizes the SISCW method has great potential for improving transferability and service-life of TPA calibration model. [ABSTRACT FROM AUTHOR]

This paper reviews the literature on emergent technologies from the field of science education. In an effort to summarize the current state of research, and identify specific types of technologies that have recently "emerged" in K‐12 science classrooms, we review papers featured in leading science education venues in recent years. The reported trends suggest that, as a field, science education has become increasingly characterized by hermeneutic and alterity relations wherein the physical world is experienced indirectly through technological representations or has become secondary to students' experiences as it is "pushed aside" by emergent technological artifacts such as computer simulations, virtual labs, mobile devices, robots, games, and digital photography and drawing. As a result, science educators are faced with the challenge of helping students view technological instruments not as transparent and neutral devices that simply "depict reality" (naïve instrumentalism) and reveal what is "really" there (naïve realism), but as powerful epistemic tools that help co‐constitute the reality being investigated, often (re)shaping what counts as "real" in revolutionary ways. It is argued that new technologies do not actually emerge in sociocultural vacuum and that more attention needs to be been given to sociocultural aspects of technological innovation in science classrooms. [ABSTRACT FROM AUTHOR]

Prenatal alcohol exposure can result in varying degrees of neurodevelopmental deficits, growth retardation, and facial dysmorphology. Variation in these adverse outcomes not only depends on the dose and pattern of alcohol exposure but also on less well understood interactions among environmental, genetic, and maternal factors. The current study tested the hypothesis that fetal genotype is an important determinant of ethanol teratogenesis by evaluating effects of ethanol exposure via embryo culture in 3 inbred strains of mice known to differ in the vulnerability of prenatal alcohol exposure in vivo. Three strains of mice, C57BL/6N (B6), DBA/2 (D2), and 129S6/SvEvTac (129S6) were assessed in a whole embryo culture beginning on embryonic day 8.25, with or without alcohol administration at 88 mM for 6 hours followed by 42 hours culture in ethanol-free media. Contrasting strain differences in susceptibility were observed for the brain, the face, and other organ systems using the Maele-Fabry and Picard scoring system. The forebrain, midbrain, hindbrain, heart, optic vesicle, caudal neural tube, and hindlimbs of the B6 mice were severely delayed in growth, whereas compared to the respective controls, only the forebrain and optic vesicle were delayed in the D2 mice, and no effects were found in the 129S6 mice. A large number of cleaved (c)-caspase 3 positive (+) cells were found in regions of the brain, optic vesicles, cranial nerve nuclei V, VII, VIII, and IX as well as the craniofacial primordial; only a few were found in corresponding regions of the B6 controls. In contrast, only a small number of c-caspase 3 immunostaining cells were found in either the alcohol treated or the controls of the D2 embryos and in 129S6 embryos. The independent apoptotic markers TUNEL and Nile blue staining further confirmed the strain differences in apoptotic responses in both the neural tube and craniofacial primordia. Under embryo culture conditions, in which alcohol exposure factors and fetal developmental staging were controlled, and maternal and intrauterine factors were eliminated, the degree of growth retardation and the extent and type of neurodevelopmental teratogenesis varied significantly across strains. Notably, the 129S6 strain was remarkably resistant to alcohol-induced growth deficits, confirming a previous in vivo study, and the D2 strain was also significantly less affected than the B6 strain. These findings demonstrate that fetal genotype is an important factor that can contribute to the variation in fetal alcohol spectrum disorder. [ABSTRACT FROM AUTHOR]

Activity-dependent myelination is a fundamental mode of brain plasticity which significantly influences network function. We recently discovered that absence seizures, which occur in multiple forms of generalized epilepsy, can induce activity-dependent myelination, which in turn promotes further progression of epilepsy. Structural alterations of myelin are likely to be widespread, given that absence seizures arise from an extensive thalamocortical network involving frontoparietal regions of the bilateral hemispheres. However, the temporal course and spatial extent of myelin plasticity is unknown, due to limitations of gold-standard histological methods such as electron microscopy (EM). In this study, we leveraged magnetization transfer and diffusion MRI for estimation of g-ratios across major white matter tracts in a mouse model of generalized epilepsy with progressive absence seizures. EM was performed on the same brains after MRI. After seizure progression, we found increased myelination (decreased g-ratios) throughout the anterior portion (genu-to-body) of the corpus callosum but not in the posterior portion (body-splenium) nor in the fornix or the internal capsule. Curves obtained from averaging g-ratio values at every longitudinal point of the corpus callosum were statistically different with p < 0.001. Seizure-associated myelin differences found in the corpus callosum body with MRI were statistically significant (p = 0.0027) and were concordant with EM in the same region (p = 0.01). Notably, these differences were not detected by diffusion tensor imaging. This study reveals widespread myelin structural change that is specific to the absence seizure network. Furthermore, our findings demonstrate the potential utility and importance of MRI-based g-ratio estimation to non-invasively detect myelin plasticity. • MRI-derived g-ratios detect activity dependent myelination changes. • Widespread but seizure-network specific differences in g-ratio were observed. • G-ratio estimation was more sensitive to myelin changes than DTI alone. [ABSTRACT FROM AUTHOR]

COVID survivors frequently experience lingering neurological symptoms that resemble cancer-therapy-related cognitive impairment, a syndrome for which white matter microglial reactivity and consequent neural dysregulation is central. Here, we explored the neurobiological effects of respiratory SARS-CoV-2 infection and found white-matter-selective microglial reactivity in mice and humans. Following mild respiratory COVID in mice, persistently impaired hippocampal neurogenesis, decreased oligodendrocytes, and myelin loss were evident together with elevated CSF cytokines/chemokines including CCL11. Systemic CCL11 administration specifically caused hippocampal microglial reactivity and impaired neurogenesis. Concordantly, humans with lasting cognitive symptoms post-COVID exhibit elevated CCL11 levels. Compared with SARS-CoV-2, mild respiratory influenza in mice caused similar patterns of white-matter-selective microglial reactivity, oligodendrocyte loss, impaired neurogenesis, and elevated CCL11 at early time points, but after influenza, only elevated CCL11 and hippocampal pathology persisted. These findings illustrate similar neuropathophysiology after cancer therapy and respiratory SARS-CoV-2 infection which may contribute to cognitive impairment following even mild COVID. [Display omitted] • Respiratory COVID induces CSF cytokine elevation and microglial reactivity • CCL11 activates hippocampal microglia and impairs neurogenesis • Respiratory COVID causes persistent loss of oligodendrocytes and myelinated axons • Respiratory influenza causes similar but less persistent cellular dysregulation Mild respiratory COVID causes neuroinflammation and multi-lineage cellular dysregulation in the central nervous system, a phenomenon mirroring cancer-therapy-related cognitive impairment. [ABSTRACT FROM AUTHOR]

Abstract: An environmental-benign methodology to synthesize 1-benzoylisoquinolines from 1-benzyl-3, 4-dihydroisoquinolines or 1-benzyl-1,2,3,4-tetrahydroisoquinolines using dioxygen as an oxidant was developed. This methodology in combination with Bischler-Napieralski reaction leads to a facile synthesis of 1-benzoylisoquinolines from phenylacetic acids and phenylethanamines. [Copyright &y& Elsevier]

Basing on the wavelengths with consistent and stable spectral signals between spectrometers, wavelength combinations were screened by different methods to obtain robust and simple near infrared spectra (NIR) calibration models that can be shared by slave spectrometers directly. Firstly, the wavelength set of Usc, at which the spectral signals between spectrometers are consistent and stable, was obtained by the method of screening the wavelengths with consistent and stable signals between spectrometers (SWCSS for short). Then, the wavelength set of Uscr whose spectral responses are correlated with dependent variables strongly was selected from Usc. Basing on Uscr, the methods of uninformative variable elimination (UVE), variable importance in projection (VIP) and selectivity ratio (SR) were applied to further screen optimal wavelength sets to obtain better NIR calibration models. These sets were recorded as UscrUVE, UscrVIP and UscrSR, respectively. The NIR partial least squares (PLS) models for predicting total alkaloids content of tobacco leaves were built on the three optimal wavelength sets, and named as UscrUVE-PLS, UscrVIP-PLS, UscrSR-PLS, respectively. Both UscrUVE-PLS and UscrVIP-PLS give satisfactory prediction errors for master and slave samples, and work better than the PLS model built on the whole wavelengths (WW-PLS) after piecewise direct standardization (PDS) calibration. The results show that further optimizing wavelength combinations based on consistent and stable spectral information cannot only simplify PLS models and improve the models' efficiency, but also ensure the models' accuracy when they are transferred to slave spectrometers. Wavelength selection based on the whole wavelengths without considering spectra consistency between spectrometers can improve the performance of the calibration models on the master spectrometer but cannot ensure the prediction accuracy of the slave samples. Image 1 • Robust PLS models were built by selecting wavelengths from those with consistent and stable signals. • Suitable wavelength selection methods provide good wavelength combinations. • The robust PLS model has good transfer performance and can be directly shared on multi-instruments. [ABSTRACT FROM AUTHOR]

Activity-dependent myelination is thought to contribute to adaptive neurological function. However, the mechanisms by which activity regulates myelination and the extent to which myelin plasticity contributes to non-motor cognitive functions remain incompletely understood. Using a mouse model of chemotherapy-related cognitive impairment (CRCI), we recently demonstrated that methotrexate (MTX) chemotherapy induces complex glial dysfunction for which microglial activation is central. Here, we demonstrate that remote MTX exposure blocks activity-regulated myelination. MTX decreases cortical Bdnf expression, which is restored by microglial depletion. Bdnf-TrkB signaling is a required component of activity-dependent myelination. Oligodendrocyte precursor cell (OPC)-specific TrkB deletion in chemotherapy-naive mice results in impaired cognitive behavioral performance. A small-molecule TrkB agonist rescues both myelination and cognitive impairment after MTX chemotherapy. This rescue after MTX depends on intact TrkB expression in OPCs. Taken together, these findings demonstrate a molecular mechanism required for adaptive myelination that is aberrant in CRCI due to microglial activation. • Methotrexate (MTX) causes a microglia-dependent reduction in Bdnf expression • Activity-regulated myelination requires Bdnf-TrkB signaling and fails after MTX • Conditional, inducible TrkB loss in OPCs impairs cognitive behavioral performance • TrkB agonism rescues cognitive performance after MTX only if OPCs express TrkB Methotrexate chemotherapy results in a microglial-dependent reduction of Bdnf expression and loss of activity-regulated myelination, which requires Bdnf to TrkB signaling. OPC-specific loss of TrkB results in cognitive impairment. Stimulating OPC TrkB signaling restores myelination and rescues cognition after MTX. [ABSTRACT FROM AUTHOR]

Summary Chemotherapy results in a frequent yet poorly understood syndrome of long-term neurological deficits. Neural precursor cell dysfunction and white matter dysfunction are thought to contribute to this debilitating syndrome. Here, we demonstrate persistent depletion of oligodendrocyte lineage cells in humans who received chemotherapy. Developing a mouse model of methotrexate chemotherapy-induced neurological dysfunction, we find a similar depletion of white matter OPCs, increased but incomplete OPC differentiation, and a persistent deficit in myelination. OPCs from chemotherapy-naive mice similarly exhibit increased differentiation when transplanted into the microenvironment of previously methotrexate-exposed brains, indicating an underlying microenvironmental perturbation. Methotrexate results in persistent activation of microglia and subsequent astrocyte activation that is dependent on inflammatory microglia. Microglial depletion normalizes oligodendroglial lineage dynamics, myelin microstructure, and cognitive behavior after methotrexate chemotherapy. These findings indicate that methotrexate chemotherapy exposure is associated with persistent tri-glial dysregulation and identify inflammatory microglia as a therapeutic target to abrogate chemotherapy-related cognitive impairment. Video Abstract Graphical Abstract Highlights • Chemotherapy depletes oligodendrocyte lineage (OL) cells in humans • Methotrexate chemotherapy disrupts OL dynamics, myelin, and cognition in mice • Methotrexate induces chronic microglial activation and astrocyte reactivity • Microglial depletion rescues glial cell dysregulation and cognitive deficits Microglial activation by methotrexate leads to a persistent disruption of oligodendrocyte lineage dynamics and astrocyte reactivity, resulting in the long-term cognitive impairment associated with chemotherapy. [ABSTRACT FROM AUTHOR]