An optimized microRNA detection platform based on PAM formation-regulated CRISPR/Cas12a activation.

MicroRNAs (miRNAs) have emerged as biomarkers for the diagnosis and prognosis of various diseases, such as cancer. Recent advancements in CRISPR/Cas12a-based biosensors in combination with hybridization chain reaction (HCR) make it a promising approach for miRNA detection. To increase the compatibility of HCR and CRISPR/Cas12a, we compared two design strategies of hairpin DNA in HCR. The results showed that different arrangements of the protospacer sequence and protospacer adjacent motif (PAM) in the hairpin DNA could affect the sensing performance. The "PAM Formation" strategy, by which the duplex PAM sites are absent in the hairpin DNA and present in the long duplex DNA after HCR, exhibited advantages in detection sensitivity. By optimizing the probe sequences and reaction conditions, we developed a miRNA detection platform. With the same crRNA, this platform enables the identification of different miRNAs by simply replacing the loop region of the target recognition probe. In addition, the proposed platform can detect single-stranded DNA and distinguishing single or multiple base mutations in the target strand. The application of discriminating the target miRNA expression levels from different cell lines validated the reliability and practicability of the sensor platform, indicating its potential applications in early clinical accurate diagnosis of cancers.

SPSI: A Novel Composite Index for Estimating Panicle Number in Winter Wheat before Heading from UAV Multispectral Imagery.

Rapid and accurate estimation of panicle number per unit ground area (PNPA) in winter wheat before heading is crucial to evaluate yield potential and regulate crop growth for increasing the final yield. The accuracies of existing methods were low for estimating PNPA with remotely sensed data acquired before heading since the spectral saturation and background effects were ignored. This study proposed a spectral-textural PNPA sensitive index (SPSI) from unmanned aerial vehicle (UAV) multispectral imagery for reducing the spectral saturation and improving PNPA estimation in winter wheat before heading. The effect of background materials on PNPA estimated by textural indices (TIs) was examined, and the composite index SPSI was constructed by integrating the optimal spectral index (SI) and TI. Subsequently, the performance of SPSI was evaluated in comparison with other indices (SI and TIs). The results demonstrated that green-pixel TIs yielded better performances than all-pixel TIs apart from TI[HOM], TI[ENT], and TI[SEM] among all indices from 8 types of textural features. SPSI, which was calculated by the formula DATT[850,730,675] + NDTICOR[850,730], exhibited the highest overall accuracies for any date in any dataset in comparison with DATT[850,730,675], TINDRE[MEA], and NDTICOR[850,730]. For the unified models assembling 2 experimental datasets, the RV2 values of SPSI increased by 0.11 to 0.23, and both RMSE and RRMSE decreased by 16.43% to 38.79% as compared to the suboptimal index on each date. These findings indicated that the SPSI is valuable in reducing the spectral saturation and has great potential to better estimate PNPA using high-resolution satellite imagery.

Qing-Zhi-Tiao-Gan-Tang (QZTGT) prevents nonalcoholic steatohepatitis (NASH) by expression pattern correction.

ETHNOPHARMACOLOGICAL RELEVANCE: Qing-Zhi-Tiao-Gan-Tang or Qing-Zhi-Tiao-Gan Decoction (QZTGT) is based on the compatibility theory of traditional Chinese medicine (TCM), that is a combination of three classical formulae for the treatment of nonalcoholic fatty liver disease (NAFLD). Its pharmacodynamic material basis is made up of quinones, flavanones, and terpenoids. AIM OF THE STUDY: This study aimed to look for a promising recipe for treating nonalcoholic steatohepatitis (NASH), a more advanced form of NAFLD, and to use a transcriptome-based multi-scale network pharmacological platform (TMNP) to find its therapy targets. MATERIALS AND METHODS: A classical dietary model of NASH was established using MCD (Methionine- and choline-deficient) diet-fed mice. Liver coefficients like ALT, AST, serum TC, and TG levels were tested following QZTGT administration. A transcriptome-based multi-scale network pharmacological platform (TMNP) was used to further analyze the liver gene expression profile. RESULTS: The composition of QZTGT was analyzed by HPLC-Q-TOF/MS, a total of 89 compounds were separated and detected and 31 of them were found in rat plasma. QZTGT improved liver morphology, inflammation and fibrosis in a classical NASH model. Transcriptomic analysis of liver samples from NASH animal model revealed that QZTGT was able to correct gene expression. We used transcriptome-based multi-scale network pharmacological platform (TMNP) to predicted molecular pathways regulated by QZTGT to improve NASH. Further validation indicated that "fatty acid degradation", "bile secretion" and "steroid biosynthesis" pathways were involved in the improvement of NASH phenotype by QZTGT. CONCLUSIONS: Using HPLC-Q-TOF/MS, the compound composition of QZTGT, a Traditional Chinese prescription, was separated, analyzed and identified systematically. QZTGT mitigated NASH symptoms in a classical dietary model of NASH. Transcriptomic and network pharmacology analysis predicted the potential QZTGT regulated pathways. These pathways could be used as therapeutic targets for NASH.

A Lightweight Authentication and Key Agreement Protocol for IoT-Enabled Smart Grid System.

The IoT-enabled Smart Grid uses IoT smart devices to collect the private electricity data of consumers and send it to service providers over the public network, which leads to some new security problems. To ensure the communication security in a smart grid, many researches are focusing on using authentication and key agreement protocols to protect against cyber attacks. Unfortunately, most of them are vulnerable to various attacks. In this paper, we analyze the security of an existent protocol by introducing an insider attacker, and show that their scheme cannot guarantee the claimed security requirements under their adversary model. Then, we present an improved lightweight authentication and key agreement protocol, which aims to enhance the security of IoT-enabled smart grid systems. Furthermore, we proved the security of the scheme under the real-or-random oracle model. The result shown that the improved scheme is secure in the presence of both internal attackers and external attackers. Compared with the original protocol, the new protocol is more secure, while keeping the same computation efficiency. Both of them are 0.0552 ms. The communication of the new protocol is 236 bytes, which is acceptable in smart grids. In other words, with similar communication and computation cost, we proposed a more secure protocol for smart grids.

Comprehensive Evaluation of Metabolism and the Contribution of the Hepatic First-Pass Effect in the Bioavailability of Glabridin in Rats.

Glabridin is a bioactive isoflavan, which has a wide range of biological properties and is widely used in the market of health products and dietary supplements. However, the transformation pathway of glabridin in vivo is unclear, and the bioavailability is controversial among different studies. Therefore, a new HPLC-Q-TOF method was developed to analyze and identify the prototype and metabolites of glabridin in rats. A total of 63 compounds were identified, including hydroxylation, demethylation, acetylation, demethylation to carboxylation, glucuronidation, and sulfate conjugation, and 43 of which were new metabolites that had not been reported. Additionally, our study verified that the oral bioavailability of glabridin was 6.63 ± 2.29% in rats. Furthermore, we found that the hepatic first-pass effect was 62.12 ± 15.7% for glabridin. These results indicated that a high hepatic first-pass effect and extensive metabolism of glabridin in vivo may lead to its limited oral bioavailability.

Identification of the main flavonoids of Abelmoschus manihot (L.) medik and their metabolites in the treatment of diabetic nephropathy.

Introduction: Huangkui capsule (HKC) is made from the ethanol extract of Abelmoschus manihot (L.) Medik [Malvaceae; abelmoschi corolla] and received approval from the China Food and Drug Administration (Z19990040) in 1999. Currently, HKC is used for treatment of the patients with diabetic nephropathy (DN) in China. The bioactive chemical constituents in HKC are total flavonoids of A. manihot (L.) Medik (TFA). The present study aims to identify the primary flavonoid metabolites in HKC and TFA and their metabolism fates in db/db mice, the animal model for the study of type 2 diabetes and DN. Methods: HKC (0.84 g/kg/d) and TFA (0.076 g/kg/d) or vehicle were respectively administered daily via oral gavage in db/db mice for 4 weeks. The metabolism fate of the main metabolites of HKC in serum, liver, kidney, heart, jejunum, colon, jejunal contents, colonic contents, and urine of db/db mice were analyzed with a comprehensive metabolite identification strategy. Results and Discussion: In db/db mice administered with HKC and TFA, 7 flavonoid prototypes and 38 metabolites were identified. The related metabolic pathways at Phases I and II reactions included dehydroxylation, deglycosylation, hydrogenation, methylation, glucuronidation, sulphation, and corresponding recombined reactions. Quercetin, isorhamnetin, quercetin sulphate, quercetin monoglucuronide, and isorhamnetin monoglucuronide presented a high exposure in the serum and kidney of db/db mice. Thereby, the present study provides a pharmacodynamic substance basis for better understanding the mechanism of A. manihot (L.) Medik for medication of DN.

Magnetic Tile Surface Defect Detection Methodology Based on Self-Attention and Self-Supervised Learning.

As the core component of permanent magnet motor, the magnetic tile defects seriously affect the quality of industrial motor. Automatic recognition of the surface defects of the magnetic tile is a difficult job since the patterns of the defects are complex and diverse. The existing defect recognition methods result in difficulty in practical application due to the complicated system structure and the low accuracy of the image segmentation and the target detection for the diversity of the defect patterns. A self-supervised learning (SSL) method, which benefits from its nonlinear feature extraction performance, is proposed in this study to improve the existing approaches. We proposed an efficient multihead self-attention method, which can automatically locate single or multiple defect areas of magnetic tile and extract features of the magnetic tile defects. We also designed an accurate full-connection classifier, which can accurately classify different defects of magnetic tile defects. A knowledge distillation process without labeling is proposed, which simplifies the self-supervised training process. The process of our method is as follows. A feature extraction model consists of standard vision transformer (ViT) backbone, which is trained by contrast learning without labeled dataset that is used to extract global and local features from the input magnetic tile images. Then, we use a full-connection neural network, which is trained by using labeled dataset to classify the known defect types. Finally, we combined the feature extraction model and defect classification model together to form a relatively simple integrated system. The public magnetic tile surface defect dataset, which holds 5 defect categories and 1 nondefect category, is used in the process of training, validating, and testing. We also use online data augmentation techs to increase training samples to make the model converge and achieve high classification accuracy. The experimental results show that the features extracted by the SSL method can get richer and more detailed features than the supervised learning model gets. The composite model reaches to a high testing accuracy of 98.3%, and gains relatively strong robustness and good generalization ability.

Impact of Enhanced Recovery After Surgery on Postoperative Recovery for Pancreaticoduodenectomy: Pooled Analysis of Observational Study.

Purpose: To assess the impact of enhanced recovery after surgery (ERAS) protocols in pancreaticoduodenectomy. Methods: Four databases were searched for studies describing ERAS program in patients undergoing pancreatic surgery published up to May 01, 2018. Primary outcomes were mortality, readmission, reoperation and postoperative complications. Secondary outcomes were the length of stay and cost. Results: A total of 19 studies met inclusion and exclusion criteria and included 3,387 patients. Meta-analysis showed a decrease in pancreatic fistula (OR = 0.79, 95% CI: 0.67 to 0.95; I 2 = 0%), infection (OR = 0.63, 95% CI: 0.50 to 0.78; I 2 = 0%), especially incision infection (OR = 0.62, 95% CI: 0.42 to 0.91; I 2 = 0%), and pulmonary infection (OR = 0.28, 95% CI: 0.12 to 0.66; I 2 = 0%). Length-of-stay (MD: -3.89 days, 95% CI: -4.98 to -2.81; I 2 = 78%) and cost were also significantly reduced. There was no significant increase in mortality, readmission, reoperation, or delayed gastric emptying. Conclusion: This analysis revealed that using ERAS protocols in pancreatic resections may help decrease the incidence of pancreatic fistula and infections. Furthermore, ERAS also reduces length of stay and cost of care. This study provides evidence for the benefit of ERAS protocols.

Pooled analysis of the clinical benefit of cyclooxygenase-2 inhibitors combined with chemotherapy in advanced non-small cell lung cancer.

BACKGROUND: The purpose of this study was to perform a systematic review of the interventions for advanced non-small cell lung cancer (NSCLC) including chemotherapy alone and chemotherapy plus COX-2 inhibitors to identify and discuss the cause of any variation across studies and to explore the best currently available evidence. METHODS: The literature was comprehensively searched to identify relevant meta-analyses, and the Jadad decision algorithm was used to select the best evidence from the included meta-analyses. Quality assessment of the meta-analyses was performed using the Quality of Reporting (QUOROM) checklist and the Oxman-Guyatt quality index. RESULTS: Five meta-analyses were selected for inclusion in this study. Three were published prior to 2018 and had Oxman-Guyatt scores of 5. Only one study had the highest QUOROM and Oxman-Guyatt scores, and that study concluded that first-line treatment with chemotherapy plus COX-2 inhibitors was superior to chemotherapy alone in terms of the overall response rate (ORR). However, no significant difference in clinical benefit, progression-free survival (PFS), overall survival (OS), or 1-year survival rate was found. In addition, toxicities of the drugs had some influence on patients with heart disease. CONCLUSIONS: The Jadad algorithm identified the optimal current meta-analysis. COX-2 inhibitors increased the ORR when combined with chemotherapy, but did not improve the survival indices. In addition, they may increase the risk of cardiovascular events and hematological toxicities in NSCLC patients.

Approach to Higher Wheat Yield in the Huang-Huai Plain: Improving Post-anthesis Productivity to Increase Harvest Index.

Both increased harvest index (HI) and increased dry matter (DM) are beneficial to yield; however, little is known about the priority of each under different yield levels. This paper aims to determine whether HI or DM is more important and identify the physiological attributes that act as indicators of increased yield. Two field experiments involving different cultivation patterns and water-nitrogen modes, respectively, were carried out from 2013 to 2016 in Huang-Huai Plain, China. Plant DM, leaf area index (LAI), and radiation interception (RI) were measured. Increased yield under low yield levels <7500 kg ha-1 was attributed to an increase in both total DM and HI, while increases under higher yield levels >7500 kg ha-1 were largely dependent on an increase in HI. Under high yield levels, HI showed a significant negative correlation with total DM and a parabolic relationship with net accumulation of DM during filling. Higher net accumulation of DM during filling helped slow down the decrease in HI, thereby maintaining a high value. Moreover, net DM accumulation during filling was positively correlated with yield, while post-anthesis accumulation showed a significant linear relationship with leaf area potential (LAP, R 2 = 0.404-0.526) and radiation interception potential (RIP, R 2 = 0.452-0.576) during grain filling. These findings suggest that the increase in LAP and RIP caused an increase in net DM accumulation after anthesis. Under DM levels >13,000 kg ha-1 at anthesis, maintaining higher LAI and RI in lower layers during grain formation contributed to higher yield. Furthermore, the ratio of upper- to lower-layer RI showed a second-order curve with yield during filling, with an increase in the optimal range with grain development. Pre-anthesis translocation amount, translocation ratios and contribution ratios also showed second-order curves under high yield levels, with optimal values of 3000-4500 kg ha-1, 25-35, and 30-50%, respectively. These results confirm the importance of HI in improving the yield, thereby providing a theoretical basis for wheat production in the Huang-Huai Plain.

Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data.

Remote sensing techniques can be efficient for non-destructive, rapid detection of wheat nitrogen (N) nutrient status. In the paper, we examined the relationships of canopy multi-angular data with aerial N uptake of winter wheat (Triticum aestivum L.) across different growing seasons, locations, years, wheat varieties, and N application rates. Seventeen vegetation indices (VIs) selected from the literature were measured for the stability in estimating aerial N uptake of wheat under 13 view zenith angles (VZAs) in the solar principal plane (SPP). In total, the back-scatter angles showed better VI behavior than the forward-scatter angles. The correlation coefficient of VIs with aerial N uptake increased with decreasing VZAs. The best linear relationship was integrated with the optimized common indices DIDA and DDn to examine dynamic changes in aerial N uptake; this led to coefficients of determination (R2) of 0.769 and 0.760 at the -10° viewing angle. Our novel area index, designed the modified right-side peak area index (mRPA), was developed in accordance with exploration of the spectral area calculation and red-edge feature using the equation: mRPA = (R760/R600)1/2 × (R760-R718). Investigating the predictive accuracy of mRPA for aerial N uptake across VZAs demonstrated that the best performance was at -10° [R2 = 0.804, p < 0.001, root mean square error (RMSE) = 3.615] and that the effect was relatively similar between -20° to +10° (R2 = 0.782, p < 0.001, RMSE = 3.805). This leads us to construct a simple model under wide-angle combinations so as to improve the field operation simplicity and applicability. Fitting independent datasets to the models resulted in relative error (RE, %) values of 12.6, 14.1, and 14.9% between estimated and measured aerial N uptake for mRPA, DIDA, and DDn across the range of -20° to +10°, respectively, further confirming the superior test performance of the mRPA index. These results illustrate that the novel index mRPA represents a more accurate assessment of plant N status, which is beneficial for guiding N management in winter wheat.

Grain number responses to pre-anthesis dry matter and nitrogen in improving wheat yield in the Huang-Huai Plain.

Wheat yield components vary between different ecological regions and yield levels. Grain number responses to pre-anthesis dry matter (DM) and nitrogen (N) in increasing yield were always investigated in spike organs, neglecting the effect of non-spike organ nutrition or overall distribution. This paper determined the relationships between grain number and pre-anthesis DM and N in spike and non-spike organs under different yield levels, with using two sorts of field experiments (different water-nitrogen modes and cultivation management patterns) from 2012-2015 in Huang-Huai plain. The results indicated that improving yield under yield of <7500 kg ha-1 depends on increasing grain number per spike (GNs) or spike number (SN) or both, increased yield under higher yield of >7500 kg ha-1 mainly depends on GNs. GNs showed significant positive relationships with above-ground DM accumulation from jointing to anthesis under high or low yield levels. Rapid DM growth in spring achieves higher GNs. Spike and non-spike DM and N contents both demonstrated strong positive relationships with GNs, spike DM distribution also shows a positive correlation, but spike N distribution ratio show negatively correlation with GNs. Improved N distribution in non-spike organs and DM partition in spike organs conduce to increasing GNs.

Canopy Vegetation Indices from In situ Hyperspectral Data to Assess Plant Water Status of Winter Wheat under Powdery Mildew Stress.

Plant disease and pests influence the physiological state and restricts the healthy growth of crops. Physiological measurements are considered the most accurate way of assessing plant health status. In this paper, we researched the use of an in situ hyperspectral remote sensor to detect plant water status in winter wheat infected with powdery mildew. Using a diseased nursery field and artificially inoculated open field experiments, we detected the canopy spectra of wheat at different developmental stages and under different degrees of disease severity. At the same time, destructive sampling was carried out for physical tests to investigate the change of physiological parameters under the condition of disease. Selected vegetation indices (VIs) were mostly comprised of green bands, and correlation coefficients between these common VIs and plant water content (PWC) were generally 0.784-0.902 (p < 0.001), indicating the green waveband may have great potential in the evaluation of water content of winter wheat under powdery mildew stress. The Photochemical Reflectance Index (PRI) was sensitive to physiological response influenced by powdery mildew, and the relationships of PRI with chlorophyll content, the maximum quantum efficiency of PSII photochemistry (Fv/Fm), and the potential activity of PSII photochemistry (Fv/Fo) were good with R2 = 0.639, 0.833, 0.808, respectively. Linear regressions showed PRI demonstrated a steady relationship with PWC across different growth conditions, with R2 = 0.817 and RMSE = 2.17. The acquired PRI model of wheat under the powdery mildew stress has a good compatibility to different experimental fields from booting stage to filling stage compared with the traditional water signal vegetation indices, WBI, FWBI1, and FWBI2. The verification results with independent data showed that PRI still performed better with R2 = 0.819 between measured and predicted, and corresponding RE = 8.26%. Thus, PRI is recommended as a potentially reliable indicator of PWC in winter wheat with powdery mildew stress. The results will help to understand the physical state of the plant, and provide technical support for disease control using remote sensing during wheat production.