A review on the effects of light-emitting diode (LED) light on the nutrients of sprouts and microgreens

Background: Sprouts and microgreens, which are tender, flavourful, rich in nutrients, have a short growth cycle, and have been recognized as functional foods in the human diet. Culturing under artificial light sources could regulate the growth, the phytochemical compound content and antioxidant capacity of sprouts and microgreens. Scope and approach: In this review, the effects of light-emitting diode (LED) light on growth, phytochemical compound content and antioxidant capacity, as well as the post-harvest quality of sprouts and microgreens were overviewed, and the underlying mechanisms were discussed. The future applications and research, which aim to improve the growth and nutritional quality of sprouts and microgreens, were also investigated. Key findings and conclusions: LED light can promote the accumulation of different phytochemicals, such as phenolic compounds, vitamins, glucosinolates, chlorophyll and carotenoids. Meanwhile, the antioxidant capacity could also be significantly increased by growth under LED light, in particular UV-B light. The accumulation of mineral elements (Ca2+, Fe2+, K+) increased after light exposure. The effects of LED light on the growth was species dependent. Therefore, growth under LED light is an efficient and promising strategy for producing sprouts and microgreens with higher nutritional values

The cumulative effects of known susceptibility variants to predict primary biliary cirrhosis risk.

Multiple genetic variants influence the risk for development of primary biliary cirrhosis (PBC). To explore the cumulative effects of known susceptibility loci on risk, we utilized a weighted genetic risk score (wGRS) to evaluate whether genetic information can predict susceptibility. The wGRS was created using 26 known susceptibility loci and investigated in 1840 UK PBC and 5164 controls. Our data indicate that the wGRS was significantly different between PBC and controls (P=1.61E-142). Moreover, we assessed predictive performance of wGRS on disease status by calculating the area under the receiver operator characteristic curve. The area under curve for the purely genetic model was 0.72 and for gender plus genetic model was 0.82, with confidence limits substantially above random predictions. The risk of PBC using logistic regression was estimated after dividing individuals into quartiles. Individuals in the highest disclosed risk group demonstrated a substantially increased risk for PBC compared with the lowest risk group (odds ratio: 9.3, P=1.91E-084). Finally, we validated our findings in an analysis of an Italian PBC cohort. Our data suggested that the wGRS, utilizing genetic variants, was significantly associated with increased risk for PBC with consistent discriminant ability. Our study is a first step toward risk prediction for PBC

Isolation and drought-tolerant function analysis of ZmPti1-1, a homologue to Pti1, from maize (Zea mays L.)

Pto-interacting 1(Pti1) has been well established to play important roles in plant disease and salt response, but its potential roles in the response to drought stress is unknown. In this study, the Pti1- like gene named as ZmPti1-1 was cloned from maize, sequence analysis showed that ZmPti1-1 encodes a polypeptide of 363 amino acids with predicted molecular mass of 39.0 kDa and an isoelectric point of 8.14. ZmPt1-1 is dramatically induced by abscisic acid (ABA) and mannitol (data not shown). In order to analyze the further drought tolerant functions, ZmPti1-1 was over-expressed in Arabidopsis. Under drought stress, compared with wild type, survival rate of the three transgenic lines, which was 70, 76 and 87%, respectively, was significantly higher than that of wild type which was 29%; there were lower water loss, lower cell membrane damage, higher relative water content, higher total soluble sugars, higher proline content and higher yield for transgenic plants. Based on the present knowledge, this is the first report that over-expression of Pti1-like gene improved drought tolerance in plants.Key words: ZmPti1-1, transgenic Arabidopsis, drought tolerance

Toxic effect of the novel chiral insecticide IPP and its biodegradation intermediate in nematode Caenorhabditis elegans

Caenorhabditis elegans, a kind of model organism, was used to investigate biodegradation pathway of IPP and M1 in nematodes, in vivo toxicity from IPP and M1 and the possible underlying molecular mechanism. The results showed that both IPP and M1 could decrease lifespan, locomotion behavior, reproductive ability and AChE activity. During IPP biodegradation process, three intermediates (M1–M3) were monitored and identified. Based on the identified metabolites and their biodegradation courses, a possible biodegradation pathway was proposed. IPP was probably transformed to different three metabolites in nematodes through oxidation and elimination of methyl and propyl etc. Under the same concentration, IPP had more severe toxicity than M1 on nematodes. IPP and M1 might reduce lifespan and decrease reproductive ability through influencing insulin/IGF signaling pathway and TOR signaling pathway. They could decrease expression levels of daf-16, sgk-1, aak-2, daf-15 and rict-1 genes, which involved in IGF and TOR signaling pathway

Comparative analysis of phenolic compounds profile, antioxidant capacity, and expression of phenolic biosynthesis-related genes in soybean microgreens grown under different light spectra

The Light-emitting diode (LED)-based light sources, which can selectively and quantitatively provide different spectra, have been frequently applied to manipulate plant growth and development. In this study, the effects of different LED light spectra on the growth, phenolic compounds profile, antioxidant capacity and transcriptional changes in genes regulating phenolic biosynthesis in soybean microgreens were investigated. The results showed that light illumination decreased the seedling length and yield but increased phenolic compounds content. Blue light and ultraviolet-A (UV-A) induced significant increases in total phenolic and total flavonoid content, as compared with the white light control. Sixty-six phenolic compounds were identified in the soybean samples, of which isoflavone, phenolic acid, and flavonol were the main components. Ten phenolic compounds obtained from the orthogonal partial least squares discriminant analysis (OPLS-DA) were reflecting the effect of light spectra. The antioxidant capacity was consistent with the phenolic metabolite levels, which showed higher levels under blue light and UV-A compared with the control. The highest transcript levels of phenolic biosynthesis-related genes were observed under blue light and UV-A. The transcript levels of GmCHI, GmFLS and GmIOMT were also upregulated under far-red and red light. Taken together, our findings suggested that the application of LED light could pave a green and effective way to produce phenolic compounds-enriched soybean microgreens with high nutrition quality, which could stimulate further investigations for improving plant nutritional value and should have a wide impact on maintaining human health

Insights into the Anaerobic Biodegradation Pathway of n-Alkanes in Oil Reservoirs by Detection of Signature Metabolites

published_or_final_versio

FLASH: Heterogeneity-Aware Federated Learning at Scale

Federated learning (FL) becomes a promising machine learning paradigm. The impact of heterogeneous hardware specifications and dynamic states on the FL process has not yet been studied systematically. This paper presents the first large-scale study of this impact based on real-world data collected from 136k smartphones. We conducted extensive experiments on our proposed heterogeneity-aware FL platform namely FLASH , to systematically explore the performance of state-of-the-art FL algorithms and key FL configurations in heterogeneity-aware and -unaware settings, finding the following. (1) Heterogeneity causes accuracy to drop by up to 9.2% and convergence time to increase by 2.32×. (2) Heterogeneity negatively impacts popular aggregation algorithms, e.g., the accuracy variance reduction brought by q-FedAvg drops by 17.5%. (3) Heterogeneity does not worsen the accuracy loss caused by gradient-compression algorithms significantly, but it compromises the convergence time by up to 2.5×. (4) Heterogeneity hinders client-selection algorithms from selecting wanted clients, thus reducing effectiveness. e.g., the accuracy increase brought by the state-of-the-art client-selection algorithm drops by 73.9%. (5) Heterogeneity causes the optimal FL hyper-parameters to drift significantly. More specifically, the heterogeneity-unaware setting favors looser deadline and higher reporting fraction to achieve better training performance. (6) Heterogeneity results in non-trivial failed clients (more than 10%) and leads to participation bias (the top 30% of clients contribute 86% of computations). Our FLASH platform and data have been publicly open sourced

Overview on pattern identification - History, nature and strategies for treating patients: A narrative review

acceptedVersio

The Use of Pattern Differentiation in WHO-Registered Traditional Chinese Medicine Trials – a systematic review

Introduction: Pattern differentiation is a critical component for traditional Chinese medicine (TCM) diagnosis and treatment. However, the issue of whether pattern differentiation is appropriately applied in TCM Interventional trials, including Chinese herbal medicine (CHM) interventions and non-herbal TCM interventions, is unclear. The aim of this study was to i) systematically review the current status of pattern differentiation used in WHO-registered clinical trials for different types of TCM interventions; and ii) provide suggestions for improving the use of pattern differentiation in future clinical trial design. Methods: The World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) database was searched for all TCM interventional trials registered up to 31 December 2017. In this systematic review trials with a TCM pattern differentiation in their design were included. Descriptive statistics were collated to demonstrate the characteristics of pattern differentiation applied for different TCM interventional trials. Results: Among 2,955 TCM interventional trials registered during 1999-2017, 376 (12.7%) trials included pattern differentiation. Of 376 trials, the use of pattern differentiation was identified in –title (30.6%), objective (50.5%), participants inclusion 4 (100%), outcomes (43.6%) and study background (12.5%). Further, 85.4% reported the specific name of the TCM intervention, 10.6% provided the intervention’s targeted pattern, 83.8% reported the specific name of the TCM pattern, 7.2% presented diagnostic criteria for the pattern studied, and 19.1% adopted a pattern-related outcome as primary outcome for evaluation. Conclusion: The reporting and application of pattern differentiation in TCM trials were inadequate and confusing, which was mainly due to lack of clarity regarding study design, objectives, diagnostic criteria and outcomes