Complex insoluble dietary fiber alleviates obesity and liver steatosis, and modulates the gut microbiota in C57BL/6J mice fed a high-fat diet.

BACKGROUND: Obesity has been demonstrated as a risk factor that seriously affects health. Insoluble dietary fiber (IDF), as a major component of dietary fiber, has positive effects on obesity, inflammation and diabetes. RESULTS: In this study, complex IDF was prepared using 50% enoki mushroom IDF, 40% carrot IDF, and 10% oat IDF. The effects and potential mechanism of complex IDF on obesity were investigated in C57BL/6 mice fed a high-fat diet. The results showed that feeding diets containing 5% complex IDF for 8 weeks significantly reduced mouse body weight, epididymal lipid index, and ectopic fat deposition, and improved mouse liver lipotoxicity (reduced serum levels of alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase), fatty liver, and short-chain fatty acid composition. High-throughput sequencing of 16S rRNA and analysis of fecal metabolomics showed that the intervention with complex IDF reversed the high-fat-diet-induced dysbiosis of gut microbiota, which is associated with obesity and intestinal inflammation, and affected metabolic pathways, such as primary bile acid biosynthesis, related to fat digestion and absorption. CONCLUSION: Composite IDF intervention can effectively inhibit high-fat-diet-induced obesity and related symptoms and affect the gut microbiota and related metabolic pathways in obesity. Complex IDF has potential value in the prevention of obesity and metabolic syndrome. © 2024 Society of Chemical Industry.

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Multisystem inflammatory syndrome in children (MIS-C) is a complex syndrome characterized by multi-organ involvement that has emerged in the context of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak. The clinical presentation of MIS-C is similar to Kawasaki disease but predominantly presents with fever and gastrointestinal symptoms, and severe cases can involve toxic shock and cardiac dysfunction. Epidemiological findings indicate that the majority of MIS-C patients test positive for SARS-CoV-2 antibodies. The pathogenesis and pathophysiology of MIS-C remain unclear, though immune dysregulation following SARS-CoV-2 infection is considered a major contributing factor. Current treatment approaches for MIS-C primarily involve intravenous immunoglobulin therapy and symptomatic supportive care. This review article provides a comprehensive overview of the definition, epidemiology, pathogenesis, clinical presentation, diagnosis, treatment, and prognosis of MIS-C.

Intelligent Fault Diagnosis of Rolling Bearings Based on a Complete Frequency Range Feature Extraction and Combined Feature Selection Methodology.

The utilization of multiscale entropy methods to characterize vibration signals has proven to be promising in intelligent diagnosis of mechanical equipment. However, in the current multiscale entropy methods, only the information in the low-frequency range is utilized and the information in the high-frequency range is discarded. In order to take full advantage of the information, in this paper, a fault feature extraction method utilizing the bidirectional composite coarse-graining process with fuzzy dispersion entropy is proposed. To avoid the redundancy of the full frequency range feature information, the Random Forest algorithm combined with the Maximum Relevance Minimum Redundancy algorithm is applied to feature selection. Together with the K-nearest neighbor classifier, a rolling bearing intelligent diagnosis framework is constructed. The effectiveness of the proposed framework is evaluated by a numerical simulation and two experimental examples. The validation results demonstrate that the extracted features by the proposed method are highly sensitive to the bearing health conditions compared with hierarchical fuzzy dispersion entropy, composite multiscale fuzzy dispersion entropy, multiscale fuzzy dispersion entropy, multiscale dispersion entropy, multiscale permutation entropy, and multiscale sample entropy. In addition, the proposed method is able to identify the fault categories and health states of rolling bearings simultaneously. The proposed damage detection methodology provides a new and better framework for intelligent fault diagnosis of rolling bearings in rotating machinery.

Vitality-Enhanced Dual-Modal Tracking System Reveals the Dynamic Fate of Mesenchymal Stem Cells for Stroke Therapy.

Mesenchymal stem cell (MSC) therapy via intravenous transplantation exhibits great potential for brain tissue regeneration, but still faces thorny clinical translation challenges as the unknown dynamic fate leads to the contentious therapeutic mechanism and the poor MSC viability in harsh lesions limits therapeutic efficiency. Here, a vitality-enhanced dual-modal tracking system is designed to improve engraftment efficiency and is utilized to noninvasively explore the fate of intravenous transplanted human umbilical cord-derived MSCs during long-term treatment of ischemic stroke. Such a system is obtained by bioorthogonally conjugating magnetic resonance imaging (MRI) contrast and near-infrared fluorescence (NIRF) imaging nanoparticles to metabolic glycoengineered MSCs with a lipoic acid-containing extracellular antioxidative protective layer. The dynamic fates of MSCs in multi-dimensional space-time evolution are digitally detailed for up to 28 days using MRI and NIRF imaging equipment, and the protective layer greatly shields MSCs from reactive oxygen spices (ROS) degradation, enhances MSC survival, and engraftment efficiency. Additionally, it is observed that the bioengineered MSCs exhibit dynamic intelligent responses corresponding to microenvironment remodeling and exert enhanced therapeutic effects. This dual-modal tracking system enables long-term tracking of MSCs while improving their viability at the lesion sites, which may serve as a valuable tool for expediting the clinical translation of MSC therapy.

The influence of benzoyl peroxide on skin microbiota and the epidermal barrier for acne vulgaris.

The disordered skin microbiome has been reported to contribute to the pathogenesis of acne vulgaris, for which benzoyl peroxide (BPO) has long been recommended as the first-line therapy. However, there are no data regarding the effect of BPO treatment on skin microbiota and the epidermal barrier in young adults with acne vulgaris. Thirty-three patients with acne vulgaris and 19 healthy controls were enrolled in the study. All patients received topical treatment with BPO 5% gel for 12 weeks. The epidermal barrier was analyzed at baseline and after treatment. Microbial diversity was analyzed using a high-throughput sequencing approach targeting the V3-V4 region of 16S rRNA genes. After receiving treatment with BPO, patients had significant improvement in their Global Acne Grading System (GAGS) score, porphyrin, and red areas (p < 0.05), and the presence of sebum, stratum corneum hydration (SCH), and transepidermal water loss (TEWL) increased (p < 0.05). When compared with baseline, microbial diversity was significantly reduced after treatment, as calculated by the goods coverage (p = 0.0017), Shannon (p = 0.0094), and Simpson (p = 0.0017) diversity indices. The prevalence of the genus Cutibacterium (before treatment: 5.64 [3.50, 7.78] vs. after treatment: 2.43 [1.81, 3.05], p = 0.011) was significantly reduced after treatment while Staphylococcus (before treatment: 43.80 [36.62, 50.98] vs. after treatment: 53.38 [44.88, 61.87], p = 0.075) tended to increase. The abundance of Staphylococcus was negatively associated with SCH (p = 0.008, r = -0.286). Despite its contribution to an improved GAGS score, BPO treatment for acne vulgaris may reduce microbial diversity and damage the epidermal barrier.

Metformin and histone deacetylase inhibitor based anti-inflammatory nanoplatform for epithelial-mesenchymal transition suppression and metastatic tumor treatment.

Epithelial-mesenchymal transition (EMT), a differentiation process with aberrant changes of tumor cells, is identified as an initial and vital procedure for metastatic processes. Inflammation is a significant inducer of EMT and provides an indispensable target for blocking EMT, however, an anti-inflammatory therapeutic with highlighted safety and efficacy is deficient. Metformin is a promising anti-inflammatory agent with low side effects, but tumor monotherapy with an anti-inflammation drug could generate therapy resistance, cell adaptation or even promote tumor development. Combination therapies with various anti-inflammatory mechanisms can be favorable options improving therapeutic effects of metformin, here we develop a tumor targeting hybrid micelle based on metformin and a histone deacetylase inhibitor propofol-docosahexaenoic acid for efficient therapeutic efficacies of anti-inflammatory drugs. Triptolide is further encapsulated in hybrid micelles for orthotopic tumor therapies. The final multifunctional nanoplatforms (HAOPTs) with hyaluronic acid (HA) modification can target tumor efficiently, inhibit tumor cell EMT processes, repress metastasis establishment and suppress metastatic tumor development in a synergistic manner. Collectively, the results afford proof of concept that the tumor targeting anti-inflammatory nanoplatform can provide a potent, safe and clinical translational approach for EMT inhibition and metastatic tumor therapy.

A novel colorimetric aptasensor for sensitive tetracycline detection based on the peroxidase-like activity of Fe3O4@Cu nanoparticles and "sandwich" oligonucleotide hybridization.

A novel colorimetric aptasensor has been developed for highly sensitive tetracycline (TC) detection based on the peroxidase-like activity of Fe3O4@Cu nanoparticles and "sandwich" oligonucleotide hybridization. The Fe3O4@Cu nanoparticles with high peroxidase-like activity were successfully synthesized under mild conditions. Then, a "sandwich" oligonucleotide hybridization probe (a short amino-modified complementary sequence of a portion of the TC aptamer (cDNA1), TC aptamers, and a long complementary to 5' terminal TC aptamer sequence (cDNA2)) was created in 96-wells plates via DNA hybridization in the absence of TC from the detection system. The unique "sandwich" oligonucleotide hybridization probe adsorbed large numbers of Fe3O4@Cu nanozymes while further enhancing its peroxidase-like activity. Based on the 3,3',5,5'-tetramethylbenzidine (TMB)-hydrogen peroxide (H2O2) reporting system, the blue color of the solution decreased linearly with the increase of TC concentration, ranging from 10-3 to 103 µg/L with an ultralow limit of detection (LOD) of 0.91 ng/L (2 pM). The proposed method was successfully applied to detect TC in spiked milk samples, with recoveries of 81.8 to 112%, demonstrating the excellent potential for highly sensitive TC detection in milk.

A Dual-Mode Method Based on Aptamer Recognition and Time-Resolved Fluorescence Resonance Energy Transfer for Histamine Detection in Fish.

Histamine produced via the secretion of histidine decarboxylase by the bacteria in fish muscles is a toxic biogenic amine and of significant concern in food hygiene, since a high intake can cause poisoning in humans. This study proposed a fluorometric and colorimetric dual-mode specific method for the detection of histamine in fish, based on the fluorescence labeling of a histamine specific aptamer via the quenching and optical properties of gold nanoparticles (AuNPs). Due to the fluorescence resonance energy transfer phenomenon caused by the proximity of AuNPs and NaYF4:Ce/Tb, resulting in the quenching of the fluorescence signal in the detection system, the presence of histamine will compete with AuNPs to capture the aptamer and release it from the AuNP surface, inducing fluorescence recovery. Meanwhile, the combined detection of the two modes showed good linearity with histamine concentration, the linear detection range of the dual-mode synthesis was 0.2-1.0 µmol/L, with a detection limit of 4.57 nmol/L. Thus, this method has good selectivity and was successfully applied to the detection of histamine in fish foodstuffs with the recoveries of 83.39~102.027% and 82.19~105.94% for Trichiurus haumela and Thamnaconus septentrionalis, respectively. In addition, this method was shown to be simple, rapid, and easy to conduct. Through the mutual verification and combined use of the two modes, a highly sensitive, rapid, and accurate dual-mode detection method for the analysis of histamine content in food was established, thereby providing a reference for the monitoring of food freshness.

Colorimetric method for Salmonella spp. detection based on peroxidase-like activity of Cu(II)-rGO nanoparticles and PCR.

Development of a rapid and sensitive method for Salmonella spp. detection is of great importance for ensuring food product safety due to its low infective dose. In this study, a colorimetric method based on the peroxidase-like activity of Cu(II)-modified reduced graphene oxide nanoparticles (Cu2+-rGO NPs) and PCR was successfully developed to detect Salmonella spp. in milk. Under optimal conditions, the developed colorimetric method exhibited high sensitivity and strong specificity for Salmonella spp. detection. The limit of detection was 0.51 CFU/mL with a linear range from 1.93 × 101 to 1.93 × 105 CFU/mL. A specificity study demonstrated that this method can specifically distinguish Salmonella typhimurium and Salmonella enteritidis from other foodborne pathogens. The application of the proposed method for milk sample detection was also validated, and the recovery rates of S. typhimurium in spiked milk sample ranged from 102.84% to 112.25%. This colorimetric sensor exhibits enormous potential for highly sensitive detection of bacteria in milk sample.

Improving the detection limit of Salmonella colorimetry using long ssDNA of asymmetric-PCR and non-functionalized AuNPs.

A colorimetric sensor based on gold nanoparticles (AuNPs) and single-stranded DNA (ssDNA) is a simple and rapid method for detecting foodborne pathogens. However, the colorimetric method employed in previous studies involved short ssDNA (<100 nucleotides), including the aptamer and PCR products, resulting in the high detection limit of this technique. In this study, a colorimetric sensor was developed based on long ssDNA of asymmetric PCR (aPCR) and non-functionalized AuNPs for detecting Salmonella Typhimurium (S. Typhimurium). In the presence of S. Typhimurium, the long ssDNA (547 nt) amplified by aPCR-protected AuNPs from NaCl-induced aggregation, while the solution retained a red color. After optimizing parameters, the limit of detection (LOD) of the colorimetric sensor was 2.56 CFU/mL with high specificity. Recovery studies showed its feasibility for detecting S. Typhimurium (102 CFU/mL, 104 CFU/mL, and 106 CFU/mL) in spiked lettuce samples. This colorimetric sensor provides new opportunities for the highly sensitive detection of bacteria in real food samples.

Tailored Chemodynamic Nanomedicine Improves Pancreatic Cancer Treatment via Controllable Damaging Neoplastic Cells and Reprogramming Tumor Microenvironment.

Pancreatic ductal adenocarcinoma (PDAC) strongly resists standard therapies since KRAS-mutated cancer cells harbor endogenous resistance toward chemotherapy-induced apoptosis and tumor-associated macrophages (TAMs) activate stroma cells to create the nearly impenetrable matrix. Herein, we developed a tailored nanocomplex through the self-assembly of synthetic 4-(phosphonooxy)phenyl-2,4-dinitrobenzenesulfonate and Fe3+ followed by hyaluronic acid decoration, realizing chemodynamic therapy (CDT) to combat PDAC. By controllably releasing its components in a GSH-sensitive manner under the distinctive redox homeostasis in cancer cells and TAMs, the nanocomplex selectively triggered a Fenton reaction to induce oxidative damage in cancer cells and simultaneously repolarized TAMs to deactivate stromal cells and thus attenuate stroma. Compared to gemcitabine, CDT remarkably inhibited tumor growth and prolonged animal survival in orthotopic PDAC models without noticeable side effects. This study provides a promising strategy to improve the treatment of PDAC through CDT-mediated controlled cancer cells damage and reprogramming of the stromal microenvironment.

A time-resolved luminescence aptasensor of ofloxacin based on rolling circle amplification and magnetic separation.

A novel sensitive, competitive, and time-resolved luminescence sensor for the detection of ofloxacin (OFL) was developed in this study. The sensor used OFL-specific aptamer as a recognition molecule and rolling circle amplification (RCA) as a signal amplification tool. In this way, the time-resolved luminescence can not only avoid background noise from sample, but also provide robust luminescence for detection. Besides, the separation and enrichment of target veterinary drug can be conducted assisted by magnetic treatment. Under optimal conditions, the logarithmic correlation between the concentration of OFL and the luminescence intensity was found to be linear in the range of 5 × 10-11-5 × 10-8 mol L-1 (R2 = 0.9988), with a detection limit (LOD) of 32.1 pmol L-1. Furthermore, this method was applied to the determination of OFL in chicken and pork samples, exhibiting good recovery (72.5-100%) and repeatability (RSD < 10.0%). These results confirm that this novel established method has good application potential for the detection of OFL in food samples.

Metformin and Docosahexaenoic Acid Hybrid Micelles for Premetastatic Niche Modulation and Tumor Metastasis Suppression.

Metastasis is the major cause of high mortality in cancer patients; thus, blocking the metastatic process is of critical importance for cancer treatments. The premetastatic niche, a specialized microenvironment with aberrant changes related to inflammation, allows the colonization of circulating tumor cells (CTCs) and serves as a potential target for metastasis prevention. However, little effort has been dedicated to developing nanomedicine to amend the premetastatic niche. Here this study reports a premetastatic niche-targeting micelle for the modulation of premetastatic microenvironments and suppression of tumor metastasis. The micelles are self-assembled with the oleate carbon chain derivative of metformin and docosahexaenoic acid, two anti-inflammatory agents with low toxicity, and coated with fucoidan for premetastatic niche-targeting. The obtained functionalized micelles (FucOMDs) exhibit an excellent blood circulation profile and premetastatic site-targeting efficiency, inhibit CTC adhesion to activated endothelial cells, alleviate lung vascular permeability, and reverse the aberrant expression of key marker proteins in premetastatic niches. As a result, FucOMDs prevent metastasis formation and efficiently suppress both primary-tumor growth and metastasis formation when combined with targeted chemotherapy. Collectively, the findings here provide proof of concept that the modulation of the premetastatic niche with targeted anti-inflammatory agents provides a potent platform and a safe and clinical translational option for the suppression of tumor metastasis.

A similarity measure method fusing deep feature for mammogram retrieval.

BACKGROUND: Breast cancer is one of the most important malignant tumors among women causing a serious impact on women's lives and mammography is one the most important methods for breast examination. When diagnosing the breast disease, radiologists sometimes may consult some previous diagnosis cases as a reference. But there are many previous cases and it is important to find which cases are the similar cases, which is a big project costing lots of time. Medical image retrieval can provide objective reference information for doctors to diagnose disease. The method of fusing deep features can improve the retrieval accuracy, which solves the "semantic gap" problem caused by only using content features and location features. METHODS: A similarity measure method combining deep feature for mammogram retrieval is proposed in this paper. First, the images are pre-processed to extract the low-level features, including content features and location features. Before extracting location features, registration with the standard image is performed. Then, the Convolutional Neural Network, the Stacked Auto-encoder Network, and the Deep Belief Network are built to extract the deep features, which are regarded as high-level features. Next, content similarity and deep similarity are calculated separately using the Euclidean distance between the query image and the dataset images. The location similarity is obtained by calculating the ratio of intersection to union of the mass regions. Finally, content similarity, location similarity, and deep similarity are fused to form the image fusion similarity. According to the similarity, the specified number of the most similar images can be returned. RESULTS: In the experiment, 740 MLO mammograms are used, which are from women in Northeast China. The content similarity, location similarity, and deep similarity are fused by different weight coefficients. When only considering low-level features, the results are better with fusing 60% content feature similarity and 40% lesion location feature similarity. On this basis, CNN deep similarity, DBN deep similarity, and SAE deep similarity are fused separately. The experiments show that when fusing 60% DBN deep feature similarity and 40% low-level feature similarity, the results have obvious advantages. At this time, the precision is 0.745, recall is 0.850, comprehensive evaluation index is 0.794. CONCLUSIONS: We propose a similarity measure method fusing deep feature, content feature, and location feature. The retrieval results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval and location-based image retrieval.

Sequential Targeting TGF-ß Signaling and KRAS Mutation Increases Therapeutic Efficacy in Pancreatic Cancer.

Pancreatic cancer is a highly aggressive malignancy that strongly resists extant treatments. The failure of existing therapies is majorly attributed to the tough tumor microenvironment (TME) limiting drug access and the undruggable targets of tumor cells. The formation of suppressive TME is regulated by transforming growth factor beta (TGF-ß) signaling, while the poor response and short survival of almost 90% of pancreatic cancer patients results from the oncogenic KRAS mutation. Hence, simultaneously targeting both the TGF-ß and KRAS pathways might dismantle the obstacles of pancreatic cancer therapy. Here, a novel sequential-targeting strategy is developed, in which antifibrotic fraxinellone-loaded CGKRK-modified nanoparticles (Frax-NP-CGKRK) are constructed to regulate TGF-ß signaling and siRNA-loaded lipid-coated calcium phosphate (LCP) biomimetic nanoparticles (siKras-LCP-ApoE3) are applied to interfere with the oncogenic KRAS. Frax-NP-CGKRK successfully targets the tumor sites through the recognition of overexpressed heparan sulfate proteoglycan, reverses the activated cancer-associated fibroblasts (CAFs), attenuates the dense stroma barrier, and enhances tumor blood perfusion. Afterward, siKras-LCP-ApoE3 is efficiently internalized by the tumor cells through macropinocytosis and specifically silencing KRAS mutation. Compared with gemcitabine, this sequential-targeting strategy significantly elongates the lifespans of pancreatic tumor-bearing animals, hence providing a promising approach for pancreatic cancer therapy.

Characterization of serine acetyltransferase (CysE) from methicillin-resistant Staphylococcus aureus and inhibitory effect of two natural products on CysE.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major hospital-acquired infective pathogen that has developed resistance to many antibiotics. It is imperious to develop novel anti-MRSA drugs to control the emergence of drug resistance. The biosynthesis of cysteine in bacteria is catalyzed by CysE and CysK. CysE was predicted to be important for bacterial viability, it could be a potential drug target. The serine acetyltransferase activity of CysE was detected and its catalytic properties were also determined. CysE homology model was built to investigate interaction sites between CysE and substrate L-Ser or inhibitors by molecular docking. Docking data showed that residues Asp94 and His95 were essential for serine acetyltransferase activity of CysE, which were confirmed by site-directed mutagenesis. Colorimetric assay was used to screen natural products and six compounds which inhibited CysE activity (IC50 ranging from 29.83 µM to 203.13 µM) were found. Inhibition types of two compounds 4 (11-oxo-ebracteolatanolide B) and 30 ((4R,4aR)-dihydroxy-3-hydroxymethyl-7,7,10a-trimethyl-2,4,4a,5,6,6a,7,8,9,10,10a,l0b-dodecahydrophenanthro[3,2-b]furan-2-one) on CysE were determined. Compounds 4 and 30 showed inhibitory effect on MRSA growth (MIC at 12.5 µg/ml and 25 µg/ml) and mature biofilm. The established colorimetric assay will facilitate further high-throughput screening of CysE inhibitors from different compound libraries. The compounds 4 and 30 may offer structural basis for developing new anti-MRSA drugs.

Breast mass detection and diagnosis using fused features with density.

BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of malignancy of the tumor is not only related to its morphology and texture features, but also closely related to the density of the tumor. However, in the current research on breast masses detection and diagnosis, people usually use the fusion feature of morphology and texture but neglect density, or only the density feature is considered. Therefore, this paper proposes a method to detect and diagnose the breast mass using fused features with density. METHODS: In this paper, we first propose a method based on sub-region clustering to detect the breast mass. The breast region is divided into sub-regions of equal size, and each sub-region is extracted based on local density feature, after that, an Unsupervised ELM (US-ELM) is used for clustering to complete the mass detection. Second, the feature model is constructed based on the mass. This model is composed of the mass region density feature, morphology feature and texture feature. And Genetic Algorithm is used for feature selection, and the optimized feature model is formed. Finally, ELM is used to diagnose benign or malignant mass. RESULTS: An experiment on the real dataset of 480 mammograms in Northeast China shows that our proposed method can effectively improve the detection and diagnosis accuracy of breast masses, where we obtained 0.9184 precision in detection of breast masses and 0.911 accuracy in diagnosis of breast masses. CONCLUSIONS: We have proposed a mass detection system, which achieves better detection accuracy performance than the existing state-of-art algorithm. We also propose a mass diagnosis system based on the fused features with density, which is more efficient than other feature model and classifier on the same dataset.

Changes in the properties of Radix Aconiti Lateralis Preparata (Fuzi, processed aconite roots) starch during processing.

Radix Aconiti Lateralis Preparata (Fuzi) is an important, toxic traditional Chinese medicine that has been widely used in clinical practice. Due to the toxicity of its raw materials, it needs to be processed before application. The changes in the physicochemical properties of Fuzi starch during processing were evaluated by scanning electron microscopy, X-ray diffraction and differential scanning calorimetry. The results showed the following: morphological properties changed from spherical to irregular and polygonal particles, while the particle size increased significantly; amylose content and solubility decreased significantly; swelling power and water-binding capacity increased significantly; the X-ray diffraction peak disappeared, and the crystallinity decreased; and the gelatinization temperature and enthalpy decreased significantly. The properties of Fuzi starch were similar to those of pregelatinized starch. These results indicated that Fuzi starch undergone repeated processes of gelatinization and aging, which destroyed the original crystal structure of the starch.

Selection and characterization, application of a DNA aptamer targeted to Streptococcus pyogenes in cooked chicken.

An aptamer against Streptococcus pyogenes was selected and identified, and a fluorescent method based on the reported aptamer was established to detect S. pyogenes in the cooked chicken. Through a twelve rounds of whole-bacterium SELEX (systematic evolution of ligands by exponential enrichment) selection in vitro, a set of aptamers binding to the whole cell of S. pyogenes were generated, harvesting a low-level dissociation constant (Kd) value of 44 ±â€¯5 nmol L-1 of aptamer S-12. Aptamer-based quantification of S. pyogenes in the cooked chicken sample was implemented in a fluorescence resonance energy transfer-based assay by using graphene oxide, resulting in a limit of detection of 70 cfu mL-1. The selected aptamer showed affinity and selectivity recognizing S. pyogenes; besides, more biosensors based on the selected aptamer as a molecular recognition element could be developed in the innovative determinations of S. pyogenes.

A similarity measure method combining location feature for mammogram retrieval.

BACKGROUND: Breast cancer, the most common malignancy among women, has a high mortality rate in clinical practice. Early detection, diagnosis and treatment can reduce the mortalities of breast cancer greatly. The method of mammogram retrieval can help doctors to find the early breast lesions effectively and determine a reasonable feature set for image similarity measure. This will improve the accuracy effectively for mammogram retrieval. METHODS: This paper proposes a similarity measure method combining location feature for mammogram retrieval. Firstly, the images are pre-processed, the regions of interest are detected and the lesions are segmented in order to get the center point and radius of the lesions. Then, the method, namely Coherent Point Drift, is used for image registration with the pre-defined standard image. The center point and radius of the lesions after registration are obtained and the standard location feature of the image is constructed. This standard location feature can help figure out the location similarity between the image pair from the query image to each dataset image in the database. Next, the content feature of the image is extracted, including the Histogram of Oriented Gradients, the Edge Direction Histogram, the Local Binary Pattern and the Gray Level Histogram, and the image pair content similarity can be calculated using the Earth Mover's Distance. Finally, the location similarity and content similarity are fused to form the image fusion similarity, and the specified number of the most similar images can be returned according to it. RESULTS: In the experiment, 440 mammograms, which are from Chinese women in Northeast China, are used as the database. When fusing 40% lesion location feature similarity and 60% content feature similarity, the results have obvious advantages. At this time, precision is 0.83, recall is 0.76, comprehensive indicator is 0.79, satisfaction is 96.0%, mean is 4.2 and variance is 17.7. CONCLUSIONS: The results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval.