Integrated physiological, metabolomic, and transcriptomic analyses elucidate the regulation mechanisms of lignin synthesis under osmotic stress in alfalfa leaf (Medicago sativa L.).

Alfalfa, an essential forage crop known for its high yield, nutritional value, and strong adaptability, has been widely cultivated worldwide. The yield and quality of alfalfa are frequently jeopardized due to environmental degradation. Lignin, a constituent of the cell wall, enhances plant resistance to abiotic stress, which often causes osmotic stress in plant cells. However, how lignin responds to osmotic stress in leaves remains unclear. This study explored the effects of osmotic stress on lignin accumulation and the contents of intermediate metabolites involved in lignin synthesis in alfalfa leaves. Osmotic stress caused an increase in lignin accumulation and the alteration of core enzyme activities and gene expression in the phenylpropanoid pathway. We identified five hub genes (CSE, CCR, CADa, CADb, and POD) and thirty edge genes (including WRKYs, MYBs, and UBPs) by integrating transcriptome and metabolome analyses. In addition, ABA and ethylene signaling induced by osmotic stress regulated lignin biosynthesis in a contradictory way. These findings contribute to a new theoretical foundation for the breeding of high-quality and resistant alfalfa varieties.

Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings.

BACKGROUND: Kobreisa littledalei, belonging to the Cyperaceae family is the first Kobresia species with a reference genome and the most dominant species in Qinghai-Tibet Plateau alpine meadows. It has several resistance genes which could be used to breed improved crop varieties. Reverse Transcription Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) is a popular and accurate gene expression analysis method. Its reliability depends on the expression levels of reference genes, which vary by species, tissues and environments. However, K.littledalei lacks a stable and normalized reference gene for RT-qPCR analysis. RESULTS: The stability of 13 potential reference genes was tested and the stable reference genes were selected for RT-qPCR normalization for the expression analysis in the different tissues of K. littledalei under two abiotic stresses (salt and drought) and two hormonal treatments (abscisic acid (ABA) and gibberellin (GA)). Five algorithms were used to assess the stability of putative reference genes. The results showed a variation amongst the methods, and the same reference genes showed tissue expression differences under the same conditions. The stability of combining two reference genes was better than a single one. The expression levels of ACTIN were stable in leaves and stems under normal conditions, in leaves under drought stress and in roots under ABA treatment. The expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression was stable in the roots under the control conditions and salt stress and in stems exposed to drought stress. Expression levels of superoxide dismutase (SOD) were stable in stems of ABA-treated plants and in the roots under drought stress. Moreover, RPL6 expression was stable in the leaves and stems under salt stress and in the stems of the GA-treated plants. EF1-alpha expression was stable in leaves under ABA and GA treatments. The expression levels of 28 S were stable in the roots under GA treatment. In general, ACTIN and GAPDH could be employed as housekeeping genes for K. littledalei under different treatments. CONCLUSION: This study identified the best RT-qPCR reference genes for different K. littledalei tissues under five experimental conditions. ACTIN and GAPDH genes can be employed as the ideal housekeeping genes for expression analysis under different conditions. This is the first study to investigate the stable reference genes for normalized gene expression analysis of K. littledalei under different conditions. The results could aid molecular biology and gene function research on Kobresia and other related species.

True Random Number Generator Based on Chaotic Oscillation of a Tunable Double-Well MEMS Resonator.

Chaotic systems have aroused interest across various scientific disciplines such as physics, biology, chemistry, and meteorology. The deterministic but unpredictable nature of a chaotic system is an ideal feature for random number generation. Microelectromechanical systems (MEMS) are a promising technology that effectively harnesses chaos, offering advantages such as a compact footprint, scalability, and low power consumption. This paper presents a true random number generator (TRNG) based on a double-well MEMS resonator integrated with an actuator and position sensor. The potential energy landscape of the proposed MEMS resonator is actively tunable with a direct current voltage. Experimental demonstrations of tunable bistability and chaotic resonance are reported in this paper. A chaotic time sequence is generated through piezoresistive sensing of the position of the MEMS resonator once it is driven into the chaotic regime. Subsequently, the randomness of the bit sequence, achieved by applying the exclusive or function to a digital chaotic sequence and its delayed differential is confirmed to meet the National Institute of Standards and Technology specifications. Moreover, the throughput and energy efficiency of the proposed MEMS-based TRNG can be adjusted from 50 kb s-1 and 0.44 pJ per bit at a low energy barrier to 167 kb s-1 and 6.74 pJ per bit at a high energy barrier by changing the MEMS device's potential well. The tunability of the proposed double-well MEMS resonator not only offers continuous adjustments in the energy efficiency of TNRG but also unveils vast and diverse research opportunities in analog computing, encryption, and secure communications.

Iron(III)-Catalyzed Amine-Release Triple Condensation of Enaminones to C3-Alkenylated Dihydroquinolinones.

C3-functionalized dihydroquinolinones represent a class of important biologically active compounds. Although methods for synthesizing C2/4-functionalized dihydroquinolinones have been extensively reported, research on the synthesis of C3-functionalized dihydroquinolinone is extremely rare. Herein, we report for the first time a method for C3-alkenylated dihydroquinolinones via iron(III)-catalyzed amine-release triple condensation of enaminones. These reactions exhibit broad substrate scope and offer operationally simple, low-cost catalyzed procedures in a single step. Subsequent intramolecular and intermolecular additions to the alkene moiety provide diverse C3-functionalized dihydroquinolinone derivatives.

Evolving landscape of PD-L2: bring new light to checkpoint immunotherapy.

Immune checkpoint blockade therapy targeting programmed cell death protein 1 (PD-1) has revolutionized the landscape of multiple human cancer types, including head and neck squamous carcinoma (HNSCC). Programmed death ligand-2 (PD-L2), a PD-1 ligand, mediates cancer cell immune escape (or tolerance independent of PD-L1) and predicts poor prognosis of patients with HNSCC. Therefore, an in-depth understanding of the regulatory process of PD-L2 expression may stratify patients with HNSCC to benefit from anti-PD-1 immunotherapy. In this review, we summarised the PD-L2 expression and its immune-dependent and independent functions in HNSCC and other solid tumours. We focused on recent findings on the mechanisms that regulate PD-L2 at the genomic, transcriptional, post-transcriptional, translational, and post-translational levels, also in intercellular communication of tumour microenvironment (TME). We also discussed the prospects of using small molecular agents indirectly targeting PD-L2 in cancer therapy. These findings may provide a notable avenue in developing novel and effective PD-L2-targeted therapeutic strategies for immune combination therapy and uncovering biomarkers that improve the clinical efficacy of anti-PD-1 therapies.

TDI-like multi-slit hyperspectral imaging for enhanced throughput via the Kalman filter.

The time-delay integration (TDI) technique is increasingly used to improve the signal-to-noise ratio (SNR) of remote sensing and imaging by exposing the scene multiple times. Inspired by the principle of TDI, we propose a TDI-like pushbroom multi-slit hyperspectral imaging (MSHSI) approach. In our system, multiple slits are used to significantly improve the throughput of the system, thereby enhancing the sensitivity and SNR through multiple exposures of the same scene during pushbroom scan. Meanwhile, a linear dynamic model for the pushbroom MSHSI is established, where the Kalman filter (KF) is employed to reconstruct the time-varying overlapped spectral images on a single conventional image sensor. Further, we designed and fabricated a customized optical system that can operate in both multi-slit and single slit modes to experimentally verify the feasibility of the proposed method. Experimental results indicate that the developed system improved SNR by a factor of about 7 compared to that of the single slit mode, while demonstrating excellent resolution in both spatial and spectral dimensions.

Short-term and long-term epidemiological impacts of sustained vector control in various dengue endemic settings: A modelling study.

As the most widespread viral infection transmitted by the Aedes mosquitoes, dengue has been estimated to cause 51 million febrile disease cases globally each year. Although sustained vector control remains key to reducing the burden of dengue, current understanding of the key factors that explain the observed variation in the short- and long-term vector control effectiveness across different transmission settings remains limited. We used a detailed individual-based model to simulate dengue transmission with and without sustained vector control over a 30-year time frame, under different transmission scenarios. Vector control effectiveness was derived for different time windows within the 30-year intervention period. We then used the extreme gradient boosting algorithm to predict the effectiveness of vector control given the simulation parameters, and the resulting machine learning model was interpreted using Shapley Additive Explanations. According to our simulation outputs, dengue transmission would be nearly eliminated during the early stage of sustained and intensive vector control, but over time incidence would gradually bounce back to the pre-intervention level unless the intervention is implemented at a very high level of intensity. The time point at which intervention ceases to be effective is strongly influenced not only by the intensity of vector control, but also by the pre-intervention transmission intensity and the individual-level heterogeneity in biting risk. Moreover, the impact of many transmission model parameters on the intervention effectiveness is shown to be modified by the intensity of vector control, as well as to vary over time. Our study has identified some of the critical drivers for the difference in the time-varying effectiveness of sustained vector control across different dengue endemic settings, and the insights obtained will be useful to inform future model-based studies that seek to predict the impact of dengue vector control in their local contexts.

Review of Miniaturized Computational Spectrometers.

Spectrometers are key instruments in diverse fields, notably in medical and biosensing applications. Recent advancements in nanophotonics and computational techniques have contributed to new spectrometer designs characterized by miniaturization and enhanced performance. This paper presents a comprehensive review of miniaturized computational spectrometers (MCS). We examine major MCS designs based on waveguides, random structures, nanowires, photonic crystals, and more. Additionally, we delve into computational methodologies that facilitate their operation, including compressive sensing and deep learning. We also compare various structural models and highlight their unique features. This review also emphasizes the growing applications of MCS in biosensing and consumer electronics and provides a thoughtful perspective on their future potential. Lastly, we discuss potential avenues for future research and applications.

Green nanopriming: responses of alfalfa (Medicago sativa L.) seedlings to alfalfa extracts capped and light-induced silver nanoparticles.

The application of nanotechnology in agriculture can remarkably improve the cultivation and growth of crop plants. Many studies showed that nanoparticles (NPs) made plants grow more vigorously. Light can make NPs aggregated, leading to the reduction of the NPs toxicity. In addition, treatment with NPs had a "hormesis effect" on plants. In this study, light-induced silver nanoparticles (AgNPs) were synthesized by using the alfalfa (Medicago sativa L.) extracts, and then the optimal synthetic condition was determined. Light-induced AgNPs were aggregated, spherical and pink, and they were coated with esters, phenols, acids, terpenes, amino acids and sugars, which were the compositions of alfalfa extracts. The concentration of free Ag+ was less than 2 % of the AgNPs concentration. Through nanopriming, Ag+ got into the seedlings and caused the impact of AgNPs on alfalfa. Compared with the control group, low concentration of light-induced AgNPs had a positive effect on the photosynthesis. It was also harmless to the leaf cells, and there was no elongation effect on shoots. Although high concentration of AgNPs was especially beneficial to root elongation, it had a slight toxic effect on seedlings due to the accumulation of silver. With the increase of AgNPs concentration, the content of silver in the seedlings increased and the silver enriched in plants was at the mg/kg level. Just as available research reported the toxicity of NPs can be reduced by using suitable synthesis and application methods, the present light induction, active material encapsulation and nanopriming minimized the toxicity of AgNPs to plants, enhancing the antioxidant enzyme system.

Mid-infrared silicon photonic phase shifter based on microelectromechanical system.

Mid-infrared (MIR) photonic integrated circuits have generated considerable interest, owing to their potential applications, such as thermal imaging and biochemical sensing. A challenging area in the field is the development of reconfigurable approaches for the enhancement of on-chip functions, where a phase shifter plays an important role. Here, we demonstrate a MIR microelectromechanical system (MEMS) phase shifter by utilizing an asymmetric slot waveguide with subwavelength grating (SWG) claddings. The MEMS-enabled device can be easily integrated into a fully suspended waveguide with SWG cladding, built on a silicon-on-insulator (SOI) platform. Through engineering of the SWG design, the device achieves a maximum phase shift of 6π, with an insertion loss of 4 dB and a half-wave-voltage-length product (VπLπ) of 2.6 V·cm. Moreover, the time response of the device is measured as 13 µs (rise time) and 5 µs (fall time).

Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods.

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event's spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election's direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election's spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.

Mapping the cryptic spread of the 2015-2016 global Zika virus epidemic.

BACKGROUND: Zika virus (ZIKV) emerged as a global epidemic in 2015-2016 from Latin America with its true geographical extent remaining unclear due to widely presumed underreporting. The identification of locations with potential and unknown spread of ZIKV is a key yet understudied component for outbreak preparedness. Here, we aim to identify locations at a high risk of cryptic ZIKV spread during 2015-2016 to further the understanding of the global ZIKV epidemiology, which is critical for the mitigation of the risk of future epidemics. METHODS: We developed an importation simulation model to estimate the weekly number of ZIKV infections imported in each susceptible spatial unit (i.e. location that did not report any autochthonous Zika cases during 2015-2016), integrating epidemiological, demographic, and travel data as model inputs. Thereafter, a global risk model was applied to estimate the weekly ZIKV transmissibility during 2015-2016 for each location. Finally, we assessed the risk of onward ZIKV spread following importation in each susceptible spatial unit to identify locations with a high potential for cryptic ZIKV spread during 2015-2016. RESULTS: We have found 24 susceptible spatial units that were likely to have experienced cryptic ZIKV spread during 2015-2016, of which 10 continue to have a high risk estimate within a highly conservative scenario, namely, Luanda in Angola, Banten in Indonesia, Maharashtra in India, Lagos in Nigeria, Taiwan and Guangdong in China, Dakar in Senegal, Maputo in Mozambique, Kinshasa in Congo DRC, and Pool in Congo. Notably, among the 24 susceptible spatial units identified, some have reported their first ZIKV outbreaks since 2017, thus adding to the credibility of our results (derived using 2015-2016 data only). CONCLUSION: Our study has provided valuable insights into the potentially high-risk locations for cryptic ZIKV circulation during the 2015-2016 pandemic and has also laid a foundation for future studies that attempt to further narrow this key knowledge gap. Our modelling framework can be adapted to identify areas with likely unknown spread of other emerging vector-borne diseases, which has important implications for public health readiness especially in resource-limited settings.

Importations of COVID-19 into African countries and risk of onward spread.

BACKGROUND: The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 cases in total by the end of March, April, May, and June following viral introduction. METHODS: We used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 cases are reached or the end of June, whichever is earlier. Specifically, 1,000 simulations were run separately under four different combinations of parameter values to test the sensitivity of our results. RESULTS: We estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 cases by end of March was close to 100% under all scenarios. In particular, we identified countries with less than 1,000 cases in total reported by end of June whilst the estimated probability of reaching 10,000 cases by then was higher than 50% even under the most optimistic scenario. CONCLUSIONS: Our study highlights particular countries that are likely to reach (or have reached) 10,000 cases far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.

Force of Infection and True Infection Rate of Dengue in Singapore: Implications for Dengue Control and Management.

National data on dengue notifications do not capture all dengue infections and do not reflect the true intensity of disease transmission. To assess the true dengue infection rate and disease control efforts in Singapore, we conducted age-stratified serosurveys among residents after a 2013 outbreak that was the largest dengue outbreak on record. The age-weighted prevalence of dengue immunoglobulin G among residents was 49.8% (95% confidence interval: 48.4, 51.1) in 2013 and 48.6% (95% confidence interval: 47.0, 50.0) in 2017; prevalence increased with age. Combining these data with those from previous serosurveys, the year-on-year estimates of the dengue force of infection from 1930 to 2017 revealed a significant decrease from the late 1960s to the mid-1990s, after which the force of infection remained stable at approximately 10 per 1,000 persons per year. The reproduction number (R0) had also declined since the 1960s. The reduction in dengue transmission may be attributed to the sustained national vector program and partly to a change in the age structure of the population. The improved estimated ratio of notified cases to true infections, from 1:14 in 2005-2009 to 1:6 in 2014-2017, signifies that the national notification system, which relies on diagnosed cases, has improved over time. The data also suggest that the magnitudes of dengue epidemics cannot be fairly compared across calendar years and that the current disease control program remains applicable.

Achieving foaming control smartly: pre-solubilized flavor oil serves as an in situ homogeneous defoamer.

In the wide application of aqueous foam, creating abundant foam and processing appropriate foaming control are both essential, depending upon the actual situation; the latter process is not only harder to achieve, but also more complicated to comprehensively understand on the molecular level. In this paper, a type of natural flavor oil, carvone, was solubilized in a micelle solution of sodium dodecyl sulfate (SDS) to study the effect on the foaming properties. The foamability and foam stability of the swollen micelle solutions were experimentally characterized, and the molecular behavior of the surfactant and oil molecules before, during and after the foaming process were investigated. It was found that the solubilized carvone co-adsorbed with SDS at the gas/water interface and caused a prominent effect on the foam film stability in several approaches, thereby making the flavor oil a possible foam controller that would not inhibit foam formation, but could eliminate foam efficiently once foam was undesired. Interestingly, it was found that the release of flavor in the foaming process was promoted. Detailed discussion of the interfacial behavior of carvone and the effect on the foaming properties of surfactants in different stages of foam may provide a theoretical foundation for exploring green and smart approaches in achieving foaming control.

Understanding about How Different Foaming Gases Effect the Interfacial Array Behaviors of Surfactants and the Foam Properties.

In this paper, the detailed behaviors of all the molecules, especially the interfacial array behaviors of surfactants and diffusion behaviors of gas molecules, in foam systems with different gases (N2, O2, and CO2) being used as foaming agents were investigated by combining molecular dynamics simulation and experimental approaches for the purpose of interpreting how the molecular behaviors effect the properties of the foam and find out the key factors which fundamentally determine the foam stability. Sodium dodecyl sulfate SDS was used as the foam stabilizer. The foam decay and the drainage process were determined by Foamscan. A texture analyzer (TA) was utilized to measure the stiffness and viscoelasticity of the foam films. The experimental results agreed very well with the simulation results by which how the different gas components affect the interfacial behaviors of surfactant molecules and thereby bring influence on foam properties was described.

Sucrose-phosphate osmotic system improves the quality characteristics of reduced-salt salted egg yolk: Profiling from protein structure and lipid distribution perspective.

This paper was dedicated to the study of the effect of sucrose-phosphate on aspects of physicochemical properties, lipid distribution and protein structure during the picklig of reduced-salt salted egg yolk (SEY). This work constructed a reduced-salt pickling system from a new perspective (promoting osmosis) by using a sucrose-phosphate-salt. Results showed that SEY-28d achieved a desirable salt content (1.07 %), hardness (573.46 g) and springiness (0.65 g). The matured SEY was in excellent quality with orange-red color and loose sandy texture. This was because the lipoprotein aggregated with each other through hydrophobic interaction to form a stable network structure. In addition, the hypertonic environment accelerated salt penetration. These also created good condition for lipid spillage. The results of confocal laser scanning microscope also verified this phenomenon. This work provides important guidance for new reduced-salt curing of traditional pickled foods, deep processing of SEY, and industry development in the field of poultry egg.

Dietary fat supplementation relieves cold temperature-induced energy stress through AMPK-mediated mitochondrial homeostasis in pigs.

BACKGROUND: Cold stress has negative effects on the growth and health of mammals, and has become a factor restricting livestock development at high latitudes and on plateaus. The gut-liver axis is central to energy metabolism, and the mechanisms by which it regulates host energy metabolism at cold temperatures have rarely been illustrated. In this study, we evaluated the status of glycolipid metabolism and oxidative stress in pigs based on the gut-liver axis and propose that AMP-activated protein kinase (AMPK) is a key target for alleviating energy stress at cold temperatures by dietary fat supplementation. RESULTS: Dietary fat supplementation alleviated the negative effects of cold temperatures on growth performance and digestive enzymes, while hormonal homeostasis was also restored. Moreover, cold temperature exposure increased glucose transport in the jejunum. In contrast, we observed abnormalities in lipid metabolism, which was characterized by the accumulation of bile acids in the ileum and plasma. In addition, the results of the ileal metabolomic analysis were consistent with the energy metabolism measurements in the jejunum, and dietary fat supplementation increased the activity of the mitochondrial respiratory chain and lipid metabolism. As the central nexus of energy metabolism, the state of glycolipid metabolism and oxidative stress in the liver are inconsistent with that in the small intestine. Specifically, we found that cold temperature exposure increased glucose transport in the liver, which fully validates the idea that hormones can act on the liver to regulate glucose output. Additionally, dietary fat supplementation inhibited glucose transport and glycolysis, but increased gluconeogenesis, bile acid cycling, and lipid metabolism. Sustained activation of AMPK, which an energy receptor and regulator, leads to oxidative stress and apoptosis in the liver; dietary fat supplementation alleviates energy stress by reducing AMPK phosphorylation. CONCLUSIONS: Cold stress reduced the growth performance and aggravated glycolipid metabolism disorders and oxidative stress damage in pigs. Dietary fat supplementation improved growth performance and alleviated cold temperature-induced energy stress through AMPK-mediated mitochondrial homeostasis. In this study, we highlight the importance of AMPK in dietary fat supplementation-mediated alleviation of host energy stress in response to environmental changes.

Cognition-Driven Structural Prior for Instance-Dependent Label Transition Matrix Estimation.

The label transition matrix has emerged as a widely accepted method for mitigating label noise in machine learning. In recent years, numerous studies have centered on leveraging deep neural networks to estimate the label transition matrix for individual instances within the context of instance-dependent noise. However, these methods suffer from low search efficiency due to the large space of feasible solutions. Behind this drawback, we have explored that the real murderer lies in the invalid class transitions, that is, the actual transition probability between certain classes is zero but is estimated to have a certain value. To mask the invalid class transitions, we introduced a human-cognition-assisted method with structural information from human cognition. Specifically, we introduce a structured transition matrix network (STMN) designed with an adversarial learning process to balance instance features and prior information from human cognition. The proposed method offers two advantages: 1) better estimation effectiveness is obtained by sparing the transition matrix and 2) better estimation accuracy is obtained with the assistance of human cognition. By exploiting these two advantages, our method parametrically estimates a sparse label transition matrix, effectively converting noisy labels into true labels. The efficiency and superiority of our proposed method are substantiated through comprehensive comparisons with state-of-the-art methods on three synthetic datasets and a real-world dataset. Our code will be available at https://github.com/WheatCao/STMN-Pytorch.