Visual detection of multiple antioxidants based on three chloroauric acid/Au-Ag nanocubes.

A colorimetric sensing method is described for discrimination of multiple antioxidants based on core-shell Au@Ag nanocubes (NCs). In order to extract data-rich colorimetric responses from the sensor array, three different concentrations of chloroaurate acid (HAuCl4) were employed as sensing elements. Interestingly, Au3+ ions can be reduced to different valence states (i.e., Au(0) and Au(I)) by different antioxidants, and thus effectively inhibit the oxidation etching process of Au@Ag NCs by Au(III) ions to varying extents, generating diverse colorimetric responses (color and absorbance). This enables identification of the six antioxidants at 10 nM via linear discriminant analysis (LDA) with relative standard deviation (RSD) of 2.52% (n = 3). The discrimination ability of the sensor array was further evaluated in antioxidant binary and multicomponent mixtures. Remarkably, identification of these six antioxidants spiked in urine was realized with 100% of accuracy. Schematic presentation of colorimetric assay for antioxidants based on three chloroauric acid/Au-Ag nanocubes.

First Report of Neopestalotiopsis rosae causing foliar and fruit spots on pomegranate in Florida.

Foliar and fruit spots were observed on pomegranate trees (Punica granatum L.) planted in orchards located at Balm and Zolfo Springs, FL, in 2019. Symptoms on leaves and fruits included dark brown to black irregular spots, ranging from 0.2 to 1.5 cm, with gray centers. Visible pycnidia were present in the center of the lesions. Leaves became chlorotic and prematurely dropped from the trees. In a disease survey performed on 24 pomegranate cultivars, all of the trees were infected and the disease severity ranged from 2 to 80%. The cultivars Bhagwa and Mridula were the most susceptible. Symptoms on the fruit were similar to those on the leaves; however incidence on the fruits was less than one percent. To isolate the pathogen, small pieces (5 mm2) of symptomatic leaves and fruits were excised from the area between diseased and healthy tissue. Excised tissue pieces were surface disinfested in 70% ethanol solution for 30 seconds, followed by 10% sodium hypochlorite (NaOCl) solution for 2 minutes, rinsed in sterilized distilled water three times, dried on a paper towel, placed onto potato dextrose agar and incubated at 25°C under 12-hour photoperiod for seven days. Fungal cultures formed white cottony aerial mycelium with undulated edges and abundant black pycnidia. Four-septate conidia were fusiform or clavate, straight or slightly curved measuring on average 29.1 (23.3- 34.4) µm long × 6.3 (5.1- 6.8) µm wide (n = 100). Conidia had three median cells which were dark brown, with a single basal hyaline appendage, 5.9 (4.1- 7.7) µm long, and two or four (usually three) apical hyaline appendages 20.3 (14.8- 24.5) µm long. Morphological features were consistent with those of the genus Neopestalotiopsis (Maharachchikumbura et al., 2014). Single-spore cultures were obtained and genomic DNA was extracted from seven isolates (one from fruit, GEV3523, and six from leaf, GEV3426 - GEV3431). Internal transcribed spacer (ITS) region, partial sequences of elongation factor (TEF), and ß-tubulin (TUB2) were amplified with the respective primer pairs ITS4 and ITS5, EF1-1567 and EF1-536, and Bt-2a and Bt-2b (Maharachchikumbura et al., 2014). BLAST analysis of the fruit isolate, GEV3523, showed homology of 100% for ITS, 100% for TEF and 99.8% for TUB2 to fungal pathogen Neopestalotiopsis rosae isolate CBS 101057 obtained from a rose plant in New Zealand (Accession Nos. MT587806, MT605118 and MT597152, respectively), whereas the six leaf isolates were 100% identical, GEV3426- GEV3431, showing homology of 100% for ITS, 99.8% for TEF and 98.4% for TUB2 to the same fungal species. Accession numbers: GEV3423 (MT587806, MT605118, MT597152) and GEV3427 (MT587804, MT605120, MT597150); for ITS, TEF and TUB2, respectively. Maximum likelihood phylogenetic analysis, based on the combined alignment of ITS, TEF, and TUB2, differentiated the leaf isolates from other species, suggesting a new Neopestalotiopsis cryptic species. Three-month-old rooted pomegranate cuttings, cultivars Bhagwa and Mridula, were inoculated with two isolates GEV3523 and GEV3527. Each cutting was treated as two distinct halves; one half was wounded by gently rubbing sterilized sand on the leaves to cause abrasions and the other half remained intact. Four cuttings from each pomegranate cultivar were spray inoculated with a spore suspension (105 conidia mL-1) and four control plants were sprayed with sterilized water. The experiment was performed once on each cultivar. Inoculated cuttings were covered with a transparent plastic bag to maintain 100% humidity and incubated for 36 hours at 26°C under 12-hour photoperiod in a growth chamber. Leaves began to show symptoms of small, irregular, brown spots with a gray center three days after inoculation. The pathogen started to produce pycnidia in the center of the lesions one week after inoculation. Symptoms developed on both wounded and unwounded inoculated leaves with 100% disease incidence on both pomegranate cultivars inoculated separately with GEV3527 and GEV3523. Disease severity on wounded leaves ranged from 10 - 25% for 'Bhagwa' and 30 - 60% for 'Mridula' and on intact leaves from 2 - 5% and 5 - 12%, respectively. Furthermore, the fruit isolate, GEV3523, caused an average disease severity of 8 and 3.5 %, on wounded leaves of 'Bhagwa' and 'Mridula', respectively, whereas the leaf isolate GEV3427 caused 19 and 45% disease severity, respectively. No symptoms were observed on control plants and no fungal growth was observed on the re-isolations performed on the control plants. Neopestalatiopsis spp. were re-isolated from leaves fulfilling Koch's postulates. To our knowledge, this is the first report of Neopestalotiopsis rosae infecting pomegranate in Florida as well as in the United States. This pathogen could represent a threat to pomegranate production in Florida due to its ability to cause premature defoliation.

Equivalent Circuit Model of Low-Frequency Magnetoelectric Effect in Disk-Type Terfenol-D/PZT Laminate Composites Considering a New Interface Coupling Factor.

This paper describes the modeling of magnetoelectric (ME) effects for disk-type Terfenol-D (Tb0.3Dy0.7Fe1.92)/PZT (Pb(Zr,Ti)O3) laminate composite at low frequency by combining the advantages of the static elastic model and the equivalent circuit model, aiming at providing a guidance for the design and fabrication of the sensors based on magnetoelectric laminate composite. Considering that the strains of the magnetostrictive and piezoelectric layers are not equal in actual operating due to the epoxy resin adhesive bonding condition, the magnetostrictive and piezoelectric layers were first modeled through the equation of motion separately, and then coupled together with a new interface coupling factor kc, which physically reflects the strain transfer between the phases. Furthermore, a theoretical expression containing kc for the transverse ME voltage coefficient αv and the optimum thickness ratio noptim to which the maximum ME voltage coefficient corresponds were derived from the modified equivalent circuit of ME laminate, where the interface coupling factor acted as an ideal transformer. To explore the influence of mechanical load on the interface coupling factor kc, two sets of weights, i.e., 100 g and 500 g, were placed on the top of the ME laminates with the same thickness ratio n in the sample fabrication. A total of 22 T-T mode disk-type ME laminate samples with different configurations were fabricated. The interface coupling factors determined from the measured αv and the DC bias magnetic field Hbias were 0.11 for 500 g pre-mechanical load and 0.08 for 100 g pre-mechanical load. Furthermore, the measured optimum thickness ratios were 0.61 for kc = 0.11 and 0.56 for kc = 0.08. Both the theoretical ME voltage coefficient αv and optimum thickness ratio noptim containing kc agreed well with the measured data, verifying the reasonability and correctness for the introduction of kc in the modified equivalent circuit model.

[Identification of transmission fluid based on NIR spectroscopy by combining sparse representation method with manifold learning].

An identification method based on sparse representation (SR) combined with autoencoder network (AN) manifold learning was proposed for discriminating the varieties of transmission fluid by using near infrared (NIR) spectroscopy technology. NIR transmittance spectra from 600 to 1 800 nm were collected from 300 transmission fluid samples of five varieties (each variety consists of 60 samples). For each variety, 30 samples were randomly selected as training set (totally 150 samples), and the rest 30 ones as testing set (totally 150 samples). Autoencoder network manifold learning was applied to obtain the characteristic information in the 600-1800 nm spectra and the number of characteristics was reduced to 10. Principal component analysis (PCA) was applied to extract several relevant variables to represent the useful information of spectral variables. All of the training samples made up a data dictionary of the sparse representation (SR). Then the transmission fluid variety identification problem was reduced to the problem as how to represent the testing samples from the data dictionary (training samples data). The identification result thus could be achieved by solving the L-1 norm-based optimization problem. We compared the effectiveness of the proposed method with that of linear discriminant analysis (LDA), least squares support vector machine (LS-SVM) and sparse representation (SR) using the relevant variables selected by principal component analysis (PCA) and AN. Experimental results demonstrated that the overall identification accuracy of the proposed method for the five transmission fluid varieties was 97.33% by AN-SR, which was significantly higher than that of LDA or LS-SVM. Therefore, the proposed method can provide a new effective method for identification of transmission fluid variety.

Spatial differences and underlying mechanisms in electronic word of mouth in the foodservice industry: A case of Sanya, China.

Studying the electronic word-of-mouth (eWOM) in the foodservice industry can not only provide guidance for merchants, but also spatially optimize the urban foodservice industry, restaurants' location selection, and customers' purchasing decisions. In this study, taking Sanya city as the research object, using big data crawling technology to collect the directory and their attribute information of 2107 restaurants with more than 100 reviews. Kernel density analysis, grid analysis and the geographically weighted regression (GWR) model were applied to reveal the distribution characteristics and influencing factors of eWOM in the foodservice industry in Sanya, China. The main results are as follows. The foodservice industry in Sanya extends along the southern coastline and is characterized by little dispersion and agglomeration at the macro level. The overall eWOM score of the foodservice industry is low. Market popularity, restaurant rating, transportation conditions, and commercial development all have a positive impact on the eWOM of the foodservice industry. Population and price have both positive and negative effects and the public services has a nonsignificant impact on the eWOM. This study not only improves the theoretical understanding of the foodservice industry, but also provides a general reference for its development in other industries and cities.

Plug-and-play protein biosensors using aptamer-regulated in vitro transcription.

Molecular biosensors that accurately measure protein concentrations without external equipment are critical for solving numerous problems in diagnostics and therapeutics. Modularly transducing the binding of protein antibodies, protein switches or aptamers into a useful output remains challenging. Here, we develop a biosensing platform based on aptamer-regulated transcription in which aptamers integrated into transcription templates serve as inputs to molecular circuits that can be programmed to a produce a variety of responses. We modularly design molecular biosensors using this platform by swapping aptamer domains for specific proteins and downstream domains that encode different RNA transcripts. By coupling aptamer-regulated transcription with diverse transduction circuits, we rapidly construct analog protein biosensors and digital protein biosensors with detection ranges that can be tuned over two orders of magnitude and can exceed the binding affinity of the aptamer. Aptamer-regulated transcription is a straightforward and inexpensive approach for constructing programmable protein biosensors that could have diverse applications in research and biotechnology.

Plug-and-play protein biosensors using aptamer-regulated in vitro transcription.

Molecular biosensors that accurately measure protein concentrations without external equipment are critical for solving numerous problems in diagnostics and therapeutics. Modularly transducing the binding of protein antibodies, protein switches or aptamers into a useful output remains challenging. Here, we develop a biosensing platform based on aptamer-regulated transcription in which aptamers integrated into transcription templates serve as inputs to molecular circuits that can be programmed to a produce a variety of responses. We modularly design molecular biosensors using this platform by swapping aptamer domains for specific proteins and downstream domains that encode different RNA transcripts. By coupling aptamer-regulated transcription with diverse transduction circuits, we rapidly construct analog protein biosensors or digital protein biosensors with detection ranges that can be tuned over two orders of magnitude. Aptamer-regulated transcription is a straightforward and inexpensive approach for constructing programmable protein biosensors suitable for diverse research and diagnostic applications.

Integrated volatile metabolomic and transcriptomic analysis provides insights into the regulation of floral scents between two contrasting varieties of Lonicera japonica.

Lonicera japonica Thunb., belonging to the Caprifoliaceae family, is an important traditional Chinese medicinal plant. The L. japonica flower (LJF) is widely used in medicine, cosmetics, drinks, and food due to its medicinal and sweet-smelling properties. Considerable efforts have been devoted to investigating the pharmacological activities of LJF; however, the regulatory mechanism of the floral scents remains unknown. We previously selected and bred an elite variety of L. japonica var. chinensis Thunb. called 'Yujin2', which has a strong aroma and is used in functional drinks and cosmetics. In order to reveal the regulatory mechanism of the floral scents of LJF, volatile metabolomic and transcriptomic analyses of the LJF at the silver flowering stage of 'Yujin2' (strong aroma) and 'Fengjin1' (bland odor) were performed. Our results revealed that a total of 153 metabolites and 9,523 genes were differentially regulated in LJF between 'Yujin2' and 'Fengjin1'. The integrated analysis of omics data indicated that the biosynthetic pathways of terpenoids (i.e., monoterpenoids, including geraniol and alpha-terpineol; sesquiterpenoids, including farnesol, farnesal, and alpha-farnesene; triterpenoid squalene), tryptophan and its derivatives (methyl anthranilate), and fatty acid derivatives, were major contributors to the stronger aroma of 'Yujin2' compared to 'Fengjin1'. Moreover, several genes involved in the terpenoid biosynthetic pathway were characterized using quantitative real-time PCR. These results provide insights into the metabolic mechanisms and molecular basis of floral scents in LJF, enabling future screening of genes related to the floral scent regulation, such as alpha-terpineol synthase, geranylgeranyl diphosphate synthase, farnesyl pyrophosphate synthase, anthranilate synthase, as well as transcription factors such as MYB, WRKY, and LFY. The knowledge from this study will facilitate the breeding of quality-improved and more fragrant variety of L. japonica for ornamental purpose and functional beverages and cosmetics.

Use of Anthropometric Measures of Obesity to Predict Diabetic Retinopathy in Patients with Type 2 Diabetes in China.

PURPOSE: Obesity is an established risk factor for type 2 diabetes (T2D). Diabetic retinopathy (DR) is a major microvascular complication of T2D. In this cross-sectional study, we investigated the association between various anthropometric indices of obesity and DR. PATIENTS AND METHODS: A representative sample of 1952 patients with T2D participated in this cross-sectional study conducted in Shanghai, China. Anthropometric measures of obesity including weight, height, waist circumference, hip circumference, body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were evaluated. The association between WHtR, WHR, and BMI and the presence of DR was examined with logistic regression models. RESULTS: The prevalence of DR was higher in T2D patients with high WHtR compared to those with normal WHtR (p<0.05). A higher BMI was associated with elevated risk of DR (model 1, p=0.034; model 2, p=0.036). WHR was unrelated to the occurrence of DR (p>0.05). CONCLUSION: WHtR and BMI but not WHR are risk factors for DR in obese patients with T2D. Patients with high WHtR and BMI should be closely monitored to prevent the development of DR.

The influence of gut microbiome on bone health and related dietary strategies against bone dysfunctions.

The link between the gut microbiome and bone health has begun to attract widespread interest in recent years. The gut microbiome are vital in many diseases involving bone loss. Probiotics, prebiotics, and dietary supplements have been suggested to protect bone health by altering the composition of the gut microbiota. Notably, studying the relationship between the gut microbiome and bone health can provide a basis for the prevention and treatment of bone diseases. This review focuses on the link between the gut microbiome and bone diseases, exploring current knowledge of the mechanisms by which gut bacteria affect bone health. In addition, the influences of dietary supplements on the interactions between the gut microbiome and bone health are discussed. This knowledge will promote new ideas for gut microbiota-mediated dietary interventions in patients with bone diseases.

Three types of passivators on the stabilization of exogenous lead-contaminated soil with different particle sizes.

Study on the form partitioning and content of heavy metals in soil particles with different sizes is crucial for preventing and controlling heavy metals pollution, but few studies regard soil contaminated by heavy metals as a homogeneous body. In this study (Fig. 1), goat manure, lime and phosphate were used to stabilize exogenous lead (Pb). These soil passivators' differential effects on total Pb and Pb with different chemical forms in soil particles of different sizes as well as Pb immobilization in soil were investigated. By passivation experiment in laboratory for 45 days, the passivation effect of the single and combined application treatments on exogenous Pb and partitioning characteristics were analyzed and compared. The characterization method of fine sand microstructure and mineral composition analysis was used. The results showed that the single application of P5 and combined application of LP5 had optimum passivation efficiency. The content of DTPA-Pb was reduced with P5 by 65.27% and the percentage of available Pb decreased significantly in soil particles of the four sizes. The content of TCLP-Pb and available Pb (weak acid extraction and reducible Pb) significantly decreased by 71.60 and 25.12% respectively after the application of LP5 in the original soil. Furthermore, most of the total Pb was enriched in coarse sand and clay, while its content was lower in fine sand and silt. The combined application treatment of GL5 significantly increased the content of weak acid extractable and reducible Pb in fine sand, silty sand and clay. Through SEM and XRD analysis, it was found that the diffraction peak of P5 treatment groups might be related to the formation of insoluble Pb that contained compounds, which were mainly mineral components, including quartz, feldspar and mica, and LP showed a big potential in the study on passivation of heavy metal Pb-contaminated soil in the natural environment. In conclusion, further studies on the different dosage and metal-contamination levels as well as different combination forms of passivators should be considered under natural conditions, the selection of suitable passivators according to soil texture is of great significance for remediation of Pb-contaminated soil.

Physiological Characteristics of Lactobacillus casei Strains and Their Alleviation Effects against Inflammatory Bowel Disease.

Lactobacillus casei, one of the most widely used probiotics, has been reported to alleviate multiple diseases. However, the effects of this species on intestinal diseases are strain-specific. Here, we aimed to screen L. casei strains with inflammatory bowel disease (IBD)-alleviating effects based on in vitro physiological characteristics. Therefore, the physiological characteristics of 29 L. casei strains were determined, including gastrointestinal transit tolerance, oligosaccharide fermentation, HT-29 cell adhesion, generation time, exopolysaccharide production, acetic acid production, and conjugated linoleic acid synthesis. The effects of five candidate strains on mice with induced colitis were also evaluated. The results showed that among all tested L. casei strains, only Lactobacillus casei M2S01 effectively relieved colitis. This strain recovered body weight, restored disease activity index score, and promoted anti-inflammatory cytokine expression. Gut microbiota sequencing showed that L. casei M2S01 restored a healthy gut microbiome composition. The western blotting showed that the alleviating effects of L. casei M2S01 on IBD were related to the inhibition of the NF-κB pathway. A good gastrointestinal tolerance ability may be one of the prerequisites for the IBDalleviating effects of L. casei. Our results verified the efficacy of L. casei in alleviating IBD and lay the foundation for the rapid screening of L. casei strain with IBD-alleviating effects.

The role of MUC2 mucin in intestinal homeostasis and the impact of dietary components on MUC2 expression.

MUC2 mucin is an important secretory protein found in the human gut. Recent studies indicated that MUC2 mucin plays a role in the protection of gut barrier, the regulation of microbiome homeostasis and the prevention of diseases. In this review, the physiological properties of MUC2 mucin and its interactions with the intestinal microbiome are firstly discussed. Its roles in intestinal diseases including inflammatory bowel disease, colorectal cancer and parasitic infections are concluded. We also reviewed dietary components known to have modulative effects on MUC2 mucin expression, such as polysaccharides, amino acids and polyphenols.

Prevalence of Diabetes, Prediabetes, and Associated Factors in an Adult Chinese Population: Baseline of a Prediabetes Cohort Study.

PURPOSE: To report baseline information of a prediabetes mellitus (PDM) cohort with the aim of exploring related factors for the progression of PDM and its complications. METHODS: This study is an exploratory and cross-sectional analysis of the baseline data from a cohort study. Residents aged 18 to 70 years from Houtang Village, Nanyue Town, Yueqing City, Zhejiang Province, China, were invited to participate between October 1, 2018 and July 1, 2019. Blood samples were collected for analysis, and questionnaire interviews were conducted to assess behavioral characteristics. The study participants were divided into DM, PDM, and normal groups for comparisons based on their blood work, and multiple multinomial logistic regression analyses were used to assess the risk factors for DM and PDM. RESULTS: Data from 406 participants were used in the baseline analysis, with a mean age of 51.2 ± 11.0 years and 160 (33.0%) males. The number of participants in the DM, PDM, and normal group was 58 (14.3%), 166 (40.9%), and 182 (44.8%), respectively. The prevalence of DM was 14.3%, and the prevalence of PDM was 40.9%. The regression analysis showed that older age (relative risk ratio (RRR) = 1.06; 95% CI, 1.01-1.11, P = 0.018), higher systolic blood pressure (RRR = 1.04; 95% CI, 1.004-1.08, P = 0.030), higher BMI (RRR = 1.20; 95% CI, 1.06-3.06, P = 0.004), higher TG (RRR = 1.80; 95% CI, 1.06-3.06, P = 0.029), and higher WBC count (RRR = 1.32; 95% CI, 1.07-1.64, P = 0.010) were significantly associated with a higher risk of DM. Meanwhile, higher systolic blood pressure (RRR = 1.03; 95% CI, 1.004-1.06, P = 0.025) was the only factor significantly associated with a higher risk of PDM. CONCLUSION: The prevalence of DM and PDM is relatively high in this wealthy East China village population. Many modifiable risk factors exist for DM and PDM, which will be closely monitored during our longitudinal observation.

Early Detection of Magnaporthe oryzae-Infected Barley Leaves and Lesion Visualization Based on Hyperspectral Imaging.

Early detection of foliar diseases is vital to the management of plant disease, since these pathogens hinder crop productivity worldwide. This research applied hyperspectral imaging (HSI) technology to early detection of Magnaporthe oryzae-infected barley leaves at four consecutive infection periods. The averaged spectra were used to identify the infection periods of the samples. Additionally, principal component analysis (PCA), spectral unmixing analysis and spectral angle mapping (SAM) were adopted to locate the lesion sites. The results indicated that linear discriminant analysis (LDA) coupled with competitive adaptive reweighted sampling (CARS) achieved over 98% classification accuracy and successfully identified the infected samples 24 h after inoculation. Importantly, spectral unmixing analysis was able to reveal the lesion regions within 24 h after inoculation, and the resulting visualization of host-pathogen interactions was interpretable. Therefore, HSI combined with analysis by those methods would be a promising tool for both early infection period identification and lesion visualization, which would greatly improve plant disease management.