Regioselective Glycosylation of Mannoside and Galactoside Acceptors Containing 2,4-OH Achieved by Altering Protecting Groups at the 1,3,6-Positions.

In this study, we systematically investigated the regioselective glycosylation of 2,4-OH mannoside and galactoside acceptors since regioselective protection of their 3- and 6-OHs is readily achieved. By altering the protecting groups at 1-, 3-, and 6-positions of such acceptors, we finally screened p-methoxyphenyl 3-OBn, 6-OTBDPS, α-mannoside, and ß-galactoside acceptors whose 2-OHs exhibited excellent selectivity for glycosylation with various glycosyl donors, leading to 1,2-linked products in 70-82% yields. By utilizing such acceptors, a series of 2,4-linked trisaccharide products (53-65% yields over two steps) have been highly efficiently synthesized without the need for complex protection/deprotection operations at the 2- and 4-positions of these acceptors.

Electron ionization mass spectrometry feature peak relationships combined with deep classification model to assist similarity algorithm for fast and accurate identification of compounds.

RATIONALE: Gas chromatography-mass spectrometry (GC-MS) combines chromatography and MS, providing full play to the advantages of high separation efficiency of GC, strong qualitative ability of MS, and high sensitivity of detector. In GC-MS data processing, determining the experimental compounds is one of the most important analytical steps, which is usually realized by one-to-one similarity calculations between the experimental mass spectrum and the standard mass spectrum library. Although the accuracy of the algorithm has been improved in recent years, it is still difficult to distinguish structurally similar mass spectra, especially isomers. At the same time, the library capacity is very large and increasing every year, and the algorithm needs to perform large numbers of calculations with irrelevant compounds in the library to recognize unknown compounds, which leads to a significant reduction in efficiency. METHODS: This work proposed to exclude a large number of irrelevant mass spectra by presearching, perform preliminary similarity calculations using similarity algorithms, and finally improve the accuracy of similarity calculations using deep classification models. The replica library of NIST17 is used as the query data, and the master library is used as the reference database. RESULTS: Compared with the traditional recognition algorithm, the preprocessing algorithm has reduced the time by 4.2 h, and by adding the deep learning models 1 and 2 as the final determination, the recognition accuracy has been improved by 1.9% and 6.5%, respectively, based on the original algorithm. CONCLUSIONS: This method improves the recognition efficiency compared to conventional algorithms and at the same time has better recognition accuracy for structurally similar mass spectra and isomers.

Simulation study of a new racetrack FAIMS analyzer to achieve both high-resolution and high-sensitivity.

A new racetrack field-asymmetric waveform ion mobility spectrometry (r-FAIMS) analyzer was developed in this study by combining the existing planar FAIMS (p-FAIMS) and cylindrical FAIMS (c-FAIMS). The ion inlet and outlet regions of r-FAIMS were consisted of a half of c-FAIMS, respectively, and these c-FAIMS were further connected by two p-FAIMS to form a racetrack shaped FAIMS. With such FAIMS working electrode configuration, the ions entering the r-FAIMS can be focused and separated in the first c-FAIMS section, be further separated in the p-FAIMS section with high-resolution, be focused and separated again in the final c-FAIMS section and eventually enter the mass spectrometer or other analyzers for analysis. Detailed simulation by using SIMION software with the default FAIMS user program showed that the ion focusing effect in the first c-FAIMS section ensures the ions entering the following p-FAIMS section as a compact ion packet. This effectively decreases the ion loss caused by Coulomb repulsion and thermal diffusion in p-FAIMS section as compared to the ions being introduced into the p-FAIMS gap randomly in the conventional design. As a result, the ion transmission efficiency of r-FAIMS is at least 3.3-fold higher than the single p-FAIMS under the operating conditions used in this study. The ion trajectory simulation results also showed that the resolving power of r-FAIMS is about the sum of the resolving powers for its c-FAIMS and p-FAIMS sections. The resolving power of r-FAIMS is at least 3.6-fold higher than the single c-FAIMS under the operation conditions used in this study. Therefore, the r-FAIMS can realize both high-resolution and high-sensitive ion mobility separation.

Toll/interleukin-1 receptor (TIR) domain-containing proteins have NAD-RNA decapping activity.

The occurrence of NAD+ as a non-canonical RNA cap has been demonstrated in diverse organisms. TIR domain-containing proteins present in all kingdoms of life act in defense responses and can have NADase activity that hydrolyzes NAD+. Here, we show that TIR domain-containing proteins from several bacterial and one archaeal species can remove the NAM moiety from NAD-capped RNAs (NAD-RNAs). We demonstrate that the deNAMing activity of AbTir (from Acinetobacter baumannii) on NAD-RNA specifically produces a cyclic ADPR-RNA, which can be further decapped in vitro by known decapping enzymes. Heterologous expression of the wild-type but not a catalytic mutant AbTir in E. coli suppressed cell propagation and reduced the levels of NAD-RNAs from a subset of genes before cellular NAD+ levels are impacted. Collectively, the in vitro and in vivo analyses demonstrate that TIR domain-containing proteins can function as a deNAMing enzyme of NAD-RNAs, raising the possibility of TIR domain proteins acting in gene expression regulation.

Boosting Energy Deprivation by Synchronous Interventions of Glycolysis and Oxidative Phosphorylation for Bioenergetic Therapy Synergetic with Chemodynamic/Photothermal Therapy.

Bioenergetic therapy is emerging as a promising therapeutic approach. However, its therapeutic effectiveness is restricted by metabolic plasticity, as tumor cells switch metabolic phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) to compensate for energy. Herein, Metformin (MET) and BAY-876 (BAY) co-loaded CuFe2O4 (CF) nanoplatform (CFMB) is developed to boost energy deprivation by synchronous interventions of glycolysis and OXPHOS for bioenergetic therapy synergetic with chemodynamic/photothermal therapy (CDT/PTT). The MET can simultaneously restrain glycolysis and OXPHOS by inhibiting hexokinase 2 (HK2) activity and damaging mitochondrial function to deprive energy, respectively. Besides, BAY blocks glucose uptake by inhibiting glucose transporter 1 (GLUT1) expression, further potentiating the glycolysis repression and thus achieving much more depletion of tumorigenic energy sources. Interestingly, the upregulated antioxidant glutathione (GSH) in cancer cells triggers CFMB degradation to release Cu+/Fe2+ catalyzing tumor-overexpressed H2O2 to hydroxyl radical (∙OH), both impairing OXPHOS and achieving GSH-depletion amplified CDT. Furthermore, upon near-infrared (NIR) light irradiation, CFMB has a photothermal conversion capacity to kill cancer cells for PTT and improve ∙OH production for enhanced CDT. In vivo experiments have manifested that CFMB remarkably suppressed tumor growth in mice without systemic toxicity. This study provides a new therapeutic modality paradigm to boost bioenergetic-related therapies.

Radial basis function neural network optimization algorithm based on dynamic inertial weight particle swarm optimization for separating overlapping peaks in ion mobility spectrometry.

RATIONALE: Ion mobility spectrometry (IMS), as a promising analytical tool, has been widely employed in the structural characterization of biomolecules. Nevertheless, the inherent limitation in the structural resolution of IMS frequently results in peak overlap during the analysis of isomers exhibiting comparable structures. METHODS: The radial basis function (RBF) neural network optimization algorithm based on dynamic inertial weight particle swarm optimization (DIWPSO) was proposed for separating overlapping peaks in IMS. The RBF network structure and parameters were optimized using the DIWPSO algorithm. By extensively training using a large dataset, an adaptive model was developed to effectively separate overlapping peaks in IMS data. This approach successfully overcomes issues related to local optima, ensuring efficient and precise separation of overlapping peaks. RESULTS: The method's performance was evaluated using experimental validation and analysis of overlapping peaks in the IMS spectra of two sets of isomers: 3'/6'-sialyllactose; fructose-6-phosphate, glucose-1-phosphate, and glucose-6-phosphate. A comparative analysis was conducted using other algorithms, including the sparrow search algorithm, DIWPSO algorithm, and multi-objective dynamic teaching-learning-based optimization algorithm. The comparison results show that the DIWPSO-RBF algorithm achieved remarkably low maximum relative errors of only 0.42%, 0.092%, and 0.41% for ion height, mobility, and half peak width, respectively. These error rates are significantly lower than those obtained using the other three algorithms. CONCLUSIONS: The experimental results convincingly demonstrate that this method can adaptively, rapidly, and accurately separate overlapping peaks of multiple components, improving the structural resolution of IMS.

A high-performance standalone planar FAIMS system for effective detection of chemical warfare agents via TSPSO algorithm.

A high-performance standalone planar field asymmetric waveform ion mobility spectrometry (p-FAIMS) system with a deconvolution algorithm (two-step particle swarm optimization algorithm, TSPSO) for overlapping peaks was developed to effectively detect chemical warfare agents (CWAs). Four CWA simulants were applied in this study to systemically evaluate the performance of the standalone p-FAIMS system. The experimental results showed that each CWA simulant in the mixture can be positively identified by carefully comparing the compensation voltage (CV) value of each peak in the FAIMS spectra for the mixture to the ones in the spectra acquired by using the same FAIMS system for the pure CWA simulant standards. The FAIMS spectrum of the CWA simulant mixture might consist of multiple overlapping peaks, which would be difficult to accurately determine the CV value for each CWA simulant peak. This problem has been effectively resolved in this study by deconvoluting the overlapping peaks via the TSPSO algorithm. As the effective peak deconvolution via TSPSO requires the degree of overlap between each FAIMS peak to be lower than a specific value, the flow rate of FAIMS carrier gas was decreased to further improve the resolution of the p-FAIMS system. After the accurate deconvolution, the resolution of original FAIMS spectrum can also be enhanced to achieve baseline separation by using TSPSO algorithm to narrow the peak width of each peak. The experimental results in this study demonstrated the possibility of using TSPSO algorithm to achieve high-resolution on a typically low-resolution standalone FAIMS. The concept in this study can potentially be applied to any low-resolution instruments to achieve high-resolution results.

An efficient strategy with a synergistic effect of hydrophilic and electrostatic interactions for simultaneous enrichment of N- and O-glycopeptides.

N- and O-glycosylation modifications of proteins are closely linked to the onset and development of many diseases and have gained widespread attention as potential targets for therapy and diagnosis. However, the low abundance and low ionization efficiency of glycopeptides as well as the high heterogeneity make glycosylation analysis challenging. Here, an enrichment strategy, using Knoevenagel copolymers modified with polydopamine-adenosine (denoted as PDA-ADE@KCP), was firstly proposed for simultaneous enrichment of N- and O-glycopeptides through the synergistic effects of hydrophilic and electrostatic interactions. The adjustable charged surface and hydrophilic properties endow the material with the capability to achieve effective enrichment of intact N- and O-glycopeptides. The experimental results exhibited excellent selectivity (1 : 5000) and sensitivity (0.1 fmol µL-1) of the prepared material for N-glycopeptides from standard protein digest samples. Moreover, it was further applied to simultaneous capturing of N- and O-glycopeptides from mouse liver protein digests. Compared to the commercially available zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) material, the number of glycoproteins corresponding to all N- and O-glycopeptides enriched with PDA-ADE@KCP was much more than that with ZIC-HILIC. Furthermore, PDA-ADE@KCP captured more O-glycopeptides than ZIC-HILIC, revealing its superior performance in O-glycopeptide enrichment. All these results indicated that the strategy holds immense potential in characterizing N- and O-intact glycopeptides in the field of proteomics.

An improved algorithm for resolving overlapping peaks in ion mobility spectrometry and its application to the separation of glycan isomers.

Despite the popularity of ion mobility spectrometry (IMS) for glycan analysis, its limited structural resolution hinders the effective separation of many glycan isomers. This leads to the overlap of IMS peaks, consequently impacting the accurate identification of glycan compositions. To this end, an improved algorithm, namely second-order differentiation combined with a simulated annealing particle swarm optimization algorithm based on sine adaptive weights (DWSA-PSO), was proposed for the separation of overlapping IMS peaks formed by glycan isomers. DWSA-PSO first performed second-order differentiation to automatically determine the number of components in overlapping peaks and exclude impossible single-peak combinations. It then introduced sinusoidal adaptive weights and a simulated annealing mechanism to improve the algorithm's search capability and global optimization performance, thereby enabling accurate and efficient separation of individual peaks. To evaluate the performance of DWSA-PSO and its application to the separation of glycan isomers, multiple sets of overlapping peaks with different degrees of overlap were simulated, and various types of multi-component overlapping peaks were formed using six disaccharide and four trisaccharide isomers. The experimental results consistently demonstrated that the DWSA-PSO algorithm outperformed both the improved particle swarm optimization (IPSO) algorithm and the dynamic inertia weight particle swarm optimization (DIWPSO) algorithm in terms of separation accuracy, running time, and fitness values. In addition, the DWSA-PSO algorithm was successfully applied to the separation of glycan isomers in malt milk beverage. All these results reveal the capability of the DWSA-PSO algorithm to facilitate the accurate identification of glycan isomers.

Overlapping peak separation algorithm for ion mobility spectra based on multistrategy JAYA.

RATIONALE: In the field of separation science, ion mobility spectrometry (IMS) plays an important role as an analytical tool. However, the lack of sufficient structural resolution is a common problem in qualitative and quantitative analysis using IMS. A method is needed to solve the problem of overlapping peaks caused by insufficient resolution. METHODS: The method uses multiple strategies to more effectively use population information to balance exploration and exploitation capabilities, prevent local optimization, accurately resolve overlapping peaks, quickly obtain optimal spectral peak model coefficients, and accurately identify compounds. RESULTS: Multistrategy JAYA algorithm's (MSJAYA) performance is compared with improved particle swarm optimization (IPSO), dynamic inertia weight particle swarm optimization (DIWPSO), and multiobjective dynamic teaching-learning-based optimization (MDTLBO). The analysis shows that MSJAYA's maximum separation error is within 0.6%, a level of accuracy not guaranteed by the other algorithms. In addition, the separation error fluctuates within a much smaller range, demonstrating MSJAYA's superior robustness. CONCLUSIONS: Compared with other overlapping peak separation algorithms, MSJAYA is more applicable because no special parameters are used. The method allows fast deconvolution analysis of strong overlapping peaks with multiple components, which greatly improves the resolution of IMS.

Microbiota-assisted iron uptake promotes immune tolerance in the intestine.

Iron deficiencies are the most common nonenteric syndromes observed in patients with inflammatory bowel disease, but little is known about their impacts on immune tolerance. Here we show that homeostasis of regulatory T cells in the intestine was dependent on high cellular iron levels, which were fostered by pentanoate, a short-chain fatty acid produced by intestinal microbiota. Iron deficiencies in Treg caused by the depletion of Transferrin receptor 1, a major iron transporter, result in the abrogation of Treg in the intestine and lethal autoimmune disease. Transferrin receptor 1 is required for differentiation of c-Maf+ Treg, major constituents of intestinal Treg. Mechanistically, iron enhances the translation of HIF-2α mRNA, and HIF-2α in turn induces c-Maf expression. Importantly, microbiota-produced pentanoate promotes iron uptake and Treg differentiation in the intestine. This subsequently restores immune tolerance and ameliorated iron deficiencies in mice with colitis. Our results thus reveal an association between nutrient uptake and immune tolerance in the intestine.

Ion storage biases in the ion funnel trap of a Hybrid ion mobility spectrometer/time of flight mass spectrometer.

A detailed experimental characterization on the ion storage biases in an ion funnel trap, related to ion structure, charge state and RF voltage applied to the ion funnel trap, is reported by using both cytochrome C and ubiquitin samples. It was first observed experimentally that an unavoidable ion overflow would occur when the incoming ions exceeded the capacity of ion funnel trap. The conformers with extended structures would lose preferentially in the ion overflow process. Accordingly, a significant structural bias in the ion mobility spectrometry/time of flight mass spectrometry (IMS-TOF MS) spectrum was created, as the peak intensities for conformers with compact structures and extended structures would continuously increase and decrease, respectively, when the ion overflow time of the ion funnel trap was increased. Furthermore, the experimental results also showed that the effect of this ion structural bias was more significant when the RF voltage applied to the ion funnel trap was increased. In addition, an ion charge state bias in the ion funnel trap was also observed. The effect of the ion structural bias depends significantly on the specific charge state of the ions. For a given analyte, its lower charge state ions show a greater sensitivity to the ion structural bias than the higher charge state ones under the same ion funnel trap operating conditions. Therefore, it is extremely important to set a reasonable operation condition for the ion funnel trap to avoid ion storage biases in IMS-TOF MS.

Lipidomic study and diagnosis of hepatocellular carcinoma tumor with rapid evaporative ionization mass spectrometry.

Liver cancer is generally considered the leading cause of cancer deaths worldwide, and hepatocellular carcinoma (HCC) contributes to more than 90% of liver cancers. The altered lipid metabolism for rapid cancer cell growth and tumor formation has been frequently proven. In this study, an ambient ionization mass spectrometry technique, rapid evaporative ionization mass spectrometry (REIMS) using a monopolar electric knife, called iKnife, was systematically optimized and employed for ex vivo analysis of 12 human HCC tumor tissue specimens together with the paired paracancerous tissue (PT) and noncancerous liver tissue (NCT) specimens. Nine free fatty acids and 34 phospholipids were tentatively identified according to their extract masses and/or tandem mass spectra. With the help of statistical methods, 7 free fatty acids and 10 phospholipids were distributed differently in 3 types of liver tissue specimens (95% confidence interval). The box plots showed these characterized lipid metabolites varied in PT, HCC, and NCT. Compared with PT and NCT, the upregulations of four common fatty acids FA 18:0, FA 20:4, FA 16:0, and FA 18:1, together with phospholipids PC 36:1, PE 38:3, PE (18:0/20:4), PA (O-36:1), PC (32:1), PC 32:0, PE 34:0, and PC (16:0/18:1), were found in HCC specimens. The sensitivity and specificity of the established statistic model for real-time HCC tumor diagnosis were 100% and 90.5%, respectively. This study demonstrated that the described REIMS technique is a potential method for rapid lipidomic analysis and characterization of HCC tumor tissue.

One-step recovery of cobalt from ammonia-ammonium carbonate system via pressurized ammonia distillation.

Ammonia leaching of Co-bearing resources has attracted attention due to its selectivity to cobalt and mild leaching conditions. However, in ammonia leach liquor, cobalt and ammonia are complexed stably, which undoubtedly increases the difficulty of preparing cobalt products from the solution. In this study, ammonia distillation process was proposed and studied to recover cobalt from NH3-(NH4)2CO3 system. First, the E-pH diagram of Co-NH3-CO32--H2O system was drawn, and the possibility of preparing cobalt products from the solution was discussed. Then, by comparing atmospheric and pressurized ammonia distillation processes, it was found that the microspherical Co3O4 product can be obtained directly through pressurized ammonia distillation. Furtherly, the effects of parameters on this process and the formation mechanism of Co3O4 were investigated systematically. Over 99% of cobalt could be recovered in one step under optimal conditions. Finally, CoCO3 products with different morphologies were also obtained directly by adding the reducing agent during pressurized ammonia distillation, and the cobalt recovery rate was hardly affected. The evaporated ammonia and residual solution can be recycled. This work realizes the one-step preparation of cobalt products and provides a new perspective on cobalt recovery from ammoniacal solution.

Hydrogen peroxide self-sufficient and glutathione-depleted nanoplatform for boosting chemodynamic therapy synergetic phototherapy.

Chemodynamic therapy (CDT), which suppresses tumors via the conversion of endogenous hydrogen peroxide (H2O2) to highly toxic hydroxyl radicals (•OH), is deemed as a cutting-edge antitumor strategy. However, the insufficient endogenous H2O2 and up-regulated antioxidant glutathione (GSH) in the tumor microenvironment (TME) greatly impede the therapeutic effect of CDT. Herein, a versatile nanoplatform MgO2@SnFe2O4@PEG (MSnFeP) is elaborately fabricated for boosting CDT synergetic phototherapy. In the TME, the activation of MSnFeP contributes to in situ supply of H2O2, generation of •OH and consumption of GSH for boosted CDT. Furthermore, photothermal therapy (PTT) and photodynamic therapy (PDT) are simultaneously stimulated by near-infrared (NIR) light exposure on MSnFeP to increase the toxic free radical yield. This strategy not only amplifies the CDT efficacy hindered by H2O2 deficiency and GSH overexpression, but also further enhances the therapeutic effect with the combination of phototherapy.

H2O2 self-sufficient nanoplatform based on CeO2 QDs decorated MgO2 nanosheet for amplified chemodynamic therapy.

Chemodynamic therapy (CDT), which employs Fenton/Fenton-like agents to decompose hydrogen peroxide (H2O2) into toxic hydroxyl radical (•OH) to induce cancer cell apoptosis and necrosis, holds great promise in tumor therapy due to its high selectivity. Nevertheless, its efficiency is impaired by the insufficient intracellular H2O2 concentration and/or the insensitive response of Fenton/Fenton-like agents to the slightly acid tumor microenvironment (pH∼7.0-6.5). Herein, we develop a novel CDT reagent based on CeO2 quantum dot (QD) decorated MgO2 nanosheets engineered with cascade reactions to boost the intracellular H2O2 level and high pH-activated (pH = 6.5) characteristic for an enhanced CDT. Under the tumor microenvironment (pH = 6.5), MgO2 nanosheets that are highly reactive can react with H2O to produce nontoxic Mg2+ and abundant H2O2, boosting the intracellular H2O2 level. The self-generated H2O2 is subsequently converted into •OH by CeO2 QD, which is served as a relatively high pH-activated (pH = 6.5) Fenton-like agent. The sufficient intracellular H2O2 supply and sensitive response to the slightly acid tumor sites significantly improve the Fenton reaction, leading to the excellent in vivo CDT results with tumor growth inhibition effect. Our work presents a distinctive paradigm for self-boosting CDT efficacy.

Two-step particle swarm optimization algorithm for effective deconvolution and resolution enhancement of various overlapping peaks.

RATIONALE: The existing particle swarm optimization (PSO) algorithms are only effective in deconvoluting the overlapping peaks in ion mobility spectra with fewer than four component peaks, which limits the applicability of these algorithms. METHODS: A high-performance two-step particle swarm optimization (TSPSO) algorithm was developed. Compared to the existing PSO algorithms, TSPSO can narrow the search ranges of all coefficients for the overlapping peaks through Gaussian model calculation, and thus can deconvolute various overlapping peaks with high accuracy, even for 30-component overlapping peaks. In addition, the TSPSO could be further applied to enhance the resolution of the spectra by narrowing the peak widths after the peak deconvolution. RESULTS: Simulated overlapping peaks were first used to evaluate the performance of TSPSO as compared to the dynamic inertia weight particle swarm optimization (DIWPSO) algorithm. The results showed that the profiles of the peaks deconvoluted by using TSPSO were more consistent with the original ones. The fitness values and the standard deviations of the fitness values from TSPSO were also at least an order of magnitude less than those from DIWPSO. By applying TSPSO, the overlapping peaks from both mass spectrometry (MS) and field asymmetric waveform ion mobility spectrometry (FAIMS) spectra can also be well deconvoluted. In addition, the resolutions of the MS and FAIMS spectra can be effectively enhanced after peak deconvolution. The enhanced spectra matched excellently with the experimental ones acquired at high-resolution modes. CONCLUSIONS: The experiment results convincingly demonstrate that the TSPSO algorithm is capable of both deconvoluting complex overlapping peaks and enhancing the spectrum resolution with high accuracy.

N6-methyladenosine RNA modification promotes viral genomic RNA stability and infection.

Molecular manipulation of susceptibility (S) genes that are antipodes to resistance (R) genes has been adopted as an alternative strategy for controlling crop diseases. Here, we show the S gene encoding Triticum aestivum m6A methyltransferase B (TaMTB) is identified by a genome-wide association study and subsequently shown to be a positive regulator for wheat yellow mosaic virus (WYMV) infection. TaMTB is localized in the nucleus, is translocated into the cytoplasmic aggregates by binding to WYMV NIb to upregulate the m6A level of WYMV RNA1 and stabilize the viral RNA, thus promoting viral infection. A natural mutant allele TaMTB-SNP176C is found to confer an enhanced susceptibility to WYMV infection through genetic variation analysis on 243 wheat varieties. Our discovery highlights this allele can be a useful target for the molecular wheat breeding in the future.

Deep learning under mass-to-charge ratio pre-retrieval to realize electron ionization mass spectrometry library retrieval.

RATIONALE: Gas chromatography-mass spectrometry (GC-MS) is an analytical technique widely used in materials science, biomedicine, and other fields. The target compound in the experiment is identified by searching for its mass spectrum in a large mass spectrum database using some algorithms. This work introduces the use of deep learning ranking for the identification of small molecules using low-resolution electron ionization MS. Because different spectra are often very similar, the algorithm produces wrong search results, and the search accuracy needs improvement. Due to the library's large amount of data, the algorithm sometimes requires a large amount of calculation and is very time consuming. METHODS: Given these two problems, this work aims to develop a model for ranking based on mass-to-charge ratio (m/z) pre-retrieval method combined with deep learning to improve search accuracy and reduce the algorithm's computational time. The master spectral library maintained by the National Institute of Standards and Technology is used as the reference library for all the experiments, and the replicate library is used as the query library to evaluate the method's performance. RESULTS: Compared with non-machine learning algorithms, the combination of m/z matching pre-retrieval and deep learning significantly improves library retrieval accuracy by about 4%. Moreover, compared with the deep learning sorting algorithm that does not use the pre-retrieval process, it improves the accuracy of spectral library retrieval by about 0.1% and reduces the computational time of the algorithm by more than 2 h. CONCLUSIONS: This method identifies compounds more efficiently and accurately than non-machine learning and deep learning algorithms without a pre-retrieval process.

Effects of Thoracic Paravertebral Block on Postoperative Anxiety and Depression for Patients Undergoing Thoracoscopic Lung Cancer Radical Surgery.

This study is aimed at investigating the effect of thoracic paravertebral block (TPVB) on the occurrence of chronic postoperative pain, postoperative anxiety, and depression in patients undergoing thoracoscopic radical lung cancer surgery. A total of 120 patients who underwent thoracoscopic radical lung cancer surgery in our hospital from June 2019 to March 2021 were included. There were 62 males and 58 females, with an age of 18-75 years old and a body mass index of 20-28 kg/m2. Patients were divided into two groups using the random number table method, TPVB group (n = 60) and normal saline group (control group, n = 60). Two-point nerve block was performed at T5-6 and T6-7 levels. Patients in the TPVB group received nerve block with 15 mL of 0.375% ropivacaine hydrochloride, while those in the control group received 5 mL of 0.9% normal saline. The numeric rating scale (NRS) scores at rest and during movement at 24 and 48 hours after surgery and the number of times the button on the patient-controlled analgesia pressed at 24 h after surgery in two groups were recorded. All patients were followed up by outpatient visits or phone visits at 1 year after surgery and assessed using Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale and Hospital Anxiety and Depression Scale (HADS). According to the inclusion, exclusion, and drop-out criteria, 108 patients were finally included, with 52 patients in the TPVB group and 56 patients in the control group. There was no statistically significant difference between the two groups in terms of age, sex, height, body weight, body mass index, ASA classification, and operation time (P > 0.05). NRS pain scores at 24 h (P = 0.0108) and 48 h (P = 0.0000) after surgery, the number of times pressing patient-controlled analgesia at 24 h after surgery (P = 0.0000), the LANSS scores (P = 0.0000), HADS anxiety score (P = 0.0000), and depression scores (P = 0.0000) at 1 year after surgery in the TPVB group were both significantly lower than those in the control group. To sum up, ultrasound-guided TPVB can effectively relieve pain at 48 hours after thoracoscopic lung cancer radical surgery and chronic postoperative pain at 6 months after V thoracoscopic lung cancer radical surgery.