Functionalization of the macropolyhedral borate anion cluster [B22H22]: isolation and characterization of the OH and OEt derivatives

Preparation and characterization of the first derivatives of the fused macropolyhedral anion [B₂₂H₂₂]²⁻ are reported. The species [B₂₂H₂₁OH]²⁻ (1) and [B₂₂H₂₁OEt]²⁻ (2) are obtained from workup of the products of the reaction between HgBr₂ and [NBzlEt₃]₂[B₂₂H₂₂]; a cluster involving the conjoining of a closo-B₁₂ icosahedron with a nido-B₁₀ cluster. Washing the products with ethanol followed by thin-layer chromatography allows the isolation of 1 and 2, reproducibly, in yields of 27 and 20%, respectively. The species were characterized by NMR spectroscopy, elemental analysis and X-ray diffraction studies. The crystal structure determinations of the two species identify novel features. Apparently the influence of the O atoms in the ions [B₂₂H₂₁OH]²⁻ and [B₂₂H₂₁OEt]²⁻ results in the lengthening of what was a gunwale B---B connection adjacent to the junction of the two cages such that the distances are 2.180 and 2.230 Å, respectively. These latter are longer than the corresponding distance in the parent species [B₂₂H₂₂]²⁻, which is 2.09 Å; quite long for a normal B---B distance. Thus it is assumed that these B atoms, in 1 and 2, one of which bears the substituent, are not bonded to each other.     

基于激光诱导击穿光谱(LIBS)的煤灰熔点快速检测

炉内结渣是影响火电机组和气化工艺可靠运行的关键因素之一,准确预测灰熔点可以提前调整炉膛出口温度以避免结渣。本论文采用激光诱导击穿光谱（LIBS）采集煤灰样中金属元素的光谱,分别建立煤灰中的金属元素的谱线强度与煤灰熔点的随机森林模型、支持向量机回归模型和线性回归模型,直接预测煤灰熔点温度。采用基于马氏距离(MD)的异常数据剔除算法和基于稀疏矩阵的基线估计与降噪算法（BEADS）,对粉煤灰样的全光谱数据进行了预处理。随机森林模型对粉煤灰熔点的预测平均相对误差（MRE）为54.74%,支持向量机回归模型的预测平均相对误差为60.08%,而线性回归模型的预测平均相对误差达到了9.78%。研究结果表明,线性回归模型对煤灰熔点的预测结果更准确。     

锗元素测定方法综述

锗在国防工业、航空航天和通信等领域中的战略性,锗含量的测定对于保证材料质量和满足国际标准至关重要。本文综述了锗含量测定方法的多种技术,包括分光光度法、原子荧光光谱法、原子吸收光谱法、电感耦合等离子体原子发射光谱法、电感耦合等离子体质谱法以及滴定法。在每个检测方法的介绍中,详细探讨了方法的原理、前处理步骤以及应用范围,并分别总结了各个方法的优势和不足。最后,强调了锗含量测定方法的意义,特别是在满足出口监管和促进科学研究方面的作用。同时对锗元素的测定方法进行了展望,为未来的发展提供了参考方向。     

Spider Silk-Improved Quartz-Enhanced Conductance Spectroscopy for Medical Mask Humidity Sensing

Spider silk is one of the hottest biomaterials researched currently, due to its excellent mechanical properties. This work reports a novel humidity sensing platform based on a spider silk-modified quartz tuning fork (SSM-QTF). Since spider silk is a kind of natural moisture-sensitive material, it does not demand additional sensitization. Quartz-enhanced conductance spectroscopy (QECS) was combined with the SSM-QTF to access humidity sensing sensitively. The results indicate that the resonance frequency of the SSM-QTF decreased monotonously with the ambient humidity. The detection sensitivity of the proposed SSM-QTF sensor was 12.7 ppm at 1 min. The SSM-QTF sensor showed good linearity of ~0.99. Using this sensor, we successfully measured the humidity of disposable medical masks for different periods of wearing time. The results showed that even a 20 min wearing time can lead to a >70% humidity in the mask enclosed space. It is suggested that a disposable medical mask should be changed <2 h.     

Acid–Base Equilibrium and Self-Association in Relation to High Antitumor Activity of Selected Unsymmetrical Bisacridines Established by Extensive Chemometric Analysis

Unsymmetrical bisacridines (UAs) represent a novel class of anticancer agents previously synthesized by our group. Our recent studies have demonstrated their high antitumor potential against multiple cancer cell lines and human tumor xenografts in nude mice. At the cellular level, these compounds affected 3D cancer spheroid growth and their cellular uptake was selectively modulated by quantum dots. UAs were shown to undergo metabolic transformations in vitro and in tumor cells. However, the physicochemical properties of UAs, which could possibly affect their interactions with molecular targets, remain unknown. Therefore, we selected four highly active UAs for the assessment of physicochemical parameters under various pH conditions. We determined the compounds’ pK_a dissociation constants as well as their potential to self-associate. Both parameters were determined by detailed and complex chemometric analysis of UV-Vis spectra supported by nuclear magnetic resonance (NMR) spectroscopy. The obtained results indicate that general molecular properties of UAs in aqueous media, including their protonation state, self-association ratio, and solubility, are strongly pH-dependent, particularly in the physiological pH range of 6 to 8. In conclusion, we describe the detailed physicochemical characteristics of UAs, which might contribute to their selectivity towards tumour cells as opposed to their effect on normal cells.     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.     

Photo-Induced Reactions between Glyoxal and Hydroxylamine in Cryogenic Matrices

In this paper, the photochemistry of glyoxal–hydroxylamine (Gly–HA) complexes is studied using FTIR matrix isolation spectroscopy and ab initio calculations. The irradiation of the Gly–HA complexes with the filtered output of a mercury lamp (λ > 370 nm) leads to their photoconversion to hydroxyketene–hydroxylamine complexes and the formation of hydroxy(hydroxyamino)acetaldehyde with a hemiaminal structure. The first product is the result of a double hydrogen exchange reaction between the aldehyde group of Gly and the amino or hydroxyl group of HA. The second product is formed as a result of the addition of the nitrogen atom of HA to the carbon atom of one aldehyde group of Gly, followed by the migration of the hydrogen atom from the amino group of hydroxylamine to the oxygen atom of the carbonyl group of glyoxal. The identification of the products is confirmed by deuterium substitution and by MP2 calculations of the structures and vibrational spectra of the identified species.     

Positron Emission Tomography Radiopharmaceuticals in Differentiated Thyroid Cancer

Differentiated thyroid cancer (DTC), arising from thyroid follicular epithelial cells, is the most common type of thyroid cancer. Despite the well-known utilization of radioiodine treatment in DTC, i.e., iodine-131, radioiodine imaging in DTC is typically performed with iodine-123 and iodine-131, with the current hybrid scanner performing single photon emission tomography/computed tomography (SPECT/CT). Positron emission tomography/computed tomography (PET/CT) provides superior visualization and quantification of functions at the molecular level; thus, lesion assessment can be improved compared to that of SPECT/CT. Various types of cancer, including radioiodine-refractory DTC, can be detected by 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG), the most well-known and widely used PET radiopharmaceutical. Several other PET radiopharmaceuticals have been developed, although some are limited in availability despite their potential clinical utilizations. This article aims to summarize PET radiopharmaceuticals in DTC, focusing on molecular pathways and applications.     

Gold Nanoparticles as Effective ion Traps in Poly(dimethylsiloxane) Cross-Linked by Metal-Ligand Coordination

At this time, the development of advanced elastic dielectric materials for use in organic devices, particularly in organic field-effect transistors, is of considerable interest to the scientific community. In the present work, flexible poly(dimethylsiloxane) (PDMS) specimens cross-linked by means of ZnCl₂-bipyridine coordination with an addition of 0.001 wt. %, 0.0025 wt. %, 0.005 wt. %, 0.04 wt. %, 0.2 wt. %, and 0.4 wt. % of gold nanoparticles (AuNPs) were prepared in order to understand the effect of AuNPs on the electrical properties of the composite materials formed. The broadband dielectric spectroscopy measurements revealed one order of magnitude decrease in loss tangent, compared to the coordinated system, upon an introduction of 0.001 wt. % of AuNPs into the polymeric matrix. An introduction of AuNPs causes damping of conductivity within the low-temperature range investigated. These effects can be explained as a result of trapping the Cl⁻ counter ions by the nanoparticles. The study has shown that even a very low concentration of AuNPs (0.001 wt. %) still brings about effective trapping of Cl⁻ counter anions, therefore improving the dielectric properties of the investigated systems. The modification proposed reveals new perspectives for using AuNPs in polymers cross-linked by metal-ligand coordination systems.     

Separation of Dihydro-Isocoumarins and Dihydro-Stilbenoids from Hydrangea macrophylla ssp. serrata by Use of Counter-Current Chromatography

Previously, different Hydrangea macrophylla ssp. serrata cultivars were investigated by untargeted LC-MS analysis. From this, a list of tentatively identified and unknown compounds that differ significantly between these cultivars was obtained. Due to the lack of reference compounds, especially for dihydro-isocoumarins, we aimed to isolate and structurally characterise these compounds from the cultivar ‘Yae-no-amacha’ using NMR and LC-MS methods. For purification and isolation, counter-current chromatography was used in combination with reversed-phase preparative HPLC as an orthogonal and enhanced purification workflow. Thirteen dihydro-isocoumarins in combination with other metabolites could be isolated and structurally identified. Particularly interesting was the clarification of dihydrostilbenoid glycosides, which were described for the first time in H. macrophylla ssp. serrata. These results will help us in further studies on the biological interpretation of our data.