Se pu = Chinese journal of chromatography最新文献

Volatile flavor compounds play vital roles when evaluating the flavor and quality of tobacco products. Pretreatment is always required owing to the wide range of flavor compounds and the complexity of the tobacco matrix. Solvent extraction （SE）， steam distillation （SD）， simultaneous distillation extraction （SDE）， supercritical fluid extraction （SFE）， and solid phase microextraction （SPME） are methods commonly used to extract and purify volatile flavor compounds. Among these methods， SPME coupled with headspace （HS） sampling has gained considerable attention in a variety of research fields because it combines sampling， extraction， concentration， and sample injection into a single procedure to deliver advantages that include convenient and simple sample preparation， small sample volumes， high sensitivities， and convenient operation.In this study， HS-SPME coupled with gas chromatography-mass spectrometry （GC-MS） was used to analyze the volatile aroma components in tobacco leaves. First， extraction efficiency was optimized by carefully evaluating multiple parameters， including types of solid phase microextraction fibers， extraction temperature， adsorption time， and desorption time. The number of chromatographic peaks， total chromatographic peak area， number of identified compounds， and internal-standard peak areas were used as indices. The optimized protocol involves incubating tobacco powder （1.0 g） under 80 ℃， extraction with an 80 μm divinylbenzene/carboxen/polydimethylsiloxane （DVB/CWR/PDMS） SPME needle for 30 min， followed by desorption from the fiber for a sufficient time （8 min）. These conditions led to a 1.6% RSD for the internal-standard peak area across five replicate experiments； hence， the developed method is highly repeatable. The volatile aroma components in tobacco leaves obtained from five different production areas were analyzed using the optimized parameters. A total of 107 volatile aroma compounds were identified， among which ketones， aromatics， and heterocyclic compounds accounted for more than 70% of the total volatile aroma components （excluding neophytadiene）. Tobacco leaves obtained from the Shangluo region contained the highest amount of total volatile aroma compounds， followed by leaves from Ankang， Hanzhong， Baoji， and Yan'an regions. Orthogonal partial least squares-discriminant analysis （OPLS-DA） was used to determine the main differential components from the various production regions， which identified 14 differential compounds （primarily ketones and alcohols）. This study provides a theoretical basis and reference for further exploring key volatile flavor compounds in leaves sourced from different production areas， as well as for identifying flavor-indicator substances and improving the quality of tobacco leaves.

Recent years have witnessed the gradual use of dendrimers to prepare and modify various separation materials， including adsorbents and chromatographic stationary phases. Polyamide-amine （PAMAM） has become one of the most widely used dendritic materials because it is simple to prepare， inexpensive， hypotoxic， and has excellent performance characteristics. PAMAM is advantageous as a modification material for adsorbents and chromatographic stationary phases compared to other traditional materials. Firstly， the large number of terminal groups on a PAMAM dendrimer provide abundant interaction sites on the surface of the functional matrix， which is beneficial for delivering superior adsorption capacity and separation selectivity. In addition， the hyperbranched structure of a PAMAM dendrimer facilitates higher grafting efficiency on the limited surface area of the matrix while simultaneously improving the uniformity of the functional groups grafted on the surface. Moreover， the controllable structure of PAMAM dendrimer effectively regulates the surface structure of separated materials. Moreover， the terminal amino functional groups of integer-generational PAMAM dendrimer are capable of carrying a high density of positive charges following protonation or quaternization， thereby facilitating good electrostatic interactions with negatively charged anionic substances that lead to excellent enrichment and separation effects. Based on the structural characteristics of integer generation PAMAM dendrimer and the mechanism of ionic interaction， the research progress of protonated or quaternized PAMAM dendrimer in the preparation of ionic adsorbents and ion chromatography stationary phases was summarized in this paper. Their future development potential and applications prospects are also discussed.

In this study， a method for the simultaneous determination of 22 organic ultraviolet absorbers （OUVs） in human serum was established by combining protein precipitation technology （PPT）， efficiency lipid removal technology （ELR） and ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. The OUVs include five benzophenone compounds， five benzotriazole compounds， two cinnamate ester compounds and their three metabolites， two salicylate compounds， two camphor derivative compounds， one triazine compound， one dibenzoylmethane compound and one amino aminobenzoic acid derivative compound. Chromatography was performed using an Acquity BEH C₁₈ column （100 mm×2.1 mm， 1.7 μm）， gradient elution was carried out using methanol-water and methanol-0.1% ammonia water as the mobile phases. Compounds were detected in both positive and negative electrospray ionization （ESI⁺/ESI^‒） modes using multiple reaction monitoring （MRM）， and quantified using stable-isotope internal standards. The experimental results showed that the 22 target compounds exhibited good linear relationships within their respective linear ranges， with the correlation coefficients （r）≥0.999 3. The method detection limits （MDLs） ranged from 0.02 to 0.48 ng/mL， and the method quantification limits （MQLs） ranged from 0.02 to 1.60 ng/mL. At the three spiked levels of low， medium and high， the spiked recoveries of the 22 target analytes ranged from 79.9% to 136.1%， the intra-day precisions were from 1.5% to 25.4%， and the inter-day precisions were from 0.6% to 23.5%. After correction by the stable-isotope internal standard method， the matrix effects of the 22 target analytes in fetal bovine serum were 83.0%‒119.9%. The developed method was successfully used to detect 22 OUVs in 110 human serum samples. With the exception of 3-benzylidene camphor （3-BC）， 2-（2H-benzotriazol-2-yl）-4-methyl-6-（2-propenyl）phenol （UV-9）， 4-methylbenzylidene camphor （4-MBC）， 2，2'-dihydroxy-4-methoxybenzophenone （BP-8）， and 2，4-dihydroxybenzophenone （BP-1）， which were not detected， the remaining 17 substances were detected with overall detection rates of 0.9%-65.5% and the detection levels were

Chromatography， a highly efficient and selective separation technology， is broadly applicable and exhibits a range of developmental prospects. The stationary phase of a chromatography column is the most important component of chromatography； hence， the development of advanced stationary-phase materials that exhibit highly resolved separation performance is a continuing research hotspot in this field. In this regard， ordered porous materials （OPMs） are advantageous owing to their precisely controllable pore sizes， morphologies， and regularly arranged pore structures， which are capable of accurately sieving molecules of different sizes and shapes， and reducing disordered molecular diffusion in the flow path. Such materials overcome the limitation of separation accuracy of traditional chromatographic materials， and effectively solve the problems faced by scientific research and industry in the purification of raw materials and products. Over the past few decades， a variety of new OPMs have been developed and used as stationary-phase matrices in chromatography columns. These materials have efficiently and rapidly separated homologues， isomers， isotopes， and other substances with similar properties， and have delivered excellent chromatographic separation and analysis results. In this review， we first discuss the influence of ordered porous structures on column efficiency and resolution during chromatographic separation from a theoretical perspective， which provides a basis for the use of OPMs as stationary phases in chromatography. This review then summarizes research progress on several different OPM types for use in chromatographic separation and analysis applications， including metal organic frameworks （MOFs）， covalent organic frameworks （COFs）， porous organic cages （POCs）， mesoporous silica materials， block copolymer （BCP） assemblies， and high internal-phase emulsion polymers （PolyHIPEs）. The review concludes by discussing current challenges faced by chromatographic OPMs as well as directions for future development.

Phthalates （PAEs） are widely employed as plasticizers in plastic products that are used in industrial， agricultural， food， medical， and other fields. PAEs are relatively weakly bonded to plastic products through non-covalent interactions. Consequently， PAEs can easily leak from the product into the environment， which exposes the public to PAEs through food intake， skin absorption from personal care products， and by inhaling air. Related studies have shown that PAEs are endocrine-disrupting substances and that long-term exposure to PAEs may result in diseases of the nervous， reproductive， cardiovascular and immune systems. In addition， excessive exposure to PAEs may trigger inflammatory responses and induce tumors. Therefore， establishing a highly sensitive assay for determining PAE levels in the human body following exposure is an important objective. PAEs generally have half-lives of less than 24 h； they are rapidly metabolized through enzymatic hydrolysis after entering the human body and excreted through urine. Therefore， most studies have focused on PAE metabolites as target compounds； hence， human body exposure to PAEs can be assessed by analyzing the types and levels of these metabolites. Herein， we established a method for simultaneously determining ten phthalate （PAE） metabolites in human urine using ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. The ten PAE metabolites in urine were separated using an ACQUITY UPLC BEH Phenyl column （50 mm×2.1 mm， 1.7 μm）. Gradient elution was performed using 0.1% formic acid aqueous solution and 0.1% formic acid in acetonitrile as the mobile phases， at a flow rate of 0.5 mL/min， a column temperature of 40 ℃， and a sample size of 20 μL. Data were acquired in negative-ion electrospray ionization （ESI） and multiple reaction monitoring （MRM） modes， and quantified using the isotope internal standard method. The method was found to be highly specific， with the ten PAE metabolites exhibiting good linearities in their linear ranges， with limits of detection （LODs） and quantification （LOQs） of 0.03-0.3 and 0.1-1 ng/mL， respectively. Under the four quality control （QC） levels， the intra-day and inter-day precisions of the ten PAE metabolites were all ≤8.3%， and the accuracy ranged from ‒10.5% to 7.3%. The method was used to assess the exposure levels of PAE metabolites in the urine samples of 60 volunteers， with 1‒6 kinds of PAE metabolites detected in the urine of each volunteer. This method is sensitive， accurate， simple， efficient， and suitable for the large-scale biological monitoring of PAE metabolites.

Gel electrophoresis is used to separate and analyze macromolecules （such as DNA， RNA， and proteins） and their fragments， and highly reproducible and efficient automatic band-detection methods have been developed to analyze gel images. Uneven background， low contrast， lane distortion， blurred band edges， and geometric deformation pose detection-accuracy challenges during automatic band detection. In order to address these issues， various correction algorithms have been proposed； however， these algorithms rely on researcher experience to adjust and optimize parameters based on image characteristics， which introduces human error while qualitatively and quantitatively processing bands. Isoelectric focusing （IEF） gel electrophoresis separates proteins with high-resolution based on isoelectric point （pI） differences. Microarray IEF （mIEF） is used for the auxiliary diagnosis of diabetes and adult β-thalassemia owing to operational ease， low sample consumption， and high throughout. This diagnostic method relies on accurately positioning and precisely determining protein bands. To avoid errors associated with correction algorithms during band analysis， this paper introduces a method for rapidly recognizing bands in gel electrophoresis patterns that relies on a deep learning object detection algorithm， and uses it to quantify and classify the IEF electrophoresis pattern of hemoglobin （Hb）. We used mIEF experiments to collect 1 665 pI-marker-free Hb IEF images as a model dataset to train the YOLOv8 model. The trained model accepts a Hb IEF image as input and infers band bounding boxes and classification results. Using inference data， the gray intensities of the pixels in each band area are summed to determine the content of each protein. The background and foreground of the image need to be separated prior to summing the abovementioned gray intensities， and the threshold method is used to achieve this. The threshold is defined as the average intensity of the background area， which is obtained by summing and averaging the background intensities of gel areas between the detection bounding boxes of each protein band. The baseline band areas are unified after removing the background. This method only requires the input image， directly outputs the corresponding electrophoretic band information， and does not rely on the experience of professionals nor is it affected by factors such as lane distortion or band deformation. In addition， the developed method does not depend on pI markers for qualitatively determining bands， thereby reducing experimental costs and improving detection efficiency. YOLOv8n delivered a detection accuracy of 92.9% and an inference time of 0.6 ms while using limited computing resources. Using Hb A2 as an example， we compared its content measured using the developed method with clinical data. The quantitative results were subjected to regression analysis， which delivered a linearity of 0.981 2 and a correlation coefficient of 0.

Polychlorinated biphenyls （PCBs） are hazardous， persistent organic pollutants that are widely used industrially. Although the use of PCBs is banned in many countries， they are still present at trace levels in food and the environment. PCBs are highly chemically stable and lipophilic； hence， they are easily enriched and accumulate in the human body through milk and dairy products. PCBs residues pose serious threats to human health； therefore establishing a reliable enrichment method is an important objective. Sample pretreatment is required to efficiently extract target PCBs owing to sample-matrix complexity and their low contents. Efficient adsorbents form the cores of novel sample-pretreatment technologies， and designing new stable adsorbents is crucial for the further development of pretreatment techniques. Zeolitic imidazolate frameworks （ZIFs） are a family of metal-organic frameworks composed of imidazole linkers and metal ions. Their large surface areas， good stabilities， high porosities， and ease of modification are distinct advantages； consequently， ZIFs are widely used to adsorb organic pollutants. However， powdered ZIFs are difficult to separate and collect， which provides reuse challenges； hence， preparing ZIF composites with other functional materials is a highly effective way of addressing this challenge. Chitosan （CS） is an inexpensive and biodegradable natural polysaccharide that gelates easily. The structure of CS contains many free amino and hydroxyl groups that facilitate chemical modification and hybridization； consequently， CS is a matrix commonly used in composite materials. In this study， we prepared CS@ZIF-8 composite beads by the in-situ synthesis of ZIF-8 on chitosan through acid-solubilization/base-fixation. An analytical method for determining 18 PCBs in milk was developed using CS@ZIF-8 composite microspheres as the adsorbent for dispersive solid-phase extraction （DSPE） coupled with gas chromatography-mass spectrometry （GC-MS）.The CS@ZIF-8 composite microspheres were characterized by scanning electron microscopy （SEM）， Fourier-transform infrared （FT-IR） spectroscopy， X-ray diffractometry （XRD）， and nitrogen-adsorption-desorption experiments， which confirmed that the material had been successfully prepared. How adsorbent dosage， extraction and desorption times， and type and volume of the desorption solvent affect the extraction efficiency were investigated， with the following optimal extraction conditions determined： 20 mg of CS@ZIF-8 as the adsorbent， 30 min of extraction by shaking， and 8 min of ultrasonic desorption with 1 mL of n-hexane. The 18 PCBs exhibited good linearities in the 1-200 μg/L under these optimal conditions， with coefficients of determination （r²） exceeding 0.999. Detection limits （S/N=3） ranged between 0.06 and 0.24 μg/L， with quantification limits （S/N=10） of 0.19-0.79 μg/L. Repeatability experiments were performed by the addition of 100 μg/L of the 18 P