Application of cefuroxime in the eradication therapy of Helicobacter pylori infection: A review article.

BACKGROUND: Helicobacter pylori infection and its associated diseases represent a significant global health concern. Patients who cannot use amoxicillin pose a therapeutic challenge and necessitate alternative medications. Preliminary research indicates that cefuroxime demonstrates promising potential for eradicating H. pylori infection, and there is a lack of comprehensive review articles on the use of cefuroxime. MATERIALS AND METHODS: This study conducts a thorough systematic literature review and synthesis. A comprehensive systematic search was conducted in PubMed, Web of Science, EMBASE, China National Knowledge Infrastructure, China Biology Medicine disc, and Wanfang Data up to January 13, 2024. The search strategy utilized the following keywords: (Cefuroxime) AND (Helicobacter pylori OR Helicobacter nemestrinae OR Campylobacter pylori OR Campylobacter pylori subsp. pylori OR Campylobacter pyloridis OR H. pylori OR Hp) for both English and Chinese language publications. Sixteen studies from five different countries or regions were included in final literature review. RESULTS: Analysis results indicate that H. pylori is sensitive to cefuroxime, with resistance rates similar to amoxicillin being relatively low. Regimens containing cefuroxime have shown favorable eradication rates, which were comparable to those of the regimens containing amoxicillin. Regarding safety, the incidence of adverse reactions in cefuroxime-containing eradication regimens was comparable to that of amoxicillin-containing regimens or other bismuth quadruple regimens, with no significant increase in allergic reactions in penicillin-allergic patients. Regarding compliance, studies consistently report high compliance rates for regimens containing cefuroxime. CONCLUSION: Cefuroxime can serve as an alternative to amoxicillin for the patients allergic to penicillin with satisfactory efficacies, safety, and compliance.

A Multiplex Recombinase-Aided qPCR Assay for Highly Sensitive and Rapid Detection of khe, blaKPC -2, and blaNDM -1 Genes in Klebsiella pneumoniae.

OBJECTIVE: This study aimed to establish a highly sensitive and rapid single-tube, two-stage, multiplex recombinase-aided qPCR (mRAP) assay to specifically detect the khe, blaKPC-2, and blaNDM-1 genes in Klebsiella pneumoniae. METHODS: mRAP was carried out in a qPCR instrument within 1 h. The analytical sensitivities of mRAP for khe, blaKPC-2, and blaNDM-1 genes were tested using recombinant plasmids and dilutions of reference strains. A total of 137 clinical isolates and 86 sputum samples were used to validate the clinical performance of mRAP. RESULTS: mRAP achieved the sensitivities of 10, 8, and 14 copies/reaction for khe, blaKPC-2, and blaNDM-1 genes, respectively, superior to qPCR. The Kappa value of qPCR and mRAP for detecting khe, blaKPC-2, and blaNDM-1 genes was 1, 0.855, and 1, respectively (p < 0.05). CONCLUSION: mRAP is a rapid and highly sensitive assay for potential clinical identification of khe, blaKPC-2, and blaNDM-1 genes in K. pneumoniae.

Posterior circulation ischemic stroke: radiomics-based machine learning approach to identify onset time from magnetic resonance imaging.

PURPOSE: Posterior circulation ischemic stroke (PCIS) possesses unique features. However, previous studies have primarily or exclusively relied on anterior circulation stroke cases to build machine learning (ML) models for predicting onset time. To date, there is no research reporting the effectiveness and stability of ML in identifying PCIS onset time. We aimed to build diffusion-weighted imaging-based ML models to identify the onset time of PCIS patients. METHODS: Consecutive PCIS patients within 24 h of definite symptom onset were included (112 in the training set and 49 in the independent test set). Images were processed as follows: volume of interest segmentation, image feature extraction, and feature selection. Five ML models, naïve Bayes, logistic regression, tree ensemble, k-nearest neighbor, and random forest, were built based on the training set to estimate the stroke onset time (binary classification: ≤ 4.5 h or > 4.5 h). Relative standard deviations (RSD), receiver operating characteristic (ROC) curves, and the calibration plot was performed to evaluate the stability and performance of the five models. RESULTS: The random forest model had the best performance in the test set, with the highest area under the curve (AUC, 0.840; 95% CI: 0.706, 0.974). This model also achieved the highest accuracy, sensitivity, specificity, positive predictive value, and negative predictive value (83.7%, 64.3%, 91.4%, 75.0%, and 86.5%, respectively). Furthermore, the model had high stability (RSD = 0.0094). CONCLUSION: The PCIS case-based ML model was effective for estimating the symptom onset time and achieved considerably high specificity and stability.

Tick-borne Rickettsia, Anaplasma, Theileria, and enzootic nasal tumor virus in ruminant, PET, and poultry animals in Pakistan.

Introduction: Pakistan is an agricultural country; most of its income is based on livestock rearing. The increasing prevalence of tick-borne pathogens among animals may affect the animal production and livelihood of owners, which eventually derange the economy of a country. Methodology: To further comprehend TBPs, 213 ticks were collected from different animals, including ruminants, pets, and poultry. After molecular and phylogenetic analysis identification, ticks were managed into different pools based on their species level (Hyalomma anatolicum = 80, Rhipicephalus microplus = 35, Hyalomma scupense = 23, Rhipicephalus turanicus = 70, and Rhipicephalus sanguineus = 5). Results and discussion: After tick species identification, further molecular PCR amplification was carried out to screen out the pathogens for the presence of Theileria, Rickettsia, Anaplasma, and enzootic nasal tumor virus (ENTV). The following pathogens were detected: 11 (5.16%) for Anaplasma, 1 (0.47%) for Rickettsia, and 9 (4.23%) for Theileria. Nevertheless, other TBPs that had not been reported so far in Pakistan 3 (1.41%), were positive for enzootic nasal tumor virus (ENTV). Besides, phylogenetic analysis of the enzootic nasal tumor virus (ENTV) strain confirmed its resemblance to the Chinese strain, while Anaplasma has comparability with Pakistan and China, Rickettsia with Pakistan, China, and Iran, and Theileria with India, South Africa, United States, Japan, and Spain. Conclusion: This study reveals that there is a considerably wider range of TBPs held in Pakistan that take in various contagious zoonotic pathogens than was previously thought. This information advances TBP epidemiology and will contribute to upgrade future control measure.

Ratiometric fluorescence platform for the ultrasensitive detection of kanamycin based on split aptamer co-recognition triggers Mg2+-DNAzyme-driven DNA walker systems.

In this work, a novel 3D-DNA walker signal amplification strategy was designed to construct a fluorescent aptasensor for the detection of kanamycin (KAN). The aptasensor utilizes split aptamers for the synergistic recognition of KAN. The presence of KAN induces the split aptamers recombination to form the Mg2+-DNAzyme structure, which is activated by Mg2+ to drive the 3D-DNA walker process for cascading signal amplification. Employing gold nanoflowers (AuNFs) as walking substrate material increases the local DNA concentration to enhance the walker efficiency. The prepared fluorescent aptasensor achieved efficient and sensitive detection of KAN with satisfactory results in the concentration range of 1 × 10-8 - 1 × 10-3 µg/kg and the detection limit of 5.63 fg/kg. Meanwhile, the designed fluorescent aptasensor exhibited favorable specificity, anti-interference, storage stability and reproducibility, and verified the feasibility of its application in milk samples. The present work provides an effective tool for the regulation of KAN contamination in animal-derived foods with promising prospects.

Naringenin inhibits APAP-induced acute liver injury through activating PPARA-dependent signaling pathway.

Acute liver injury (ALI) refers to the damage to the liver cells of patients due to drugs, food, and diseases. In this work, we used a network pharmacology approach to analyze the relevant targets and pathways of the active ingredients in Citri Reticulatae Pericarpium (CRP) for the treatment of ALI and conducted systematic validation through in vivo and in vitro experiments. The network pharmacologic results predicted that naringenin (NIN) was the main active component of CRP in the treatment of ALI. GO functional annotation and KEGG pathway enrichment showed that its mechanism may be related to the regulation of PPARA signaling pathway, PPARG signaling pathway, AKT1 signaling pathway, MAPK3 signaling pathway and other signaling pathways. The results of in vivo experiments showed that (NIN) could reduce the liver lesions, liver adipose lesions, hepatocyte injury and apoptosis in mice with APAP-induced ALI, and reduce the oxidative stress damage of mouse liver cells and the inflammation-related factors to regulate ALI. In vitro experiments showed that NIN could inhibit the proliferation, oxidative stress and inflammation of APAP-induced LO2 cells, promote APAP-induced apoptosis of LO2 cells, and regulate the expression of apoptotic genes in acute liver injury. Further studies showed that NIN inhibited APAP-induced ALI mainly by regulating the PPARA-dependent signaling pathway. In conclusion, this study provides a preliminary theoretical basis for the screening of active compounds in CRP for the prevention and treatment of ALI.

Dispersive nonreciprocity between a qubit and a cavity.

The dispersive interaction between a qubit and a cavity is ubiquitous in circuit and cavity quantum electrodynamics. It describes the frequency shift of one quantum mode in response to excitations in the other and, in closed systems, is necessarily bidirectional, i.e., reciprocal. Here, we present an experimental study of a nonreciprocal dispersive-type interaction between a transmon qubit and a superconducting cavity, arising from a common coupling to dissipative intermediary modes with broken time reversal symmetry. We characterize the qubit-cavity dynamics, including asymmetric frequency pulls and photon shot noise dephasing, under varying degrees of nonreciprocity by tuning the magnetic field bias of a ferrite component in situ. We introduce a general master equation model for nonreciprocal interactions in the dispersive regime, providing a compact description of the observed qubit-cavity dynamics agnostic to the intermediary system. Our result provides an example of quantum nonreciprocal phenomena beyond the typical paradigms of non-Hermitian Hamiltonians and cascaded systems.

Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.

PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm. METHODS: Patients diagnosed with HCC who underwent locoregional therapy were retrospectively collected. We constructed a deep learning-based subtraction model and automatically generated arterial subtraction images. Two radiologists evaluated LR-TR category on ordinary images and then evaluated again on ordinary images plus arterial subtraction images after a 2-month washout period. The reference standard for viability was tumor stain on the digital subtraction hepatic angiography within 1 month after MRI. RESULTS: 286 observations of 105 patients were ultimately enrolled. 157 observations were viable and 129 observations were nonviable according to the reference standard. The sensitivity and accuracy of LR-TR algorithm for detecting viable HCC significantly increased with the application of arterial subtraction images (87.9% vs. 67.5%, p < 0.001; 86.4% vs. 75.9%, p < 0.001). And the specificity slightly decreased without significant difference when the arterial subtraction images were added (84.5% vs. 86.0%, p = 0.687). The AUC of LR-TR algorithm significantly increased with the addition of arterial subtraction images (0.862 vs. 0.768, p < 0.001). The arterial subtraction images also improved inter-reader agreement (0.857 vs. 0.727). CONCLUSION: Extended application of deep learning-based arterial subtraction images on extracellular agents-enhanced MRI can increase the sensitivity of LR-TR algorithm for detecting viable HCC without significant change in specificity.

Inhibition of GLUD1 mediated by LASP1 and SYVN1 contributes to hepatitis B virus X protein-induced hepatocarcinogenesis.

Glutamate dehydrogenase 1 (GLUD1) is implicated in oncogenesis. However, little is known about the relationship between GLUD1 and hepatocellular carcinoma (HCC). In the present study, we demonstrated that the expression levels of GLUD1 significantly decreased in tumors, which was relevant to the poor prognosis of HCC. Functionally, GLUD1 silencing enhanced the growth and migration of HCC cells. Mechanistically, the upregulation of interleukin-32 through AKT activation contributes to GLUD1 silencing-facilitated hepatocarcinogenesis. The interaction between GLUD1 and AKT, as well as α-ketoglutarate regulated by GLUD1, can suppress AKT activation. In addition, LIM and SH3 protein 1 (LASP1) interacts with GLUD1 and induces GLUD1 degradation via the ubiquitin-proteasome pathway, which relies on the E3 ubiquitin ligase synoviolin (SYVN1), whose interaction with GLUD1 is enhanced by LASP1. In hepatitis B virus (HBV)-related HCC, the HBV X protein (HBX) can suppress GLUD1 with the participation of LASP1 and SYVN1. Collectively, our data suggest that GLUD1 silencing is significantly associated with HCC development, and LASP1 and SYVN1 mediate the inhibition of GLUD1 in HCC, especially in HBV-related tumors.

Recent advances in microbial fuel cell-based self-powered biosensors: a comprehensive exploration of sensing strategies in both anode and cathode modes.

With the rapid development of society, it is of paramount importance to expeditiously assess environmental pollution and provide early warning of toxicity risks. Microbial fuel cell-based self-powered biosensors (MFC-SPBs) have emerged as a pivotal technology, obviating the necessity for external power sources and aligning with the prevailing trends toward miniaturization and simplification in biosensor development. In this case, vigorous advancements in MFC-SPBs have been acquired in past years, irrespective of whether the target identification event transpires at the anode or cathode. The present article undertakes a comprehensive review of developed MFC-SPBs, categorizing them into substrate effect and microbial activity effect based on the nature of the target identification event. Furthermore, various enhancement strategies to improve the analytical performance like accuracy and sensitivity are also outlined, along with a discussion of future research trends and application prospects of MFC-SPBs for their better developments.

Antibacterial Activities and Underlying Mechanisms of the Compound SYAUP-491 against Xanthomonas oryzae pv. oryzae.

SYAUP-491 is a novel alkyl sulfonamide. In this study, in vivo and in vitro tests were performed along with a proteomic analysis to determine the effects and underlying mechanisms of the antibacterial activity of SYAUP-491 against the causative agent of bacterial leaf blight in rice. The antibacterial test results suggested that SYAUP-491 exhibited significant activities against Xanthomonas oryzae pv. oryzae (Xoo) in vitro and in vivo. The minimal EC50 values reached 6.96 µg/mL and the curative activity reached 74.1%. Detailed studies demonstrated that SYAUP-491 altered membrane permeability and caused morphological changes. Based on proteomics results, SYAUP-491 might inhibit bacterial protein synthesis. SYAUP-491 may disrupt and alter cell membrane permeability and could further act on ribosomes in the bacterial body. Given the above results, SYAUP-491 could serve as a new lead compound in the research of antibacterial control of plant pathogenic bacterial disease.

Acidity-Triggered "Sticky Spotlight": CCK2R-Targeted TME-Sensitive NIR Fluorescent Probes for Tumor Imaging In Vivo.

Cancer which causes high mortality globally threatens public health seriously. There is an urgent need to develop tumor-specific near-infrared (NIR) imaging agents to achieve precise diagnosis and guide effective treatment. In recent years, imaging probes that respond to acidic environments such as endosomes, lysosomes, or acidic tumor microenvironments (TMEs) are being developed. However, because of their nonspecific internalization by both normal and tumor cells, resulting in a poor signal-to-noise ratio in diagnosis, these pH-sensitive probes fail to be applied to in vivo tumor imaging. To address this issue, a cholecystokinin-2 receptor (CCK2R)-targeted TME-sensitive NIR fluorescent probe R2SM was synthesized by coupling pH-sensitive heptamethine cyanine with a CCK2R ligand, minigastrin analogue 11 (MG11) for in vivo imaging, in which MG11 would target overexpressed CCK2Rs in gastrointestinal stromal tumors (GISTs). Cell uptake assay demonstrated that R2SM exhibited a high affinity for CCK2R, leading to receptor-mediated internalization and making probes finally accumulated in the lysosomes of tumor cells, which suggested in the tumor tissues, the probes were distributed in the extracellular acidic TME and intracellular lysosomes. With a pKa of 6.83, R2SM can be activated at the acidic TME (pH = 6.5-6.8) and lysosomes (pH = 4.5-5.0), exhibiting an apparent pH-dependent behavior and generating more intense fluorescence in these acidic environments. In vivo imaging showed that coupling of MG11 with a pH-sensitive NIR probe facilitated the accumulation of probe and enhanced the fluorescence in CCK2R-overexpressed HT-29 tumor cells. A high signal was observed in the tumor region within 0.5 h postinjection, indicating its potential application in intraoperative imaging. Fluorescence imaging of R2SM exhibited higher tumor-to-liver and tumor-to-kidney ratios (2.1:1 and 2.3:1, respectively), compared separately with the probes that are lipophilic, pH-insensitive, or MG11-free. In vitro and in vivo studies demonstrated that the synergistic effect of tumor targeting with pH sensitivity plays a vital role in the high signal-to-noise ratio of the NIR imaging probe. Moreover, different kinds of tumor-targeting vectors could be conjugated simultaneously with the NIR dye, which would further improve the receptor affinity and targeting efficiency.

IbNF-YA1 is a key factor in the storage root development of sweet potato.

As a major worldwide root crop, the mechanism underlying storage root yield formation has always been a hot topic in sweet potato [Ipomoea batatas (L.) Lam.]. Previously, we conducted the transcriptome database of differentially expressed genes between the cultivated sweet potato cultivar "Xushu18," its diploid wild relative Ipomoea triloba without storage root, and their interspecific somatic hybrid XT1 with medium-sized storage root. We selected one of these candidate genes, IbNF-YA1, for subsequent analysis. IbNF-YA1 encodes a nuclear transcription factor Y subunit alpha (NF-YA) gene, which is significantly induced by the natural auxin indole-3-acetic acid (IAA). The storage root yield of the IbNF-YA1 overexpression (OE) plant decreased by 29.15-40.22% compared with the wild type, while that of the RNAi plant increased by 10.16-21.58%. Additionally, IAA content increased significantly in OE plants. Conversely, the content of IAA decreased significantly in RNAi plants. Furthermore, real-time quantitative reverse transcription-PCR (qRT-PCR) analysis demonstrated that the expressions of the key genes IbYUCCA2, IbYUCCA4, and IbYUCCA8 in the IAA biosynthetic pathway were significantly changed in transgenic plants. The results indicated that IbNF-YA1 could directly target IbYUCCA4 and activate IbYUCCA4 transcription. The IAA content of IbYUCCA4 OE plants increased by 71.77-98.31%. Correspondingly, the storage root yield of the IbYUCCA4 OE plant decreased by 77.91-80.52%. These findings indicate that downregulating the IbNF-YA1 gene could improve the storage root yield in sweet potato.

Architecture and activation of human muscle phosphorylase kinase.

The study of phosphorylase kinase (PhK)-regulated glycogen metabolism has contributed to the fundamental understanding of protein phosphorylation; however, the molecular mechanism of PhK remains poorly understood. Here we present the high-resolution cryo-electron microscopy structures of human muscle PhK. The 1.3-megadalton PhK α4ß4γ4δ4 hexadecamer consists of a tetramer of tetramer, wherein four αßγδ modules are connected by the central ß4 scaffold. The α- and ß-subunits possess glucoamylase-like domains, but exhibit no detectable enzyme activities. The α-subunit serves as a bridge between the ß-subunit and the γδ subcomplex, and facilitates the γ-subunit to adopt an autoinhibited state. Ca2+-free calmodulin (δ-subunit) binds to the γ-subunit in a compact conformation. Upon binding of Ca2+, a conformational change occurs, allowing for the de-inhibition of the γ-subunit through a spring-loaded mechanism. We also reveal an ADP-binding pocket in the ß-subunit, which plays a role in allosterically enhancing PhK activity. These results provide molecular insights of this important kinase complex.

Bacterial capsules: Occurrence, mechanism, and function.

In environments characterized by extended multi-stress conditions, pathogens develop a variety of immune escape mechanisms to enhance their ability to infect the host. The capsules, polymers that bacteria secrete near their cell wall, participates in numerous bacterial life processes and plays a crucial role in resisting host immune attacks and adapting to their niche. Here, we discuss the relationship between capsules and bacterial virulence, summarizing the molecular mechanisms of capsular regulation and pathogenesis to provide new insights into the research on the pathogenesis of pathogenic bacteria.

Modification of nitrilase based on computer screening and efficient biosynthesis of 4-cyanobenzoic acid.

4-cyanobenzoic acid serves as a crucial intermediate for the synthesis of various high-value organic compounds. The enzymatic hydrolysis of terephthalonitrile to produce 4-cyanobenzoic acid using nitrilase offers the advantages of a simple reaction pathway, environmental friendliness, and easy product separation. In order to efficiently develop nitrilases that meet industrial production requirements, the virtual screening method used in the study is established and mature. From a total of 371 amino acids in the nitrilase AfNIT, which exhibits activity in terephthalonitrile hydrolysis, three candidate sites (F168, S192, and T201) were identified, and a "small and accurate" mutant library was constructed. The triple mutant F168V/T201N/S192F was screened from this small mutant library with a specific activity of 227.3 U mg-1 , which was 3.8 times higher than that of the wild-type AfNIT. Using the whole-cell biocatalyst containing the mutant F168V/T201N/S192F, terephthalonitrile was successfully hydrolyzed at a concentration of 150 g L-1 to produce 4-cyanobenzoic acid with a final yield of 170.3 g L-1 and a conversion rate of 98.7%. The obtained nitrilase mutant F168V/T201N/S192F in this study can be effectively applied in the biomanufacturing of 4-cyanobenzoic acid using terephthalonitrile as a substrate. Furthermore, the results also demonstrate the significant improvement in predictive accuracy achieved through the latest AI-assisted computer simulation methods. This approach represents a promising and feasible new technological pathway for assisting enzyme engineering research, laying a theoretical foundation for other related studies.

Construction of a gene model related to the prognosis of patients with gastric cancer receiving immunotherapy and exploration of COX7A1 gene function.

BACKGROUND: GC is a highly heterogeneous tumor with different responses to immunotherapy, and the positive response depends on the unique interaction between the tumor and the tumor microenvironment (TME). However, the currently available methods for prognostic prediction are not satisfactory. Therefore, this study aims to construct a novel model that integrates relevant gene sets to predict the clinical efficacy of immunotherapy and the prognosis of GC patients based on machine learning. METHODS: Seven GC datasets were collected from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database and literature sources. Based on the immunotherapy cohort, we first obtained a list of immunotherapy related genes through differential expression analysis. Then, Cox regression analysis was applied to divide these genes with prognostic significancy into protective and risky types. Then, the Single Sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to score the two categories of gene sets separately, and the scores differences between the two gene sets were used as the basis for constructing the prognostic model. Subsequently, Weighted Correlation Network Analysis (WGCNA) and Cytoscape were applied to further screen the gene sets of the constructed model, and finally COX7A1 was selected for the exploration and prediction of the relationship between the clinical efficacy of immunotherapy for GC. The correlation between COX7A1 and immune cell infiltration, drug sensitivity scoring, and immunohistochemical staining were performed to initially understand the potential role of COX7A1 in the development and progression of GC. Finally, the differential expression of COX7A1 was verified in those GC patients receiving immunotherapy. RESULTS: First, 47 protective genes and 408 risky genes were obtained, and the ssGSEA algorithm was applied for model construction, showing good prognostic discrimination ability. In addition, the patients with high model scores showed higher TMB and MSI levels, and lower tumor heterogeneity scores. Then, it is found that the COX7A1 expressions in GC tissues were significantly lower than those in their corresponding paracancerous tissues. Meanwhile, the patients with high COX7A1 expression showed higher probability of cancer invasion, worse clinical efficacy of immunotherapy, worse overall survival (OS) and worse disease-free survival (DFS). CONCLUSIONS: The ssGSEA score we constructed can serve as a biomarker for GC patients and provide important guidance for individualized treatment. In addition, the COX7A1 gene can accurately distinguish the prognosis of GC patients and predict the clinical efficacy of immunotherapy for GC patients.

Effects of Dityrosine on Lactic Acid Metabolism in Mice Gastrocnemius Muscle During Endurance Exercise via the Oxidative Stress-Induced Mitochondria Damage.

Dityrosine (Dityr) has been detected in commercial food as a product of protein oxidation and has been shown to pose a threat to human health. This study aims to investigate whether Dityr causes a decrease in lactic acid metabolism in the gastrocnemius muscle during endurance exercise. C57BL/6 mice were administered Dityr or saline by gavage for 13 weeks and underwent an endurance exercise test on a treadmill. Dityr caused a severe reduction in motion displacement and endurance time, along with a significant increase in lactic acid accumulation in the blood and gastrocnemius muscle in mice after exercise. Dityr induced significant mitochondrial defects in the gastrocnemius muscle of mice. Additionally, Dityr induced serious oxidative stress in the gastrocnemius muscle, accompanied by inflammation, which might be one of the causes of mitochondrial dysfunction. Moreover, significant apoptosis in the gastrocnemius muscle increased after exposure to Dityr. This study confirmed that Dityr induced oxidative stress in the gastrocnemius muscle, which further caused significant mitochondrial damage in the gastrocnemius muscle cell, resulting in decreased capacity of lactic acid metabolism and finally affected performance in endurance exercise. This may be one of the possible mechanisms by which highly oxidized foods cause a decreased muscle energy metabolism.

Self-aspiration sampling design for rapid analyses of volatile organic compounds based on atmospheric pressure chemical ionization/photoionization combined ionization source mass spectrometry.

Development of combined mass spectrometry ionization sources has enabled expansion of the application and scope of mass spectrometry. A novel hybrid ionization system combining vacuum ultraviolet (VUV) and atmospheric pressure chemical ionization (APCI) was constructed. Gaseous samples were self-aspirated into an ionization zone through a capillary by negative pressure, generated by high-speed airflow based on the Venturi effect. Compared with APCI mode alone, the signal-to-noise ratio (S/N) in APCI/VUV mode was increased by about 276-times. To increase the ionization efficiency further, correlated experimental conditions were optimized. Four types of volatile organic compounds (VOCs) were tested to evaluate the performance of the APCI/VUV ion source. Excellent linearity and limit of detection were achieved for compounds in mixed solutions. Quantitative analyses of four VOCs (toluene, cyclohexanone, styrene and ethylbenzene) using APCI/VUV-MS were done, and the relative standard deviations (RSDs) were 1.57%, 6.30%, 4.49% and 8.21%, respectively, indicating that the APCI/VUV ionization source had excellent reproducibility. Our results demonstrated that the developed method was promising for analyzing VOCs as well as being rapid, simple, and easy to operate.