Effects of Potassium Bicarbonate on Gel, Antioxidant and Water Distribution of Reduced-Phosphate Silver Carp Surimi Batter under Cold Storage.

The changes in storage loss, water distribution status, gel characteristics, thiobarbituric acid reactive substances (TBARSs), total volatile basic nitrogen, and total plate count of cooked reduced-phosphate silver carp surimi batter during cold storage at 4 °C were investigated. The storage loss, content of free water, pH, hardness, TBARSs, total volatile basic nitrogen value, and total plate count of all cooked silver carp surimi batters significantly increased (p < 0.05) with an increase in cold storage time. Meanwhile, the content of immobilized water, whiteness, springiness, and cohesiveness significantly decreased (p < 0.05). At the same cold storage time, the sample of cooked reduced-phosphate silver carp surimi batter had lower water mobility, darker color, and better texture characteristics than the cooked silver carp surimi batter without potassium bicarbonate; however, the values of TBARSs, total volatile basic nitrogen, and total plate count were not significantly different (p > 0.05). This meant that there was no difference between potassium bicarbonate and sodium tripolyphosphate in antioxidant and antibacterial activity during the cold storage of silver carp surimi batter. To summarize, the use of potassium bicarbonate instead of sodium tripolyphosphate could produce cooked reduced-phosphate silver carp surimi batter with better water-holding capacity and gel characteristics during cold storage.

KASP-IEva: an intelligent typing evaluation model for KASP primers.

KASP marker technology has been used in molecular marker-assisted breeding because of its high efficiency and flexibility, and an intelligent evaluation model of KASP marker primer typing results is essential to improve the efficiency of marker development on a large scale. To this end, this paper proposes a gene population delineation method based on NTC identification module and data distribution judgment module to improve the accuracy of K-Means clustering, and introduces a decision tree to construct the KASP-IEva primer typing evaluation model. The model firstly designs the NTC identification module and data distribution judgment module to extract four types of data, grouping and categorizing to achieve the improvement of the distinguishability of amplification product signals; secondly, the K-Means algorithm is used to aggregate and classify the data, to visualize the five aggregated clusters and to obtain the morphology location eigenvalues; lastly, the evaluation criteria for the typing effect level are constructed, and the logical decision tree is used to make conditional discrimination on the eigenvalues in order to realize the score prediction. The performance of the model was tested by the KASP marker typing test results of 2519 groups of cotton varieties, and the following conclusions were obtained: the model is able to visualize the aggregation and classification effects of the amplification products of NTC, pure genotypes, heterozygous genotypes, and untyped genotypes, enabling rapid and accurate KASP marker typing evaluation. Comparing and analyzing the model evaluation results with the expert evaluation results, the average accuracy rate of the four grades evaluated by the model was 87%, and the overall evaluation results showed an uneven distribution of the grades with significant differential characteristics. When evaluating 2519 KASP fractal maps, the expert evaluation consumes 15 hours, and the model evaluation only uses 8min27.45s, which makes the model intelligent evaluation significantly better than the expert evaluation from the perspective of time. The establishment of the model will further enhance the application of KASP markers in molecular marker-assisted breeding and provide technical support for the large-scale screening and identification of excellent genotypes.

Haploidentical donor stem cell transplantation had a lower incidence of bronchiolitis obliterans syndrome compared with HLA-matched sibling donor transplantation in patients with hematologic malignancies: Benefit from ATG?

Background: Haploidentical donor stem cell transplantation (HID-SCT) based on antithymocyte globulin (ATG) for graft-versus-host disease (GVHD) prophylaxis had achieved a similar incidence of chronic graft-versus-host disease (cGVHD) with human leukocyte antigen (HLA)-matched sibling donor stem cell transplantation (MSD-SCT). However, bronchiolitis obliterans syndrome (BOS), which serves as pulmonary cGVHD, was rarely compared between HID and MSD transplantation. Methods: One thousand four hundred five patients with hematologic malignancies who underwent allogeneic SCT were enrolled in this retrospective study. Based on donor type, we divided the patients into three groups: HID, MSD, and match unrelated donor (MUD) groups. The cumulative incidences and risk factors of BOS were analyzed. Results: The 5-year cumulative incidence of BOS was 7.2% in the whole population. HID transplantation had a lower 5-year cumulative incidence of BOS than MSD transplantation (4.1% vs. 10.0%, p < 0.001) and a similar incidence with MUD transplantation (4.1% vs. 6.2%, p = 0.224). The 5-year cumulative incidence of BOS was lower in the ATG group than that in the non-ATG group in both the whole and MSD populations (4.6% vs. 11.2%, p < 0.001, and 4.1% vs. 11.2%, p = 0.042, respectively). The 5-year incidence of BOS in mixed grafts [peripheral blood stem cell (PBSC) plus bone marrow] group was also lower than that in the PBSC group (4.2% vs. 9.1, p = 0.001). Multivariate analysis showed that HID, ATG, and mixed grafts were protective factors for BOS [odds ratio (OR) 0.3, 95% CI 0.2-0.6, p < 0.001; OR 0.3, 95% CI 0.2-0.7, p = 0.001; OR 0.3, 95% CI 0.1-0.8, p = 0.013], and acute graft-versus-host disease (aGVHD) and cGVHD were independent risk factors for BOS (OR 2.1, 95% 1.1-4.3, p = 0.035; OR 10.1, 95% CI 4.0-25.0, p < 0.001). Conclusions: HID transplantation had a lower incidence of BOS than MSD transplantation, which might be associated with ATG and mixed grafts.

DA-ActNN-YOLOV5: Hybrid YOLO v5 Model with Data Augmentation and Activation of Compression Mechanism for Potato Disease Identification.

To solve the problems of weak generalization of potato early and late blight recognition models in real complex scenarios, susceptibility to interference from crop varieties, colour characteristics, leaf spot shapes, disease cycles and environmental factors, and strong dependence on storage and computational resources, an improved YOLO v5 model (DA-ActNN-YOLOV5) is proposed to study potato diseases of different cycles in multiple regional scenarios. Thirteen data augmentation techniques were used to expand the data to improve model generalization and prevent overfitting; potato leaves were extracted by YOLO v5 image segmentation and labelled with LabelMe for building data samples; the component modules of the YOLO v5 network were replaced using model compression technology (ActNN) for potato disease detection when the device is low on memory. Based on this, the features extracted from all network layers are visualized, and the extraction of features from each network layer can be distinguished, from which an understanding of the feature learning behavior of the deep model can be obtained. The results show that in the scenario of multiple complex factors interacting, the identification accuracy of early and late potato blight in this study reached 99.81%. The introduced data augmentation technique improved the average accuracy by 9.22%. Compared with the uncompressed YOLO v5 model, the integrated ActNN runs more efficiently, the accuracy loss due to compressed parameters is less than 0.65%, and the time consumption does not exceed 30 min, which saves a lot of computational cost and time. In summary, this research method can accurately identify potato early and late blight in various scenarios.

An Industrial-Grade Solution for Crop Disease Image Detection Tasks.

Crop leaf diseases can reflect the current health status of the crop, and the rapid and automatic detection of field diseases has become one of the difficulties in the process of industrialization of agriculture. In the widespread application of various machine learning techniques, recognition time consumption and accuracy remain the main challenges in moving agriculture toward industrialization. This article proposes a novel network architecture called YOLO V5-CAcT to identify crop diseases. The fast and efficient lightweight YOLO V5 is chosen as the base network. Repeated Augmentation, FocalLoss, and SmoothBCE strategies improve the model robustness and combat the positive and negative sample ratio imbalance problem. Early Stopping is used to improve the convergence of the model. We use two technical routes of model pruning, knowledge distillation and memory activation parameter compression ActNN for model training and identification under different hardware conditions. Finally, we use simplified operators with INT8 quantization for further optimization and deployment in the deep learning inference platform NCNN to form an industrial-grade solution. In addition, some samples from the Plant Village and AI Challenger datasets were applied to build our dataset. The average recognition accuracy of 94.24% was achieved in images of 59 crop disease categories for 10 crop species, with an average inference time of 1.563 ms per sample and model size of only 2 MB, reducing the model size by 88% and the inference time by 72% compared with the original model, with significant performance advantages. Therefore, this study can provide a solid theoretical basis for solving the common problems in current agricultural disease image detection. At the same time, the advantages in terms of accuracy and computational cost can meet the needs of agricultural industrialization.

Combined effects of high-pressure processing and pre-emulsified sesame oil incorporation on physical, chemical, and functional properties of reduced-fat pork batters.

In this study, the changes in emulsion stability, colour, textural properties, and protein secondary structure of reduced-fat pork batters (50% pork back-fat and 50% pre-emulsified sesame oil) treated under different pressures (0.1, 200 and 400 MPa) were investigated. The emulsion stability, cooking yield, L* value, texture properties, initial relaxation times of T2b, T21, and T22, and peak ratios of P21 in the samples treated under 200 and 400 MPa significantly increased (p < 0.05) compared with those at 0.1 MPa, but the a* and b* values, and the peak ratio of P22 significantly decreased (p < 0.05). The sample treated at 200 MPa exhibited the best emulsion stability, textural properties, water-holding capacity and sensory scores among the samples. High-pressure processing induced structural changes from α-helical to ß-sheet, ß-turn, and random coil structures, enhancing protein-water incorporation and lowering water mobility. High-pressure processing and pre-emulsified sesame oil improved the techno-functional properties and emulsion stability of reduced-fat pork batters.

Oral eltrombopag versus subcutaneous recombinant human thrombopoietin for promoting platelet engraftment after allogeneic stem cell transplantation: A prospective, non-inferiority, randomized controlled trial.

Delayed platelet engraftment (DPE) is associated with poor survival and increased transplantation-related mortality after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Therefore, treatments are needed to improve platelet engraftment and prevent DPE. We performed a phase three, non-inferior, randomized controlled study of eltrombopag or recombinant human thrombopoietin (rhTPO) to promot platelet engraftment after allo-HSCT. Candidates for allo-HSCT were randomly assigned to receive oral eltrombopag (50 mg daily) or subcutaneous rhTPO (15000U daily) from the first-day post-transplantation. The primary endpoint was the cumulative numbers of platelet engraftment (platelet recovery ≥20 × 109 /L, without transfusion, for seven consecutive days) on day 60 after transplantation. We performed intention-to-treat analyses with a non-inferior margin of -15%. A total of 92 participants underwent randomization. 44 and 48 patients were randomized to the eltrombopag and rhTPO groups, respectively. The median duration of follow-up was 360 days (range: 12-960 days). The cumulative incidence of platelet engraftment on day 60 after transplantation in eltrombopag group was 86.4% (38/44) compared with 85.4% (41/48) in the rhTPO group (absolute risk difference [ARD] 1%, one-sided lower limit of 95% confidence interval [CI] -13.28%, Pnon-inferirioty  = 0.014). The rate of DPE in the eltrombopag group was 6.8% (3/44) compared with 12.5% (6/48) in the rhTPO group (ARD -5.7%, one-sided higher limit of 95% CI 6.28%, Pnon-inferirioty  = 0.063). Approximately, three-fourths of non-hematologic adverse events were not observed in the eltrombopag group but three patients (3/48, 6%) experienecd them in the rhTPO group. In addition, platelet transfusions unite from day 0 to day 21, or from day 22 to day 60, progression-free survival, overall survival were not significantly different between both groups. Eltrombopag was non-inferior to rhTPO in promoting platelet engraftment post allo-HSCT for patients with hematological malignancy. Oral eltrombopag was more convenient for patients than subcutaneous rhTPO (NCT03515096).