Downregulation of chloride voltage-gated channel 7 contributes to hyperalgesia following spared nerve injury.

Alterations in anion balance potential, along with the involvement of cation-chloride cotransporters, play pivotal roles in the development of hyperalgesia after peripheral nerve injury. Chloride voltage-gated channel seven (CLCN7) is the predominant member of the CLC protein family. Investigations on CLCN7 have focused primarily on its involvement in osteosclerosis and lysosomal storage disorders; nevertheless, its contribution to neuropathic pain has not been determined. In this investigation, we noted high expression of CLCN7 in neurons situated within the spinal dorsal horns and dorsal root ganglions (DRGs). Immunofluorescence analysis revealed that CLCN7 was predominantly distributed among IB4-positive and CGRP-positive neurons. Furthermore, the expression of CLCN7 was observed to be mainly reduced in neurons within the spinal dorsal horns and in small- and medium-sized neurons located in the DRGs of spared nerve injury mice. Knockdown of CLCN7 via siRNA in the DRGs resulted in increased mechanical and thermal hyperalgesia in naïve mice. Furthermore, the excitability of cultured DRG neurons in vitro was augmented upon treatment with CLCN7 siRNA. These findings suggested that CLCN7 downregulation following SNI was crucial for the manifestation of mechanical and thermal hyperalgesia, highlighting potential targeting strategies for treating neuropathic pain.

Pangenome graph layout by Path-Guided Stochastic Gradient Descent.

MOTIVATION: The increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human-readable graph layout: a graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graph's potential excessive size, this is a significant challenge. RESULTS: In response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by SGD. We show that our implementation efficiently computes the low-dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features. AVAILABILITY AND IMPLEMENTATION: We integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi.

Genetic variation underlying differential ammonium and nitrate responses in Arabidopsis thaliana.

Nitrogen is an essential element required for plant growth and productivity. Understanding the mechanisms and natural genetic variation underlying nitrogen use in plants will facilitate the engineering of plant nitrogen use to maximize crop productivity while minimizing environmental costs. To understand the scope of natural variation that may influence nitrogen use, we grew 1,135 Arabidopsis thaliana natural genotypes on two nitrogen sources, nitrate and ammonium, and measured both developmental and defense metabolite traits. By using different environments and focusing on multiple traits, we identified a wide array of different nitrogen responses. These responses are associated with numerous genes, most of which were not previously associated with nitrogen responses. Only a small portion of these genes appear to be shared between environments or traits, while most are predominantly specific to a developmental or defense trait under a specific nitrogen source. Finally, by using a large population, we were able to identify unique nitrogen responses, such as preferring ammonium or nitrate, which appear to be generated by combinations of loci rather than a few large-effect loci. This suggests that it may be possible to obtain novel phenotypes in complex nitrogen responses by manipulating sets of genes with small effects rather than solely focusing on large-effect single gene manipulations.

TLR7 enhancing follicular helper T (Tfh) cells response in C57BL/6 mice infected with Plasmodium yoelii NSM TLR7 mediated Tfh cells in P. yoelii infected mice.

Toll-like receptors (TLRs) play an important role in inducing innate and acquired immune responses against infection. However, the effect of Toll-like receptor 7 (TLR7) on follicular helper T (Tfh) cells in mice infected with Plasmodium is still not clear. The results showed that the splenic CD4+ CXCR5+ PD-1+ Tfh cells were accumulated after Plasmodium yoelii NSM infection, the content of splenic Tfh cells was correlated to parasitemia and/or the red blood cells (RBCs) counts in the blood. Moreover, the expression of TLR7 was found higher than TLR2, TLR3 and TLR4 in splenic Tfh cells of the WT mice. TLR7 agonist R848 and the lysate of red blood cells of infected mice (iRBCs) could induce the activation and differentiation of splenic Tfh cells. Knockout of TLR7 leads to a decrease in the proportion of Tfh cells, down-regulated expression of functional molecules CD40L, IFN-γ, IL-21 and IL-10 in Tfh cells; decreased the proportion of plasma cells and antibody production and reduces the expression of STAT3 and Ikzf2 in Tfh cells. Administration of R848 could inhibit parasitemia, enhance splenic Tfh cell activation and increase STAT3 and Ikzf2 expression in Tfh cells. In summary, this study shows that TLR7 could regulate the function of Tfh cells, affecting the immune response in the spleen of Plasmodium yoelii NSM-infected mice.

Trained immunity from the perspective of Plasmodium infection.

The immune system of vertebrates includes innate immunity and adaptive immunity, and the network between them enables the host to fight against invasions of various pathogens. Recently, studies discovered that immune memory is one of the features of innate immunity, breaking the previous opinion that immune memory exists only in adaptive immunity. Immune memory supports innate immune cells to respond efficiently upon reinfection or restimulation. During the Plasmodium infection, the innate immune system is the first to be triggered, and innate immune cells are activated by components from Plasmodium or Plasmodium-infected red blood cells. Innate immune cells could be induced to develop memory after the activation and may play an important role in the subsequent infection of Plasmodium or other pathogens and stimulation. This review will discuss the recent findings relevant to trained immunity and Plasmodium infection, facilitating the understanding of the role of trained immunity in malaria and other diseases and the development of therapeutic strategies based on trained immunity.

Scaling Supercapacitive Swing Adsorption of CO2 Using Bipolar Electrode Stacks.

Supercapacitive swing adsorption (SSA) modules with bipolar stacks having 2, 4, 8, and 12 electrode pairs made from BPL 4 × 6 activated carbon are constructed and tested for carbon dioxide capture applications. Tests are performed with simulated flue gas (15%CO2 /85%N2) at 2, 4, 8, and 12 V, respectively. Reversible adsorption with sorption capacities (≈58 mmol kg-1) and adsorption rates (≈38 µmol kg-1 s-1) are measured for all stacks. The productivity scales with the number of cells in the module, and increases from 70 to 390 mmol h-1 m-2. The energy efficiency and energy consumption improve with increasing number of bipolar electrodes from 67% to 84%, and 142 to 60 kJ mol-1, respectively. Overall, the results show that SSA modules with bipolar electrodes can be scaled without reducing the adsorptive performance, and with improvement of energetic performance.

Isolation, identification, and pathogenicity of two novel goose astrovirus from goslings with severe gout in China.

Goose astroviruses (GAstVs) are important pathogens which can cause gout in goslings leading to huge economic losses for the goose farming industry in China. In 2023, an infectious disease characterized by visceral gout broke out in commercial goose farms in Guangxi and Guangdong provinces of China. In this study, two GAstV strains of GXNN and GDCS were successfully isolated from these two disease-ridden goose farms. The complete genomic lengths of these two strains were 7166 bp, and phylogenetic analysis showed that they were both GAstV-2 subtypes. The 3-dimensional structures of the capsid protein were predicted and six characteristic mutation sites at amino acid positions 60, 61, 228, 229, 456 and 523 were found within the strong antigenic regions. A recombination event occurred at 6833-7070 nt between the GAstV TZ03 and Turkey astrovirus CA/00 and this was detected in both the GXNN and GDCS strains. Another recombinant event occurred at 63-2747 nt between the GAstV XT1 and GAstV SDPY and this was detected in the GDCS strain. When 1-day-old goslings were infected with the novel GXNN and GDCS strains, they showed severe visceral gout. This was accompanied by enlarged spleens, liver hemorrhages and urate deposits in the kidneys and ureters and their blood urea nitrogen levels were significantly elevated. The mortality rates of the GXNN- and GDCS-infected groups were pathogenically high at 80 % and 60 %, respectively. These results will promote our understanding of the evolution and epidemic potential of GAstVs in China.

Multi-feature, Chinese-Western medicine-integrated prediction model for diabetic peripheral neuropathy based on machine learning and SHAP.

BACKGROUND: Clinical studies have shown that diabetic peripheral neuropathy (DPN) has been on the rise, with most patients presenting with severe and progressive symptoms. Currently, most of the available prediction models for DPN are derived from general clinical information and laboratory indicators. Several Traditional Chinese medicine (TCM) indicators have been utilised to construct prediction models. In this study, we established a novel machine learning-based multi-featured Chinese-Western medicine-integrated prediction model for DPN using clinical features of TCM. MATERIALS AND METHODS: The clinical data of 1581 patients with Type 2 diabetes mellitus (T2DM) treated at the Department of Endocrinology of the First Affiliated Hospital of Anhui University of Chinese Medicine were collected. The data (including general information, laboratory parameters and TCM features) of 1142 patients with T2DM were selected after data cleaning. After baseline description analysis of the variables, the data were divided into training and validation sets. Four prediction models were established and their performance was evaluated using validation sets. Meanwhile, the accuracy, precision, recall, F1 score and area under the curve (AUC) of ROC were calculated using ten-fold cross-validation to further assess the performance of the models. An explanatory analysis of the results of the DPN prediction model was carried out using the SHAP framework based on machine learning-based prediction models. RESULTS: Of the 1142 patients with T2DM, 681 had a comorbidity of DPN, while 461 did not. There was a significant difference between the two groups in terms of age, cause of disease, systolic pressure, HbA1c, ALT, RBC, Cr, BUN, red blood cells in the urine, glucose in the urine, and protein in the urine (p < 0.05). T2DM patients with a comorbidity of DPN exhibited diverse TCM symptoms, including limb numbness, limb pain, hypodynamia, thirst with desire for drinks, dry mouth and throat, blurred vision, gloomy complexion, and unsmooth pulse, with statistically significant differences (p < 0.05). Our results showed that the proposed multi-featured Chinese-Western medicine-integrated prediction model was superior to conventional models without characteristic TCM indicators. The model showed the best performance (accuracy = 0.8109, precision = 0.8029, recall = 0.9060, F1 score = 0.8511, and AUC = 0.9002). SHAP analysis revealed that the dominant risk factors that caused DPN were TCM symptoms (limb numbness, thirst with desire for drinks, blurred vision), age, cause of disease, and glycosylated haemoglobin. These risk factors were exerted positive effects on the DPN prediction models. CONCLUSIONS: A multi-feature, Chinese-Western medicine-integrated prediction model for DPN was established and validated. The model improves early-stage identification of high-risk groups for DPN in the diagnosis and treatment of T2DM, while also providing informative support for the intelligent management of chronic conditions such as diabetes.

Temperature-responsive hydrogel-grafted vessel-on-a-chip: Exploring cold-induced endothelial injury.

Cold-induced vasoconstriction is a significant contributor that leads to chilblains and hypothermia in humans. However, current animal models have limitations in replicating cold-induced acral injury due to their low sensitivity to cold. Moreover, existing in vitro vascular chips composed of endothelial cells and perfusion systems lack temperature responsiveness, failing to simulate the vasoconstriction observed under cold stress. This study presents a novel approach where a microfluidic bioreactor of vessel-on-a-chip was developed by grafting the inner microchannel surface of polydimethylsiloxane with a thermosensitive hydrogel skin composed of N-isopropyl acrylamide and gelatin methacrylamide. With a lower critical solution temperature set at 30°C, the gel layer exhibited swelling at low temperatures, reducing the flow rate inside the channel by 10% when the temperature dropped from 37°C to 4°C. This well mimicked the blood stasis observed in capillary vessels in vivo. The vessel-on-a-chip was further constructed by culturing endothelial cells on the surface of the thermosensitive hydrogel layer, and a perfused medium was introduced to the cells to provide a physiological shear stress. Notably, cold stimulation of the vessel-on-a-chip led to cell necrosis, mitochondrial membrane potential (ΔΨm) collapse, cytoskeleton disaggregation, and increased levels of reactive oxygen species. In contrast, the static culture of endothelial cells showed limited response to cold exposure. By faithfully replicating cold-induced endothelial injury, this groundbreaking thermosensitive vessel-on-a-chip technology offers promising advancements in the study of cold-induced cardiovascular diseases, including pathogenesis and therapeutic drug screening.

Establishment and external validation of an early warning model of diabetic peripheral neuropathy based on random forest and logistic regression.

OBJECTIVE: The primary objective of this study was to investigate the risk factors for diabetic peripheral neuropathy (DPN) and to establish an early diagnostic prediction model for its onset, based on clinical data and biochemical indices. METHODS: Retrospective data were collected from 1,446 diabetic patients at the First Affiliated Hospital of Anhui University of Chinese Medicine and were split into training and internal validation sets in a 7:3 ratio. Additionally, 360 diabetic patients from the Second Affiliated Hospital were used as an external validation cohort. Feature selection was conducted within the training set, where univariate logistic regression identified variables with a p-value < 0.05, followed by backward elimination to construct the logistic regression model. Concurrently, the random forest algorithm was applied to the training set to identify the top 10 most important features, with hyperparameter optimization performed via grid search combined with cross-validation. Model performance was evaluated using ROC curves, decision curve analysis, and calibration curves. Model fit was assessed using the Hosmer-Lemeshow test, followed by Brier Score evaluation for the random forest model. Ten-fold cross-validation was employed for further validation, and SHAP analysis was conducted to enhance model interpretability. RESULTS: A nomogram model was developed using logistic regression with key features: limb numbness, limb pain, diabetic retinopathy, diabetic kidney disease, urinary protein, diastolic blood pressure, white blood cell count, HbA1c, and high-density lipoprotein cholesterol. The model achieved AUCs of 0.91, 0.88, and 0.88 for the training, validation, and test sets, respectively, with a mean AUC of 0.902 across 10-fold cross-validation. Hosmer-Lemeshow test results showed p-values of 0.595, 0.418, and 0.126 for the training, validation, and test sets, respectively. The random forest model demonstrated AUCs of 0.95, 0.88, and 0.88 for the training, validation, and test sets, respectively, with a mean AUC of 0.886 across 10-fold cross-validation. The Brier score indicates a good calibration level, with values of 0.104, 0.143, and 0.142 for the training, validation, and test sets, respectively. CONCLUSION: The developed nomogram exhibits promise as an effective tool for the diagnosis of diabetic peripheral neuropathy in clinical settings.

Identifying the twist factor of twisted partially coherent optical beams.

Twisted partially coherent light, characterized by its unique twist factor, offers novel control over the statistical properties of random light. However, the recognition of the twist factor remains a challenge due to the low coherence and the stochastic nature of the optical beam. This paper introduces a method for the recognition of twisted partially coherent beams by utilizing a circular aperture at the source plane. This aperture produces a characteristic hollow intensity structure due to the twist phase. A deep learning model is then trained to identify the twist factor of these beams based on this signature. The model, while simple in structure, effectively eliminates the need for complex optimization layers, streamlining the recognition process. This approach offers a promising solution for enhancing the detection of twisted light and paves the way for future research in this field.

Improved Tumor Infiltration and Immunomodulation for Tumor Therapy: A Pathway Based on Tetrahedral Framework Nucleic Acids Coupled Bacterial Nanocells.

Growing evidence indicates that the tumor microenvironment (TME) can be combined with other therapeutic modalities, including cytotoxic chemotherapy and targeted therapies, to produce unanticipated results in oncology treatment. Here, we proposed a novel bacterial nanomaterial capable of targeting peritumoral biofilm and modulating TME. It was based on tetrahedral framework nucleic acids (T) that were chemically attached to aptamer AS1411 and 5-fluorouracil (AT5). Additionally, the oral pathogenic bacterium Streptococcus mutans (S.m) was employed as a biocarrier for synergetic biofilm targeting and immunomodulation. In this article, the effect of AT5-coupled S.m-derived nanocells (S.m-AT5) was investigated in vitro and in vivo. Due to bacteria aggregation in the tumor-specific biofilm, these nanocells released greater medication concentrations. Furthermore, they exerted an immunomodulatory effect by stimulating the maturation of dendritic cells (DCs) and regulation of T cells. This chemo-immunostimulation combination has a powerful antitumor impact. It may also be an advanced approach for boosting the survival rate of cancer patients.

Oxygen-Assisted Supercapacitive Swing Adsorption of Carbon Dioxide.

We report on the supercapacitive swing adsorption (SSA) of carbon dioxide at different voltage windows in the presence of oxygen using activated carbon electrodes, and deliquescent, aqueous electrolytes. The presence of O2 in the CO2/N2 gas mixture results in an up to 11 times higher CO2 adsorption capacity with 3 M MgBr2 (at 0.6 V) and up to 4-5 times higher adsorption capacity with 3 M MgCl2 (at 1 V). A tradeoff between high CO2 adsorption capacities and lower coulombic efficiencies was observed at voltages above 0.6 V. The energetic and adsorptive performance of the electrodes in the presence of oxygen below 0.5 V was similar to the performance with a CO2/N2 mixture without oxygen at 1 V. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) of the electrodes demonstrate that the specific capacitance increases while the diffusion resistance decreases in the presence of oxygen. Oxygen concentrations ranging between 5-20 % give similar energetic and adsorptive performance. The electrodes exhibit stable performance for up to 100 cycles of operation.

High-Voltage Supercapacitive Swing Adsorption of Carbon Dioxide.

Supercapacitive swing adsorption (SSA) with garlic roots-derived activated carbon achieves a record adsorption capacity of 312 mmol kg-1 at a low energy consumption of 72 kJ mol-1 and high mass loadings (>30 mg cm-2 ) at 1.0 V for 85%N2 /15%CO2 mixtures. The activated carbons are inexpensively prepared in a one-step process using potassium carbonate, and air as activators. The adsorption capacity further increases with increasing voltage. At a voltage of 1.4 V, a sorption capacity of 524 mmol kg-1 at an energy consumption of 130 kJ mol-1 can be achieved. The volumetric sorption capacity is also enhanced and reaches values of 85.7 mol m-3 at 1.0 V, and 126 mol m-3 at 1.4 V. Cycle stability for at least 130 h is demonstrated.

Immunological characteristics of CD103+CD8+ Tc cells in the liver of C57BL/6 mouse infected with plasmodium NSM.

CD103 is an important marker of tissue-resident memory T cells (TRM) which play important roles in fighting against infection. However, the immunological characteristics of CD103+ T cells are not thoroughly elucidated in the liver of mouse infected with Plasmodium. Six- to eight-week-old C57BL/6 mice were infected with Plasmodium yoelii nigeriensis NSM. Mice were sacrificed on 12-16 days after infection and the livers were picked out. Sections of the livers were stained, and serum aspartate aminotransferase (AST) and alanine transaminase (ALT) levels were measured. Moreover, lymphocytes in the liver were isolated, and the expression of CD103 was determined by using qPCR. The percentage of CD103 on different immune cell populations was dynamically observed by using flow cytometry (FCM). In addition, the phenotype and cytokine production characteristics of CD103+CD8+ Tc cell were analyzed by using flow cytometry, respectively. Erythrocyte stage plasmodium infection could result in severe hepatic damage, a widespread inflammatory response and the decrease of CD103 expression on hepatic immune cells. Only CD8+ Tc and γδT cells expressed higher levels of CD103 in the uninfected state.CD103 expression in CD8+ Tc cells significantly decreased after infection. Compared to that of CD103- CD8+ Tc cells, CD103+ CD8+ Tc cells from the infected mice expressed lower level of CD69, higher level of CD62L, and secreted more IL-4, IL-10, IL-17, and secreted less IFN-γ. CD103+CD8+ Tc cells might mediate the hepatic immune response by secreting IL-4, IL-10, and IL-17 except IFN-γ in the mice infected with the erythrocytic phase plasmodium, which could be involved in the pathogenesis of severe liver damage resulted from the erythrocytic phase plasmodium yoelii nigeriensis NSM infection.

A review of synthetic biology tools in Yarrowia lipolytica.

Yarrowia lipolytica is a non-conventional oleaginous yeast with great potential for industrial production. Y. lipolytica has a high propensity for flux through tricarboxylic acid cycle intermediates. Therefore, this host is currently being developed as a workhorse, and is rapidly emerging in biotechnology fields, especially for industrial chemical production, whole-cell bioconversion, and the treatment and recycling of industrial waste. In recent studies, Y. lipolytica has been rewritten and introduced with non-native metabolites of certain compounds of interest owing to the advancement in synthetic biology tools. In this review, we collate recent progress to present a detailed and insightful summary of the major developments in synthetic biology tools and techniques for Y. lipolytica, including promoters, terminators, selection markers, autonomously replicating sequences, DNA assembly techniques, genome editing techniques, and subcellular organelle engineering. This comprehensive overview would be a useful resource for future genetic engineering studies to improve the yield of desired metabolic products in Y. lipolytica.

[Prescription and medication rules of traditional Chinese medicine for prevention and treatment of diabetic microangiopathy based on literature mining].

This study explored the prescription and medication rules of traditional Chinese medicine(TCM) in the prevention and treatment of diabetic microangiopathy based on literature mining. Relevant literature on TCM against diabetic microangiopathy was searched and prescriptions were collected. Microsoft Excel 2021 software was used to establish a prescription database, and an analysis was conducted on the frequency, properties, flavors, meridian tropism, and efficacy classifications of drugs. Association rule analysis, cluster analysis, and factor analysis were performed using SPSS Modeler 18.0 and SPSS Statistics 26.0 software. The characteristic active components and mechanisms of action of medium-high frequency drugs in the analysis of medication rules were explored through li-terature mining. A total of 1 327 prescriptions were included in this study, involving 411 drugs, with a total frequency reaching 19 154 times. The top five high-frequency drugs were Astragali Radix, Angelicae Sinensis Radix, Poria, Salviae Miltiorrhizae Radix et Rhizoma, and Rehmanniae Radix. The cold and warm drugs were used in combination. Drugs were mainly sweet, followed by bitter and pungent, and acted on the liver meridian. The majority of drugs were effective in tonifying deficiency, clearing heat, activating blood, and resolving stasis. Association rule analysis identified the highly supported drug pair of Astragali Radix-Angelicae Sinensis Radix and the highly confident drug combination of Poria-Alismatis Rhizoma-Corni Fructus. The strongest correlation was found among Astragali Radix, Angelicae Sinensis Radix, Poria, and Salviae Miltiorrhizae Radix et Rhizoma through the complex network analysis. Cluster analysis identified nine categories of drug combinations, while factor analysis identified 16 common factors. The analysis of active components in high-frequency drugs for the treatment of diabetic microangiopathy revealed that these effective components mainly exerted their effects by inhibiting oxidative stress and suppressing inflammatory reactions. The study found that the pathogenesis of diabetic microangiopathy was primarily characterized by deficiency in origin, with a combination of deficiency and excess. Deficiency was manifested as Qi deficiency and blood deficiency, while excess as phlegm-heat and blood stasis. The key organ involved in the pathological changes was the liver. The treatment mainly focused on supplementing Qi and nourishing blood, supplemented by clearing heat, coo-ling blood, activating blood, and dredging collaterals. Commonly used formulas included Danggui Buxue Decoction, Liuwei Dihuang Pills, Erzhi Pills, and Buyang Huanwu Decoction. The mechanisms of action of high-frequency drugs in the treatment of diabetic microangiopathy were often related to the inhibition of oxidative stress and suppression of inflammatory reactions. These findings can provide references for the clinical treatment of diabetic microangiopathy and the development of targeted drugs.

Electrochemically activated carbon-halogen bond cleavage and C-C coupling monitored by in situ shell-isolated nanoparticle-enhanced Raman spectroscopy.

The electroreductive cleavage of carbon-halogen bonds has attracted increasing attention in both electrosynthesis and pollution remediation. Herein, by employing the in situ electrochemical shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) technique, we have successfully investigated the electroreductive dehalogenation process of aryl halides with the thiol group on a smooth Au electrode in aqueous solution at different pH values. The obtained potential-dependent Raman spectra directly reveal a mixture of the reduction products 4,4'-biphenyldithiol (BPDT) and thiophenol (TP). The conversion ratios of the C-Cl and C-Br bonds at pH = 7 are 37% and 55%, respectively. Furthermore, quantitative analysis of the intensity variations of ν(C-Cl), ν(C-Br) and aromatic ν(CC) stretching modes suggests electroreductive dehalogenation via both direct electron transfer reduction and electrocatalytic hydrodehalogenation. Molecular evidence for the C-C cross coupling process through TP reaction with benzene free radical intermediates is found at negative potentials, which leads to the increasing selectivity of biphenyl products.

Discovery of Potential Lipid Biomarkers for Human Colorectal Cancer by In-Capillary Extraction Nanoelectrospray Ionization Mass Spectrometry.

Discovering cancer biomarkers is of significance for clinical medicine and disease diagnosis. In this article, we develop an in-capillary extraction nanoelectrospray ionization mass spectrometry (ICE-nanoESI-MS) method to rapidly and in situ investigate human colorectal cancer for discovering lipid biomarkers. The ICE-nanoESI-MS method is performed using a tungsten microdissecting probe for in situ microsampling of surgical human colorectal cancer tumors and their paired distal noncancerous tissues during/after surgery. After sampling, the tungsten probe and the adhered tissues are inserted into a nanospray tip prefilled with some solvent for simultaneous in-capillary extraction and nanoESI-MS detection under ambient and open-air conditions. Online coupling of the Paternò-Büchi reaction and radical-direct fragmentation with ICE-nanoESI-MS is easily realized, which provides the opportunity to precisely determine carbon-carbon double bond (C═C) locations and stereospecific numbering (sn) positions of lipid biomarkers. Subsequently, a total of 12 pairs of colorectal cancer tumors and distal noncancerous tissues from different patients are investigated by our proposed ICE-nanoESI-MS method. A significant increase in lysophospholipids and fatty acids as well as a significant decrease in ceramides are discovered, and lysophospholipids are found as the potential biomarkers related to the formation and pathogenesis of human colorectal cancer.

Local vibration induced vascular pathological structural changes and abnormal levels of vascular damage indicators.

BACKGROUND: The vascular component of the hand-arm-vibration syndrome (HAVS) is often characterized by vibration-induced white fingers (VWF). Active substances secreted by the vascular endothelial cells (VEC) maintain a dynamic balance but damage to the blood vessels may occur when the equilibrium is altered, thus forming an important pathological basis for VWF. This study was aimed at investigating vascular damage indicators as a basis for an early detection of disorders caused by vibration, using the rat tail model. METHODS AND RESULTS: Experiments were conducted using a control group of rats not exposed to vibration while two exposed groups having different exposure durations of 7 and 14 days were randomly formed. Following exposure, the structural changes of tail tissue samples in anesthetized rats were observed. Enzyme-linked immunosorbent assay (ELISA) was used for analyzing four vascular damage indicators myosin regulatory light chain (MLC2), endothelin-1 (ET-1), vinculin (VCL) and 5-hydroxytryptamine (5-HT) in tail blood samples. We found that both vascular smooth muscle and endothelial cells displayed changes in morphology characterized by vacuolization and swelling in the vibration-exposed group. The levels of vascular damage indicators were altered under the vibration. CONCLUSION: The degree of vascular pathology increased with the longer duration exposure. Furthermore, the levels of MLC2, ET-1 and 5-HT in rat plasma were associated with vascular injury caused by local vibration.