Melatonin enhances biomass, phenolic accumulation, and bioactivities of rosemary (Rosmarinus officinalis) in vitro shoots under UV-B stress.

Melatonin is a stress-related hormone that plays a critical role in triggering the plant defence system and regulating secondary metabolism when plants are exposed to stress. To explore the potential roles of melatonin in response to Ultraviolet-B (UV-B) radiation, we examined the effects of exogenous melatonin on rosemary in vitro shoots under UV-B stress. The application of melatonin (50 µM) alleviated the adverse effects of UV-B stress on the biomass, photosynthetic pigment contents, and membrane lipids of the rosemary in vitro shoots. Melatonin significantly increased superoxide dismutase (1.15.1.1, SOD), peroxidase (1.11.1.7, POD), and catalase (1.11.1.6, CAT) activities by 62%, 99%, and 53%, respectively. The contents of total phenols, rosmarinic acid, and carnosic acid increased under UV-B stress, and they further increased by the melatonin treatment by 41%, 68%, and 67%, respectively, compared with the control group. Under UV-B stress, the increased total phenol content in melatonin-pretreated plants could be attributed to the activation of phenylalanine ammonia-lyase (4.3.1.5, PAL) and tyrosine aminotransferase (2.6.1.5, TAT). In addition, melatonin enhanced the antioxidant and antibacterial activities of the rosemary in vitro shoots under UV-B stress. These results suggest that melatonin can alleviate the damage caused by UV-B stress and also enhance the secondary metabolism and bioactivity of rosemary in vitro shoots.

Development of Single-Segment Substitution Lines and Fine-Mapping of qSPP4 for Spikelets Per Panicle and qGW9 for Grain Width Based on Rice Dual-Segment Substitution Line Z783.

Single segment substitution line (SSSL) libraries are an ideal platform for breeding by design. To develop SSSLs-Xihui18 covering the whole genome, a novel rice chromosome segment substitution line (CSSL), Z783, carrying two substitution segments (average length of 6.55 Mb) on Chr.4 and Chr.9 was identified, which was a gap in the library previously. Z783 was developed from the progeny of recipient "Xihui18" (an indica restorer line) and donor "Huhan3" (a japonica cultivar) by advanced backcross combined molecular marker-assisted selection (MAS). It displayed multiple panicles and less spikelets and wide grains. Then, a F2 population derived from Xihui18/Z783 was used to map quantitative trait loci (QTLs) for yield-related traits by the mixed linear model method. Nine QTLs were detected (p < 0.05). Furthermore, three SSSLs were constructed by MAS, and all 9 QTLs could be validated, and 15 novel QTLs could be detected by these SSSLs by a one-way ANOVA analysis. The genetic analysis showed that qSSP4 for less spikelets and qGW9 for wide grain all displayed dominant gene action in their SSSLs. Finally, qSSP4 and qGW9 were fine-mapped to intervals of 2.75 Mb and 1.84 Mb, on Chromosomes 4 and 9, respectively. The results lay a solid foundation for their map cloning and molecular breeding by design.

How does UV-B stress affect secondary metabolites of Scutellaria baicalensis in vitro shoots grown at different 6-benzyl aminopurine concentrations?

Ultraviolet-B (UV-B) radiation is one of the abiotic stresses that can significantly affect the secondary metabolite accumulation in in vitro tissue cultures of medicinal plants. The present study investigated the effects of UV-B radiation on the secondary metabolites and antioxidant activities of Scutellaria baicalensis in vitro shoots grown at different concentrations of 6-benzyl aminopurine (6-BA), which is the cytokinin most widely used in plant tissue culture. The UV-B radiation caused significant increases in lipid peroxidation, total phenolic, and flavonoid contents, and antioxidant activities in the in vitro shoots grown at lower 6-BA concentrations (0 and 1 mg L-1 ), while it did not cause any significant changes in those grown at higher 6-BA concentrations (2 and 3 mg L-1 ). However, the UV-B radiation significantly altered the contents of main individual flavonoids at both lower and higher 6-BA concentrations. Upon UV-B radiation, aglycones (including baicalein, wogonin, and scutellarein) increased, while glucuronides such as baicalin and wogonoside decreased; this was more evident at higher 6-BA concentrations. This study demonstrated that the effects of UV-B radiation on the secondary metabolites of S. baicalensis in vitro shoots highly depended on the 6-BA concentration in the culture medium.

In vitro production of atractylon and ß-eudesmol from Atractylodes chinensis by adventitious root culture.

Atractylodes chinensis is a medicinal plant widely used for the treatment of gastric disorders, and its main bioactive compounds are atractylon and ß-eudesmol. This study was purposed to establish the adventitious root culture system of A. chinensis for in vitro production of atractylon and ß-eudesmol. The main parameters in the adventitious root induction and suspension cultures were optimized to maximize the culture efficiency. Adventitious roots were induced most efficiently from leaf explants on Murashige and Skoog (MS) solid medium containing 1.5 mg/L naphthaleneacetic acid (NAA) and 30 g/L sucrose with the highest root induction rate of approximately 92% and 12.9 roots per explant. During the adventitious root suspension culture, the root biomass and the accumulated content of the target compounds simultaneously increased to reach the maximum values after 8 weeks of culture. The maximum yield of the target compounds (total concentration 3.38 mg/g DW, total yield 2.66 mg) was achieved in the roots cultured in ½ MS liquid medium supplemented with 2.0 mg/L IBA, 3.2 mg/L NAA, and 40 g/L sucrose with the inoculum density of 8 g/L. Through the central composite design experiment, it was found that the combined use of different types of auxins in the suspension culture could further improve root growth and metabolite accumulation than the application of only one type of auxin. This work provides a new possibility to have a promising candidate for the industrial production of A. chinensis pharmaceuticals without relying on wild resources or field cultivation. KEY POINTS: • The induction culture was optimized for efficient root induction. • Suspension culture was optimized for the atractylon and ß-eudesmol production. • Combined use of different auxins improves root growth and metabolite accumulation.

Ultrasound-assisted enzymatic extraction of Scutellaria baicalensis root polysaccharide and its hypoglycemic and immunomodulatory activities.

Scutellaria baicalensis is a medicinal plant possessing abundant bioactive polysaccharides. This study aimed to optimize the ultrasound-assisted enzymatic extraction of S. baicalensis root polysaccharide (SRP) and investigate its hypoglycemic and immunomodulatory activities. The optimal extraction conditions found in this study were as follows: cellulase concentration 165.6 U/mL, temperature 57.3 °C, liquid-solid ratio 44.8 mL/g, time 50 min, and ultrasonic power 225 W; with the yield reached up to 12.27 %. The ion exchange and gel filtration chromatographies were used to obtain a purified SRP. The carbohydrate content of SRP was 85.09 %, with a relatively high content of uronic acids (11.27 %). The SRP had a molecular weight of 89.7 kDa and was composed of eight monosaccharides. The inhibitory activity of SRP against α-amylase and α-glucosidase was determined. It was revealed that SRP could effectively inhibit these two enzymes with IC50 values of 1.23 and 0.63 mg/mL, respectively. Finally, the immunomodulatory effect of SRP on the dendritic cell activation was investigated, and the expressions of MHC II, CD80, CD86, and CD40 increased by 1.56, 1.96, 1.75, and 1.70 times, respectively, by the SRP treatment. This work will provide a foundation for SRP's efficient extraction and utilization for diabetes and immune therapy.

Deploying Machine Learning Based Segmentation for Scientific Imaging Analysis at Synchrotron Facilities.

Scientific user facilities present a unique set of challenges for image processing due to the large volume of data generated from experiments and simulations. Furthermore, developing and implementing algorithms for real-time processing and analysis while correcting for any artifacts or distortions in images remains a complex task, given the computational requirements of the processing algorithms. In a collaborative effort across multiple Department of Energy national laboratories, the "MLExchange" project is focused on addressing these challenges. MLExchange is a Machine Learning framework deploying interactive web interfaces to enhance and accelerate data analysis. The platform allows users to easily upload, visualize, label, and train networks. The resulting models can be deployed on real data while both results and models could be shared with the scientists. The MLExchange web-based application for image segmentation allows for training, testing, and evaluating multiple machine learning models on hand-labeled tomography data. This environment provides users with an intuitive interface for segmenting images using a variety of machine learning algorithms and deep-learning neural networks. Additionally, these tools have the potential to overcome limitations in traditional image segmentation techniques, particularly for complex and low-contrast images.

Optimization of ultrasound-assisted enzymatic pretreatment for enhanced extraction of baicalein and wogonin from Scutellaria baicalensis roots.

It is of great theoretical interest and industrial significance to improve the extraction efficiency of baicalein and wogonin from Scutellaria baicalensis roots because of their high pharmacological activities. The present study was aimed to establish the optimized ultrasound-assisted enzymatic pretreatment (UAEP) process by which ultrasound irradiation and the exogenous enzyme were simultaneously applied to efficiently transform baicalin and wogonoside into baicalein and wogonin, enhancing their extraction efficiency. Single-factor experiment and Box-Behnken design were used to optimize the main UAEP conditions to maximize the total extraction yield of baicalein and wogonin. The optimized UAEP conditions were cellulase concentration of 1.1%, pH of 5.5, UAEP temperature of 56.5 °C, UAEP time of 39.4 min, and ultrasonic power of 200 W with the total extraction yield of 82.51 ± 0.85 mg/g DW. The comparison of the established technique with the reference method based on the enzymatic pretreatment revealed that the productive efficiency was significantly improved with the transformation rates nearly doubled. These results suggest that the optimized UAEP process has the potential to be applied for the green, simple, and efficient extraction of baicalein and wogonin in the pharmaceutical and food industry.

MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies.

Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are programmatically demanding and computationally costly. The MLExchange project aims to build a collaborative platform equipped with enabling tools that allow scientists and facility users who do not have a profound ML background to use ML and computational resources in scientific discovery. At the high level, we are targeting a full user experience where managing and exchanging ML algorithms, workflows, and data are readily available through web applications. Since each component is an independent container, the whole platform or its individual service(s) can be easily deployed at servers of different scales, ranging from a personal device (laptop, smart phone, etc.) to high performance clusters (HPC) accessed (simultaneously) by many users. Thus, MLExchange renders flexible using scenarios-users could either access the services and resources from a remote server or run the whole platform or its individual service(s) within their local network.

A Micelle Electrolyte Enabled by Fluorinated Ether Additives for Polysulfide Suppression and Li Metal Stabilization in Li-S Battery.

The Li-S battery is a promising next-generation technology due to its high theoretical energy density (2600 Wh kg-1) and low active material cost. However, poor cycling stability and coulombic efficiency caused by polysulfide dissolution have proven to be major obstacles for a practical Li-S battery implementation. In this work, we develop a novel strategy to suppress polysulfide dissolution using hydrofluoroethers (HFEs) with bi-functional, amphiphlic surfactant-like design: a polar lithiophilic "head" attached to a fluorinated lithiophobic "tail." A unique solvation mechanism is proposed for these solvents whereby dissociated lithium ions are readily coordinated with lithiophilic "head" to induce self-assembly into micelle-like complex structures. Complex formation is verified experimentally by changing the additive structure and concentration using small angle X-ray scattering (SAXS). These HFE-based electrolytes are found to prevent polysulfide dissolution and to have excellent chemical compatibility with lithium metal: Li||Cu stripping/plating tests reveal high coulombic efficiency (>99.5%), modest polarization, and smooth surface morphology of the uniformly deposited lithium. Li-S cells are demonstrated with 1395 mAh g-1 initial capacity and 71.9% retention over 100 cycles at >99.5% efficiency-evidence that the micelle structure of the amphiphilic additives in HFEs can prohibit polysulfide dissolution while enabling facile Li+ transport and anode passivation.

Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China.

China experiences severe particulate matter pollution associated with rapid economic growth and accelerated urbanization. In this study, concentrations of PM2.5 (fine particulate matter with an aerodynamic diameter ≤ 2.5 µm) throughout China, and specifically in nine typical urban agglomerations and one economic region, were statistically analyzed using high-resolution ground-based PM2.5 observations from June 2014 to May 2018. The spatial variation of PM2.5 was also explored via spatial autocorrelation analysis. High annual mean PM2.5 concentrations were predominantly concentrated in the Beijing-Tianjin-Hebei, Central Plain, Northern Slope of Tianshan Mountain, and Cheng-Yu urban agglomerations, as well as the Huaihai Economic Region. The proportion of air quality nationwide monitoring sites where annual average PM2.5 concentrations exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II annual standard were 82.8%, 77.1%, and 70.8% in 2015, 2016, and 2017, respectively. Moreover, the frequency of PM2.5 concentrations meeting the CAAQS Grade I 24-h standard increased in five national-level urban agglomerations, and the average annual PM2.5 decreased from 2015 to 2017 with a reduction rate of over 20%. The southern Beijing-Tianjin-Hebei agglomeration and surrounding areas revealed the highest PM2.5 pollution in four seasons. Monthly mean PM2.5 typically exhibited a characteristic "U" shape. Diurnal mean PM2.5 concentrations were generally consistent with typical urban agglomerations, with maximum and minimum PM2.5 values occurring at approximately 08:00-12:00 and 15:00-17:00, respectively, except for the Northern Slope of Tianshan Mountain urban agglomeration (NSTM-UA) (14:00 and 08:00, respectively). A positive spatial autocorrelation of PM2.5 concentrations was observed in all urban agglomerations (except NSTM-UA); high-high agglomeration centers of PM2.5 pollution were located far inland with a circular distribution, and low-low agglomeration centers formed at the periphery of the high-high agglomeration region. This study is key for understanding the difference in PM2.5 concentrations among urban agglomerations and region-oriented air pollution control strategies are highly suggested.

An Adaptive Weighting Algorithm for Interpolating the Soil Potassium Content.

The concept of spatial interpolation is important in the soil sciences. However, the use of a single global interpolation model is often limited by certain conditions (e.g., terrain complexity), which leads to distorted interpolation results. Here we present a method of adaptive weighting combined environmental variables for soil properties interpolation (AW-SP) to improve accuracy. Using various environmental variables, AW-SP was used to interpolate soil potassium content in Qinghai Lake Basin. To evaluate AW-SP performance, we compared it with that of inverse distance weighting (IDW), ordinary kriging, and OK combined with different environmental variables. The experimental results showed that the methods combined with environmental variables did not always improve prediction accuracy even if there was a strong correlation between the soil properties and environmental variables. However, compared with IDW, OK, and OK combined with different environmental variables, AW-SP is more stable and has lower mean absolute and root mean square errors. Furthermore, the AW-SP maps provided improved details of soil potassium content and provided clearer boundaries to its spatial distribution. In conclusion, AW-SP can not only reduce prediction errors, it also accounts for the distribution and contributions of environmental variables, making the spatial interpolation of soil potassium content more reasonable.