Prenatal diagnosis and genetic analysis of small supernumerary marker chromosomes in the eastern chinese han population: A retrospective study of 36 cases.

BACKGROUND: Small supernumerary marker chromosomes (sSMCs) are additional chromosomes with unclear structures and origins, and their correlations with clinical fetal phenotypes remain incompletely understood, which reduces the accuracy of genetic counseling. METHODS: We conducted a retrospective analysis of a cohort of 36 cases of sSMCs diagnosed in our center. We performed G-banding and chromosomal microarray analysis (CMA). The resulting karyotypes were compared with case reports in the literature and various databases including OMIM, DECIPHER, ClinVar, ClinGen, ISCA, DGV, and PubMed. RESULTS: Karyotype analysis data revealed that 19 out of 36 fetuses were mosaic. Copy number variants (CNVs) analysis results showed that 27 out of 36 fetuses harbored pathogenic/likely pathogenic variants. Among these 27 cases, 11 fetuses carried sex chromosome-related CNVs, including 4 female cases exhibiting Turner syndrome phenotypes and 7 cases showing Y chromosome deletions. In the remaining 16 fetuses with autosomal CNVs, 9 fetuses carried variants associated with Cat eye syndrome, Emanuel syndrome, Tetrasomy 18p, and 15q11-q13 duplication syndrome. Among these, 22 fetuses were terminated, and the remaining 5 fetuses were delivered and developed normally. Additionally, we identified a few variants with unclear pathogenicity. CONCLUSION: Cytogenetic analysis is essential for identifying the pathogenicity of sSMCs and increasing the accuracy of genetic counseling.

Whole genome sequencing and analysis of Armillaria gallica Jzi34 symbiotic with Gastrodia elata.

BACKGROUND: Armillaria species are plant pathogens, but a few Armillaria species can establish a symbiotic relationship with Gastrodia elata, a rootless and leafless orchid, that is used as a Chinese herbal medicine. Armillaria is a nutrient source for the growth of G. elata. However, there are few reports on the molecular mechanism of symbiosis between Armillaria species and G. elata. The genome sequencing and analysis of Armillaria symbiotic with G. elata would provide genomic information for further studying the molecular mechanism of symbiosis. RESULTS: The de novo genome assembly was performed with the PacBio Sequel platform and Illumina NovaSeq PE150 for the A. gallica Jzi34 strain, which was symbiotic with G. elata. Its genome assembly contained ~ 79.9 Mbp and consisted of 60 contigs with an N50 of 2,535,910 bp. There were only 4.1% repetitive sequences in the genome assembly. Functional annotation analysis revealed a total of 16,280 protein coding genes. Compared with the other five genomes of Armillaria, the carbohydrate enzyme gene family of the genome was significantly contracted, while it had the largest set of glycosyl transferase (GT) genes. It also had an expansion of auxiliary activity enzymes AA3-2 gene subfamily and cytochrome P450 genes. The synteny analysis result of P450 genes reveals that the evolutionary relationship of P450 proteins between A. gallica Jzi34 and other four Armillaria was complex. CONCLUSIONS: These characteristics may be beneficial for establishing a symbiotic relationship with G. elata. These results explore the characteristics of A. gallica Jzi34 from a genomic perspective and provide an important genomic resource for further detailed study of Armillaria. This will help to further study the symbiotic mechanism between A. gallica and G. elata.

Deglycosylation Inactivation Initiated by a Novel Periplasmic Dehydrogenase Complex Provides a Novel Strategy for Eliminating the Recalcitrant Antibiotic Kanamycin.

Biodegradation using enzyme-based systems is a promising approach to minimize antibiotic loads in the environment. Aminoglycosides are refractory antibiotics that are generally considered non-biodegradable. Here, we provide evidence that kanamycin, a common aminoglycoside antibiotic, can be degraded by an environmental bacterium through deglycosylation of its 4'-amino sugar. The unprecedented deglycosylation inactivation of kanamycin is initiated by a novel periplasmic dehydrogenase complex, which we designated AquKGD, composed of a flavin adenine dinucleotide-dependent dehydrogenase (AquKGDα) and a small subunit (AquKGDγ) containing a twin-arginine signal sequence. We demonstrate that the formation of the AquKGDα-AquKGDγ complex is required for both the degradation activity of AquKGD and its translocation into the periplasm. Native AquKGD was successfully expressed in the periplasmic space of Escherichia coli, and physicochemical analysis indicated that AquKGD is a stable enzyme. AquKGD showed excellent degradation performance, and complete elimination of kanamycin from actual kanamycin manufacturing waste was achieved with immobilized AquKGD. Ecotoxicity and cytotoxicity tests suggest that AquKGD-mediated degradation produces less harmful degradation products. Thus, we propose a novel enzymatic antibiotic inactivation strategy for effective and safe treatment of recalcitrant kanamycin residues.

Extraction and identification of steroidal saponins from Polygonatum cyrtonema Hua using natural deep eutectic solvent-synergistic quartz sand-assisted extraction method.

In this study, quartz sand with particularly sharp nanoscale edges acted like a nanoscale knife physically cut cells of Polygonatum cyrtonema Hua into nanosized particles and was synergized with natural deep eutectic solvent to extract steroidal saponins of Polygonatum cyrtonema Hua. The natural deep eutectic solvent (choline chloride-lactic acid)-synergistic quartz sand-assisted extraction was optimized using response surface methodology. The steroidal saponins purified with AB-8 macroporous resin were identified using ultra-high-performance liquid chromatography-triple time of flight mass spectrometry. The results showed that the experimental total saponins content value (36.97 ± 0.12 mg dioscin equivalent/g dry weight) at optimal extraction conditions with a temperature of 68°C, a rotational speed of 20 400 rpm, shear time of 4.3 min, the liquid-solid ratio of 38 ml/g, was close to the maximum possible theoretical value (36.64 mg dioscin equivalent/g dry weight). A total of 20 steroidal saponins were identified, among which the content of (25R)-Kingianoside E was the highest (102.66 ± 3.47 mg/g). Furthermore, a new steroid saponin (3ß,25S)-26-(ß-D-glucopyranosyloxy)-22-hydroxyfurost-5-en-3-yl 4-O-ß-D-glucopyranosyl-ß-D-galactopyranoside+Glc was found for the first time. These results revealed that natural deep eutectic solvent-synergistic quartz sand-assisted extraction was an efficient and green method to extract a variety of steroidal saponins.

A semi-continuous efficient strategy for removing phosphorus and nitrogen from eel aquaculture wastewater using the self-flocculating microalga Desmodesmus sp. PW1.

The phosphorus content in eel aquaculture wastewater exceeds the discharge standard, and the amount of wastewater discharged is substantial. Therefore, there is an urgent need to explore an economical and efficient method of treating aquaculture wastewater. This study explored the use of Desmodesmus sp. PW1, a type of microalgae, to treat eel aquaculture wastewater. By optimizing the conditions, Desmodesmus sp. PW1 achieved a total phosphorus (TP) removal efficiency of 92.3%, as well as total nitrogen (TN) and ammonia nitrogen (NH4+-N) removal efficiency of 99%, using a photoperiod of 24:0, a temperature of 25 °C, and an inoculation amount of 15%. Furthermore, Desmodesmus sp. PW1 demonstrated a high self-flocculating efficiency (>90%) within 100 min of settling, which facilitated biomass recovery. Subsequently, a semi-continuous treatment process mode was established with a sewage renewal rate of 90%. The results showed that after four rounds of sewage renewal operations, the microalgae biomass in the sewage treatment system could be maintained between 160.0 and 220.0 mg/L, and the average removal rate of TP was 0.13 mg/(L * h). The lipid content of algae cells collected in the semi-continuous treatment system for eel aquaculture wastewater was as high as 36.5%, and the biodiesel properties met the biodiesel standards authorized by Europe and the United States. Overall, this study provides an economical and effective strategy for converting wastewater into high-value microalgae products.

A newly isolated microalga Chlamydomonas sp. YC to efficiently remove ammonium nitrogen of rare earth elements wastewater.

The aim of this study was to establish a practical approach to remove ammonium nitrogen of rare earth elements (REEs) wastewater by an indigenous photoautotrophic microalga. Firstly, a new microalgal strain was successfully isolated from REEs wastewater and identified as Chlamydomonas sp. (named Chlamydomonas sp. YC). The obtained results showed that microalga could completely remove the NH4+-N of 10% REEs wastewater after 10 days of cultivation; however, the highest NH4+-N removal rate was attained by microalga to treat undiluted REEs wastewater. Then, three cultivation modes including batch, semi-continuous and continuous cultivation methods were developed to evaluate the ability of NH4+-N removal rate by this microalga to treat diluted (10%) and undiluted REEs wastewater. It was found that, Chlamydomonas sp. YC exhibited superior performance towards NH4+-N removal rates (32.75-61.05 mg/(L·d)) by semi-continuous and continuous processes for the treatments of 10% and undiluted REEs wastewater in comparison to the results (19.50-30.38 mg/(L·d) by batch process. Interestingly, under the same treatment conditions, among the three cultivation modes, microalga exhibited the highest removal rates of NH4+-N in undiluted REEs wastewater by semi-continuous (61.05 mg/(L·d)) and continuous (57.10 mg/(L·d) processes. In term of the biochemical analysis, microalgal biomass obtained from the wastewater treatment had 35.40-44.40% carbohydrate and 4.97-6.03% lipid, which could be potential ingredients for sustainable biofuels production. And the highest carbohydrate and lipid productivities attained by Chlamydomonas sp. YC in the continuous mode were 226.36 mg/(L·d) and 32.98 mg/(L·d), respectively. Taken together, the established processes mediated with Chlamydomonas sp. YC via continuous cultivation was the great promising approaches to efficiently remove NH4+-N of REEs wastewater and produce valuable biomass for sustainable and renewable biofuels in a simultaneous manner.

Development of the Volatile Fingerprint of Qu Aurantii Fructus by HS-GC-IMS.

Volatile components are important active ingredients of Rutaceae. In this study, HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) was used to study the volatile compounds of Qu Aurantii Fructus, and a total of 174 peaks were detected, 102 volatile organic compounds (131 peaks) were identified. To compare the volatile compounds of Qu Aurantii Fructus with its similar medical herb, Aurantii Fructus, and their common adulterants, principal component analysis (PCA) and cluster analysis (CA) were performed based on the signal intensity of all the detected peaks. The results showed that Qu Aurantii Fructus and Aurantii Fructus (Citrus aurantium L.) were clustered into one group, while their common adulterants could be well distinguished in a relatively independent space. In order to distinguish Qu Aurantii Fructus from Aurantii Fructus, the peaks other than the average intensity ±2 standard deviation (95% confidence interval) were taken as the characteristic components by using the Gallery Plot plug-in software. Additionally, the fingerprint method was established based on the characteristic compounds, which can be used to distinguish among Qu Aurantii Fructus, Aurantii Fructus and their common adulterants quickly and effectively. We found that the characteristic components with higher content of Qu Aurantii Fructus were nerol, decanal, coumarin and linalool. This study provides a novel method for rapid and effective identification of Qu Aurantii Fructus and a new dimension to recognize the relationship between Qu Aurantii Fructus and Aurantii Fructus.

Anticonvulsant Activity of Bombyx batryticatus and Analysis of Bioactive Extracts Based on UHPLC-Q-TOF MS/MS and Molecular Networking.

Bombyx batryticatus (BB) is an anticonvulsant animal medicine in traditional Chinese medicine (TCM) and acts on the central nervous system. This research aimed to study the anticonvulsant effects of different polarity fractions of extracts from BB and to explore the components conferring anticonvulsant activity. Materials and methods: Crude extracts of BB at 20 g/kg were divided into different polarity fractions (petroleum ether, chloroform, ethyl acetate, water) and were administered to groups of mice before injecting pentylenetetrazol (PTZ) to induce convulsions. The animals were placed in chambers, and their behaviors were recorded for 30 min following the injection. Latency time, percent of protection, convulsion, convulsion rate, and convulsion score were determined for these mice. The compounds present in the different fractions were analyzed, and those from the fraction that conferred anticonvulsant activity were identified by high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF MS) and molecular networking (MN). The chloroform extract fractions (B-C) clearly increased the seizure latency time and protection percentage and decreased the convulsion percentage compared to the control group. The anticonvulsant effect of other extract fractions was not significant. Our study shows that the chloroform extract fractions (B-C) of BB have a significant anticonvulsant effect. We also identified 17 compounds including lumichrome, pheophorbide A, and episyringaresinol 4'-O-beta-d-glucopyranose that were found for the first time. The results of this study may lay the groundwork for studying compounds derived from Bombyx batryticatus and their anticonvulsant effect.

Innovative health risk assessment of heavy metals in Chinese herbal medicines based on extensive data.

In the present study, the concentrations of lead (Pb), cadmium (Cd), arsenic (As), mercury (Hg), and copper (Cu) in 2245 batches of Chinese herbal medicines (CHMs) were measured using inductively coupled plasma-mass spectroscopy (ICP-MS). We developed a risk assessment strategy that assessed the heavy metal-associated health risk of CHMs based on our large dataset. Using a combination of the mean and 95th percentile (P95) values of the chronic daily intake (CDI), hazard quotient (HQ), hazard index (HI), and lifetime cancer risk (CR), the health risks of the average exposure population and the high exposure population were estimated, respectively. To obtain a precise and realistic risk assessment, the exposure frequency and exposure duration were determined using questionnaire data from 20,917 randomly selected volunteers. Additionally, given the specific ingestion characteristics of CHMs, the safety factor and the transfer rates of heavy metals were highlighted as well. The concentrations of Pb, Cd, As, Hg, and Cu in 2245 batches of CHMs were 1.566, 0.299, 0.391, 0.074, and 8.386 mg/kg, respectively. The mean HI values indicated that consumption of most CHMs would not pose an unacceptable health risk to the average exposure population, except for argy wormwood leaf (1.326), morinda root (2.095), plantain herb (1.540), chrysanthemum flower (1.146), and Indian madder root (2.826). In addition, CR assessment for Pb and As revealed that, for the average exposure population, the risk of developing cancers was lower than the acceptable levels (1 × 10-4) in the clinic. However, the P95 of the HI and CR values indicated that more attention should be paid to the systemic effects of CHMs in terms of both non-carcinogenic and carcinogenic health risks for the high exposure population. Furthermore, in order to serve population health better, national and international guidelines have now been established. The risk assessment strategy developed in this study is the first of its kind, and contributed to the risk assessment, guidelines, and safety standards for heavy metals in CHMs.

microRNA-605 rs2043556 polymorphisms affect clopidogrel therapy through modulation of CYP2B6 and P2RY12 in acute coronary syndrome patients.

Clopidogrel therapy reduces the occurrence of major vascular events in acute coronary syndrome (ACS) patients, but treatment efficacy is variable. The present study aims to determine the mechanisms that underlie associations between certain miRNA polymorphisms and clinical outcomes of clopidogrel therapy. Our study focused on 9 miRNA single nucleotide polymorphisms in addition to CYP2C19*2 and CYP2C19*3. We found that the miR-605 rs2043556 AG genotype significantly decreased the risk of acute myocardial infarction (odds ratio, OR = 0.13, 95%CI 0.02-0.96, P = .045) and that the rs2043556 GG genotype significantly decreased the risk of unstable angina (OR = 0.19, 95%CI 0.05-0.65, P = .008) in ACS patients receiving clopidogrel therapy for more than one year. Dual-luciferase analysis indicated that miR-605 significantly decreased the mRNA expression of CYP2B6 and P2RY12 (P < .01). In cells treated with miR-605-A, the protein and mRNA expression of CYP2B6 and P2RY12 were significantly lower than that of cells treated with miR-605-G (P < .05). The results demonstrate that miR-605 targets the mRNA of the CYP2B6 and P2RY12 genes, and that rs2043556 A/G polymorphisms in miR-605 modulate the mRNA and protein expression of CYP2B6 and P2RY12 differently, which may impact the effect of clopidogrel in ACS patients.

A Rapid Method with UPLC for the Determination of Fusaric Acid in Fusarium Strains and Commercial Food and Feed Products.

A rapid, sensitive and validated method for the determination of fusaric acid (FA) in several Fusarium strains and different commercial food and feed products is reported based on ultra-performance liquid chromatography. This method requires only crude sample by a simple extraction with methanol, and requires a very short time of 8 min for completion. Separation of FA was performed at injection volume of 1 µl with a 20:80 (v/v) water/acetonitrile mobile phase containing 0.1 % formic acid at a flow rate of 0.05 ml/min and detected with UV at 220 nm. Nice linearity and good correlation coefficient (R2 > 0.99) were obtained in the concentration range of 1-200 µg/ml. Validation was demonstrated using blank samples spiked at three different concentrations with standard solution, and the method yielded more than 98.2 % recovery efficiencies and below 2.56 % R.S.D. when applied in the analysis of FA produced by Fusarium verticillioides and a set of transgenic strains of this fungus. Satisfactory recoveries in the range of 79.1-105.8 % and R.S.D lower than 10 % were also obtained for the tested commercial food and feed products. The concentration FA detection in the transgenic strains ranged from 9.65 to 135 µg/kg (0.29-4.05 µg per gram of biomass). However, FA was not detected in most of the commercial products with the exception of niblet, oatmeal, red kidney bean and soybean, for which the concentrations of FA ranged from 2.5 to 18 µg/kg (below the permitted maximum). These results show that the proposed method has a great potential application to analyze FA from different sources rapidly.

[A case of arrhythmias syncope diagnosed by implantable loop recorder].

Syncope is a clinical symptom for many kinds of diseases. The reasons for some syncope are still not clear even after a comprehensive and systematic examination, known as unexplained syncope. The clinical data of one patient with recurrent syncope, who had received the implanted loop recorder (ILR) in Xiangya Hospital, Central South University, were retrospectively analyzed. The instrument recorded the first syncope at a time of recurrence for the sustained ventricular tachycardia in 704 days after ILR. The patient was thus diagnosed as arrhythmic syncope and received an operation with implantable cardioverter defibrillator. The ILR is a new type of examination device for patients suffering from syncope with suspected cardiac rhythm due to its long monitoring time, low infection rate and high safety. It possesses high clinical value in the diagnosis of patients with arrhythmic syncope.

Effective methods for extracting extracellular polymeric substances from Shewanella oneidensis MR-1.

Extracellular polymeric substances (EPS) play crucial roles in bio-aggregate formation and survival of bacterial cells. To develop an effective but harmless method for EPS extraction from Shewanella oneidensis MR-1, five extraction methods, i.e. centrifugation (control), heating (40, 45, 50, and 60 °C), and treatments with H2SO4, ethylenediaminetetraacetic acid (EDTA) and NaOH, were examined, respectively. Results from scanning electron microscope and flow cytometric analyses indicate that MR-1 cells were severely broken by H2SO4, NaOH and heating temperature ≥45 °C. Proteins and polysaccharides in EPS extracted by heating at 40 °C were 7.12 and 1.60 mg g-1 dry cell, respectively. Although EDTA treatment had a relatively lower yield of EPS (proteins and polysaccharides yields of 5.15 and 1.30 mg g-1 dry cell, respectively), cell lysis was barely found after EPS extraction. Three peaks were identified from the three-dimensional excitation-emission matrix spectrum of each EPS sample, suggesting the presence of protein-like substances. Furthermore, the peak intensity was in good accordance with protein concentration measured by the chemical analysis. In short, heating (40 °C) and EDTA treatments were found the most suitable methods for EPS extraction considering the cell lysis and EPS content, composition and functional groups together.

Non-antiplatelet effect of clopidogrel: improving endothelial function in Chinese healthy subjects with different CYP2C19 genotype.

Clopidogrel has been shown to improve endothelial function in vitro and in patients with coronary artery disease. However, it remains unclear whether such an effect of clopidogrel is associated with CYP2C19 polymorphisms that determine the antiplatelet effect of clopidogrel. After genotyping, 12 healthy participants were enrolled in the study. Among them, six participants were CYP2C19*1/*1 (extensive metabolizers; EM) and the other six participants were CYP2C19*2/*2 or *3 (poor metabolizers; PM). All participants received 300 mg clopidogel orally. Endothelial function was assessed by measurement of flow-mediated dilation of the brachial artery, and adenosine diphosphate-induced platelet aggregation was determined by using optical aggregometry at 0, 4 and 24 h after administration of 300 mg clopidogrel. Flow-mediated dilation was significantly higher at 4 and 24 h after a loading-dose administration of clopidogrel in both the CYP2C19 EM and PM groups, but showed no significant difference between the two groups. Adenosine diphosphate-induced platelet aggregation was significantly inhibited at 4 and 24 h after administration of clopidogrel in the CYP2C19 EM group. However, there was no statistical correlation between the change in flow-mediated dilation and adenosine diphosphate-induced platelet aggregation in the two CYP2C19 groups. This is the first study to report that clopidogrel improves endothelial function in healthy Chinese subjects, which is unrelated with the CYP2C19 genotype and independent of antiplatelet action.

Dual-learning Multi-hop Nonnegative Matrix Factorization for community detection.

As an important branch of network science, community detection has garnered significant attention. Among various community detection methods, nonnegative matrix factorization (NMF)-based community detection approaches have become a popular research topic. However, most NMF-based methods overlook the network's multi-hop information, let alone the community detection results specific to each hop of the network. In this paper, we propose Dual-learning Multi-hop NMF (DL-MHNMF), a method that considers not only the multi-hop connectivity between two nodes but also factors in the shared results across multiple hops and the impact of differences in the specific results at each hop on the shared outcomes. An efficient iterative optimization algorithm with guaranteed theoretical convergence is proposed for solving DL-MHNMF. Methodologically, by iteratively removing the specific results during the optimization process of DL-MHNMF, we achieve enhanced detection accuracy, which is also verified by subsequent experiments. Specifically, we compare fourteen algorithms on eleven publicly available datasets, and experimental results show that our algorithm outperforms most state-of-the-art methods. The source code is availiable at https://github.com/bx20000827/DL-MHNMF.git.

Plasma Ionomic Profile and Interaction Patterns in Coronary Artery Disease Patients.

Humans are exposed to various chemical elements that have been associated with the development and progression of diseases such as coronary artery disease (CAD). Unlike previous research, we employed a multi-element approach to investigate CAD patients and those with comorbid conditions such as diabetes (CAD-DM2), high blood pressure (CAD-HBP), or high blood lipids (CAD-HBL). Plasma concentrations of 21 elements, including lithium (Li), boron (B), aluminum (Al), calcium (Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), strontium (Sr), cadmium (Cd), tin (Sn), stibium (Sb), barium (Ba), and lead (Pb), were measured in CAD patients (n = 201) and healthy subjects (n = 110) using inductively coupled plasma-mass spectrometry (ICP-MS). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were utilized to analyze the ionomic profiles. Spearman correlation analysis was employed to identify the interaction patterns among individual elements. We found that levels of Ba, Li, Ni, Zn and Pb were elevated in the CAD group compared to the healthy group, while Sb, Ca, Cu, Ti, Fe, and Se were lower. Furthermore, the CAD-DM2 group exhibited higher levels of Ni and Cd, while the CAD-HBP group showed lower levels of Co and Mn. In the CAD-HBL group, Ti was increased, whereas Ba, Cr, Cu, Co, Mn, and Ni were reduced. In conclusion, ionomic profiles can be utilized to differentiate CAD patients from healthy individuals, potentially providing insights for future treatment or dietary interventions.

[Fingerprint analysis of Fritillaria thunbergii using rapid resolution liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry].

A fingerprint method for quality assessment of Fritillaria thunbergii was developed by rapid resolution liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (RRLC-Q-TOF-MS). The separation was performed using Agilent Eclipse Plus C18 column (2.1 mm x 100 mm, 1.8 microm) by gradient elution with acetonitrile and 0.1% formic acid aqueous solution (containing 10 mmol x L(-1) ammonium formate) as the mobile phase. Q-TOF-MS was used to obtain the accurate mass for precursor and product ions. Under this chromatographic and MS condition, 12 batches of F. thunbergii and its adulterants (F. hupehensis and F. pallidiflora) were analyzed by RRLC-Q-TOF-MS. Fifteen steroidal alkaloids were identified from F. thunbergii, F. hupehensis and F. pallidiflora and nine were assigned as the common characteristic peaks for F. thunbergii. The RRLC-Q-TOF-MS fingerprint of F. thunbergii was different significantly with those of F. hupehensis and F. pallidiflora. The quality of 12 batches of F. thunbergii samples were finally evaluated by hierarchical clustering analysis (HCA) and principle component analysis (PCA). This convenient and high specific method could be used to identify and evaluate the quality of the F. thunbergii.

Community Detection via Multihop Nonnegative Matrix Factorization.

Community detection aims at finding all densely connected communities in a network, which serves as a fundamental graph tool for many applications, such as identification of protein functional modules, image segmentation, social circle discovery, to name a few. Recently, nonnegative matrix factorization (NMF)-based community detection methods have attracted significant attention. However, most existing methods neglect the multihop connectivity patterns in a network, which turn out to be practically useful for community detection. In this article, we first propose a novel community detection method, namely multihop NMF (MHNMF for brevity), which takes into account the multihop connectivity patterns in a network. Subsequently, we derive an efficient algorithm to optimize MHNMF and theoretically analyze its computational complexity and convergence. Experimental results on 12 real-world benchmark networks demonstrate that MHNMF outperforms 12 state-of-the-art community detection methods.

Unsupervised Feature Selection via Graph Regularized Nonnegative CP Decomposition.

Unsupervised feature selection has attracted remarkable attention recently. With the development of data acquisition technology, multi-dimensional tensor data has been appeared in enormous real-world applications. However, most existing unsupervised feature selection methods are non-tensor-based which results the vectorization of tensor data as a preprocessing step. This seemingly ordinary operation has led to an unnecessary loss of the multi-dimensional structural information and eventually restricted the quality of the selected features. To overcome the limitation, in this paper, we propose a novel unsupervised feature selection model: Nonnegative tensor CP (CANDECOMP/PARAFAC) decomposition based unsupervised feature selection, CPUFS for short. In specific, we devise new tensor-oriented linear classifier and feature selection matrix for CPUFS. In addition, CPUFS simultaneously conducts graph regularized nonnegative CP decomposition and newly-designed tensor-oriented pseudo label regression and feature selection to fully preserve the multi-dimensional data structure. To solve the CPUFS model, we propose an efficient iterative optimization algorithm with theoretically guaranteed convergence, whose computational complexity scales linearly in the number of features. A variation of the CPUFS model by incorporating nonnegativity into the linear classifier, namely CPUFSnn, is also proposed and studied. Experimental results on ten real-world benchmark datasets demonstrate the effectiveness of both CPUFS and CPUFSnn over the state-of-the-arts.