Causal relationship between immune cells and telomere length: mendelian randomization analysis.

BACKGROUND: The causal relationship between immune cells and telomere length remains controversial. METHODS: Data on the immune cells were obtained from a previous study with 3,757 participants. Data on telomere length were obtained from the OpenGWAS database. Genome-Wide Association Study (GWAS) data were obtained and screened for eligible instrumental variables (IVs) using the TwoSampleMR package and the Phenoscanner database. To investigate the genetic causality between immune cells and telomere length, Mendelian randomization (MR) analysis and Bayesian weighted Mendelian randomization (BWMR) analysis were used. RESULTS: MR analysis showed that there is indeed a genetic causal relationship between immune cells and telomere length. A total of 16 immune cells were successfully validated. A positive correlation was found between telomere length and immune cells such as CD28 + CD45RA + CD8br %CD8br (OR = 1.002, 95%CI: 1.000-1.003). A negative correlation was found between telomere length and immune cells such as Transitional AC (OR = 0.991, 95%CI: 0.984-0.997) (P < 0.05). Reverse MR analysis similarly confirmed that telomere length can affect four types of immune cells, including CD25 on IgD + CD24- (OR = 1.291, 95%CI: 1.060-1.571), at the genetic level. CONCLUSION: There is indeed a mutual genetic causality between immune cells and telomere length, which will provide theoretical basis and support for more subsequent clinical studies.

Proton Transfer Processes in 2-Butenenitrile Dimer Cation Studied by Mass-Selective Infrared Spectroscopy.

2-Butenenitrile (2-Bu) is a recently discovered crucial interstellar molecule. Herein, an abnormal NH band was observed in the infrared spectrum of the 2-Bu dimer cation, suggestive of a proton transfer reaction within the cluster. Through a comprehensive theoretical analysis of the IR spectrum of (2-Bu)2+, we discovered not only the formation of a new C-N bond through the attachment of one 2-Bu to another but also the occurrence of a proton transfer reaction in the cluster. This proton was identified as originating from the methyl group of the attaching 2-Bu in the cluster based on the analysis of IR spectra of (2-Bu)+ and [2-Bu-acrylonitrile (AN)]+. Furthermore, the detailed reaction process of this ion-molecule reaction is examined with theoretical calculation. This finding contributes significantly to our deeper understanding of ion-molecule reactions in the gas phase and the formation of nitrogen-containing prebiotic molecules in the interstellar medium.

Cuproptosis-Related Genes MTF1 and LIPT1 as Novel Prognostic Biomarker in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a life-threatening hematologic malignant disease with high morbidity and mortality in both adults and children. Cuproptosis, a novel mode of cell death, plays an important role in tumor development, but the functional mechanisms of cuproptosis-related genes (CRGs) in AML are unclear. The differential expression of CRGs between tumors such as AML and normal tissues in UCSC XENA, TCGA and GTEx was verified using R (version: 3.6.3). Lasso regression, Cox regression and Nomogram were used to screen for prognostic biomarkers of AML and to construct corresponding prognostic models. Kaplan-Meier analysis, ROC analysis, clinical correlation analysis, immune infiltration analysis and enrichment analysis were used to further investigate the correlation and functional mechanisms of CRGs with AML. The ceRNA regulatory network was used to identify the mRNA-miRNA-lncRNA regulatory axis. Cuproptosis-related genes LIPT1, MTF1, GLS and CDKN2A were highly expressed in AML, while FDX1, LIAS, DLD, DLAT, PDHA1, SLC31A1 and ATP7B were lowly expressed in AML. Lasso regression, Cox regression, Nomogram and calibration curve finally identified MTF1 and LIPT1 as two novel prognostic biomarkers of AML and constructed the corresponding prognostic models. In addition, all 12 CRGs had predictive power for AML, with MTF1, LIAS, SLC31A1 and CDKN2A showing more reliable results. Further analysis showed that ATP7B was closely associated with mutation types such as FLT3, NPM1, RAS and IDH1 R140 in AML, while the expression of MTF1, LIAS and ATP7B in AML was closely associated with immune infiltration. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) revealed that biological functions such as metal ion transmembrane transporter activity, haptoglobin binding and oxygen carrier activity, pathways such as interferon alpha response, coagulation, UV response DN, apoptosis, hypoxia and heme metabolism all play a role in the development of AML. The ceRNA regulatory network revealed that 6 lncRNAs such as MALAT1, interfere with MTF1 expression through 6 miRNAs such as hsa-miR-32-5p, which in turn affect the development and progression of AML. In addition, APTO-253 has the potential to become an AML-targeted drug. The cuproptosis-related genes MTF1 and LIPT1 can be used as prognostic biomarkers in AML. A total of six lncRNAs, including MALAT1, are involved in the expression and regulation of MTF1 in AML through six miRNAs such as hsa-miR-32-5p.

[Non-targeted metabolomics of spleen and liver metabolism in mice treated with Pruni Semen processed with different methods].

Ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was employed to investigate the impacts of Pruni Semen processed with different methods(raw and fried) on the liver and spleen metabolism in mice. A total of 24 male mice were randomly assigned to three groups: raw Pruni Semen group, fried Pruni Semen group, and control(deionized water) group. Mice in the three groups were orally administrated with 0.01 g·mL~(-1) Pruni Semen decoction or deionized water for one week. After that, the liver and spleen tissues were collected, and liquid chromatography-mass spectrometry(LC-MS)-based metabolomic analysis was carried out to investigate the impact of Pruni Semen on the liver and spleen metabolism in mice. Compared with thte control group, the raw Pruni Semen group showed up-regulation of 11 metabolites and down-regulation of 57 metabolites in the spleen(P<0.05), as well as up-regulation of 15 metabolites and down-regulation of 58 metabolites in the liver(P<0.05). The fried Pruni Semen group showed up-regulation of 31 metabolites and down-regulation of 10 metabolites in the spleen(P<0.05), along with up-regulation of 26 metabolites and down-regulation of 61 metabolites in the liver(P<0.05). The differential metabolites identified in the raw Pruni Semen group were primarily associated with alanine, aspartate, and glutamate metabolism, purine metabolism, amino sugar and nucleotide sugar metabolism, and D-glutamine and D-glutamate metabolism. The differential metabolites identified in the fried Pruni Semen group predominantly involved riboflavin metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, alanine, aspartate, and glutamate metabolism, D-glutamine and D-glutamate metabolism, and glutathione metabolism. The findings suggest that both raw and fried Pruni Semen have the potential to modulate the metabolism of the liver and spleen in mice by influencing the glutamine and glutamate metabolism.

Simultaneous measurement of axial strain and temperature based on a twin-core single-hole fiber with the optical Vernier effect.

An ultrasensitive optical fiber sensor based on the optical Vernier effect is proposed for the simultaneous measurement of axial strain and temperature. The sensor structure comprises two cascaded Mach-Zehnder interferometers (MZIs) with different free space ranges. The single MZI is built up by fusion splicing a segment of ∼3 mm twin-core single-hole fiber (TCSHF) between two pieces of ∼5 mm none core fibers (NCF). When acting separately, each MZI can respond linearly to the axial strain change with a sensitivity of ∼ 0.6 pm/µÎµ and temperature with a sensitivity of ∼34 pm/°C. When the two MZIs are cascaded in series, the sensitivities are amplified about 30 times because of the optical Vernier effect. Experimental results demonstrate that the cascaded structure exhibits a high axial strain sensitivity of ∼ 17 pm/µÎµ in the range of 0 to 2000 µÎµ and temperature sensitivity of ∼1.16 nm/°C in the range of 30 to 70 °C. Moreover, the cascaded structure can simultaneously measure the axial strain and temperature change in the acceptable error ranges.

Rapid and sensitive detection of aqueous ammonia harnessing nanocomposite functionalized tilted fiber Bragg grating.

A high sensitive aqueous ammonia sensor based on tilted fiber Bragg grating (TFBG) had been reported. The sensors were fabricated by a 10 ° TFBG coated by a membrane receptor named as Polyaniline/Graphene oxide on the surface of the fiber. The correlative concentrations of aqueous ammonia were demodulated by global monitoring of the envelope area of cladding modes in the transmitted spectrum of the TFBG. Tests have shown that the proposed sensor can provide a linear and rapid response of aqueous ammonia within 22 seconds, in a concentration range from 1-12 ppm. Moreover, the limit of detection can even reach 0.08 ppm, through the theoretical analysis of our experimental results. The proposed sensor has good performance, is easy to manufacture and of small size, making it a good choice for real-time, in-situ, label-free detection of aqueous ammonia in the future.

A high neutrophil-to-platelet ratio is associated with hematoma expansion in patients with spontaneous intracerebral hemorrhage: a retrospective study.

BACKGROUND: Early hematoma expansion (HE) occurs in 20 to 40% of spontaneous intracerebral hemorrhage (ICH) patients and is a primary determinant of early deterioration and poor prognosis. Previous studies have shown that inflammation is a major pathological feature of ICH, and the neutrophil-to-platelet ratio (NPR) is a marker of systemic inflammation. Therefore, we aimed to assess the association between the NPR and HE in ICH patients. METHODS: We retrospectively collected and analyzed data from ICH patients who received treatment at our institution from January 2018 to November 2019. The NPR was calculated from the admission blood test. Brain computed tomography (CT) scans were performed at admission and repeated within 24 h. Hematoma growth was defined as relative growth > 33% or absolute growth > 6 ml. RESULTS: A total of 317 patients were enrolled in our study. Multivariate logistic regression analysis indicated that the NPR was an independent predictor of HE [odds ratio (OR) = 1.742; 95% CI: 1.508-2.012, p < 0.001]. Receiver operating characteristic (ROC) curve analysis revealed that the NPR could predict HE, with an area under the curve of 0.838 (95% CI, 0.788-0.888, p < 0.001). The best predictive cut-off of the NPR for HE was 5.47 (sensitivity, 75.3%; specificity, 77.6%). CONCLUSIONS: A high NPR was associated with an increased risk of HE in patients with ICH.

Single-photon ionization induced C-C or C-N bond formation in pyrrole clusters.

The formation of photodimers of nitrogen heterocyclic compounds (NHCs) can partially explain the DNA damage due to radiation. Pyrrole and its derivatives, as major components of DNA, are used to understand the phenomena at the molecular level. With the aid of vacuum ultraviolet (VUV)-infrared (IR) spectroscopy and theoretical calculations, herein, we explore the possibility of the formation of a new C-C or C-N bond in pyrrole (py) clusters in a supersonic jet after single-photon ionization. Both neutral (py)2 and (py)3 clusters are stabilized by multiple interactions, such as N-H⋯π hydrogen bonds and π⋯π interactions. With 118 nm light ionization of the (py)2, we elucidate that the two py are more inclined to be stabilized by a newly formed C-C or C-N covalent bond, besides the π-stacked parallel structure of (py)2+. The (py)3+ with a C-C or C-N covalent bonded (py)2+ core mainly contributes to the IR spectrum of (py)3+. The present results are helpful to elucidate the mechanism of DNA damage at a molecular level.

Mendelian randomization analysis to analyze the genetic causality between different levels of obesity and different allergic diseases.

BACKGROUND: The causal relationship between obesity and different allergic diseases remains controversial. METHODS: The Two Sample MR package and Phenoscanner database were used to obtain and filter Genome-Wide Association Study (GWAS) data from the Open GWAS database. Mendelian randomization (MR) analysis was used to study the causal relationship between different levels of obesity and different allergic diseases. The data sets related to obesity and asthma were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package. Cluster Profiler and GO plot packages were used for enrichment analysis to verify the results of MR analysis. RESULTS: Two-sample MR analysis showed a causal relationship between obesity and childhood allergy (age < 16), allergic asthma and atopic dermatitis (P < 0.05). In addition, there was also a causal relationship between allergic asthma and obesity (P < 0.05), while there was no genetic causal relationship between obesity and allergic rhinitis, eczema, lactose intolerance and so on (P > 0.05). Subgroup analysis revealed a causal relationship between both class 1 and class 2 obesity and childhood allergy (age < 16) (P < 0.05). Obesity class 1 was associated with allergic asthma, while obesity class 3 was associated with atopic dermatitis (P < 0.05). Bioinformatics analysis shows that there were common DEGs between obesity and allergic asthma. CONCLUSION: Obesity is a risk factor for childhood allergy (age < 16), allergic asthma and atopic dermatitis, while allergic asthma is also a risk factor for obesity. Class 1 and class 2 obesity are both causally associated with childhood allergy (age < 16). In addition, there is a causal relationship between milder obesity and allergic asthma, while heavier obesity is causally related to atopic dermatitis.

Machine learning algorithms for integrating clinical features to predict intracranial hemorrhage in patients with acute leukemia.

BACKGROUND: Intracranial hemorrhage (ICH) in acute leukemia (AL) patients leads to high morbidity and mortality, treatment approaches for ICH are generally ineffective. Thus, early identification of which subjects are at high risk of ICH is of key importance. Currently, machine learning can achieve well predictive capability through constructing algorithms that simultaneously exploit the information coming from clinical features. METHODS: After rigid data preprocessing, 42 different clinical features from 948 AL patients were used to train different machine learning algorithms. We used the feature selection algorithms to select the top 10 features from 42 clinical features. To test the performance of the machine learning algorithms, we calculated area under the curve (AUC) values from receiver operating characteristic (ROC) curves along with 95% confidence intervals (CIs) by cross-validation. RESULTS: With the 42 features, RF exhibited the best predictive power. After feature selection, the top 10 features were international normalized ratio (INR), prothrombin time (PT), creatinine (Cr), indirect bilirubin (IBIL), albumin (ALB), monocyte (MONO), platelet (PLT), lactic dehydrogenase (LDH), fibrinogen (FIB) and prealbumin (PA). Among the top 10 features, INR, PT, Cr, IBIL and ALB had high predictive performance with an AUC higher than 0.8 respectively. CONCLUSIONS: The RF algorithm exhibited a higher cross-validated performance compared with the classical algorithms, and the selected important risk features should help in individualizing aggressive treatment in AL patients to prevent ICH. Efforts that will be made to test and optimize in independent samples will warrant the application of such algorithm and predictors in the future.

Simultaneous measurement of axial strain and lateral stress based on cascaded interference structure.

To solve the cross-sensitivity problem in the dual-parameter optical fiber system, a new type of sensor based on cascaded interference structure is proposed without cross-sensitivity. The design consists of a Michelson interferometer and a Sagnac interferometer based on a high-birefringence suspended core fiber segment. After calculating by the analogous Fast Fourier Transformation (FFT) and filtering by FFT filter, the spectrum of the sensor responds linearly to the change of axial strain and lateral stress. The sensitivity to lateral stress is 3.13 nm/(kPa) in the range from 0 to 1200 Pa and the axial strain is 1.846e-4 (nm·µÉ›)-1 from 0 to 4000 µÉ›. The capability of the proposed sensor for dual-parameter sensing is also experimentally demonstrated. The precision rate for dual-parameter sensing is as high as 66.7%, reflecting the sensor's usability for simultaneous measurement of axial strain and lateral stress.

Comparison of mitogenomes of three Petalocephala species (Hemiptera: Cicadellidae: Ledrinae) and their phylogenetic analysis.

Ledrinae is a unique group of leafhoppers with a distinct appearance. Petalocephala is the largest Ledrinae genus that is difficult to identify except by dissecting the male genitals. To date, research on Ledrinae is relatively less compared with other leafhoppers. Therefore, to better understand this group, we sequenced and analyzed three complete Petalocephala mitochondrial genomes. We comparatively analyzed these general Petalocephala genomic features (including size, AT content, AT/GC skew, 13 protein-coding gene nucleotide compositions, etc.), and predicted 22 transfer RNA secondary structures. We obtained highly consistent phylogenetic results within Cicadellidae based on mitogenomic data using the maximum likelihood and Bayesian methods. Our results showed that all subfamilies were monophyletic and had a high node support rate, and there was a sister group relationship between Ledrinae and all other leafhopper groups. Furthermore, treehoppers were found to originate from leafhoppers and showed sister group relationships with Megophthalminae. Within Ledrinae, all phylogenetic trees supporting phylogenetic relationships were as follows: ([P. dicondylica + P. gongshanensis] + [Tituria pyramidata + [Ledra auditura + P. gongshanensis]]) Based on the complete mitogenome phylogenetic analysis and the comparison of morphological characteristics, we propose that Petalocephala is not monophyletic.

Dancing in local space: rolling hoop orbital amplification combined with local cascade nanozyme catalytic system to achieve ultra-sensitive detection of exosomal miRNA.

The exosomal miRNA (exo-miRNA) derived from tumor cells contains rich biological information that can effectively aid in the early diagnosis of disease. However, the extremely low abundance imposes stringent requirements for accurate detection techniques. In this study, a novel, protease-free DNA amplification strategy, known as "Rolling Hoop Orbital Amplification" (RHOA), was initially developed based on the design concept of local reaction and inspired by the childhood game of rolling iron ring. Benefiting from the local space constructed by the DNA orbital, the circular DNA enzyme rolls directionally and interacts efficiently with the amplification element, making it nearly 3-fold more productive than conventional free-diffusion amplification. Similarly, the localized cascade nanozyme catalytic system formed by bridging DNA probes also exhibits outperformed than free ones. Therefore, a localized energized high-performance electrochemiluminescence (ECL) biosensor was constructed by bridging cascading nanozymes on the electrode surface through DNA probes generated by RHOA, with an impressive limit of detection (LOD) of 1.5 aM for the detection of exosomal miRNA15a-5p and a stable linearity over a wide concentration range from 10- 2 to 108 fM. Thus, this work is a focused attempt at the localized reaction, which is expected to provide a reliable method for accurately detecting of exo-miRNAs.

An Optical Fiber Sensor for Axial Strain, Curvature, and Temperature Measurement Based on Single-Core Six-Hole Optical Fiber.

In this paper, the field distribution and effective refractive index of transmission modes in single-core six-hole optical fiber were researched by modeling and simulation experiments. Based on the simulation results, a new type of sensor for axial strain, curvature, and temperature applications measurement was designed and fabricated. The experimental results showed that the axial strain sensitivities at different dips were -0.97 pm/µÎµ and -1.05 pm/µÎµ in the range from 0 to 2000 µÎµ, and the temperature sensitivities were 35.17 pm/°C and 47.27 pm/°C in the range from 25 to 75 °C. In addition, the proposed sensor also detected the curvature change with sensitivities of 7.36 dB/m-1 and 20.08 dB/m-1 from -2.582 m-1 to -1.826 m-1, respectively. Finally, through theoretical analysis, it can be deduced that this has potential application in the field of simultaneous measurement of strain and temperature.

Recent research on inherited metabolic diseases in children. / å„¿ç«¥é—ä¼ ä»£è°¢ç— çš„ç ”ç©¶è¿›å±•.

With the improvement in the research level and the diagnosis and treatment technology of inherited metabolic diseases (IMD), the research on pediatric IMD in China has made great progress, but there is still some distance from the international level. Due to the vast territory of China and the uneven distribution of medical resources, the regional characteristics of IMD remain unclear in China, and there are many problems and difficulties in early diagnosis and treatment. Therefore, it is necessary to improve the understanding of pediatric IMD among pediatricians, so as to improve the diagnosis and treatment level, achieve an early identification, diagnosis, and treatment of pediatric IMD, and effectively reduce the fatality and disability rates of children with IMD. This article reviews the research progress of IMD in children in China, and analyzes the features of representative IMDs. Citation:Chinese Journal of Contemporary Pediatrics, 2022, 24(3): 326-331.

Fingolimod loaded niosomes attenuates sevoflurane induced cognitive impairments.

Neurocognition is a severe, neurological challenge caused due to sevoflurane application for induction of anaesthesia. The plan of this study is to investigate the effect of fingolimod loaded niosomes on the cognitive impairment induced by sevoflurane. Span 40 and cholesterol were used in reverse phase evaporation techniques for the preparation of fingolimod -loaded niosomes. The positively charged niosomes were obtained by using chloride salts of 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP). The Fingolimod loaded niosomes has average particle size of 223.5 nm and the surface charge measured as + 8.7 ± 1.2 mV in presence of DOTAP. The Fingolimod loaded niosomes formulation shows higher entrapment efficiency. Fingolimod loaded positively charged niosomes were efficiently retained drug and increase the sustain release property. Fingolimod niosomes increases the spontaneous alternation in Y maze and reduces the escape latency in the Morris water maze test, which leads to significant (p < 0.01) improvement in spatial short-term and long-term memory. The neuronal death in the hippocampus due to the sevoflurane exposure was attenuated by fingolimod loaded niosomes, which was proved by histopathological study. It could be defined that fingolimod loaded niosomes attenuates the sevoflurane induced cognitive impairment.

Efficacy and safety of ultrasound-guided quadratus lumborum block in patients receiving percutaneous nephrolithotomy under general anaesthesia.

PURPOSE: The aim of this study was to explore the overall efficacy and safety of ultrasound-guided quadratus lumborum block combined with general anaesthesia in patients undergoing percutaneous nephrolithotomy (PCNL). METHODS: The study included 76 patients who underwent PCNL at our hospital between October 2018 and October 2019. The patients were randomly divided into the study group (ultrasound-guided quadratus lumborum block combined with general anaesthesia, 38 cases) and the control group (general anaesthesia, 38 cases). The intra-operative estimated blood loss, operative time and intra-operative anaesthetic usage were recorded. Moreover, the effective pressing times of the posterior cerebral artery (PCA) and the dosage of sufentanil in patient-controlled intravenous analgesia (PCIA) were observed within 48 hours after operation. RESULTS: The dosage of propofol and remifentanil, the time of intestinal exhaust recovery time and the hospital study in the study group were lower than those in the control group. The HR and MAP of the two groups, with a trend towards gradual decrease at T0 and T1, were lower than those at T0. At 2, 6, 8 and 24 hours after operation, the visual analogue scale/score (VAS) of the study group was lower than that of the control group. The analgesic rescue rate, the dosage of sufentanil and the effective PCA compression times in the study group were lower than those in the control group. The total incidence of adverse reactions in postanaesthesia care unit in the study group was significantly lower than that in the control group (8/38 vs 18/38). CONCLUSION: The combination of ultrasound-guided quadratus lumborum block and general anaesthesia effectively exerts beneficial outcomes in terms of validly reducing the dose of tranquilisers and anaesthetic analgesics during PCNL, which is able to treat patients with anaesthetic mode of low opioids.

C-UNet: Complement UNet for Remote Sensing Road Extraction.

Roads are important mode of transportation, which are very convenient for people's daily work and life. However, it is challenging to accuratly extract road information from a high-resolution remote sensing image. This paper presents a road extraction method for remote sensing images with a complement UNet (C-UNet). C-UNet contains four modules. Firstly, the standard UNet is used to roughly extract road information from remote sensing images, getting the first segmentation result; secondly, a fixed threshold is utilized to erase partial extracted information; thirdly, a multi-scale dense dilated convolution UNet (MD-UNet) is introduced to discover the complement road areas in the erased masks, obtaining the second segmentation result; and, finally, we fuse the extraction results of the first and the third modules, getting the final segmentation results. Experimental results on the Massachusetts Road dataset indicate that our C-UNet gets the higher results than the state-of-the-art methods, demonstrating its effectiveness.

Iterative Min Cut Clustering Based on Graph Cuts.

Clustering nonlinearly separable datasets is always an important problem in unsupervised machine learning. Graph cut models provide good clustering results for nonlinearly separable datasets, but solving graph cut models is an NP hard problem. A novel graph-based clustering algorithm is proposed for nonlinearly separable datasets. The proposed method solves the min cut model by iteratively computing only one simple formula. Experimental results on synthetic and benchmark datasets indicate the potential of the proposed method, which is able to cluster nonlinearly separable datasets with less running time.

Kernel Probabilistic K-Means Clustering.

Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian optimization. To solve this problem, an equivalent model, called kernel probabilistic k-means (KPKM), is proposed here. The novel model relates KFCM to kernel k-means (KKM) in a unified mathematic framework. Moreover, the proposed KPKM can be addressed by the active gradient projection (AGP) method, which is a nonlinear programming technique with constraints of linear equalities and linear inequalities. To accelerate the AGP method, a fast AGP (FAGP) algorithm was designed. The proposed FAGP uses a maximum-step strategy to estimate the step length, and uses an iterative method to update the projection matrix. Experiments demonstrated the effectiveness of the proposed method through a performance comparison of KPKM with KFCM, KKM, FCM and k-means. Experiments showed that the proposed KPKM is able to find nonlinearly separable structures in synthetic datasets. Ten real UCI datasets were used in this study, and KPKM had better clustering performance on at least six datsets. The proposed fast AGP requires less running time than the original AGP, and it reduced running time by 76-95% on real datasets.