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The Mn2O3@ZnMn2O4/C hollow microspheres were synthesized by room-temperature stirring and then annealing under air atmosphere. Benefiting from the unique structure, its application in AZIBs as cathode exhibits excellent electrochemical performance.

Based on a typical prototype of a soil slope in engineering practice, a numerical model of a three-stage soil slope supported by the anchor frame structure was established by means of FLAC3D code. The dynamic responses of three-stage soil slope and frame structure were studied by performing a series of bidirectional Wenchuan motions in terms of the failure mode of three-stage structure, the acceleration of soil slope, the displacement of frame structure, and the anchor stress of frame structure. The response accelerations in both horizontal and vertical directions are the most largely amplified at the slope top of each stage subjected to different shaking cases. The platforms among the stages reduce the amplification effect of response acceleration. The residual displacement of frame structure increases significantly as the intensity of shaking case increases. The frame structure at each stage presents a combined displacement mode consisting of a translation and a rotation around the vertex. The anchor stress of frame structure is mainly increased by the first intense pulse of Wenchuan seismic wave, and it is sensitive to the intensity of shaking case. The anchor stress of frame structure at the first stage is the most considerably enlarged by earthquake loading.

Accurately identifying important areas of biodiversity is one of the key issues in ecology and biodiversity research, as well as an important basis for the delineation of the red line for ecologi-cal protection and territorial spatial planning. With China's typical plateau mountainous area (Yunnan Province) as a research case, we used the net primary productivity (NPP) quantitative index method, InVEST model and InVEST model focusing on topographic relief to identify biodiversity important areas. The results showed that NPP quantitative index method was not suitable for the plateau mountainous areas with obvious vertical zonal development. The identified area contained only 26.1% of the protected areas. The InVEST model had higher identification accuracy than the NPP quantitative index method in Yunnan Province. The identified area covered 49.4% of the protected natural areas. Fragmentation was obvious in northwest Yunnan. The InVEST model focusing on topographic relief improved the identification accuracy of important areas of biodiversity, including 71.7% of nature reserves. The deficiency of NPP quantitative index method in water area identification was made up and the fragmentation problem of InVEST model was solved. The area of biodiversity important areas was 119466.94 km精确识别生物多样性重要区是生态学和生物多样性研究的关键问题之一,也是生态保护红线划定和国土空间规划的重要基础。本研究以中国典型高原山区云南省为研究案例,分别用净初级生产力(NPP)定量指标法、InVEST模型和顾及地形起伏的InVEST模型识别研究区生物多样性重要区。结果表明: NPP定量指标法不适用于垂直地带性发育明显的高原山区,其识别区域仅包含自然保护地的26.1%;InVEST模型较NPP定量指标法在云南省具有较高的识别精度,识别区域包含自然保护地的49.4%,但在滇西北破碎化格局明显;顾及地形起伏的InVEST模型提高了生物多样性重要区的识别精度,包含71.7%的自然保护区,同时弥补了NPP定量指标法对水域识别的缺漏,解决了InVEST模型的破碎化问题;云南省生物多样性重要区面积达119466.94 km

Cyclopeptides usually play a pivotal role, either in the viability or virulence of fungi. Two types of cyclopeptides, six new hydroxamate siderophore cyclohexapeptides (1–6), including acremonpeptides E and F, and their complexes with aluminum and ferric ions, one new cyclic pentapeptolide, aselacin D (9), together with a known compound, aselacin C (10), were isolated and characterized from the sponge-derived fungus Acremonium persicinum F10. In addition, two new siderophore analogues chelating gallium ions (Ga3+), Ga (III)-acremonpeptide E (7) and Ga (III)-acremonpeptide F (8), using isolated acremonpeptides E and F, were prepared. The planar structures of 1–10 were elucidated by HRESIMS and (1D and 2D) NMR. The absolute configurations of amino acids were determined by means of the advanced Marfey’s method and X-ray single-crystal diffraction analysis. X-ray fluorescence (XRF) spectrometer was performed to disclose the elements of compound 1, indicating the existence of aluminum (Al). Al (III)-acremonpeptides E (1), Ga (III)-acremonpeptides E (5), Al (III)-acremonpeptide F (7), and Ga (III)-acremonpeptide F (8) displayed high in vitro anti-fungal activities, which are comparable to amphotericin B, against Aspergillus fumigatus and Aspergillus niger.

Despite a much higher proportion of intragenic heterochromatin-containing genes in crop genomes, the importance of intragenic heterochromatin in crop development remains unclear. Intragenic heterochromatin can be recognised by a protein complex, ASI1-AIPP1-EDM2 (AAE) complex, to regulate alternative polyadenylation. Here, we investigated the impact of rice ASI1 on global poly(A) site usage through poly(A) sequencing and ASI1-dependent regulation on rice development. We found that OsASI1 is essential for rice pollen development and flowering. OsASI1 dysfunction has an important impact on global poly(A) site usage, which is closely related to heterochromatin marks. Intriguingly, OsASI1 interacts with the intronic heterochromatin of OsXRNL, a nuclear XRN family exonuclease gene involved in the processing of an miRNA precursor, to promote the processing of full-length OsXRNL and regulate miRNA abundance. We found that OsASI1-mediated regulation of pollen development partially depends on OsXRNL. Finally, we characterised the rice AAE complex and its involvement in alternative polyadenylation and pollen development. Our findings help to elucidate an epigenetic mechanism governing miRNA abundance and rice development, and provide a valuable resource for studying the epigenetic mechanisms of many important processes in crops.

The basin region of nine highland lakes plays an important role in the economic development of Yunnan Province, in which, the basin region of the five lakes (Dianchi, Fuxianhu, Xingyunhu, Qiluhu and Yangzonghai Lake, hereinafter was called Five-lake Basin) locating in the central region of Yunnan Province is the most active economic and social development area of industry, agriculture and tourism, closely related to the eco-environmental quality of the whole basin. In this study, the eco-environmental quality of the Five-lake Basin from 1988 to 2018 was monitored and evaluated based on remote sensing ecological index (RSEI). The results showed that although the eco-environmental quality in this area had a trend of turning better from 1988 to 2018, with the mean value of RSEI increasing from 0.368 to 0.481, whereas the overall eco-environmental quality of the basin was poor. The area with improved eco-environmental quality accounted for 57.6%, which was mainly distributed in the mountains between lakes, while the declining area was mainly the flat area around the lake. The eco-environmental quality of Dianchi Lake, Fuxianhu Lake, and Yangzonghai Lake was improved during the study period, but the eco-environmental quality of Qiluhu Lake and Xingyunhu Lake deteriorated obviously in the last 10 years. The change of eco-environmental quality in each lake was consistent with the change of water quality. In the future, the improvement of eco-environmental quality needs more social attention and government investment.九大高原湖泊流域在云南省经济发展中占有举足轻重的地位,其中,滇中五大湖泊流域(滇池、抚仙湖、星云湖、杞麓湖、阳宗海,下文称五湖流域)是云南工农业、旅游业等经济和社会发展最活跃的地区,与流域生态环境质量密切相关。本研究基于遥感生态指数(RSEI)对滇中五湖流域1988—2018年的生态环境质量进行监测和评价。结果表明: 尽管1988—2018年间研究区生态环境质量呈转好趋势,RSEI平均值由0.368增加到0.481,但流域整体生态环境质量欠佳;生态环境质量提高的面积占比57.6%,主要分布在湖泊之间的山地,下降区域主要为湖周的平地区;研究期间,滇池、抚仙湖、阳宗海的生态环境质量持续变好,但近10年,杞麓湖和星云湖的生态环境质量明显变差,各湖泊生态环境质量变化与湖泊水质变化存在一致性。未来生态环境质量的改善还需更多的社会关注和政府投入。.

The anchoring frame beam is a widely used supporting structure in slope engineering. In this work, the dynamic behavior of anchoring frame beam under earthquake loading was studied by means of shaking table test and dynamic numerical simulation. The results of numerical simulation were compared with the test results in terms of the horizontal acceleration amplification, the vertical acceleration amplification, and the time history of displacement response. The behavior of axial stress of anchor was mainly studied by dynamic numerical simulation. The numerical results are generally consistent with those apparent in shaking table test. The results show that the natural frequency of the supported soil slope presents a decreasing trend during the shaking table test. The soil slope performs an amplification effect on input horizontal acceleration in time domain, and the energy within a frequency range that is around the natural frequency of soil slope is also amplified. Both the horizontal and the vertical acceleration amplifications present an increasing trend with the increase in input acceleration. The acceleration amplification differs greatly under different seismic motions. The frame beam presents a translation displacement together with a rotation around the vertex of frame beam. The residual deformation of frame beam increases obviously with the increase of input acceleration. A larger value of axial stress is observed at the anchor located at the bottom of frame beam. The axial stress of anchor decreases rapidly in anchorage segment, and it tends to zero within a short length under Wenchuan shaking event. The distribution curve of axial stress along the length of anchor presents two peak values after earthquake loading, which is much different from that induced by the self-weight.

Cost-efficient catalyst for hydrogen evolution reaction (HER) and methanol oxidization reaction (MOR) is of great importance for industrial application. The alloying of platinum with cheap transition metal offers a great opportunity to reduce cost and enhance the electro-catalytic performance. Herein, we report a simple and green route to synthesize porous Pt-Cu catalysts, where Pt-Cu solid particles were first produced by using cuprous chloride (CuCl) nanoparticles as the template, followed by a dealloying treatment to obtain final porous product. The porous alloy nanoparticles show higher catalytic activity and superior stability for HER and methanol oxidation reaction, which is beneficial from the porous structure and synergetic effect between Pt and Cu.

A composite time series of the merged satellite altimeters sea surface height anomaly (SSHA) data and satellite-observed sea surface temperature (SST) data were used to identify eddies in the Western North Pacific Ocean (WNPO), where there were numbers of intense typhoons. This study systematically investigated 15 super typhoons during the period of 2000-2008 in the WNPO to study their impacts on the pre-typhoon ocean features, e.g., the cyclonic ocean eddy (COE) feature (closed contours of SSHA < −6 cm) and neutral condition (SSHA between −6 and 6 cm). Two new COEs are generated by two super typhoons, and 18 pre-existing COEs are intensified by 13 super typhoons. 5 of the 13 super typhoons each influenced two pre-exisiting COEs. Although the typhoon-induced maximum cooling centers had a right bias along the tracks due to wind conditions, pre-existing COEs also play a significant role in determining the strength and location of large SST cooling. Three possible factors (maximum wind speed, typhoon translation speed and the typhoon forcing time, Tf) are employed to explain the interactions. Above all, the changes of the COE geometric and physical parameters (e.g., effective radius, area, SST, SSHA, and eddy kinetic energy) were mostly related to the typhoon forcing time, Tf. This is because Tf is a parameter that is a combination of the typhoon's translation speed, intensity and size. Although the typhoons may significantly impact COEs, such samples were not commonly observed. Thus, the impact of typhoon on the strength of COEs is generally inefficient.

A series of new oxoaporphine derivatives were synthesized and their inhibitory activity of topoisomerase I, cytotoxicity and DNA-binding properties were studied. Oxoaporphine can strongly inhibit topoisomerase I at concentrations of 5–50 µM and the cytotoxicity of the derivatives are more potent than their lead compound. Hypochromism, broadening and red shift in the absorption spectra were observed when these compounds bind to calf thymus DNA (CT DNA). These spectral characteristics were consistent with the intercalative binding of these compounds.

A method of dual-process sample selection based on support vector machine (SVM) is proposed to select informative features in this paper. Samples in a training set are used to train a SVM model, and the samples excluding support vector samples are chosen to select critical features in the procedure of recursive feature elimination (RFE). The effect of the dual-process sample selection method on feature selection is evaluated using the classification and the clustering performance of the selected features. The proposed dual-process sample selection method is applied to five gene expression datasets, and the experimental results show that the method is useful to improve the performance of the feature selection method based on fuzzy interactive self-organizing data algorithm (ISODATA). This indicates the method is reliable and effective for selecting informative genes from gene expression data. Key words: Feature selection, support vector machine, fuzzy interactive self-organizing data algorithm (ISODATA), dual-process sample selection.

In continuation of our search for new antibacterial and antioxidant metabolites from sponge-derived fungi, one new tyrosol derivative, hypocrol A (1), together with four known congeners, trichodenol B (2), 4-hydroxyphenethyl acetate (3), 4-hydroxyphenethyl tetradecanoate (4) and 1-oleyltyrosol (5), was isolated from the strain Hypocrea koningii PF04. Their planar structures were unequivocally elucidated by spectroscopic methods and comparison with the literature data. All the compounds displayed weak antibacterial activities against Staphylococcus aureus, methicillin-resistant S. aureus and Escherichia coli, whereas compounds 1 and 2 exhibited a moderate antioxidant efficacy in the DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay with IC50 values of 48.5 and 97.4 μg/mL, respectively.

A feature selection method based on sensitivity analysis and the fuzzy Interactive Self-Organizing Data Algorithm (ISODATA) is proposed for selecting features from high dimensional gene expression data sets. First, feature sensitivities for discriminating classes are calculated on the basis of the fuzzy ISODATA method. Then, candidate feature subsets are generated according to feature sensitivities with the recursive feature elimination procedure. Finally, the obtained optimal feature subsets are evaluated using both supervised and unsupervised methods to validate their abilities for separating different categories. The proposed method is applied to five microarray datasets, and the experimental results indicate its effectiveness.

In order to further improve the noninvasive measurement precision of human blood components and achieve clinical requirements, we propose a new measurement method based on the dynamic dual wavelength time-resolved transmittance measurement, combined with the advanced time gate technology and Laplasse transform to detect human blood components noninvasively in the blocked blood flow conditions. Simulation results show that when p0, emphasizing the importance of early arriving photons contribution can enhance the detection sensitivity of human body blood parameters.

The aim of this study was to investigate the effect of 17-methoxyl-7-hydroxy-benzene-furanchalcone (MHBFC) on nuclear factor-kappa-binding (NF-κB) and the inflammatory response in rats with myocardial ischemia reperfusion injury (MI/RI). Sprague-Dawley rats were randomly divided into 7 groups, and the rat MI/RI model was established by the ligation of the left anterior descending for 30 minutes followed by ligation release for 1 hour. Areas of myocardial infarction were measured using Evans blue-2,3,5-Triphenyltetrazolium chloride (TTC) staining. Levels of malondialdehyde, glutathione peroxidase, and total superoxide dismutase were assessed. Release of interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-10 (IL-10) was measured by means of an enzyme-linked immunosorbent assay. NF-κBp65 and intercellular adhesion molecule-1 protein expression and caspase-3 and adenine nucleotide translocator-1 messenger RNA expression were evaluated by immunohistochemistry and reverse transcription polymerase chain reaction, respectively. Pretreatment with MHBFC decreased the infarction areas, the malondialdehyde, IL-1β and IL-6 levels, the expression of caspase-3, NF-κBp65, and intercellular adhesion molecule-1. Further, MHBFC increased total superoxide dismutase and glutathione peroxidase activities, the release of IL-10, and the expression of adenine nucleotide translocator-1 messenger RNA compared with the results of the model group. The experiment showed that MHBFC protected the heart against MI/RI possibly by reducing lipid peroxidation damage while inhibiting the activity of NF-κBp65 and the inflammatory response.

A novel method of feature selection combined with sample selection is proposed to select discriminant features in this paper. Based on support vector machine trained on training set, the samples excluding the misclassified samples and support vector samples are used to select informative features during the procedure of recursive feature selection. The feature selection method is applied to seven datasets, and the classification results of the selected discriminant features show that the method is effective and reliable for selecting features with high classification information.

A new phenylethanoid glycoside, named taraffinisoside A (1), together with five known glycosides were isolated from the stems and leaves of Tarphochlamys affinis. The structure of taraffinisoside A was identified on the basis of detailed spectral analysis. Compounds 1–4 and 6 showed potent antioxidant activities with IC50 values of 10.36, 19.73, 43.95, 15.30 and 46.04 μM by 1,1-diphenyl-2-picryhydrazyl radical-scavenging assay. Compounds 1, 2 and 4 showed anti-HBV activities, with IC50 values of 0.50, 0.72 and 0.26 mM for HBsAg and 0.93, 0.42 and 0.07 mM for HBeAg, respectively.

Background MicroRNAs are known to be generated from primary transcripts mainly through the sequential cleavages by two enzymes, Drosha and Dicer. The sequence of a mature microRNA, especially the ‘seeding sequence’, largely determines its binding ability and specificity to target mRNAs. Therefore, methods that predict mature microRNA sequences with high accuracy will benefit the identification and characterization of novel microRNAs and their targets, and contribute to inferring the post-transcriptional regulation network at a genome scale. Methodology/Principal Findings We have developed a method, MiRmat, to predict the mature microRNA sequence. MiRmat is essentially composed of two parts: the prediction of Drosha processing site and the identification of Dicer processing site. Based on the analysis of microRNAs from 12 species, we found that the patterns of free energy profiles are conserved among vertebrate microRNA hairpins. Therefore, we introduced in our method the free energy distribution pattern of the downstream part of pri-microRNA secondary structure and Random Forest algorithm to predict the mature microRNA sequence. Based on the evaluation on an independent test dataset from 10 vertebrates, MiRmat was shown to identify 77.8% of the Drosha processing sites and 92.8% of the Dicer sites within a deviation of 2 nt. In a more stringent evaluation by excluding the microRNAs sharing the same family between the training set and test set, MiRmat kept a rather well performance of 71.9% and 87.2% of the identification rate on the Drosha and Dicer site respectively, which represents the ability to deal with the novel microRNA family. MiRmat outperforms other state-of-the-art methods and has a high degree of efficacy for the prediction of mature microRNA sequences of vertebrates. Conclusion MiRmat was developed for identifying microRNA mature sequence(s) by introducing the free energy distribution of RNA stem-loop structure and the Random Forest algorithm. We prove that MiRmat has better performance than the existing tools and is applicable among vertebrates. MiRmat is freely available at http://mcube.nju.edu.cn/jwang/lab/soft/MiRmat/.

Interleukin 16 (IL-16) can be detected by ELISA in pleural effusion (PE) and its concentration is higher than in serum. This study investigated the cellular sources of IL-16 in PE.The samples of PE were collected from 34 patients who were newly diagnosed having PE in the pleural cavity. We performed cell culture to purify the pleural mesothelial cells (PMC), Wright staining to count the purity and immunocytochemical stain to identify the cultured cells. The intracellular IL-16 expression was detected by flow cytometry (FCM). The different cells in PE were first separated by magnetic cell sorting (MCAS) then the separated cells were cultured in RPMI1640 with 10% fetal calf serum (FCS). We extracted the supernatant and detected IL-16 concentration by ELISA. The IL-16 protein was detected by immunohistochemistry and double immunofluorescence staining.The percentages of cells which secreted IL-16 were: CD3(+)CD8(-) cells ((74.27 ± 15.56)%, n = 34); CD3(+)CD8(+) cells ((69.86 ± 18.55)%, n = 34); CD19(+) cells ((45.30 ± 18.77)%, n = 15); CD14(+) cells ((16.91 ± 16.69)%, n = 15); and PMC ((2.05 ± 1.85)%, n = 7). The concentrations of IL-16 in the supernatant from cultured cells were: CD4(+) cells ((102.50 ± 42.51) ng/L, n = 5); CD8(+) cells ((92.58 ± 18.34) ng/L, n = 5); CD19(+) cells ((79.85 ± 5.62) ng/L, n = 5); CD14(+) cells ((58.51 ± 25.38) ng/L, n = 5); and PMC ((18.14 ± 8.37) ng/L, n = 5). In lymphocytes, monocytes/macrophages and PMC, we could observe the cells that expressed IL-16 protein. In paraffin-embedded sections, we also could observe by immunohistochemistry the CD4(+)IL-16(+) cells, CD8(+)IL-16(+) cells, CD19(+)IL-16(+) cells, and CD14(+)IL-16(+) cells.IL-16 in PE is mainly secreted by T lymphocytes, including CD3(+)CD8(-) cells and CD3(+)CD8(+) cells. CD19(+) cells and CD14(+) cells can also secrete IL-16, but the percentage of PMC that can secrete IL-16 is very low.

Objective.The effects of low-intensity 630 nm semiconductor laser irradiation at 3.6 J/cm2(LISL) on wound healing in diabetic rats were studied in this paper.Methods.36 diabetic rats with dorsal cutaneous excisional wounds were divided into three LISL groups and a control group randomly. The three LISL groups were irradiated with LISL at 5, 10, and 20 mW/cm2five times a week for two weeks, respectively. The process of wound healing was assessed by assessing blood glucose, calculating percentage of wound closure, histopathological evaluation, and immunohistochemical quantification.Results.Blood glucose of all groups remained at similar levels throughout the experiment. LISL could obviously promote wound contraction, fibroblasts proliferation, and collagen synthesis, alter bFGF and TGF-β1 expression, and reduce inflammatory reaction in the early and middle phases of chronic wound-healing process. However, LISL could not shorten cicatrization time, and the treatment effects were not sensitive to illuminate parameters in the later phase of the experiment.Conclusions.LISL might have auxiliary effects in the early and middle phases of wound healing in STZ-induced diabetic rats, but the reciprocity rule might not hold. The wound-healing process of early-phase diabetes rats shows typical characteristics of self-limited disease.

A rabbit model of endophthalmitis was established to evaluate the antiinflammatory effect of low-level laser therapy (LLLT) as an adjunct to treatment for Staphylococcus epidermidis endophthalmitis. Rabbits were randomly divided into three groups to receive intravitreal injections into their left eye: group A received 0.5 mg vancomycin (100 μl), group B received 0.5 mg vancomycin + 0.2 mg dexamethasone (100 μl), and group C received 0.5 mg vancomycin (100 μl) and continuous wave semiconductor laser irradiation (10 mW, λ = 632 nm) focused on the pupil. Slit lamp examination and B-mode ultrasonography were conducted to evaluate the symptoms of endophthalmitis. Polymorphonuclear cells and tumour necrosis factor alpha (TNF-α) in aqueous fluid were measured at 0 h, and 1, 2, 3, 7 and 15 days. A histology test was conducted at 15 days. B-mode ultrasonography and histology revealed that groups B and C had less inflammation than group A at 15 days. Groups B and C had fewer polymorphonuclear cells and lower levels of TNF-α in aqueous fluid than group A at 2, 3 and 7 days (P0.05). There was no significant difference between groups B and C (P0.05). There was no significant difference between groups A, B and C at 15 days (P0.05). As an adjunct to vancomycin therapy to treat S. epidermidis endophthalmitis, LLLT has an antiinflammatory effect similar to that of dexamethasone.

To evaluate the efficiency and safety of an optimized CO(2) Laser glaucoma surgery system for laser sclerectomy with iridectomy.Rabbit trials were performed to evaluate the efficiency and safety.IOP was significantly decreased in laser group compared with trabeculectomy group(P0.05) from 7(th) postoperative day to 60(th) day. Compared with trabeculectomy group, histopathology studies confirmed fewer complications and better effects were found in laser group.CO(2) laser sclerectomy with iridectomy is effective and safe in terms of IOP lowering.

In the studies of Drosophila embryogenesis, a large number of two-dimensional digital images of gene expression patterns have been produced to build an atlas of spatio-temporal gene expression dynamics across developmental time. Gene expressions captured in these images have been manually annotated with anatomical and developmental ontology terms using a controlled vocabulary (CV), which are useful in research aimed at understanding gene functions, interactions, and networks. With the rapid accumulation of images, the process of manual annotation has become increasingly cumbersome, and computational methods to automate this task are urgently needed. However, the automated annotation of embryo images is challenging. This is because the annotation terms spatially correspond to local expression patterns of images, yet they are assigned collectively to groups of images and it is unknown which term corresponds to which region of which image in the group. In this paper, we address this problem using a new machine learning framework, Multi-Instance Multi-Label (MIML) learning. We first show that the underlying nature of the annotation task is a typical MIML learning problem. Then, we propose two support vector machine algorithms under the MIML framework for the task. Experimental results on the FlyExpress database (a digital library of standardized Drosophila gene expression pattern images) reveal that the exploitation of MIML framework leads to significant performance improvement over state-of-the-art approaches.

The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interaction, and networks during Drosophila embryogenesis. To provide text-based pattern searching, the images in the Berkeley Drosophila Genome Project (BDGP) study are annotated with ontology terms manually by human curators. We present a systematic approach for automating this task, because the number of images needing text descriptions is now rapidly increasing. We consider both improved feature representation and novel learning formulation to boost the annotation performance. For feature representation, we adapt the bag-of-words scheme commonly used in visual recognition problems so that the image group information in the BDGP study is retained. Moreover, images from multiple views can be integrated naturally in this representation. To reduce the quantization error caused by the bag-of-words representation, we propose an improved feature representation scheme based on the sparse learning technique. In the design of learning formulation, we propose a local regularization framework that can incorporate the correlations among terms explicitly. We further show that the resulting optimization problem admits an analytical solution. Experimental results show that the representation based on sparse learning outperforms the bag-of-words representation significantly. Results also show that incorporation of the term-term correlations improves the annotation performance consistently.

Background Drosophila gene expression pattern images document the spatiotemporal dynamics of gene expression during embryogenesis. A comparative analysis of these images could provide a fundamentally important way for studying the regulatory networks governing development. To facilitate pattern comparison and searching, groups of images in the Berkeley Drosophila Genome Project (BDGP) high-throughput study were annotated with a variable number of anatomical terms manually using a controlled vocabulary. Considering that the number of available images is rapidly increasing, it is imperative to design computational methods to automate this task. Results We present a computational method to annotate gene expression pattern images automatically. The proposed method uses the bag-of-words scheme to utilize the existing information on pattern annotation and annotates images using a model that exploits correlations among terms. The proposed method can annotate images individually or in groups (e.g., according to the developmental stage). In addition, the proposed method can integrate information from different two-dimensional views of embryos. Results on embryonic patterns from BDGP data demonstrate that our method significantly outperforms other methods. Conclusion The proposed bag-of-words scheme is effective in representing a set of annotations assigned to a group of images, and the model employed to annotate images successfully captures the correlations among different controlled vocabulary terms. The integration of existing annotation information from multiple embryonic views improves annotation performance.

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.

To prepare the fusion protein of a single chain variable fragment 637 (scFv637) against human acetylcholine receptor (AChR) and human serum albumin (HSA) to increase the stability of scFv637.HSA gene was amplified by PCR and cloned into vector pHEN2 containing a scFv637 gene to construct recombinant vector pHEN2-scFv637-HSA and then transformed into E. coli HB2151 for expression. The expression of fusion protein in periplasm of E. coli was detected by dot hybridization. Relative molecular mass of fusion protein was checked by SDS-PAGE and Western blot.Agarose gel electrophoresis analysis showed that the size of HSA gene and fusion gene was about 1,770 bp and 7,054 bp, respectively. DNA sequencing proved that the nucleotide sequence of constructed scFv637-HSA gene was correct and it was cloned into the open reading frame (ORF) of pHEN2. scFv637-HSA fusion protein only existed in periplasm of E. coli HB2151 transformed with pHEN2-scFv637-HSA. SDS-PAGE and Western blot analysis indicated that relative molecular mass of fusion protein was about 95,900.The scFv637-HSA fusion protein can be successfully expressed in E. coli HB2151, which provides a sound basis for further research into its function and clinical application.

Heuristic hill-climbing search algorithm can do effectively pruning. In practice, it can be used to search a large hypothesis space to get an optimal or an approximate optimal solution. Beam search algorithm retains its advantage in efficiency while reducing the risk of converging to locally optimal hypotheses. Beam search algorithm is widely used in AI field. To k-size beam search, due to only k paths is maintained the key to optimize the accuracy of beam search is how to select the k paths. In most of search algorithms, the k candidates with the most high performance measure value are selected at each search step. In this paper, the author presented some methods of candidate selection of beam search approaches, and the thought of avoiding "full of blood brother nodes" is presented. The experiments were done on the UCI repository of machine learning databases

It is very important but difficult to identify which genes in gene expression data can contribute most to tumor subtype classification. An approach to select a small subset of genes for leukemia subtype classification from large scale gene expression profile is proposed in this paper. Having removed the noisy genes with little relevance to the classification task, the "sequential floating forward search" method was employed to generate candidate feature subsets consisting of informative genes, and then, a support vector machine was employed as a classifier to select the optimal feature subset with minimum classification errors. The results of our experiment showed that all the samples can be correctly classified without any error with only five genes.

A method based on support vector machines is proposed for cancer molecular classification. The Bhattacharyya distance of each gene is calculated as the criterion for filtering 'noisy-genes' which do not contribute to classification, and then based on the expression values of the informative genes, a linear support vector machine is used as the classifier to classify different cancers. This process has been applied to the human acute leukemia dataset as a test case. The effectiveness and feasibility of the method is proved by the results that all the samples in the dataset can be correctly classified without any error.