Traditional Chinese medicine combined with conventional treatment for the patients after percutaneous coronary intervention: A systematic review and meta-analysis

Purpose: To evaluate the efficacy, quality of care and safety of Traditional Chinese Medicine (TCM) after Percutaneous Coronary Intervention (PCI). using systematic review and meta-analysis of randomized controlled trials.Methods: Relevant studies published between January 1st 2010 and August 20th, 2021, on traditional Chinese medicine (TCM) and conventional treatment (CT) after PCI were sourced from different databases including CNKI, CBM, Web of Science, PubMed, Embase and Cochrane library. The TCM was composed of preparations of chinese eaglewood, peppermint, radix notoginseng, scabrous elephant foot herb, Tongxinluo, Danhong, Naoxintong capsule, Huxin Formula and liquorice root while the CT included aspirin (100 mg/day), clopidogrel (75 mg/day), and statins. PRISMA guidelines were used. Primary outcome was to evaluate the efficacy, quality of care and safety of TCM versus conventional treatment post percutaneous coronary intervention (PCI).Results: 110 randomized controlled trials (RCTs) were retrieved and analyzed. The results from metaanalysis showed an enhanced left ventricular ejection fraction (LVEF) % among patients that received TCM compared to those on CT [mean difference ± sd (MD)=5.17, 95% CI (3.29-7.06), Z = 5.38, (P < 0.001)]. Further, hypersensitive C-reactive protein (HS-CRP) level in TCM group was found to be relatively lower than that of the CT group (CG) [MD=-1.44, 95% CI (-2.87-0.00), Z=1.96, (P=0.05)]. In terms of safety, TCM group relative risk score in fixed-effect model was lower than that of the CG [RR=0.66, 95% CI (0.40, 1.10), Z=1.66,].Conclusion: It can be inferred from the results that TCM has more advantages in terms of clinical efficacy, quality of care and safety compared to conventional therapy. However, the lack of substantial research in deploying TCM for the treatment of CHD demands further exploration and strong evidence prior to clinical application of TCM

Development of TaqMan® MGB fluorescent real-time PCR assay for the detection of anatid herpesvirus 1

<p>Abstract</p> <p>Background</p> <p>Anatid herpesvirus 1 (AHV-1) is an alphaherpesvirus associated with latent infection and mortality in ducks and geese and is currently affecting the world-wide waterfowl production severely. Here we describe a fluorescent quantitative real-time PCR (FQ-PCR) method developed for fast measurement of AHV-1 DNA based on TaqMan MGB technology.</p> <p>Results</p> <p>The detection limit of the assay was 1 × 10¹standard DNA copies, with a sensitivity of 2 logs higher than that of the conventional gel-based PCR assay targeting the same gene. The real-time PCR was reproducible, as shown by satisfactory low intra-assay and inter-assay coefficients of variation.</p> <p>Conclusion</p> <p>The high sensitivity, specificity, simplicity and reproducibility of the AHV-1 fluorogenic PCR assay, combined with its wide dynamic range and high throughput, make this method suitable for a broad spectrum of AHV-1 etiologically related application.</p

Assessment of hydrological connectivity characteristics of riparian zones and their correlation with root–soil composites at different bank heights of a first-class river in China

Under the combined effects of topography and vegetation, hydrological connectivity characteristics of riverbank slopes become complex and unclear, which limit the utilization and protection of riparian zones. To quantify the hydrological connectivity in root–soil composites, we conducted dyeing and tracing experiments in a high elevation plot and a low elevation plot on the bank of the Fenhe River. Soil and root properties and hydrological connectivity indexes in the plots were measured and analyzed. The results showed that the soil dyeing area ratio was approximate 1 in the soil depth of 0–5 cm and then decreased to 0.1 from 5 cm to 25 cm. The dyeing area ratio, maximum dyed depth, length index, peak value and non-uniformity coefficient of the high plot (Pc2) were 27%, 26%, 5%, 40% and 45% greater than those of the low plot (Pc1). The index of hydrological connectivity (IHC) of Pc2 was 7%, 44% and 71% greater than Pc1 in the soil depths 0–10 cm, 10–20 cm and 20–30 cm respectively. There was no significant correlation between the IHC and the physical properties of the soil at different depths, and the soil hydrological connectivity was closely related to the plant roots with diameter less than 1mm. The study primarily explored the characteristics of hydrological connectivity in root–soil composites. The results provide a scientific basis for exploring hydrological connectivity of riparian zones, which can support future riparian zone protection and restoration efforts in similar regions

GrapeNet: A Lightweight Convolutional Neural Network Model for Identification of Grape Leaf Diseases

Most convolutional neural network (CNN) models have various difficulties in identifying crop diseases owing to morphological and physiological changes in crop tissues, and cells. Furthermore, a single crop disease can show different symptoms. Usually, the differences in symptoms between early crop disease and late crop disease stages include the area of disease and color of disease. This also poses additional difficulties for CNN models. Here, we propose a lightweight CNN model called GrapeNet for the identification of different symptom stages for specific grape diseases. The main components of GrapeNet are residual blocks, residual feature fusion blocks (RFFBs), and convolution block attention modules. The residual blocks are used to deepen the network depth and extract rich features. To alleviate the CNN performance degradation associated with a large number of hidden layers, we designed an RFFB module based on the residual block. It fuses the average pooled feature map before the residual block input and the high-dimensional feature maps after the residual block output by a concatenation operation, thereby achieving feature fusion at different depths. In addition, the convolutional block attention module (CBAM) is introduced after each RFFB module to extract valid disease information. The obtained results show that the identification accuracy was determined as 82.99%, 84.01%, 82.74%, 84.77%, 80.96%, 82.74%, 80.96%, 83.76%, and 86.29% for GoogLeNet, Vgg16, ResNet34, DenseNet121, MobileNetV2, MobileNetV3_large, ShuffleNetV2_×1.0, EfficientNetV2_s, and GrapeNet. The GrapeNet model achieved the best classification performance when compared with other classical models. The total number of parameters of the GrapeNet model only included 2.15 million. Compared with DenseNet121, which has the highest accuracy among classical network models, the number of parameters of GrapeNet was reduced by 4.81 million, thereby reducing the training time of GrapeNet by about two times compared with that of DenseNet121. Moreover, the visualization results of Grad-cam indicate that the introduction of CBAM can emphasize disease information and suppress irrelevant information. The overall results suggest that the GrapeNet model is useful for the automatic identification of grape leaf diseases

Characterization of the duck enteritis virus UL55 protein

<p>Abstract</p> <p>Background</p> <p>Characteration of the newly identified duck enteritis virus UL55 gene product has not been reported yet. Knowledge of the protein UL55 can provide useful insights about its function.</p> <p>Results</p> <p>The newly identified duck enteritis virus UL55 gene was about 561 bp, it was amplified and digested for construction of a recombinant plasmid pET32a(+)/UL55 for expression in Escherichia coli. SDS-PAGE analysis revealed the recombinant protein UL55(pUL55) was overexpressed in Escherichia coli BL21 host cells after induction by 0.2 mM IPTG at 37°C for 4 h and aggregated as inclusion bodies. The denatured protein about 40 KDa named pUL55 was purified by washing five times, and used to immune rabbits for preparation of polyclonal antibody. The prepared polyclonal antibody against pUL55 was detected and determined by Agar immundiffusion and Neutralization test. The results of Wstern blotting assay and intracellular analysis revealed that pUL55 was expressed most abundantly during the late phase of replication and mainly distributed in cytoplasm in duck enteritis virus infected cells.</p> <p>Conclusions</p> <p>In this study, the duck enteritis virus UL55 protein was successfully expressed in prokaryotic expression system. Besides, we have prepared the polyclonal antibody against recombinant prtein UL55, and characterized some properties of the duck enteritis virus UL55 protein for the first time. The research will be useful for further functional analysis of this gene.</p

Expression and intracellular localization of duck enteritis virus pUL38 protein

Knowledge of the intracellular location of a protein can provide useful insights into its function. Bioinformatic studies have predicted that the DEV pUL38 mainly targets the cytoplasm and nucleus. In this study, we obtained anti-pUL38 polyclonal sera. These antibodies were functional in western blotting and immunofluorescence in DEV-infected duck embryo fibroblasts (DEFs). pUL38 was expressed as a 51-kDa protein from 8 h post-infection onward, initially showing a diffuse distribution throughout the cytoplasm, and later in the nucleus. Furthermore, pUL38 was found in purified virus. These results provide the first evidence of the kinetics of expression and intracellular localization of DEV pUL38

Expressing gK gene of duck enteritis virus guided by bioinformatics and its applied prospect in diagnosis

<p>Abstract</p> <p>Background</p> <p>Duck viral enteritis, which is caused by duck enteritis virus (DEV), causes significant economic losses in domestic and wild waterfowls because of the high mortality and low egg production rates. With the purpose of eliminating this disease and decreasing economic loss in the commercial duck industry, researching on glycoprotein K (gK) of DEV may be a new kind of method for preventing and curing this disease. Because glycoproteins project from the virus envelope as spikes and are directly involved in the host immune system and elicitation of the host immune responses, and also play an important role in mediating infection of target cells, the entry into cell for free virus and the maturation or egress of virus. The gK is one of the major envelope glycoproteins of DEV. However, little information correlated with gK is known, such as antigenic and functional characterization.</p> <p>Results</p> <p>Bioinformatic predictions revealed that the expression of the full-length gK gene (<it>fgK</it>) in a prokaryotic system is difficult because of the presence of suboptimal exon and transmembrane domains at the C-terminal. In this study, we found that the <it>fgK </it>gene might not be expressed in a prokaryotic system in accordance with the bioinformatic predictions. Further, we successfully used bioinformatics tools to guide the prokaryotic expression of the <it>gK </it>gene by designing a novel truncated <it>gK </it>gene (<it>tgK</it>). These findings indicated that bioinformatics provides theoretical data for target gene expression and saves time for our research. The recombinant tgK protein (tgK) was expressed and purified by immobilized metal affinity chromatography (IMAC). Western blotting and indirect enzyme-linked immunosorbent assay (ELISA) showed that the tgK possessed antigenic characteristics similar to native DEV-gK.</p> <p>Conclusions</p> <p>In this work, the DEV-<it>tgK </it>was expressed successfully in prokaryotic system for the first time, which will provide usefull information for prokaryotic expression of alphaherpesvirus gK homologs, and the recombinant truncated gK possessed antigenic characteristics similar to native DEV gK. Because of the good reactionogenicity, specificity and sensitivity, the purified tgK could be useful for developing a sensitive serum diagnostic kit to monitor DEV outbreaks.</p

Improved EfficientNet for corn disease identification

IntroductionCorn is one of the world's essential crops, and the presence of corn diseases significantly affects both the yield and quality of corn. Accurate identification of corn diseases in real time is crucial to increasing crop yield and improving farmers' income. However, in real-world environments, the complexity of the background, irregularity of the disease region, large intraclass variation, and small interclass variation make it difficult for most convolutional neural network models to achieve disease recognition under such conditions. Additionally, the low accuracy of existing lightweight models forces farmers to compromise between accuracy and real-time.MethodsTo address these challenges, we propose FCA-EfficientNet. Building upon EfficientNet, the fully-convolution-based coordinate attention module allows the network to acquire spatial information through convolutional structures. This enhances the network's ability to focus on disease regions while mitigating interference from complex backgrounds. Furthermore, the adaptive fusion module is employed to fuse image information from different scales, reducing interference from the background in disease recognition. Finally, through multiple experiments, we have determined the network structure that achieves optimal performance.ResultsCompared to other widely used deep learning models, this proposed model exhibits outstanding performance in terms of accuracy, precision, recall, and F1 score. Furthermore, the model has a parameter count of 3.44M and Flops of 339.74M, which is lower than most lightweight network models. We designed and implemented a corn disease recognition application and deployed the model on an Android device with an average recognition speed of 92.88ms, which meets the user's needs.DiscussionOverall, our model can accurately identify corn diseases in realistic environments, contributing to timely and effective disease prevention and control

Characterization of duck enteritis virus UL53 gene and glycoprotein K

<p>Abstract</p> <p>Background</p> <p>Most of the previous research work had focused on the epidemiology and prevention of duck enteritis virus (DEV). Whilst with the development of protocols in molecular biology, nowadays more and more information about the genes of DEV was reported. But little information about DEV UL53 gene and glycoprotein K(gK) was known except our reported data.</p> <p>Results</p> <p>In our paper, the fluorescent quantitative real-time PCR(FQ-RT-PCR) assay and nucleic acid inhibition test were used to study the transcription characteristic of the DEV UL53 gene. Except detecting the mRNA of DEV UL53 gene, the product gK encoded by UL53 gene was detected through the expression kinetics of UL53 gene by the purified rabbit anti-UL53 protein polyclonal antibodies. Western-blotting and indirect immunofluorescence assays were used to detect gK. From the results of these experiments, the UL53 gene and gK were respectively identified as a late gene and a really late protein. On the other hand, the indirect immunofluorescence assay provided another information that the intracellular localization of DEV gK was mainly distributed in cytoplasm.</p> <p>Conclusions</p> <p>By way of conclusions, we conceded that DEV UL53 gene is a really late gene, which is coincident with properties of UL53 homologs from other herpesvirus, such as ILTV(Infectious Laryngotracheitis virus) and HSV-1(Herpes simplex virus type 1). The properties of intracellular localization about gK protein provided a foundation for further functional analysis and further studies will be focused on constructing of the UL53 gene DEV mutant.</p