Cucurbit[n]uril-Immobilized Sensor Arrays for Indicator-Displacement Assays of Small Bioactive Metabolites

The patterned immobilization of chemosensors into nano/microarrays has often boosted utilization in diagnostics and environmental sensing applications. While this is a standard approach for biosensors, e.g., with antibodies, other proteins, and DNA, arraying is not yet adopted widely for supramolecular chemosensors which are still predominantly used in solution systems. Here we introduce the patterned immobilization of cucurbit[n]urils (CBn) into multiplexed microarrays and elucidate their prospects for the advancement of surface-bound indicator-displacement assays to detect small molecule analytes. The microarrays were generated by microchannel cantilever spotting of functionalized CBn and subsequent self-assembly of the corresponding indicator dyes from solution. Enhanced sensitivity of surface-bound microarrays was established in demonstrations with small bioactive metabolites (spermine, amantadine, and cadaverine) compared to bulk assays. Furthermore, the integration of the CBn/indicator microarrays into microfluidic channels provides an efficient route for real-time monitoring of the sensing process, allows easier handling, and reduces need for analyte volume. The concept was further extended to differential sensing of analytes on diplex or multiplex CBn/indicator microarrays, opening up a route for multicomponent sensing of small molecule analytes in complex liquids

Binding affinity-based intracellular drug detection enabled by a unimolecular cucurbit[7]uril-dye conjugate

Label-free fluorescence-based chemosensing has been increasingly brought into focus due to its simplicity and high sensitivity for intracellular monitoring of molecules. Currently used methods, such as conventional indicator displacement assays (IDAs), pose limitations related to dissociation upon dilution, random diffusion of the released indicators, and high sensitivity to interference by agents from the ambient cellular environment (e.g., salts, enzymes, and proteins). Herein we report a potentially widely applicable strategy to overcome the limitations of conventional IDAs by employing a macrocyclic cucurbit[7]uril (CB7) host covalently coupled to a nitrobenzoxadiazole (NBD) fluorescent dye (CB7-NBD conjugate). As a proof of concept, we demonstrated that the CB7-NBD unimolecular conjugate responded to various target analytes even in the complex live cell system. Moreover, the sensing system was compatible with fluorescence imaging, fluorescence-assisted cell sorting (FACS), and fluorescence spectrometry with a microplate reader. These experiments demonstrated an application of covalently bound unimolecular CB7-NBD conjugate as a sensor for detecting diverse analytes in the intracellular compartment of live cells

Breeding response of transcript profiling in developing seeds of Brassica napus

<p>Abstract</p> <p>Background</p> <p>The upgrading of rapeseed cultivars has resulted in a substantial improvement in yield and quality in China over the past 30 years. With the selective pressure against fatty acid composition and oil content, high erucic acid- and low oil-content cultivars have been replaced by low erucic acid- and high oil-content cultivars. The high erucic acid cultivar Zhongyou 821 and its descendent, low erucic acid cultivar Zhongshuang 9, are representatives of two generations of the most outstanding Chinese rapeseed cultivars (<it>B. napus</it>) developed the past 2 decades. This paper compares the transcriptional profiles of Zhongshuang 9 and Zhongyou 821 for 32 genes that are principally involved in lipid biosynthesis during seed development in order to elucidate how the transcriptional profiles of these genes responded to quality improvement over the past 20 years.</p> <p>Results</p> <p>Comparison of the cultivar Zhongyou 821 with its descendent, Zhongshuang 9, shows that the transcriptional levels of seven of the 32 genes were upregulated by 30% to 109%, including <it>FAD3</it>, <it>ACCase, FAE1</it>, <it>GKTP</it>, <it>Caleosin</it>, <it>GAPDH</it>, and <it>PEPC</it>. Of the 32 genes, 10 (<it>KAS3, β-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, α-CT </it>and <it>SUC1</it>) were downregulated by at least 20% and most by 50%. The <it>Napin </it>gene alone accounted for over 75% of total transcription from all 32 genes assessed in both cultivars. Most of the genes showed significant correlation with fatty acid accumulation, but the correlation in ZS9 was significantly different from that in ZY821. Higher <it>KCR2 </it>activity is associated with higher C16:0, C18:0, and C18:2 in both cultivars, lower C22:1 and total fatty acid content in ZY821, and lower 18:1 in ZS9.</p> <p>Conclusion</p> <p>This paper illustrates the response of the transcription levels of 32 genes to breeding in developing rapeseed seeds. Both cultivars showed similar transcription profiles, with the <it>Napin </it>gene predominantly transcribed. Selective pressure for zero erucic acid, low glucosinolate, high oleic acid and high oil content, as well as high yield, resulted in higher <it>FAD3</it>, <it>ACCase, FAE1</it>, <it>GKTP</it>, <it>Caleosin</it>, <it>GAPDH</it>, and <it>PEPC </it>expression levels and lower <it>KAS3, β-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, α-CT </it>and <it>SUC1 </it>expression levels. It also resulted in altered relationships between these genes during storage accumulation in seed development.</p

Further Dimensions for Sensing in Biofluids: Distinguishing Bioorganic Analytes by the Salt-Induced Adaptation of a Cucurbit[7]uril-Based Chemosensor

Insufficient binding selectivity of chemosensors often renders biorelevant metabolites indistinguishable by the widely used indicator displacement assay. Array-based chemosensing methods are a common workaround but require additional effort for synthesizing a chemosensor library and setting up a sensing array. Moreover, it can be very challenging to tune the inherent binding preference of macrocyclic systems such as cucurbit[n]urils (CBn) by synthetic means. Using a novel cucurbit[7]uril-dye conjugate that undergoes salt-induced adaptation, we now succeeded in distinguishing 14 bioorganic analytes from each other through the facile stepwise addition of salts. The salt-specific concentration-resolved emission provides additional information about the system at a low synthetic effort. We present a data-driven approach to translate the human-visible curve differences into intuitive pairwise difference measures. Ion mobility experiments combined with density functional theory calculations gave further insights into the binding mechanism and uncovered an unprecedented ternary complex geometry for CB7. TThis work introduces the non-selectively binding, salt-adaptive cucurbit[n]uril system for sensing applications in biofluids such as urine, saliva, and blood serum

Using a deep-learning approach to infer and forecast the Indonesian Throughflow transport from sea surface height

The Indonesian Throughflow (ITF) connects the tropical Pacific and Indian Oceans and is critical to the regional and global climate systems. Previous research indicates that the Indo-Pacific pressure gradient is a major driver of the ITF, implying the possibility of forecasting ITF transport by the sea surface height (SSH) of the Indo-Pacific Ocean. Here we used a deep-learning approach with the convolutional neural network (CNN) model to reproduce ITF transport. The CNN model was trained with a random selection of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations and verified with residual components of the CMIP6 simulations. A test of the training results showed that the CNN model with SSH is able to reproduce approximately 90% of the total variance of ITF transport. The CNN model with CMIP6 was then transformed to the Simple Ocean Data Assimilation (SODA) dataset and this transformed model reproduced approximately 80% of the total variance of ITF transport in the SODA. A time series of ITF transport, verified by Monitoring the ITF (MITF) and International Nusantara Stratification and Transport (INSTANT) measurements of ITF, was then produced by the model using satellite observations from 1993 to 2021. We discovered that the CNN model can make a valid prediction with a lead time of 7 months, implying that the ITF transport can be predicted using the deep-learning approach with SSH data

Influence of body mass index and waist–hip ratio on male semen parameters in infertile men in the real world: a retrospective study

BackgroundIt is suggested that body mass index (BMI) can affect male semen quality; however, the results remain controversial. In addition, most studies have focused on the effect of obesity on semen quality. Evidence on the relationship of underweight or waist-hip ratio (WHR) with semen quality is rare. This study aimed to assess the association of BMI and WHR with semen quality.MethodsData, including BMI and WHR, was collected from 715.00 men who underwent a fertility evaluation. BMI (kg/m2) was categorized as &lt;18.50 (underweight), 18.50–24.90 (normal), 25.00–27.90 (overweight), and ≥28.00 (obese) kg/m2 for analysis. WHR was categorized as &lt;0.81 (normal) and ≥0.81 (high). Semen volume, sperm concentration, progressive motility, and total motile sperm count were detected by experienced clinical technicians.ResultsSpearman’s correlation showed that BMI was weakly associated with sperm progressive motility (r = 0.076, P &lt; 0.05), while WHR showed no relationship with semen parameters. The azoospermia rate was significantly higher (33.33% vs. 2.10%, P &lt; 0.001) and the sperm concentration was lower (P &lt; 0.05) in the underweight group. The nonlinear correlation analysis showed that BMI was negatively associated with sperm concentration while BMI was more than 22.40 kg/m2 (P &lt; 0.05), while WHR was negatively related to sperm progressive motility within 0.82 to 0.89 (P &lt; 0.05). Furthermore, the multivariate logistic analysis showed that follicular stimulating hormone (FSH) was an independent risk factor for normal sperm concentration (odds ratio [OR]: 0.791, P = 0.001) and morphology (OR: 0.821, P = 0.002), BMI was an independent risk factor for normal sperm progressive motility, and testosterone was an independent risk factor for sperm morphology (OR: 0.908, P = 0.023).ConclusionBMI and WHR were significantly associated with semen parameters, while BMI was an independent risk factor for normal sperm progressive motility. Reproductive hormones, including FSH and testosterone, had a significant influence on sperm concentration and sperm morphology