The Odorant-Binding Protein Gene obp11 Shows Different Spatiotemporal Roles in the Olfactory System of Apis mellifera ligustica and Apis cerana cerana

Odorant-binding proteins participate in the olfactory system of the honeybee. Apis mellifera ligustica and Apis cerana cerana are species of honeybee that have different biologic functions. The two species have diversified olfactory systems, with A. cerana displaying sensitive olfactory involvement in collecting nectar and pollen from small plants; and A. mellifera collecting from large nectariferous plants. We hypothesized that, given this difference in biologic activity, the gene obp11 of A. mellifera and A. cerana may show different olfactory expression patterns. We cloned and sequenced the obp11 genes from A. mellifera (Amobp11) and A. cerana (Acobp11). Using quantitative real-time PCR, we demonstrated that nurse workers, which have the highest olfactory sensitivity in the A. mellifera hive, have the highest expression of Amobp11; whereas 1-day-emerged  workers, which have lowest olfactory sensitivity, have correspondingly low expression. However, the highest expression of Acobp11 is observed for foragers, which display the highest olfactory sensitivity in the A. cerana population. The OBP11 protein from the two species is highly conserved, with an apparent molecular weight and predicted extracellular localization that is similar to other OBP proteins. The expression of the obp11 gene in A. mellifera and A. cerana correlates with the different roles of the olfactory system for the two different species. These findings support the critical role of odorant-binding proteins in the Apis olfactory syste

Behavioral Responses of Apis mellifera Adult Workers to Odors from Healthy Brood and Diseased Brood

Studies of adult workers’ responses to infected brood were undertaken to isolate discrete volatile compounds that elicited honeybee hygienic behavior. Using a freeze-killed brood assay, we determined that in healthy colonies adult workers recognized and emptied infected cells with a 95% clearance rate. SPME-GC-MS results emptied >95% infected cells indicated differences in the composition and relative content of volatile compounds released by healthy and diseased brood. Additionally, we determined that the main volatile compound released from the pathogen Ascosphaera apis was phenethyl alcohol. The Y-tube olfactometer indicated that 10- to 20-day-old workers of healthy colonies, but only 15-day-old workers of diseased colonies, were significantly sensitive to differences in characteristic volatile compounds. This information could facilitate honey bee selection based on mechanisms that contribute to chalkbrood disease tolerance

Effects of Short-Term Dietary Fiber Intervention on Gut Microbiota in Young Healthy People

Gut microbiota are critical to many aspects of human health including immune and metabolic health. Long-term diet influences the community structure and activity of the trillions of microorganisms residing in the human gut, but it remains unclear how the human gut microbiome responds to short-term intervention with dietary fiber. This study explored the effects of mixed dietary fibers on gut microbiota in young, healthy people. Twelve healthy, young adults participated in a randomized, crossover trial comparing the effects of polyglucan, inulin and resistant malt dextrin on gut microbiota composition and bacterial abundances. During the study, the subjects followed their normal diets without any constraints. Microbial community profiles were determined by absolute quantification 16S rRNA gene amplicon sequencing. Mixed model analysis did not reveal an effect of dietary intervention on microbial community structure. At the genus level, dietary fiber intervention for 4 days significantly promoted the growth of Alloprevotella, Parabacteroides and Parasutterella and inhibited the growth of Adlercreutzia, Anaerovorax, Enterococcus, Intestinibacter and Ruminococcus 2 compared with the baseline. Addition of whey albumen powder for 4 days promoted the growth of Corynebacterium, Collinsella, Olsenella and Lactococcus but interfered with the growth of Megasphaera. Our results should be corroborated by randomized clinical trials with large sample size

Using Multiple Statistical Methods to Derive Dietary Patterns Associated with Cardiovascular Disease in Patients with Type 2 Diabetes: Results from a Multiethnic Population-Based Study

Background. There are few reports on the relationship between dietary patterns and cardiovascular disease (CVD) risk in patients with type 2 diabetes (T2D). This study aimed to explore relationships between dietary patterns and CVD risk in the T2D population using multiple statistical analysis methods. Methods. A total of 2,984 patients with T2D from the Xinjiang Multi-Ethnic Cohort, 555 of whom were suffering from CVD, were enrolled in this study. Participants’ dietary intake was measured by the semiquantitative food frequency questionnaire (FFQ). Three statistical methods were used to construct dietary patterns, including principal component analysis (PCA) method, reduced-rank regressions (RRR) method, and partial least-squares regression (PLS) method. Then, the association between dietary patterns and CVD risk in T2D patients was analyzed by logistic regression. After excluding participants with CVD, the associations between dietary patterns and 10-year CVD risk scores were subsequently evaluated to reduce reverse causality. Results. In this study, four dietary patterns were identified by three methods. Adjustment for confounding factors, subjects with the highest scores on the “high-protein and high-carbohydrate” patterns derived from PCA, RRR, and PLS had higher odds of CVD than those with the lowest scores (OR: 2.89, 95% CI: 2.11–3.96, P t r e n d < 0.001 ; OR: 2.96, 95% CI: 2.17–4.03, P t r e n d < 0.001 ; OR: 2.01, 95% CI: 1.50–2.70, P t r e n d < 0.001 , respectively). However, the dietary pattern of PCA-prudent was not significantly related to the odds of having CVD in T2D patients (adjusted ORQ4vsQ1: 0.93, 95% CI: 0.70–1.24, P t r e n d = 0.474 ). Interestingly, we also found significant associations between “high-protein and high-carbohydrate” patterns and the elevated predicted 10-year CVD risk in T2D patients (all P t r e n d < 0.05 ). Conclusion. The positive correlation between “high-protein and high-carbohydrate” patterns and CVD risk in T2D patients was robust across all three data-driven approaches. These findings may have public health significance, encouraging an emphasis on food choices in the usual diet and promoting nutritional interventions for patients with T2D to prevent CVD

Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study

Background: Waist circumference (WC), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) are considered surrogate indicators of abdominal fat deposition, but the longitudinal association of these indices with cardiovascular (CV) events in adults with type 2 diabetes (T2D) remains unclear. Our study aimed to examine the associations between abdominal obesity indices and incident CV events among people with T2D and to compare their predictive performance in risk assessment. Methods: The present study included 2328 individuals with T2D from the Xinjiang Multi-Ethnic Cohort. Multivariable Cox regression analyses were applied to assess the associations between abdominal obesity indices and CV events. Harrell's concordance statistic (C-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were utilized to evaluate the predictive performance of each abdominal obesity index. Results: At a median follow-up period of 59 months, 289 participants experienced CV events. After multivariable adjustment, each 1-SD increase in WC, VAI, LAP, and CVAI was associated with a higher risk of CV events in people with T2D, with adjusted hazard ratios (HRs) being 1.57 [95% CI (confidence interval): 1.39–1.78], 1.11 (95% CI 1.06–1.16), 1.46 (95% CI 1.36–1.57), and 1.78 (95% CI 1.57–2.01), respectively. In subgroup analyses, these positive associations appeared to be stronger among participants with body mass index (BMI) < 25 kg/m2 compared to overweight/obese participants. As for the predictive performance, CVAI had the largest C-statistic (0.700, 95% CI 0.672–0.728) compared to VAI, LAP, WC, and BMI (C-statistic: 0.535 to 0.670, all P for comparison < 0.05). When the abdominal obesity index was added to the basic risk model, the CVAI index also showed the greatest incremental risk stratification (C-statistic: 0.751 vs. 0.701, P < 0.001; IDI: 4.3%, P < 0.001; NRI: 26.6%, P < 0.001). Conclusions: This study provided additional evidence that all abdominal obesity indices were associated with the risk of CV events and highlighted that CVAI might be a valuable abdominal obesity indicator for identifying the high risk of CV events in Chinese populations with T2D. These results suggest that proactive assessment of abdominal obesity could be helpful for the effective clinical management of the diabetic population

Graphene/silicon heterojunction for reconfigurable phase-relevant activation function in coherent optical neural networks

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1 V (0.5 mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200 mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits

Highly Sensitive Determination of Hydrogen Peroxide and Glucose by Fluorescence Correlation Spectroscopy

BACKGROUND: Because H(2)O(2) is generated by various oxidase-catalyzed reactions, a highly sensitive determination method of H(2)O(2) is applicable to measurements of low levels of various oxidases and their substrates such as glucose, lactate, glutamate, urate, xanthine, choline, cholesterol and NADPH. We propose herein a new, highly sensitive method for the measurement of H(2)O(2) and glucose using fluorescence correlation spectroscopy (FCS). METHODOLOGY/PRINCIPAL FINDINGS: FCS has the advantage of allowing us to determine the number of fluorescent molecules. FCS measures the fluctuations in fluorescence intensity caused by fluorescent probe movement in a small light cavity with a defined volume generated by confocal illumination. We thus developed a highly sensitive determination system of H(2)O(2) by FCS, where horseradish peroxidase (HRP) catalyzes the formation of a covalent bond between fluorescent molecules and proteins in the presence of H(2)O(2). Our developed system gave a linear calibration curve for H(2)O(2) in the range of 28 to 300 nM with the detection limit of 8 nM. In addition, by coupling with glucose oxidase (GOD)-catalyzed reaction, the method allows to measure glucose in the range of 80 nM to 1.5 µM with detection limit of 24 nM. The method was applicable to the assay of glucose in blood plasma. The mean concentration of glucose in normal human blood plasma was determined to be 4.9 mM. CONCLUSIONS/SIGNIFICANCE: In comparison with commercial available methods, the detection limit and the minimum value of determination for glucose are at least 2 orders of magnitude more sensitive in our system. Such a highly sensitive method leads the fact that only a very small amount of plasma (20 nL) is needed for the determination of glucose concentration in blood plasma