Effects of Protection Time on Infection of Rice Panicle Blast.

Panicle blast, caused by Magnaporthe oryzae, is a destructive disease of rice worldwide. Clarifying the susceptibility of rice panicles at different stages is of great significance for effective disease management. Field experiments were conducted in two paddy fields at Wuyuan County in 2016 and 2017 to determine the effects of head covering and its timing on the infection of rice panicle blast. Results revealed that panicle blast was reduced significantly by covering rice heads with sulfuric acid paper bags, regardless of the covering time, ranging from initial heading to 15 days afterward, suggesting that rice panicles could be infected by blast pathogen even 15 days after initial heading. Panicle blast incidence was also found to be significantly influenced by plant dates, with higher panicle blast incidence observed in plots planted on early dates, suggesting adjusting plant dates could help rice panicles escape the infection by blast pathogen. The results from this study also highlighted the importance of cultivars and environmental conditions to panicle blast. In conclusion, besides planting blast-resistant cultivars, it is important to protect rice heads from the initial heading to the early dough stages, and fungicides should be applied according to infection warnings based on host, inoculum, and weather conditions.

Deep recognition of rice disease images: how many training samples do we really need?

BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while lacking research to systematically and scientifically explore the impact of different data sizes on the image recognition task for rice diseases. In this study, a functional model was developed to predict the relationship between the size of dataset and the accuracy rate of model recognition. RESULTS: Training VGG16 deep learning models with different quantities of images of rice blast-diseased leaves and healthy rice leaves, it was found that the test accuracy of the resulting models could be well fitted with an exponential model (A = 0.9965 - e(-0.0603×I50-1.6693)). Experimental results showed that with an increase of image quantity, the recognition accuracy of deep learning models would show a rapid increase at first. Yet when the image quantity increases beyond a certain threshold, the accuracy of image classification would not improve much, and the marginal benefit would be reduced. This trend remained similar when the composition of the dataset was changed, no matter whether (i) the disease class was changed, (ii) the number of classes was increased or (iii) the image data were augmented. CONCLUSIONS: This study provided a scientific basis for the impact of data size on the accuracy of rice disease image recognition, and may also serve as a reference for researchers for database construction. © 2024 Society of Chemical Industry.

Comparison of the efficacy and safety of total laparoscopic hysterectomy without and with uterine manipulator combined with pelvic lymphadenectomy for early cervical cancer.

OBJECTIVE: Some studies have reported that the prognosis of total laparoscopic hysterectomy (TLH) for early-stage cervical cancer (CC) is worse than that of open surgery. And this was associated with the use of uterine manipulator or not. Therefore, this study retrospectively analyzes the efficacy and safety of TLH without uterine manipulator combined with pelvic lymphadenectomy for early-stage CC. METHODS: Fifty-eight patients with CC (stage IB1-IIA1) who received radical hysterectomy from September 2019 to January 2020 were divided into no uterine manipulator (n = 26) and uterine manipulator group (n = 32). Then, clinical characteristics were collected and intraoperative/postoperative related indicators were compared. RESULTS: Patients in the no uterine manipulator group had significantly higher operation time and blood loss than in the uterine manipulator group. Notably, there was no significant difference in hemoglobin change, blood transfusion rate, number of pelvic nodules, anal exhaust time, complications and recurrence rate between the two groups. Additionally, patients in the uterine manipulator group were prone to urinary retention (15.6%) and lymphocyst (12.5%), while the no uterine manipulator group exhibited high probability of bladder dysfunction (23.1%) and urinary retention (15.4%). Furthermore, the 1-year disease-free survival rate and the 1-year overall survival rate were not significantly different between the two groups. CONCLUSION: There was no significant difference in the efficacy and safety of TLH with or without uterine manipulator combined with pelvic lymphadenectomy in the treatment of patients with early-stage CC. However, the latter requires consideration of the negative effects of high operation time and blood loss.

Temporal Progress and Spatial Patterns of Northern Corn Leaf Blight in Corn Fields in China.

Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, is a devastating disease of corn in China. To enhance our understanding of NCLB epidemiology, the temporal progress and spatial patterns of NCLB were investigated. A susceptible corn cultivar, Xianyu 335, was planted in a field in Beijing in 2016 and 2017. Leaf lesions of NCLB on each plant were counted twice a week during the growing seasons. In addition, temporal disease progress was monitored for 8 weeks in three commercial corn fields in each of Yanqing, Miyun, Daxing, and Haidian Districts of Beijing in 2017, and the spatial patterns of diseased plants and NCLB lesion counts per plant were assessed in three commercial corn fields with moderate to high NCLB incidence in Yanqing District. The results demonstrated that a logistic model was the most appropriate to describe the temporal progress of NCLB incidence. The initial disease incidence was the key factor affecting disease epidemics under various conditions in the four districts of Beijing during the study. The higher the initial incidence of NCLB, the higher the final incidence. Thus, the earlier in the season NCLB incidence attained 1%, the higher was the final disease incidence. Greater than 1.0 variance-to-mean ratios suggested that the leaf lesions of NCLB tended to be aggregated on a plant. According to results from join-counts, variance of moving window averages, and semivariogram analysis, diseased corn plants and lesion numbers on each plant were aggregated in the field. The clustered pattern of NCLB lesions and infected plants suggested that conidia produced locally on diseased plants were important for disease spread within the field. The aggregated pattern of diseased plants suggested that plants should be sampled from more sites in a field to accurately estimate incidence of NCLB.

Evaluation of Rice Responses to the Blast Fungus Magnaporthe oryzae at Different Growth Stages.

Rice blast, caused by the fungus Magnaporthe oryzae, is the most damaging disease for rice worldwide. However, the reactions of rice to M. oryzae at different growth stages are largely unknown. In the present study, two temperate japonica rice cultivars, M-202 and Nipponbare, were inoculated synchronously at different vegetative growth stages, V1 to V10. Plants of M-202 at each stage from V1 to reproductive stage R8 were inoculated with M. oryzae race (isolate) IB-49 (ZN61) under controlled conditions. Disease reactions were recorded 7 days postinoculation by measuring the percentage of diseased area of all leaves, excluding the youngest leaf. The results showed that the plants were significantly susceptible at the V1 to V4 stages with a disease severity of 26.7 to 46.8% and disease index of 18.62 to 37.76 for M-202. At the V1 to V2 stages, the plants were significantly susceptible with a disease a severity of 28.6 to 39.3% and disease index of 23.65 to 29.82 for Nipponbare. Similar results were observed when plants of M-202 were inoculated at each growth stage with a disease severity of 29.7 to 60.6% and disease index of 21.93 to 59.25 from V1 to V4. Susceptibility decreased after the V5 stage (severity 4.6% and index 2.17) and became completely resistant at the V9 to V10 stages and after the reproductive stages, suggesting that plants have enhanced disease resistance at later growth stages. These findings are useful for managing rice blast disease in commercial rice production worldwide.

Spatial Analysis of Rice Blast in China at Three Different Scales.

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At the regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from 10 June to 10 September during 2009 to 2014, and surveyed in 143 fields in September 2016; at the county scale, three surveys were done covering one to five counties in 2015 to 2016; and, at the field scale, blast was evaluated in six fields in 2015 to 2016. Spatial cluster and hot spot analyses were conducted in the geographic information system on the geographical pattern of the disease at regional scale, and geostatistical analysis was performed at all three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1,080 km at regional scale and 5 to 10 m at field scale but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Dynamics of verticillium species microsclerotia in field soils in response to fumigation, cropping patterns, and flooding.

Verticillium dahliae is a soilborne, economically significant fungal plant pathogen that persists in the soil for up to 14 years as melanized microsclerotia (ms). Similarly, V. longisporum is a very significant production constraint on members of the family Brassicaceae. Management of Verticillium wilt has relied on methods that reduce ms below crop-specific thresholds at which little or no disease develops. Methyl bromide, a broad-spectrum biocide, has been used as a preplant soil fumigant for over 50 years to reduce V. dahliae ms. However, reductions in the number of ms in the vertical and horizontal soil profiles and the rate at which soil recolonization occurs has not been studied. The dynamics of ms in soil before and after methyl bromide+chloropicrin fumigation were followed over 3 years in six 8-by-8-m sites in two fields. In separate fields, the dynamics of ms in the 60-cm-deep vertical soil profile pre- and postfumigation with methyl bromide+chloropicrin followed by various cropping patterns were studied over 4 years. Finally, ms densities were assessed in six 8-by-8-m sites in a separate field prior to and following a natural 6-week flood. Methyl bromide+chloripicrin significantly reduced but did not eliminate V. dahliae ms in either the vertical or horizontal soil profiles. In field studies, increases in ms were highly dependent upon the crop rotation pattern followed postfumigation. In the vertical soil profile, densities of ms were highest in the top 5 to 20 cm of soil but were consistently detected at 60-cm depths. Six weeks of natural flooding significantly reduced (on average, approximately 65% in the total viable counts of ms) but did not eliminate viable ms of V. longisporum.

Cell-free DNA testing for early hepatocellular carcinoma surveillance.

BACKGROUND: Liver cirrhosis (LC) is the highest risk factor for hepatocellular carcinoma (HCC) development worldwide. The efficacy of the guideline-recommended surveillance methods for patients with LC remains unpromising. METHODS: A total of 4367 LCs not previously known to have HCC and 510 HCCs from 16 hospitals across 11 provinces of China were recruited in this multi-center, large-scale, cross-sectional study. Participants were divided into Stage Ⅰ cohort (510 HCCs and 2074 LCs) and Stage Ⅱ cohort (2293 LCs) according to their enrollment time and underwent Tri-phasic CT/enhanced MRI, US, AFP, and cell-free DNA (cfDNA). A screening model called PreCar Score was established based on five features of cfDNA using Stage Ⅰ cohort. Surveillance performance of PreCar Score alone or in combination with US/AFP was evaluated in Stage Ⅱ cohort. FINDINGS: PreCar Score showed a significantly higher sensitivity for the detection of early/very early HCC (Barcelona stage A/0) in contrast to US (sensitivity of 51.32% [95% CI: 39.66%-62.84%] at 95.53% [95% CI: 94.62%-96.38%] specificity for PreCar Score; sensitivity of 23.68% [95% CI: 14.99%-35.07%] at 99.37% [95% CI: 98.91%-99.64%] specificity for US) (P < 0.01, Fisher's exact test). PreCar Score plus US further achieved a higher sensitivity of 60.53% at 95.08% specificity for early/very early HCC screening. INTERPRETATION: Our study developed and validated a cfDNA-based screening tool (PreCar Score) for HCC in cohorts at high risk. The combination of PreCar Score and US can serve as a promising and practical strategy for routine HCC care. FUNDING: A full list of funding bodies that contributed to this study can be found in Acknowledgments section.

The development of a cSMART-based integrated model for hepatocellular carcinoma diagnosis.

BACKGROUND: Hepatocellular carcinoma (HCC) generally arises from a background of liver cirrhosis (LC). Patients with cirrhosis and suspected HCC are recommended to undergo serum biomarker tests and imaging diagnostic evaluation. However, the performance of routine diagnostic methods in detecting early HCC remains unpromising. METHODS: Here, we conducted a large-scale, multicenter study of 1675 participants including 490 healthy controls, 577 LC patients, and 608 HCC patients from nine clinical centers across nine provinces of China, profiled gene mutation signatures of cell-free DNA (cfDNA) using Circulating Single-Molecule Amplification and Resequencing Technology (cSMART) through detecting 931 mutation sites across 21 genes. RESULTS: An integrated diagnostic model called "Combined method" was developed by combining three mutation sites and three serum biomarkers. Combined method outperformed AFP in the diagnosis of HCC, especially early HCC, with sensitivities of 81.25% for all stages and 66.67% for early HCC, respectively. Importantly, the integrated model exhibited high accuracy in differentiating AFP-negative, AFP-L3-negative, and PIVKA-II-negative HCCs from LCs.

Effects of Image Dataset Configuration on the Accuracy of Rice Disease Recognition Based on Convolution Neural Network.

In recent years, the convolution neural network has been the most widely used deep learning algorithm in the field of plant disease diagnosis and has performed well in classification. However, in practice, there are still some specific issues that have not been paid adequate attention to. For instance, the same pathogen may cause similar or different symptoms when infecting plant leaves, while the same pathogen may cause similar or disparate symptoms on different parts of the plant. Therefore, questions come up naturally: should the images showing different symptoms of the same disease be in one class or two separate classes in the image database? Also, how will the different classification methods affect the results of image recognition? In this study, taking rice leaf blast and neck blast caused by Magnaporthe oryzae, and rice sheath blight caused by Rhizoctonia solani as examples, three experiments were designed to explore how database configuration affects recognition accuracy in recognizing different symptoms of the same disease on the same plant part, similar symptoms of the same disease on different parts, and different symptoms on different parts. The results suggested that when the symptoms of the same disease were the same or similar, no matter whether they were on the same plant part or not, training combined classes of these images can get better performance than training them separately. When the difference between symptoms was obvious, the classification was relatively easy, and both separate training and combined training could achieve relatively high recognition accuracy. The results also, to a certain extent, indicated that the greater the number of images in the training data set, the higher the average classification accuracy.

Stem and Crown Rot of Chickpea in California Caused by Sclerotinia trifoliorum.

The identities of Sclerotinia isolates obtained from chickpea plants showing stem and crown rot were determined using morphological characteristics, variations in group I introns, and internal transcribed spacer (ITS) sequences. Isolates could be separated into two groups based on growth rates at 22°C, fast growing (about 40 mm per day) versus slow growing (about 20 mm per day). All fast-growing isolates induced stronger color change of a pH-indicating medium than did slow-growing isolates at 22°C. The slow-growing isolates contained at least one group I intron in the nuclear small subunit rDNA, whereas all fast-growing isolates lacked group I introns in the same DNA region. ITS sequences of the slow-growing isolates were identical to sequences of Sclerotinia trifoliorum. Those of the fast-growing isolates were identical to sequences of S. sclerotiorum. Finally, the slow-growing isolates showed ascospore dimorphism, a definitive character of S. trifoliorum, whereas the fast-growing isolates showed no ascospore dimorphism. Isolates of both species were pathogenic on chickpea and caused symptoms similar to those observed in the field. This study not only associated the differences between S. sclerotiorum and S. trifoliorum in growth rates, group I introns, ITS sequences, and ascospore morphology, but also represented the first report that S. trifoliorum causes stem and crown rot of chickpea in North America.

Phylogenetic Analyses of Phytopathogenic Isolates of Verticillium spp.

ABSTRACT To better understand the genetic relationships between Verticillium dahliae isolates from lettuce and other phytopathogenic Verticillium spp. isolates from various hosts and geographic locations, the complete intergenic spacer (IGS) region of the nuclear ribosomal RNA gene (rDNA) and the beta-tubulin gene were amplified and sequenced. The sequences of the complete IGS region and the beta-tubulin gene were used alone and in combination to infer genetic relationships among different isolates of Verticillium with the maximum-likelihood distance method. Phylogenetic analyses set sequences into four distinct groups comprising isolates of V. albo-atrum, V. tricorpus, and V. dahliae from cruciferous and noncruciferous hosts. Within the four Verticillium groups, isolates of V. dahliae from cruciferous hosts displayed the closest affinity to V. dahliae from noncruciferous hosts. Isolates of V. dahliae from noncruciferous hosts could be further divided into four subgroups based on sequence similarities within the IGS region. Cross-pathogenicity tests demonstrated that most Verticillium isolates were as virulent on other hosts as on their hosts of origin. A phenogram based on the cross pathogenicity of individual isolates resembled those derived from the IGS and beta-tubulin sequence comparisons. On the basis of the data presented, the potential origin of some isolates of V. dahliae pathogenic on lettuce is proposed.

The Sclerotinia sclerotiorum mating type locus (MAT) contains a 3.6-kb region that is inverted in every meiotic generation.

Sclerotinia sclerotiorum is a fungal plant pathogen and the causal agent of lettuce drop, an economically important disease of California lettuce. The structure of the S. sclerotiorum mating type locus MAT has previously been reported and consists of two idiomorphs that are fused end-to-end as in other homothallics. We investigated the diversity of S. sclerotiorum MAT using a total of 283 isolates from multiple hosts and locations, and identified a novel MAT allele that differed by a 3.6-kb inversion and was designated Inv+, as opposed to the previously known S. sclerotiorum MAT that lacked the inversion and was Inv-. The inversion affected three of the four MAT genes: MAT1-2-1 and MAT1-2-4 were inverted and MAT1-1-1 was truncated at the 3'-end. Expression of MAT genes differed between Inv+ and Inv- isolates. In Inv+ isolates, only one of the three MAT1-2-1 transcript variants of Inv- isolates was detected, and the alpha1 domain of Inv+ MAT1-1-1 transcripts was truncated. Both Inv- and Inv+ isolates were self-fertile, and the inversion segregated in a 1∶1 ratio regardless of whether the parent was Inv- or Inv+. This suggested the involvement of a highly regulated process in maintaining equal proportions of Inv- and Inv+, likely associated with the sexual state. The MAT inversion region, defined as the 3.6-kb MAT inversion in Inv+ isolates and the homologous region of Inv- isolates, was flanked by a 250-bp inverted repeat on either side. The 250-bp inverted repeat was a partial MAT1-1-1 that through mediation of loop formation and crossing over, may be involved in the inversion process. Inv+ isolates were widespread, and in California and Nebraska constituted half of the isolates examined. We speculate that a similar inversion region may be involved in mating type switching in the filamentous ascomycetes Chromocrea spinulosa, Sclerotinia trifoliorum and in certain Ceratocystis species.