Process-based dynamic identification indicators of soybean chilling damage and analysis of the corresponding spatiotemporal characteristics in Northeast China.

Northeast China (NEC) is one of the main soybean-producing areas among the northern-latitude regions. Climate warming leads to frequent extreme disasters, and the threat of chilling damage to soybean production in NEC cannot be ignored. The study aimed to construct a dynamic disaster identification index based on the static evaluation of soybean after the disaster, taking into account the process of soybean chilling damage and using the historical disaster records to realize the dynamic prediction and analysis before the disaster. Taking soybean in NEC as the research object, chilling damage indicators of soybeans in NEC were constructed by dividing the mature regions, using daily temperature anomaly and negative temperature anomaly day data with the comprehensive consideration of the chilling damage intensity, duration, and temperature recovery. The results showed that the comprehensive indicators determined by the cumulative value of temperature anomaly-the cumulative days of negative temperature anomaly had better applicability in NEC than the single factor indicator. The indicator results were basically consistent with the historical disaster records, and the accuracy rate of the indicator verification reached 90.9%. Based on the analysis of the constructed indicators, the frequency of delayed chilling damage in NEC showed a fluctuating downward trend from 1961 to 2020. The station ratio of delayed chilling damage in NEC showed a fluctuating downward trend, with the most obvious downward trend occurring for severe damage, followed by moderate damage, and the least obvious trend observed for light damage. The scope of chilling damage gradually narrowed, with the frequency increasing from southeast to northwest. The high-risk areas of chilling damage were concentrated mainly in the northern part of Heilongjiang Province and the East Four Leagues. The risk of chilling damage in most areas of Jilin Province and Liaoning Province was relatively low. The study results provide basic support for the risk research of soybean chilling damage and for ensuring disaster monitoring and early warnings, and the risk assessment based on the chilling damage process has positive significance for adjusting agricultural structure and improving the distribution of soybean varieties.

Comparative study of visual function and ocular aberrations of two different one-piece designed hydrophilic acrylic intraocular lens.

PURPOSE: To determine whether the aspherical IOL, Tecnis ZCB00, can improve the visual quality by measuring visual acuity, wavefront aberrations, and contrast sensitivity. METHODS: It was a retrospective case series. Patients who underwent phacoemulsification cataract surgery were divided into two groups. One group (Group TC) was implanted with one-piece aspherical acrylic IOL (Tecnis ZCB00, AMO); the other (Group SA) was implanted with one-piece spherical acrylic IOL (Sensar AAB00, AMO). Eighty-eight eyes were selected into this study, among them 43 eyes in 26 male cases and 45 eyes in 29 female cases. Thirty-six eyes in 23 cases were in Group TC, and 52 eyes in 32 cases were in Group SA. Three months postoperatively, aberrations were analyzed with i-Trace visual function analyzer (Tracy Technologies, USA). Contrast sensitivities were measured with Takaci-CGT-1000 contrast glare tester (Seiko, Japan). RESULTS: All the 88 eyes underwent phacoemulsification with intraocular lens implantation, without complications during or after surgery. Three months postoperatively, the uncorrected vision acuity in Group TC was significantly better than in Group SA (P = 0.007). At the pupil size of 5.0 mm, higher-order aberrations in Group TC were significantly higher than in Group SA (P = 0.02), especially the spherical aberration (Z 40 ) (P < 0.001); at the pupil size of 4.0 mm, Z 40 in Group SA was statistically higher than in Group TC (P < 0.001); at the pupil size of 3.0 mm, higher-order aberrations such as coma (Z 3-1,1 ) and trefoil aberration (Z 3-3,3 ) in Group SA were obviously higher than in Group TC (P = 0.01). In the low spatial frequency, the contrast sensitivity and the glare sensitivity in Group TC were significantly higher than in Group SA (P < 0.05). CONCLUSIONS: By the short-term follow-up (3 months), the aspherical acrylic IOL can reduce the higher-order aberrations (especially the spherical aberration) and increase the contrast sensitivity to improve the visual performance.

MicroBundleCompute: Automated segmentation, tracking, and analysis of subdomain deformation in cardiac microbundles.

Advancing human induced pluripotent stem cell derived cardiomyocyte (hiPSC-CM) technology will lead to significant progress ranging from disease modeling, to drug discovery, to regenerative tissue engineering. Yet, alongside these potential opportunities comes a critical challenge: attaining mature hiPSC-CM tissues. At present, there are multiple techniques to promote maturity of hiPSC-CMs including physical platforms and cell culture protocols. However, when it comes to making quantitative comparisons of functional behavior, there are limited options for reliably and reproducibly computing functional metrics that are suitable for direct cross-system comparison. In addition, the current standard functional metrics obtained from time-lapse images of cardiac microbundle contraction reported in the field (i.e., post forces, average tissue stress) do not take full advantage of the available information present in these data (i.e., full-field tissue displacements and strains). Thus, we present "MicroBundleCompute," a computational framework for automatic quantification of morphology-based mechanical metrics from movies of cardiac microbundles. Briefly, this computational framework offers tools for automatic tissue segmentation, tracking, and analysis of brightfield and phase contrast movies of beating cardiac microbundles. It is straightforward to implement, runs without user intervention, requires minimal input parameter setting selection, and is computationally inexpensive. In this paper, we describe the methods underlying this computational framework, show the results of our extensive validation studies, and demonstrate the utility of exploring heterogeneous tissue deformations and strains as functional metrics. With this manuscript, we disseminate "MicroBundleCompute" as an open-source computational tool with the aim of making automated quantitative analysis of beating cardiac microbundles more accessible to the community.

MicroBundlePillarTrack: A Python package for automated segmentation, tracking, and analysis of pillar deflection in cardiac microbundles.

Movies of human induced pluripotent stem cell (hiPSC)-derived engineered cardiac tissue (microbundles) contain abundant information about structural and functional maturity. However, extracting these data in a reproducible and high-throughput manner remains a major challenge. Furthermore, it is not straightforward to make direct quantitative comparisons across the multiple in vitro experimental platforms employed to fabricate these tissues. Here, we present "MicroBundlePillarTrack," an open-source optical flow-based package developed in Python to track the deflection of pillars in cardiac microbundles grown on experimental platforms with two different pillar designs ("Type 1" and "Type 2" design). Our software is able to automatically segment the pillars, track their displacements, and output time-dependent metrics for contractility analysis, including beating amplitude and rate, contractile force, and tissue stress. Because this software is fully automated, it will allow for both faster and more reproducible analyses of larger datasets and it will enable more reliable cross-platform comparisons as compared to existing approaches that require manual steps and are tailored to a specific experimental platform. To complement this open-source software, we share a dataset of 1,540 brightfield example movies on which we have tested our software. Through sharing this data and software, our goal is to directly enable quantitative comparisons across labs, and facilitate future collective progress via the biomedical engineering open-source data and software ecosystem.

MicroBundlePillarTrack: A Python package for automated segmentation, tracking, and analysis of pillar deflection in cardiac microbundles.

Movies of human induced pluripotent stem cell (hiPSC)-derived engineered cardiac tissue (microbundles) contain abundant information about structural and functional maturity. However, extracting these data in a reproducible and high-throughput manner remains a major challenge. Furthermore, it is not straightforward to make direct quantitative comparisons across the multiple in vitro experimental platforms employed to fabricate these tissues. Here, we present "MicroBundlePillarTrack," an open-source optical flow-based package developed in Python to track the deflection of pillars in cardiac microbundles grown on experimental platforms with two different pillar designs ("Type 1" and "Type 2" design). Our software is able to automatically segment the pillars, track their displacements, and output time-dependent metrics for contractility analysis, including beating amplitude and rate, contractile force, and tissue stress. Because this software is fully automated, it will allow for both faster and more reproducible analyses of larger datasets and it will enable more reliable cross-platform comparisons as compared to existing approaches that require manual steps and are tailored to a specific experimental platform. To complement this open-source software, we share a dataset of 1,540 brightfield example movies on which we have tested our software. Through sharing this data and software, our goal is to directly enable quantitative comparisons across labs, and facilitate future collective progress via the biomedical engineering open-source data and software ecosystem.

Transcriptome analysis reveals key drought-stress-responsive genes in soybean.

Drought is the most common environmental stress and has had dramatic impacts on soybean (Glycine max L.) growth and yield worldwide. Therefore, to investigate the response mechanism underlying soybean resistance to drought stress, the drought-sensitive cultivar "Liaodou 15" was exposed to 7 (mild drought stress, LD), 17 (moderate drought stress, MD) and 27 (severe drought stress, SD) days of drought stress at the flowering stage followed by rehydration until harvest. A total of 2214, 3684 and 2985 differentially expressed genes (DEGs) in LD/CK1, MD/CK2, and SD/CK3, respectively, were identified by RNA-seq. Weighted gene co-expression network analysis (WGCNA) revealed the drought-response TFs such as WRKY (Glyma.15G021900, Glyma.15G006800), MYB (Glyma.15G190100, Glyma.15G237900), and bZIP (Glyma.15G114800), which may be regulated soybean drought resistance. Second, Glyma.08G176300 (NCED1), Glyma.03G222600 (SDR), Glyma.02G048400 (F3H), Glyma.14G221200 (CAD), Glyma.14G205200 (C4H), Glyma.19G105100 (CHS), Glyma.07G266200 (VTC) and Glyma.15G251500 (GST), which are involved in ABA and flavonoid biosynthesis and ascorbic acid and glutathione metabolism, were identified, suggesting that these metabolic pathways play key roles in the soybean response to drought. Finally, the soybean yield after rehydration was reduced by 50% under severe drought stress. Collectively, our study deepens the understanding of soybean drought resistance mechanisms and provides a theoretical basis for the soybean drought resistance molecular breeding and effectively adjusts water-saving irrigation for soybean under field production.

Multifactor effects on the N2O emissions and yield of potato fields based on the DNDC model.

Maintaining or increasing grain yields while also reducing the emissions of field agricultural greenhouse gases is an important objective. To explore the multifactor effects of nitrogen fertilizer on nitrous oxide (N2O) emissions and the yield of potato fields and to verify the applicability of the denitrification-decomposition (DNDC) model when used to project the N2O emission load and yield, this research chooses a potato field in Shenyang northeast China from 2017 to 2019 as the experiment site. The experiment includes four nitrogen levels observing the emission of N2O by static chamber/gas chromatograph techniques. The results of this study are as follows: (1) DNDC has a good performance regarding the projection of N2O emissions and yields. The model efficiency index EFs were 0.45 ~ 0.88 for N2O emissions and 0.91, 0.85, and 0.85 for yields from 2017 to 2019. (2) The annual precipitation, soil organic carbon, and soil bulk density had the most significant influence on the accumulated N2O emissions during the growth period of potatoes. The annual precipitation, annual average temperature, and CO2 mass concentration had the most significant influences on yield. (3) Under the premise of a normal water supply, sowing potatoes within 5 days after the 5-day sliding average temperature in this area exceeds 10℃ can ensure the temperature required for the normal growth of potatoes and achieve the purpose of maintaining and increasing yield. (4) The application of 94.5 kg·hm-2 nitrogen and 15 mm irrigation represented the best results for reducing N2O emissions while also maintaining the yield in potato fields.

[Establishment of indices for soybean low temperature damages in key growth stage in high cold region]. / é«˜å¯’åŒºå¤§è±†å ³é”®ç”Ÿè‚²æœŸä½Žæ¸©å†·å®³æŒ‡æ ‡æž„å»º.

Establishment of indices for low temperature damage of soybeans is important for systematically analyzing the adaptation strategies to climate change and collaborative adaptation technology for disaster prevention and mitigation and other stresses in high cold region. Based on historical data of low temperature damage and phenophase of soybean from 1980 to 2020 and daily temperature data from 78 meteorological stations in Heilongjiang Province, we used GIS to match the phenophase and meteorological data, by considering the accumulated temperature anomaly in different growth stages, and constructed a comprehensive soybean low temperature damages index (CSCDI) in high cold region. Using K-S distribution fitting test and the lower limit value of confidence intervals, we constructed the level index of soybean low temperature damage. The results showed that the CSCDI lower limits of mild, moderate and severe low temperature damage were 0.061, 0.115 and 0.237 from sowing to emergence stage, were 0.072, 0.152 and 0.312 from emergence to flowering, and 0.133, 0.245 and 0.412 from flowering to maturity, respectively. The time distribution of soybean low temperature damage inversed by CSCDI in Heilongjiang Province was consistent with the historical disaster records. The spatial distribution showed obvious latitude characteristics, with the frequency of low temperature damage increasing gradually from south to north.