Selectivity Quantification with the Fluorescent Quantitative Model-Assisted Semi-Selective Probe (Carbon Dots): Accurate Determination of Chlortetracycline in Aqueous Environments with Interference.

Probes such as carbon dots (C-dots) have extensive and important applications in the quantitative analysis of complex biological and environmental systems. However, the development of probes is often hindered by incomplete selectivity, i.e., a probe that responds to one substance is also prone to respond to coexisting structurally similar substances. Therefore, the above dilemma often leads to be developed as semi-selective probes, so that the development of probes is abandoned halfway. This work shows how a semi-selective probe can enhance selectivity by combining a proper multivariate calibration model. Primarily, we developed a semi-selective fluorescent probe that responded to tetracyclines (TCs) with discarded tobacco leaves. Then, we introduced the multivariate quantitative fluorescence model (QFM) to enhance its selectivity and solve the problem of fluorescence spectral shift. For the determination of chlortetracycline (CTC) with this semi-selective C-dots probe in mineral and lake water samples and compared to the traditional quantitative model, the introduced QFM resulted in an average relative predictive error (ARPE) in mineral water spiked samples decreased from 57.1 to 5.6%, which reduced the ARPE in the lake water spiked samples from 18.1 to 4.7%. The above results show that the QFM-assisted semi-selective probe C-dots strategy (QFMC-dots) can enhance selectivity, and QFMC-dots achieved high-selective and accurate determination of CTC in interfering mineral and lake water samples, with the limit of detection and limit of quantitation of 0.55 and 1.66 µM, respectively. The proposed strategy of enhancing selectivity by introducing a proper multivariate calibration model can reduce the difficulty and increase success rate of developing probes, which can be expected to provide an interesting alternative for the development of probes, especially when encountering semi-selective problems.

Rab11a Is Essential for the Development and Integrity of the Stereocilia and Kinocilia in the Mammalian Organ of Corti.

The cochlea hair cells transform mechanic sounds to neural signals with a remarkable sensitivity and resolution. This is achieved via the precisely sculpted mechanotransduction apparatus of the hair cells and the supporting structure of the cochlea. The shaping of the mechanotransduction apparatus, the staircased stereocilia bundles on the apical surface of the hair cells, requires an intricate regulatory network including planar cell polarity (PCP) and primary cilia genes in orienting stereocilia bundles and building molecular machinery of the apical protrusions. The mechanism linking these regulatory components is unknown. Here, we show that a small GTPase known for its role in protein trafficking, Rab11a, is required for ciliogenesis in hair cells during development in mice. In addition, in the absence of Rab11a, stereocilia bundles lost their cohesion and integrity, and mice are deaf. These data indicate an essential role of protein trafficking in the formation of hair cell mechanotransduction apparatus, implicating a role of Rab11a or protein trafficking in linking the cilia and polarity regulatory components with the molecular machinery in building the cohesive and precisely shaped stereocilia bundles.

The correlation between the body shape and otolithic function in patients with obstructive sleep apnea.

OBJECTIVE: To identify the typical pattern of changes of vestibular-evoked myogenic potentials (VEMPs) and explore the relationship between VEMPs and the anthropometry factors in patients with obstructive sleep apnea (OSA). METHODS: Patients diagnosed as OSA after overnight polysomnography (PSG) tests were enrolled as the study group. Healthy volunteers were recruited as the control group. Anthropometry data of the body shape and VEMPs results were collected completely. The correlation analysis was conducted among those parameters. RESULTS: Forty-nine patients with OSA who were diagnosed in the Therapy Center of Sleep-disordered Breathing in our hospital and sex- and age-matched healthy controls as well. Significant changes in ocular and cervical VEMPs (oVEMP and cVEMP) in the study group were observed, which were reduced response rates, elevated thresholds, decreased amplitudes, and prolonged first wave latencies. In oVEMP, the first wave (n1) latency was significantly correlated with weight, body mass index (BMI), neck circumference, waist circumference, hip circumference, and apnea hypopnea index (AHI). In a tentative application, combined use of BMI and oVEMP n1 latency increased the detection rate during OSA screening prior to PSG. CONCLUSION: OSA can negatively affect function of otolithic organs and their pathways. The first wave latency of the VEMPs waveform may be another important parameter to define peripheral nervous system lesions caused by systemic diseases as OSA.

Uneven Effects of Sleep Apnea on Semicircular Canals and Otolithic Organs.

OBJECTIVE: This study aimed to explore how obstructive sleep apnea (OSA) affects the function of each vestibular organ and to identify the correlations among them. METHODS: A prospective study was conducted involving 32 healthy controls and 64 patients with OSA. The objective detection methods of the utricle and saccule are vestibular-evoked myogenic potentials (VEMPs). A combination of the caloric test and video head impulse test (vHIT) was used to comprehensively evaluate the objective function of semicircular canals. RESULTS: Elevated thresholds (p < 0.001), decreased waveform amplitudes (p < 0.001), prolonged first wave latencies (p < 0.001), and shortened first interpeak latencies (p < 0.001) were observed in both ocular VEMP (oVEMP) and cervical VEMP (cVEMP). A significant difference was found in the caloric test comparison (χ2 = 4.030, p = 0.045) but not in the vHIT. The intergroup comparison of normal rates among the VEMPs, caloric test, and vHIT groups showed a significant difference (p < 0.001). CONCLUSION: The impairment of vestibular function in patients with OSA was uneven and biased. More attention should be given to vestibular dysfunction in the diagnosis and treatment of OSA.

Rab11a Regulates the Development of Cilia and Establishment of Planar Cell Polarity in Mammalian Vestibular Hair Cells.

Vestibular organs have unique planar cell polarity (Figure 1A), and their normal development and function are dependent on the regular polarity of cilia (Figure 1B) requires. Rab11a is a small G protein that participates in the transportation of intracellular and extracellular materials required for polarity formation; however, our understanding of the mechanisms of the actions of Rab11a in vestibular organs is limited. Here, we showed that the general shape of the utricle was abnormal in Rab11a CKO/CKO mice. These mice also showed abnormal morphology of the stereocilia bundles, which were reduced in both length and number, as well as disturbed tissue-level polarity. Rab11a affected the distribution of polarity proteins in the vestibular organs, indicating that the normal development of cilia requires Rab11a and intraflagellar transportation. Furthermore, small G protein migration works together with intraflagellar transportation in the normal development of cilia. FIGURE 1Morphological changes of stereocilia in the extrastriolar hair cells from Rab11a single or Rab11a/IFT88 double-mutant utricles. (A) Medial view of a mouse left inner ear with its five vestibular sensory organs (gray). Enlarged are the utricle showing their subdivisions, LPR (yellow line), and striola (blue). LES, lateral extrastriola; MES, medial extrastriola; LPR, line of polarity reversal. (B) Schematic view of vestibular hair cell. Kinocilium is marked with ace-tubulin. Basal body is marked with γ-tubulin. (C,C1,D,D1) Normal appearance of the stereocilia of extrastriolar hair cells of wild-type controls. (E,E1,F,F1) Altered morphology in Rab11a CKO/CKO animals. (G,G1,H,H1) The changes in the stereocilia morphology were more severe in Rab11a CKO/CKO /IFT 88 CKO/+ mice. (I-L) Higher magnification of confocal images of hair cells. (M-P) Scanning electron microscopy images of hair cells from wild-type controls and Rab11a mutants. (I,M) Morphology of normal. hair cells of wild-type controls. (J,N) The number of stereocilia on a single hair cell was deceased in the Rab11a mutant. (K,O) Stereocilia were shorter in mutants compared to the wild-type controls. (L,P) The staircase-like hair bundle architecture of hair cells was lost in Rab11a mutant mice. (Q) The percentage of hair cells with abnormal development of static cilia bundles in the extrastriola region was counted as a percentage of the total (n = 5). The percentage of abnormal hair cells was higher in Rab11a CKO/CKO , IFT88 CKO/+ mice compared to Rab11a CKO/CKO . The abnormal ratios of single and double knockout hair cells were 42.1 ± 5.7 and 71.5 ± 10.4, respectively. In (A-J), for all primary panels, hair cell stereociliary bundles were marked with phalloidin (green), the actin-rich cuticular plate of hair cells was labeled with ß-spectrin (red), while the basal body of the hair cell was labeled with γ-tubulin (blue). Scale bars: 10 µm (C-H1), 5 µm (J-N). *P < 0.05.

Discrimination of Fresh Tobacco Leaves with Different Maturity Levels by Near-Infrared (NIR) Spectroscopy and Deep Learning.

The maturity affects the yield, quality, and economic value of tobacco leaves. Leaf maturity level discrimination is an important step in manual harvesting. However, the maturity judgment of fresh tobacco leaves by grower visual evaluation is subjective, which may lead to quality loss and low prices. Therefore, an objective and reliable discriminant technique for tobacco leaf maturity level based on near-infrared (NIR) spectroscopy combined with a deep learning approach of convolutional neural networks (CNNs) is proposed in this study. To assess the performance of the proposed maturity discriminant model, four conventional multiclass classification approaches-K-nearest neighbor (KNN), backpropagation neural network (BPNN), support vector machine (SVM), and extreme learning machine (ELM)-were employed for a comparative analysis of three categories (upper, middle, and lower position) of tobacco leaves. Experimental results showed that the CNN discriminant models were able to precisely classify the maturity level of tobacco leaves for the above three data sets with accuracies of 96.18%, 95.2%, and 97.31%, respectively. Moreover, the CNN models with strong feature extraction and learning ability were superior to the KNN, BPNN, SVM, and ELM models. Thus, NIR spectroscopy combined with CNN is a promising alternative to overcome the limitations of sensory assessment for tobacco leaf maturity level recognition. The development of a maturity-distinguishing model can provide an accurate, reliable, and scientific auxiliary means for tobacco leaf harvesting.

The transcriptome characteristics of vestibular organs from delayed endolymphatic hydrops patients (Meniere's disease).

OBJECTIVES: To identify genes that are related to delayed endolymphatic hydrops (DEH) in patients by RNA-Seq analysis. DESIGN: Observational study. SETTING: Eye & ENT Hospital, Fudan University (Shanghai, China). PARTICIPANTS: We collected the entire vestibular system from four patients with DEH who underwent labyrinthectomy. Three control samples were collected from patients with acoustic neuroma or facial neuroma treated via the translabyrinthine approach. High-throughput RNA-Seq analysis was performed to investigate gene expression in the pathological vestibular system. MAIN OUTCOME MEASURES: Our bioinformatic analysis identified 17 genes that were upregulated and eight genes that were downregulated in patients with DEH compared with the controls. RESULTS: The altered gene expression profile suggested that DEH is closely related to neuropathy and autoimmune disease. In addition, many of the differentially regulated genes were involved in cell adhesion, suggesting a role of cell adhesion in DEH. Immunofluorescence analysis confirmed the expression of PMP2 and CLDN19 in the cytoplasm of hair cells and scattered expression of MPZ at cell junctions. The protein expression levels were higher in specimens from patients with Ménière's disease and DEH compared with controls. CONCLUSIONS: The protein expression profile of vestibular organs in patients with endolymphatic hydrops exhibited a degree of similarity to that of Ménière's disease. Endolymphatic hydrops is characterised by autoimmune abnormalities. DEH and Ménière's disease are likely to be different manifestations of the same disease, with disparate clinical symptoms. RNA-Seq is a useful analytical tool to characterise the vestibular pathology based on its transcriptome.

Planar cell polarity governs the alignment of the nasopharyngeal epithelium in mammals.

Planar cell polarity (PCP) signalling specifies the orientation of epithelial cells and regulates directional beating of motile cilia of multiciliated epithelial cells. Clinically, defects in cilia function are associated with nasopharyngeal symptoms. The polarity of the nasopharyngeal epithelium is poorly understood. Here, we demonstrated PCP in the nasopharyngeal epithelium. Multiciliated cells (MCCs) were uniformly aligned with their long axis parallel to the tissue axis of the nasopharynx (NP). In addition, PCP proteins exhibited an asymmetrical localisation between adjacent cells. Motile cilia were uniformly aligned in the same direction within both individual cells and neighbouring cells, which manifested as cilial polarity in MCCs. Mutation of Vangl2, a mammalian homologue of the Drosophila PCP gene, resulted in significant disruption of the orientation of epithelial cells. Finally, keratin-5-positive basal cells constantly replenished the luminal ciliated cells; the new dynamic ciliated cells were also oriented parallel to the tissue axis. These results indicate a role for the PCP pathway in the uniform orientation of dynamically replenished epithelial cells in the NP.

Enhancing the selectivity of liquid chromatography-mass spectrometry by using trilinear decomposition on LC-MS data: An application to three-way calibration of coeluting analytes in human plasma.

The high selectivities of liquid chromatography and mass spectrometry make liquid chromatography-mass spectrometry one of the most popular tools for quantitative analysis in complex chemical, biological, and environmental systems, while the potential mathematical selectivity of liquid chromatography-mass spectrometry is rarely investigated. This work discussed the mathematical selectivity of liquid chromatography-mass spectrometry by three-way calibration based on the trilinear model, with an application to quantitative analysis of coeluting aromatic amino acids in human plasma. By the trilinear decomposition of the constructed liquid chromatography-mass spectrometry-sample trilinear model and individual regression of the decomposed relative intensity versus concentration, the proposed three-way calibration method successfully achieved quantitative analysis of coeluting aromatic amino acids in human plasma, even in the presence of uncalibrated interferent(s) and a varying background. This analytical method can ease the requirements for sample preparation and complete chromatographic separation of components, reduce the use of organic solvents, decrease the time of chromatographic separation, and increase the peak capacity of liquid chromatography-mass spectrometry. As a "green analytical method", the liquid chromatography-mass spectrometry three-way calibration method can provide a promising tool for direct and fast quantitative analysis in complex systems containing uncalibrated spectral interferents, especially for the situation where the coelution problem is difficult to overcome.

Concurrent Occurrence of Congenital Ossicular Anomaly and Localized Cholesteatoma: Series of 10 Cases.

OBJECTIVE: The objective of this study is to describe the clinical features, managements and outcomes of a rare coexistence of congenital ossicular anomaly and localized cholesteatoma. A literature review on these cases and each congenital disorder is also presented. METHODS: A retrospective chart review was performed on patients diagnosed with congenital ossicular anomaly with concurrent localized cholesteatoma from 2008 to 2017. Clinical data of these patients were collected. RESULTS: A total of 10 patients were identified. All patients presented with unilateral hearing loss. Pure-tone audiometry showed conductive hearing loss in all affected ears with an average air conduction (AC) threshold of 59 dB. High-resolution computed tomography scans of the temporal bone diagnosed ossicular anomaly for 90% (9/10); however, only 50% (5/10) had a diagnosis of localized cholesteatoma. A transcanal exploratory tympanotomy under the microscope was performed to discover whether the localized tiny-sized cholesteatoma around the ossicular chain did not have direct contact with the ossicular chain, which could be diagnosed as congenital cholesteatoma. We removed the localized cholesteatoma and reconstructed the ossicular chain in each patient. All localized cholesteatomas were found in the posterior-superior quadrant of the middle ear. Ossicular chain anomalies were associated with the incus and/or the stapes in all cases. Hearing improvement was achieved in each of the 6 patients who were followed up postoperatively, with an average AC threshold of 35 dB. The clinical features of congenital ossicular anomaly with concurrent congenital cholesteatoma were compared with those of each congenital disorder. The pathogenesis of each condition was also discussed. CONCLUSIONS: Congenital ossicular anomaly with concurrent congenital cholesteatoma is rare. It shares similar clinical features with congenital ossicular anomaly occurring alone, therefore awareness should be raised for a possible concurrent congenital cholesteatoma which was easy to miss in the diagnosis (50%) by the radiologist. A patient's hearing level can be improved by removal of the cholesteatoma and reconstruction of the ossicular chain. Localized cholesteatoma does not usually show residuals or recurrence.

[Medication regularities of traditional Chinese medicine formulas for six kinds of pains by data-mining approach].

To study and compare the medication regularities of traditional Chinese medicine formulas(TCMFs) for the six kinds of pains,namely abdominal pain,headache,epigastric pain,hypochondriac pain,heartache and backache,using a data-mining approach,in order to provide reference for relevant studies for the compatibility mechanism and new compound development of related TCMFs. A total of 2 443 TCMFs for pains were collected from the Dictionary of Chinese Medicine Prescriptions,and analyzed using the Apriori algorithm based on three indicators,namely confidence,lift and support,so as to study pivotal traditional Chinese medicines(TCMs) for each pain and their compatibility regularities. The results showed that deficiency tonifying medicines(such as Glycyrrhizae Radix et Rhizoma and Angelicae Sinensis Radix),Qi-regulating medicines(like Aucklandiae Radix) and blood circulation promoting medicines(like Chuanxiong Rhizoma) were commonly used TCMs for pains. However,there were many differences between drugs for various kinds of pains. For example,Magnoliae Officinalis Cortex was used frequently for abdominal pain and epigastric pain,while Saposhnikoviae Radix was used frequently for headache. The latent association rules with significant lift included Carthami Flos → Angelicae Sinensis Radix for abdominal pain,Astragali Radix → Glycyrrhizae Radix et Rhizoma for headache,Hordei Fructus Germinatus → Citri Reticulatae Pericarpium for epigastric pain,Gentianae Radix et Rhizoma → Bupleuri Radix for hypochondriac pain,and Caryophylli Flos → Moschus for backache. This study showed that based on the TCMFs from the Dictionary of Chinese Medicine Prescriptions,the data-mining approach can reveal the differences and similarities in the use of TCMs for the six kinds of pains,and discover the latent composition regularities of relevant TCMs.

A hybrid variable selection strategy based on continuous shrinkage of variable space in multivariate calibration.

When analyzing high-dimensional near-infrared (NIR) spectral datasets, variable selection is critical to improving models' predictive abilities. However, some methods have many limitations, such as a high risk of overfitting, time-intensiveness, or large computation demands, when dealing with a high number of variables. In this study, we propose a hybrid variable selection strategy based on the continuous shrinkage of variable space which is the core idea of variable combination population analysis (VCPA). The VCPA-based hybrid strategy continuously shrinks the variable space from big to small and optimizes it based on modified VCPA in the first step. It then employs iteratively retaining informative variables (IRIV) and a genetic algorithm (GA) to carry out further optimization in the second step. It takes full advantage of VCPA, GA, and IRIV, and makes up for their drawbacks in the face of high numbers of variables. Three NIR datasets and three variable selection methods including two widely-used methods (competitive adaptive reweighted sampling, CARS and genetic algorithm-interval partial least squares, GA-iPLS) and one hybrid method (variable importance in projection coupled with genetic algorithm, VIP-GA) were used to investigate the improvement of VCPA-based hybrid strategy. The results show that VCPA-GA and VCPA-IRIV significantly improve model's prediction performance when compared with other methods, indicating that the modified VCPA step is a very efficient way to filter the uninformative variables and VCPA-based hybrid strategy is a good and promising strategy for variable selection in NIR. The MATLAB source codes of VCPA-GA and VCPA-IRIV can be freely downloaded in the website: https://cn.mathworks.com/matlabcentral/profile/authors/5526470-yonghuan-yun.

Medication regularities of traditional Chinese medicine formulas for six kinds of pains by data-mining approach / 中国中药杂志

To study and compare the medication regularities of traditional Chinese medicine formulas(TCMFs) for the six kinds of pains,namely abdominal pain,headache,epigastric pain,hypochondriac pain,heartache and backache,using a data-mining approach,in order to provide reference for relevant studies for the compatibility mechanism and new compound development of related TCMFs. A total of 2 443 TCMFs for pains were collected from the Dictionary of Chinese Medicine Prescriptions,and analyzed using the Apriori algorithm based on three indicators,namely confidence,lift and support,so as to study pivotal traditional Chinese medicines(TCMs) for each pain and their compatibility regularities. The results showed that deficiency tonifying medicines(such as Glycyrrhizae Radix et Rhizoma and Angelicae Sinensis Radix),Qi-regulating medicines(like Aucklandiae Radix) and blood circulation promoting medicines(like Chuanxiong Rhizoma) were commonly used TCMs for pains. However,there were many differences between drugs for various kinds of pains. For example,Magnoliae Officinalis Cortex was used frequently for abdominal pain and epigastric pain,while Saposhnikoviae Radix was used frequently for headache. The latent association rules with significant lift included Carthami Flos → Angelicae Sinensis Radix for abdominal pain,Astragali Radix → Glycyrrhizae Radix et Rhizoma for headache,Hordei Fructus Germinatus → Citri Reticulatae Pericarpium for epigastric pain,Gentianae Radix et Rhizoma → Bupleuri Radix for hypochondriac pain,and Caryophylli Flos → Moschus for backache. This study showed that based on the TCMFs from the Dictionary of Chinese Medicine Prescriptions,the data-mining approach can reveal the differences and similarities in the use of TCMs for the six kinds of pains,and discover the latent composition regularities of relevant TCMs.

[Rapid determination of nine components in the first extraction process of Xingnaojing injection by using ultraviolet spectroscopy].

In this study, an analytical method based on ultraviolet spectroscopy was established for the rapid determination of nine components including isophorone, 4-methylene-isophorone, curcumenone, curcumenol, curdione, curzerenone, furanodienone, curcumol and germacrone in the first extraction process of Xingnaojing injection. 166 distillate samples of Gardeniae Fructus and Radix Curcumae were collected in the first extraction process of Xingnaojing injection. The ultraviolet spectra of these samples were collected, and the contents of the nine components in these samples were determined by high performance liquid chromatography. Least squares support vector machine and radial basis function artificial neural network were used to establish the multivariate calibration models between the ultraviolet spectra and the contents of the nine components. The results showed that the established ultraviolet spectrum analysis method can determine the contents of the nine components in the distillates accurately, with root mean square error of prediction of 0.068, 0.147, 0.215, 0.319, 1.01, 1.27, 0.764, 0.147, 0.610 mg•L⁻¹, respectively. This proposed method is a rapid, simple and low-cost tool for the monitoring and endpoint determination of the extraction process of Xingnaojing injection to reduce quality defects and variations.

Calibration transfer of near-infrared spectroscopy by canonical correlation analysis coupled with wavelet transform.

Calibration model transfer has played a prominent role in the practical application of NIR spectral analysis. The change of instruments and sample physical states may lead to variation of the NIR spectrum, which results in the applicability of the model in judicatory practice being unsatisfactory. Therefore, a transfer for the calibration model considering both the variation of instruments and sample states is a necessity to ensure its availability. In this paper, a novel approach, namely canonical correlation analysis coupled with wavelet transform (WTCCA), was proposed for calibration transfer between two near infrared spectrometers (a portable and a laboratory instrument), and simultaneously, among three physical states (tobacco powder, tobacco filament and intact leaf) to determine the content of total sugars, reducing sugars, and nicotine in tobacco leaf samples, respectively. Wavelet transform (WT) is introduced to reduce noise and deduct background shifts from the spectra by compression, and then, calibration transfer by canonical correlation analysis (CTCCA) extracts the compressed spectral similarities using canonical scores for spectra correction. Three similar standardization algorithms, including piecewise direct standardization (PDS), piecewise direct standardization with wavelet transform (WTPDS), and CTCCA were compared with WTCCA to evaluate its relative performance. The obtained results showed that the employment of WTCCA yielded the lowest root mean standard error of prediction (RMSEP) on the three analytes in three physical states. For the tobacco powder dataset, the RMSEP values had a reduction of 25.83%, 13.96%, and 14.22% compared with the values of direct prediction without spectra transfer, respectively. For the tobacco filament dataset, the corresponding values were decreased by 18.06%, 14.90%, and 13.61% and for the intact leaf dataset, the values had dropped by 10.70%, 18.21%, and 28.21%, respectively. In summary, the comprehensive investigation carried out in the present work shows that WTCCA is very appropriate for correcting the variations caused by the change of machines and sample states. Furthermore, WTCCA is a promising calibration transfer method which can be recommended for on-line/in-line application.

Anticancer and anti-angiogenic activities of extract from Actinidia eriantha Benth root.

ETHNOPHARMACOLOGICAL RELEVANCE: The roots of Actinidia eriantha Benth (AER) are commonly used traditional folk medicine for the treatment of gastric carcinoma, nasopharyngeal carcinoma, and breast carcinoma. Besides, the anti-proliferative and immunomodulatory effects of AER polysaccharides on tumor-bearing mice have been reported previously. AIM OF THE STUDY: This work was carried out to investigate the anticancer and anti-angiogenic activities of AER. MATERIALS AND METHODS: The growth inhibitory effects of ethanol extracts from the leaves (EEL), stems (EES) and roots (EER) of A. eriantha on human gastric carcinoma SGC7901 cells, human nasopharyngeal carcinoma CNE2 cells, human breast carcinoma MCF7 cells and human umbilical vein endothelial cells (HUVECs) were evaluated by MTT assay. The ethyl acetate fraction from EER (EA-EER) was further investigated for the anticancer activity against SGC7901 cells and the anti-angiogenic activity in HUVECs in vitro. The apoptosis in SGC7901 cells and HUVECs was confirmed by DAPI nuclear staining and flow cytometry analysis, the effect on cellular DNA fragmentation was detected in SGC7901 cells. And the cell cycle-arresting activity in HUVECs was determined by flow cytometry. Moreover, the inhibitory effect of EA-EER on cell migration in HUVECs was observed by both wound-healing and Transwell migration assays. RT-PCR and Western-blotting were performed to determine the mRNA and protein expression levels, respectively, including Bax, Bcl-2 and caspase-3 in SGC7901 cells, as well as VEGF-A and VEGFR-2 in HUVECs. Furthermore, the in vivo anti-angiogenic activity of EA-EER was evaluated by using chick embryo chorioallantoic membrane (CAM) assay. Ultimately, the chemical components in EA-EER were isolated and purified by repeated column chromatography followed by structure characterization using 1H and 13C nuclear magnetic resonance and mass spectroscopy. RESULTS: Compared with EEL and EES, EER displayed the strongest growth inhibitory effect on SGC7901 cells, CNE2 cells and HUVECs. Among the EER fractions, EA-EER exhibited the most potent growth inhibitory activity against SGC7901 cells, CNE2 cells and HUVECs. Moreover, EA-EER induced obvious apoptosis in SGC7901 and HUVECs, and significantly inhibited the proliferation of HUVECs via blockade of cell cycle G1 to S progression. Furthermore, EA-EER suppressed the expression of Bcl-2 and improved the expression Bax and caspase-3 in SGC7901 cells. EA-EER not only inhibited migration of HUVECs, but also down-regulated the expression of VEGF-A and VEGFR-2 in HUVECs. In vivo, EA-EER exposure reduced the formation of blood vessels in chick embryos. A bio-guided isolation of EA-EER led to the isolation of three compounds for the first time, namely (6R, 7E, 9S)-6, 9-hydroxy-megastigman-4, 7-dien-3-one-9-O-ß-D-glucopyranoside, Oleanolic acid-23-O-ß-D-glucopyranoside, 3ß, 23, 24-trihydroxyl-12-oleanen-28-oic acid. CONCLUSION: The present research demonstrated that the significant anticancer and anti-angiogenic effects of AER, providing the supportive evidence for its traditional use in the treatment for cancer. It was suggested that AER could be use as a potential source of cancer therapeutic drug.

Hydrogel derived from decellularized porcine adipose tissue as a promising biomaterial for soft tissue augmentation.

Decellularized extracellular matrix (ECM) scaffolds from human adipose tissue, characterized by impressive adipogenic induction ability, are promising for soft tissue augmentation. However, scaffolds from autologous human adipose tissue are limited by the availability of tissue resources and the time necessary for scaffold fabrication. The objective of the current study was to investigate the adipogenic properties of hydrogels of decellularized porcine adipose tissue (HDPA). HDPA induced the adipogenic differentiation of human adipose-derived stem cells (ADSCs) in vitro, with significantly increased expression of adipogenic genes. Subcutaneous injection of HDPA in immunocompetent mice induced host-derived adipogenesis without cell seeding, and adipogenesis was significantly enhanced with ADSCs seeding. The newly formed adipocytes were frequently located on the basal side in the non-seeding group, but this trend was not observed in the ADSCs seeding group. Our results indicated that, similar to human adipose tissue, the ECM scaffold derived from porcine adipose tissue could provide an adipogenic microenvironment for adipose tissue regeneration and is a promising biomaterial for soft tissue augmentation. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 1756-1764, 2017.

[Application of Intelligent Optimization Algorithms to Wavelength Selection of Near-Infrared Spectroscopy].

Near infrared spectroscopy (NIRS) is a kind of indirect analysis technology, whose application depends on the setting up of relevant calibration model. In order to improve interpretability, accuracy and modeling efficiency of the prediction model, wavelength selection becomes very important and it can minimize redundant information of near infrared spectrum. Intelligent optimization algorithm is a sort of commonly wavelength selection method which establishes algorithm model by mathematical abstraction from the background of biological behavior or movement form of material, then iterative calculation to solve combinatorial optimization problems. Its core strategy is screening effective wavelength points in multivariate calibration modeling by using some objective functions as a standard with successive approximation method. In this work, five intelligent optimization algorithms, including ant colony optimization (ACO), genetic algorithm (GA), particle swarm optimization (PSO), random frog (RF) and simulated annealing (SA) algorithm, were used to select characteristic wavelength from NIR data of tobacco leaf for determination of total nitrogen and nicotine content and together with partial least squares (PLS) to construct multiple correction models. The comparative analysis results of these models showed that, the total nitrogen optimums models of dataset A and B were PSO-PLS and GA-PLS models. GA-PLS and SA-PLS models were the optimums for nicotine, respectively. Although not all predicting performance of these optimization models was superior to that of full spectrum PLS models, they were simplified greatly and their forecasting accuracy, precision, interpretability and stability were improved. Therefore, this research will have great significance and plays an important role for the practical application. Meanwhile, it could be concluded that the informative wavelength combination for total nitrogen were 4 587~4 878 and 6 700~7 200 cm(-1), and that for tobacco nicotine were 4 500~4 700 and 5 800~6 000 cm(-1). These selected wavelengths have actually physical significance.

Rapid determination of nine components in the first extraction process of Xingnaojing injection by using ultraviolet spectroscopy / 中国中药杂志

In this study, an analytical method based on ultraviolet spectroscopy was established for the rapid determination of nine components including isophorone, 4-methylene-isophorone, curcumenone, curcumenol, curdione, curzerenone, furanodienone, curcumol and germacrone in the first extraction process of Xingnaojing injection. 166 distillate samples of Gardeniae Fructus and Radix Curcumae were collected in the first extraction process of Xingnaojing injection. The ultraviolet spectra of these samples were collected, and the contents of the nine components in these samples were determined by high performance liquid chromatography. Least squares support vector machine and radial basis function artificial neural network were used to establish the multivariate calibration models between the ultraviolet spectra and the contents of the nine components. The results showed that the established ultraviolet spectrum analysis method can determine the contents of the nine components in the distillates accurately, with root mean square error of prediction of 0.068, 0.147, 0.215, 0.319, 1.01, 1.27, 0.764, 0.147, 0.610 mg•L⁻¹, respectively. This proposed method is a rapid, simple and low-cost tool for the monitoring and endpoint determination of the extraction process of Xingnaojing injection to reduce quality defects and variations.

Calibration transfer via an extreme learning machine auto-encoder.

In order to solve the spectra standardization problem in near-infrared (NIR) spectroscopy, a Transfer via Extreme learning machine Auto-encoder Method (TEAM) has been proposed in this study. A comparative study among TEAM, piecewise direct standardization (PDS), generalized least squares (GLS) and calibration transfer methods based on canonical correlation analysis (CCA) was conducted, and the performances of these algorithms were benchmarked with three spectral datasets: corn, tobacco and pharmaceutical tablet spectra. The results show that TEAM is a stable method and can significantly reduce prediction errors compared with PDS, GLS and CCA. TEAM can also achieve the best RMSEPs in most cases with a small number of calibration sets. TEAM is implemented in Python language and available as an open source package at https://github.com/zmzhang/TEAM.