In many parts of the world, apple trees suffer from severe foliar damage each year due to infection of Alternaria blotch (Alternaria alternata f. sp. Mali), resulting in serious economic losses to ...growers. Traditional methods for disease detection and severity classification mostly rely on manual labor, which is slow, labor-intensive and highly subjective. There is an urgent need to develop an effective protocol to rapidly and accurately evaluate disease severity. In this study, DeeplabV3+, PSPNet and UNet were used to assess the severity of apple Alternaria leaf blotch. For identifications of leaves and disease areas, the dataset with a total of 5382 samples was randomly split into 74% (4004 samples) for model training, 9% (494 samples) for validation, 8% (444 samples) for testing and 8% (440 samples) for overall testing. Apple leaves were first segmented from complex backgrounds using the deep-learning algorithms with different backbones. Then, the recognition of disease areas was performed on the segmented leaves. The results showed that the PSPNet model with MobileNetV2 backbone exhibited the highest performance in leaf segmentation, with precision, recall and MIoU values of 99.15%, 99.26% and 98.42%, respectively. The UNet model with VGG backbone performed the best in disease-area prediction, with a precision of 95.84%, a recall of 95.54% and a MIoU value of 92.05%. The ratio of disease area to leaf area was calculated to assess the disease severity. The results showed that the average accuracy for severity classification was 96.41%. Moreover, both the correlation coefficient and the consistency correlation coefficient were 0.992, indicating a high agreement between the reference values and the value that the research predicted. This study proves the feasibility of rapid estimation of the severity of apple Alternaria leaf blotch, which will provide technical support for precise application of pesticides.
Deoxynivalenol (DON) in raw and processed grain poses significant risks to human and animal health. In this study, the feasibility of classifying DON levels in different genetic lines of barley ...kernels was evaluated using hyperspectral imaging (HSI) (382-1030 nm) in tandem with an optimized convolutional neural network (CNN). Machine learning methods including logistic regression, support vector machine, stochastic gradient descent, K nearest neighbors, random forest, and CNN were respectively used to develop the classification models. Spectral preprocessing methods including wavelet transform and max-min normalization helped to enhance the performance of different models. A simplified CNN model showed better performance than other machine learning models. Competitive adaptive reweighted sampling (CARS) in combination with successive projections algorithm (SPA) was applied to select the best set of characteristic wavelengths. Based on seven wavelengths selected, the optimized CARS-SPA-CNN model distinguished barley grains with low levels of DON (<5 mg/kg) from those with higher levels (5 mg/kg < DON ≤ 14 mg/kg) with an accuracy of 89.41%. The lower levels of DON class I (0.19 mg/kg ≤ DON ≤ 1.25 mg/kg) and class II (1.25 mg/kg < DON ≤ 5 mg/kg) were successfully distinguished based on the optimized CNN model, yielding a precision of 89.81%. The results suggest that HSI in tandem with CNN has great potential for discrimination of DON levels of barley kernels.
Abstract Structural optimization is essential to improve the performance of mixing equipment. An efficient optimization strategy based on computational fluid dynamics, machine learning, and the ...multi‐objective genetic algorithm was proposed to predict and optimize the performance of the stirred tank. Single‐factor analysis was performed to study the effects of structural parameters on power consumption and mixing time, which were reduced by 16.0% and 1.4%, respectively, in the optimized stirred vessel. To further optimize the stirred tank geometries and maximize the integrated performance, XGB coupled NSGA‐ІІ were utilized to minimize the power consumption and mixing time. The optimal design parameters from the Pareto front were identified by two well‐known decision‐making methods (LINMAP and TOPSIS), which decreased power consumption and mixing time by 12.3% and 13.4% compared to the stirred tank with the baseline structure. This research further confirmed the accuracy and reliability of the machine learning‐based optimization method.
Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat ...products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.
The number of elderly patients diagnosed with hepatocellular carcinoma (HCC) is expected to increase. The present study aims to evaluate the role of age on treatments and outcome of HCC patients. ...1530 patients firstly diagnosed with HCC were retrospectively included and classified as older (≥65 years, n = 318, 21%) and younger patients (<65 years, n = 1212, 79%). The two groups were compared with clinical characteristics, tumor burden, Barcelona Clinics Liver Cancer (BCLC) stage, treatments and long-term prognosis. Elderly patients were more HCV infected, had more diabetes, poorer performance status, and were less aggressively treated. The proportion of HCC within BCLC stage 0-A, B or C was similar between the two groups, but elderly patients were more presented with BCLC stage D. The overall survival of older patients was poorer compared to younger patients before and after propensity score matching. However, elderly patients were less often effectively treated with surgery and loco-regional therapies across different BCLC stages. After stratified by BCLC stages or treatments, older patients showed comparable long-term outcome to younger patients. Performance status, BCLC stages and effective treatments, rather than age, was independent factors determining prognosis in the whole cohort and only elderly patients by multivariate analysis. In conclusion, older could have comparable survival to younger patients within the same tumor stage or after similar treatments. Thus, equally active treatments should be encouraged to elderly patients.
Blastocystis is a common protist that can infect domestic and wild animals worldwide. Yak (Bos grunniens), an ancient species which can survive in alpine regions, has supplied necessities to local ...residents in plateau areas for generations. However, the infections with Blastocystis in yaks has been ignored for a long time. In the present study, the infections and genotypes of Blastocystis spp. in domestic yaks from Qinghai Province (northwestern China) were explored.
Of 1027 faecal samples collected from yaks in seven regions of Qinghai Province, northwestern China, the total prevalence of Blastocystis was 27.07% (278/1027) targeting the small subunit ribosome rRNA (SSU rRNA) gene. This protist was detected in yaks within each examined age group, geographical origin and season. Significant difference in prevalence was found in yaks from different geographical origins. The highest prevalence (48.94%) was observed in animals from Haixi county. Sequence analysis revealed three animal-specific subtypes (ST10, ST12 and ST14) of Blastocystis spp. in these yaks, with ST10 being the predominant subtype widely distributed in all investigated regions, seasons and age groups. Interestingly, this is the first report about subtype ST12 infecting yaks.
To our knowledge, this is the first systematic report on Blastocystis prevalence in yaks from China, and the findings provide fundamental data for establishing effective control measures for this protist in yaks as well as other animals in China.
Expression of lymphoid enhancer factor 1 (LEF1) is frequently altered in different human cancers. This study aimed to assess LEF1 expression in colon cancer tissues and to explore changed phenotypes, ...gene expressions, and the possible mechanism after knocked down LEF1 expression in colon cancer cell lines. A total of 106 colon cancer and matched paratumorous normal tissues were used to assess LEF1 expression using immunohistochemistry and qRT-PCR. LEF1 lentivirus was used to knockdown LEF1 expression for the assessment of cell viability, cell cycle distribution, apoptosis, and gene expressions. The nude mouse xenograft assay was performed to detect the effects of LEF1 knockdown in vivo. The data showed that the levels of LEF1 mRNA and protein were significantly increased in human colon cancer tissues compared to the matched paratumorous normal tissues and were associated with infiltration depth, lymph node and distant metastases, advanced TNM (tumor-node-metastasis) stages, and shorter overall survival. Furthermore, LEF1 knockdown reduced tumor cell viability, invasion capacity, MMP2 and MMP-9 expression, but induced apoptosis. Nude mouse xenograft assay showed that LEF1 knockdown suppressed tumor formation and growth in vivo. In addition, the expression of Notch pathway-related proteins RBP-jκ and Hes1 was reduced in LEF1 knockdown cells. Taken together, LEF1 protein was overexpressed in colon cancer tissues and knockdown of LEF1 expression inhibited colon cancer growth in vitro and in vivo. These data suggest that targeting of LEF1 expression should be further evaluated for colon cancer prevention and therapy.
Abstract
Background
Cryptosporidium baileyi
is an economically important zoonotic pathogen that causes serious respiratory symptoms in chickens for which no effective control measures are currently ...available. An accumulating body of evidence indicates the potential and usefulness of metabolomics to further our understanding of the interaction between pathogens and hosts, and to search for new diagnostic or pharmacological biomarkers of complex microorganisms. The aim of this study was to identify the impact of
C. baileyi
infection on the serum metabolism of chickens and to assess several metabolites as potential diagnostic biomarkers for
C. baileyi
infection.
Methods
Ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) and subsequent multivariate statistical analysis were applied to investigate metabolomics profiles in the serum samples of chickens infected with
C. baileyi
, and to identify potential metabolites that can be used to distinguish chickens infected with
C. baileyi
from non-infected birds.
Results
Multivariate statistical analysis identified 138 differential serum metabolites between mock- and
C. baileyi
-infected chickens at 5 days post-infection (dpi), including 115 upregulated and 23 downregulated compounds. These metabolites were significantly enriched into six pathways, of which two pathways associated with energy and lipid metabolism, namely glycerophospholipid metabolism and sphingolipid metabolism, respectively, were the most enriched. Interestingly, some important immune-related pathways were also significantly enriched, including the intestinal immune network for IgA production, autophagy and cellular senescence. Nine potential
C. baileyi
-responsive metabolites were identified, including choline, sirolimus, all-
trans
retinoic acid, PC(14:0/22:1(13Z)), PC(15:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PE(16:1(9Z)/24:1(15Z)), phosphocholine, SM(d18:0/16:1(9Z)(OH)) and sphinganine.
Conclusions
This is the first report on serum metabolic profiling of chickens with early-stage
C. baileyi
infection. The results provide novel insights into the pathophysiological mechanisms of
C. baileyi
in chickens.
Graphic abstract
Neospora caninum infection is a major cause of abortion in cattle, which results in serious economic losses to the cattle industry. However, there are no effective drugs or vaccines for the control ...of N. caninum infections. There is increasing evidence that microRNAs (miRNAs) are involved in many physiological and pathological processes, and dysregulated expression of host miRNAs and the biological implications of this have been reported for infections by various protozoan parasites. However, to our knowledge, there is presently no published information on host miRNA expression during N. caninum infection.
The expression profiles of miRNAs were investigated by RNA sequencing (RNA-seq) in caprine endometrial epithelial cells (EECs) infected with N. caninum at 24 h post infection (pi) and 48 hpi, and the functions of differentially expressed (DE) miRNAs were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The transcriptome data were validated by using quantitative real-time polymerase chain reaction. One of the upregulated DEmiRNAs, namely chi-miR-146a, was selected to study the effect of DEmiRNAs on the propagation of N. caninum tachyzoites in caprine EECs.
RNA-seq showed 18 (17 up- and one downregulated) and 79 (54 up- and 25 downregulated) DEmiRNAs at 24 hpi and 48 hpi, respectively. Quantitative real-time polymerase chain reaction analysis of 13 randomly selected DEmiRNAs (10 up- and three downregulated miRNAs) confirmed the validity of the RNA-seq data. A total of 7835 messenger RNAs were predicted to be potential targets for 66 DEmiRNAs, and GO and KEGG enrichment analysis of these predicted targets revealed that DEmiRNAs altered by N. caninum infection may be involved in host immune responses (e.g. Fc gamma R-mediated phagocytosis, Toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, transforming growth factor-β signaling pathway, mitogen-activated protein kinase signaling pathway) and metabolic pathways (e.g. lysine degradation, insulin signaling pathway, AMP-activated protein kinase signaling pathway, Rap1 signaling pathway, calcium signaling pathway). Upregulated chi-miR-146a was found to promote N. caninum propagation in caprine EECs.
This is, to our knowledge, the first report on the expression profiles of host miRNAs during infection with N. caninum, and shows that chi-miR-146a may promote N. caninum propagation in host cells. The novel findings of the present study should help to elucidate the interactions between host cells and N. caninum.
Eimeria necatrix, the most highly pathogenic coccidian in chicken small intestines, can cause high morbidity and mortality in susceptible birds and devastating economic losses in poultry production, ...but the underlying molecular mechanisms in interaction between chicken and E. necatrix are not entirely revealed. Accumulating evidence shows that the long-non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) are key regulators in various infectious diseases. However, the expression profiles and roles of these two non-coding RNAs (ncRNAs) during E. necatrix infection are still unclear.
The expression profiles of mRNAs, lncRNAs and circRNAs in mid-segments of chicken small intestines at 108 h post-infection (pi) with E. necatrix were analyzed by using the RNA-seq technique.
After strict filtering of raw data, we putatively identified 49,183 mRNAs, 818 lncRNAs and 4153 circRNAs. The obtained lncRNAs were classified into four types, including 228 (27.87%) intergenic, 67 (8.19%) intronic, 166 (20.29%) anti-sense and 357 (43.64%) sense-overlapping lncRNAs; of these, 571 were found to be novel. Five types were also predicted for putative circRNAs, including 180 exonic, 54 intronic, 113 antisense, 109 intergenic and 3697 sense-overlapping circRNAs. Eimeria necatrix infection significantly altered the expression of 1543 mRNAs (707 upregulated and 836 downregulated), 95 lncRNAs (49 upregulated and 46 downregulated) and 13 circRNAs (9 upregulated and 4 downregulated). Target predictions revealed that 38 aberrantly expressed lncRNAs would cis-regulate 73 mRNAs, and 1453 mRNAs could be trans-regulated by 87 differentially regulated lncRNAs. Additionally, 109 potential sponging miRNAs were also identified for 9 circRNAs. GO and KEGG enrichment analysis of target mRNAs for lncRNAs, and sponging miRNA targets and source genes for circRNAs identified associations of both lncRNAs and circRNAs with host immune defense and pathogenesis during E. necatrix infection.
To the best of our knowledge, the present study provides the first genome-wide analysis of mRNAs, lncRNAs and circRNAs in chicken small intestines infected with E. necatrix. The obtained data will offer novel clues for exploring the interaction mechanisms between chickens and Eimeria spp.
PDF
