Bacillus licheniformis Jrh14-10 enhances alkaline tolerance in Arabidopsis thaliana by regulating crosstalk between ethylene and polyamine pathways.

Plant growth-promoting rhizobacteria (PGPR) are known for their role in ameliorating plant stress, including alkaline stress, yet the mechanisms involved are not fully understood. This study investigates the impact of various inoculum doses of Bacillus licheniformis Jrh14-10 on Arabidopsis growth under alkaline stress and explores the underlying mechanisms of tolerance enhancement. We found that all tested doses improved the growth of NaHCO3-treated seedlings, with 109 cfu/mL being the most effective. Transcriptome analysis indicated downregulation of ethylene-related genes and an upregulation of polyamine biosynthesis genes following Jrh14-10 treatment under alkaline conditions. Further qRT-PCR analysis confirmed the suppression of ethylene biosynthesis and signaling genes, alongside the activation of polyamine biosynthesis genes in NaHCO3-stressed seedlings treated with Jrh14-10. Genetic analysis showed that ethylene signaling-deficient mutants (etr1-3 and ein3-1) exhibited greater tolerance to NaHCO3 than the wild type, and the growth-promoting effect of Jrh14-10 was significantly diminished in these mutants. Additionally, Jrh14-10 was found unable to produce 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, indicating it does not reduce the ethylene precursor ACC in Arabidopsis. However, Jrh14-10 treatment increased the levels of polyamines (putrescine, spermidine, and spermine) in stressed seedlings, with spermidine particularly effective in reducing H2O2 levels and enhancing Fv/Fm under NaHCO3 stress. These findings reveal a novel mechanism of PGPR-induced alkaline tolerance, highlighting the crosstalk between ethylene and polyamine pathways, and suggest a strategic redirection of S-adenosylmethionine towards polyamine biosynthesis to combat alkaline stress.

Baseline sensitivity and toxicity mechanisms of prochloraz to Alternaria alternata strains associated with maize leaf blight in Heilongjiang province in China.

Alternaria species are fungal pathogens that can infect maize, causing leaf blight disease and significant economic losses. This study aimed to determine the baseline sensitivity to prochloraz of A. alternata isolates obtained from diseased maize leaves collected from Heilongjiang province by assessing the half-maximal effective concentration (EC50) values. The EC50 values of prochloraz ranged from 0.0550 µg/mL to 2.3258 µg/mL, with an average of 0.9995 ± 0.5192 µg/mL. At EC50 (1.2495 µg/mL) and 2EC50 (2.4990 µg/mL), prochloraz increased the number of mycelial offshoots, disrupted the cell membrane integrity of conidia and mycelia, and resulted in a reduced ergosterol content in the mycelia. Prochloraz significantly affected the mycelial cell membrane permeability and increased the malondialdehyde (MDA) content and superoxide dismutase (SOD) activity. No cross-resistance was detected between prochloraz and other fungicides. These data demonstrate that prochloraz is a promising fungicide for managing maize leaf blight caused by A. alternata and provide novel insights into understanding the mechanism of prochloraz toxicity against A. alternata isolates.

Constructing Co@TiO2 Nanoarray Heterostructure with Schottky Contact for Selective Electrocatalytic Nitrate Reduction to Ammonia.

Electrochemical nitrate (NO3 - ) reduction reaction (NO3 - RR) is a potential sustainable route for large-scale ambient ammonia (NH3 ) synthesis and regulating the nitrogen cycle. However, as this reaction involves multi-electron transfer steps, it urgently needs efficient electrocatalysts on promoting NH3  selectivity. Herein, a rational design of Co nanoparticles anchored on TiO2  nanobelt array on titanium plate (Co@TiO2 /TP) is presented as a high-efficiency electrocatalyst for NO3 - RR. Density theory calculations demonstrate that the constructed Schottky heterostructures coupling metallic Co with semiconductor TiO2  develop a built-in electric field, which can accelerate the rate determining step and facilitate NO3 - adsorption, ensuring the selective conversion to NH3 . Expectantly, the Co@TiO2 /TP electrocatalyst attains an excellent Faradaic efficiency of 96.7% and a high NH3  yield of 800.0 µmol h-1  cm-2  under neutral solution. More importantly, Co@TiO2 /TP heterostructure catalyst also presents a remarkable stability in 50-h electrolysis test.

Pd-Doped Co3 O4 Nanoarray for Efficient Eight-Electron Nitrate Electrocatalytic Reduction to Ammonia Synthesis.

Ammonia (NH3 ) is an indispensable feedstock for fertilizer production and one of the most ideal green hydrogen rich fuel. Electrochemical nitrate (NO3 - ) reduction reaction (NO3 - RR) is being explored as a promising strategy for green to synthesize industrial-scale NH3 , which has nonetheless involved complex multi-reaction process. This work presents a Pd-doped Co3 O4 nanoarray on titanium mesh (Pd-Co3 O4 /TM) electrode for highly efficient and selective electrocatalytic NO3 - RR to NH3 at low onset potential. The well-designed Pd-Co3 O4 /TM delivers a large NH3 yield of 745.6 µmol h-1 cm-2 and an extremely high Faradaic efficiency (FE) of 98.7% at -0.3 V with strong stability. These calculations further indicate that the doping Co3 O4 with Pd improves the adsorption characteristic of Pd-Co3 O4 and optimizes the free energies for intermediates, thereby facilitating the kinetics of the reaction. Furthermore, assembling this catalyst in a Zn-NO3 - battery realizes a power density of 3.9 mW cm-2 and an excellent FE of 98.8% for NH3 .

Defective TiO2- x for High-Performance Electrocatalytic NO Reduction toward Ambient NH3 Production.

Synthesis of green ammonia (NH3 ) via electrolysis of nitric oxide (NO) is extraordinarily sustainable, but multielectron/proton-involved hydrogenation steps as well as low concentrations of NO can lead to poor activities and selectivities of electrocatalysts. Herein, it is reported that oxygen-defective TiO2 nanoarray supported on Ti plate (TiO2- x /TP) behaves as an efficient catalyst for NO reduction to NH3 . In 0.2 m phosphate-buffered electrolyte, such TiO2- x /TP shows competitive electrocatalytic NH3 synthesis activity with a maximum NH3 yield of 1233.2 µg h-1  cm-2 and Faradaic efficiency of 92.5%. Density functional theory calculations further thermodynamically faster NO deoxygenation and protonation processes on TiO2- x (101) compared to perfect TiO2 (101). And the low energy barrier of 0.7 eV on TiO2- x (101) for the potential-determining step further highlights the greatly improved intrinsic activity. In addition, a Zn-NO battery is fabricated with TiO2- x /TP and Zn plate to obtain an NH3 yield of 241.7 µg h-1  cm-2 while providing a peak power density of 0.84 mW cm-2 .

Rational Construction of Heterostructured Cu3 P@TiO2 Nanoarray for High-Efficiency Electrochemical Nitrite Reduction to Ammonia.

Electroreduction of nitrite (NO2 - ) to valuable ammonia (NH3 ) offers a sustainable and green approach for NH3 synthesis. Here, a Cu3 P@TiO2 heterostructure is rationally constructed as an active catalyst for selective NO2 - -to-NH3 electroreduction, with rich nanosized Cu3 P anchored on a TiO2 nanoribbon array on Ti plate (Cu3 P@TiO2 /TP). When performed in the 0.1 m NaOH with 0.1 m NaNO2 , the Cu3 P@TiO2 /TP electrode obtains a large NH3 yield of 1583.4 µmol h-1  cm-2 and a high Faradaic efficiency of 97.1%. More importantly, Cu3 P@TiO2 /TP also delivers remarkable long-term stability for 50 h electrolysis. Theoretical calculations indicate that intermediate adsorption/conversion processes on Cu3 P@TiO2 interfaces are synergistically optimized, substantially facilitating the conversion of NO2 - -to-NH3 .

High-Performance Electrocatalytic Reduction of Nitrite to Ammonia under Ambient Conditions on a FeP@TiO2 Nanoribbon Array.

Electrochemical nitrite (NO2-) reduction is recognized as a promising strategy for synthesizing valuable ammonia (NH3) and degrading NO2- pollutants in wastewater. The six-electron process for the NO2- reduction reaction is complex and necessitates a highly selective and stable electrocatalyst for efficient conversion of NO2- to NH3. Herein, a FeP nanoparticle-decorated TiO2 nanoribbon array on a titanium plate (FeP@TiO2/TP) is proposed as an efficient catalyst for NH3 production under ambient conditions. In 0.1 M NaOH with 0.1 M NO2-, such a FeP@TiO2/TP affords a large NH3 yield of 346.6 µmol h-1 cm-2 and a high Faradaic efficiency of 97.1%. Additionally, it demonstrates excellent stability and durability during long-term cycling tests and electrolysis experiments.

Ambient Ammonia Synthesis via Nitrate Electroreduction in Neutral Media on Fe3O4 Nanoparticles-decorated TiO2 Nanoribbon Array.

Electrochemical nitrate (NO3-) reduction is a potential approach to produce high-value ammonia (NH3) while removing NO3- pollution, but it requires electrocatalysts with high efficiency and selectivity. Herein, we report the development of Fe3O4 nanoparticles decorated TiO2 nanoribbon array on titanium plate (Fe3O4@TiO2/TP) as an efficient electrocatalyst for NO3--to-NH3 conversion. When operated in 0.1 M phosphate-buffered saline and 0.1 M NO3-, such Fe3O4@TiO2/TP achieves a prominent NH3 yield of 12394.3 µg h-1 cm-2 and a high Faradaic efficiency of 88.4%. In addition, it exhibits excellent stability during long-time electrolysis.

The third-person perspective full-body illusion induced by visual-tactile stimulation in virtual reality for stroke patients.

This paper attempts to induce the third-person perspective full body illusion (3PP-FBI) with virtual reality (VR) in stroke patients. Nineteen individuals with stroke were recruited. The 3PP-FBI induction method, which was well-established in healthy individuals, using synchronous visual-tactile stimulation on one body part was used. Questionnaire scores and proprioceptive drift values were collected under different conditions for characterizing the induced 3PP-FBI. Results showed that synchronous visual-tactile stimulation of a single body part (back or upper limb) was sufficient to elicit 3PP-FBI in stroke patients, forming a sense of ownership (SOO) over the entire virtual body. Moreover, the intensity of 3PP-FBI was stronger when the back was stimulated, compared to stimulating the impaired upper limb. This study demonstrated the viability of visual-guided rehabilitation training while having a SOO to a virtual body from the third-person perspective, in anticipation of achieving better rehabilitation outcome for movements beyond the first-person perspective.

Review of machine learning methods for RNA secondary structure prediction.

Secondary structure plays an important role in determining the function of noncoding RNAs. Hence, identifying RNA secondary structures is of great value to research. Computational prediction is a mainstream approach for predicting RNA secondary structure. Unfortunately, even though new methods have been proposed over the past 40 years, the performance of computational prediction methods has stagnated in the last decade. Recently, with the increasing availability of RNA structure data, new methods based on machine learning (ML) technologies, especially deep learning, have alleviated the issue. In this review, we provide a comprehensive overview of RNA secondary structure prediction methods based on ML technologies and a tabularized summary of the most important methods in this field. The current pending challenges in the field of RNA secondary structure prediction and future trends are also discussed.

Highly Stable Colorimetric Sensing by Assembly of Gold Nanoparticles with SYBR Green I: From Charge Screening to Charge Neutralization.

Aggregation of plasmonic gold nanoparticles (AuNPs) has been widely used for label-free colorimetric sensing. Adding salt is a commonly used method to induce a color change, but salt-induced aggregation by charge screening is a slow kinetic process, making quantitative and reproducible measurement difficult. Herein, we explored an alternative method by charge neutralization using positively charged molecules, such as a DNA-staining dye, SYBR Green I (SG), for efficient and stable assembly of AuNPs. Even submicromolar SG effectively triggered the aggregation of AuNPs in less than 1 min, and the resulting intense blue color was stable for over 10 h. The charge neutralization effect of SG was confirmed with zeta potential measurements. Besides, pH-dependent aggregation of AuNPs by SG agreed well with the pKa of the nitrogen atoms responsible for the positive charges in the SG structure. Moreover, the charge neutralization effect was also observed from polycations such as polyamines. The SG-induced assembly of AuNPs was developed into a label-free colorimetric sensing platform. Benefiting from the intense blue color, this new sensing strategy allowed visual detection of as low as 0.1 nM DNA, 50-fold lower than that by salt. Such a charge neutralization strategy may inspire further thinking on fundamental colloidal science and its applications in analytical chemistry. This work itself significantly improved AuNP-based colorimetric sensors in terms of detection time, signal stability, and sensitivity.

Oxidative Capacity Storage of Transient Singlet Oxygen from Photosensitization with a Redox Mediator for Improved Chemiluminescent Sensing.

Singlet oxygen, generated from type-II photosensitization, has become increasingly popular in bioassay development in recent years. However, the transient nature of singlet oxygen in water (lifetime shorter than 4 µs) as well as its high activity make it easily inactivated by solvent molecules and other coexisting species, thus deteriorating use in the analytical sensitivity. Here, we proposed the use of a simple redox mediator for storing the energy of the transient singlet oxygen. To demonstrate such an idea, singlet oxygen generated from photosensitization of the double strand DNA-SYBR Green I (dsDNA-SG) complex was explored as a redox donor that can be modulated through formation and deformation of the dsDNA structure. After screening of a series of redox mediators with luminol chemiluminescence (CL) as the probe, ferrocyanide (K4Fe(CN)6) was found to be the most efficient, resulting in ∼30-fold intensified luminol CL. By storing the oxidative capacity of singlet oxygen in ferrocyanide, the dsDNA-SG complex was evolved into a photosensitization-mediated chemiluminescence (PMCL) biosensing platform for DNA detection. Such a PMCL sensing platform allows label- and amplification-free detection of picomolar-scale DNA with a limit of detection (LOD) of 1.5 pM (0.45 fmol in absolute). The excellent sensitivity of PMCL sensing confirmed that such a facile storage approach to oxidative capacity would be appealing for singlet-oxygen-involved biosensing.

Prediction of plant-derived xenomiRs from plant miRNA sequences using random forest and one-dimensional convolutional neural network models.

BACKGROUND: An increasing number of studies reported that exogenous miRNAs (xenomiRs) can be detected in animal bodies, however, some others reported negative results. Some attributed this divergence to the selective absorption of plant-derived xenomiRs by animals. RESULTS: Here, we analyzed 166 plant-derived xenomiRs reported in our previous study and 942 non-xenomiRs extracted from miRNA expression profiles of four species of commonly consumed plants. Employing statistics analysis and cluster analysis, our study revealed the potential sequence specificity of plant-derived xenomiRs. Furthermore, a random forest model and a one-dimensional convolutional neural network model were trained using miRNA sequence features and raw miRNA sequences respectively and then employed to predict unlabeled plant miRNAs in miRBase. A total of 241 possible plant-derived xenomiRs were predicted by both models. Finally, the potential functions of these possible plant-derived xenomiRs along with our previously reported ones in human body were analyzed. CONCLUSIONS: Our study, for the first time, presents the systematic plant-derived xenomiR sequences analysis and provides evidence for selective absorption of plant miRNA by human body, which could facilitate the future investigation about the mechanisms underlying the transference of plant-derived xenomiR.

Seizure evolution can be characterized as path through synaptic gain space of a neural mass model.

Physiologically based models could facilitate better understanding of mechanisms underlying epileptic seizures. In this paper, we attempt to reveal the dynamic evolution of intracranial EEG activity during epileptic seizures based on synaptic gain identification procedure of a neural mass model. The distribution of average excitatory, slow and fast inhibitory synaptic gain in the parameter space and their temporal evolution, i.e., the path through the model parameter space, were analyzed in thirty seizures from ten temporal lobe epileptic patients. Results showed that the synaptic gain values located roughly on a plane before seizure onset, dispersed during seizure and returned to the plane when seizure terminated. Cluster analysis was performed on seizure paths and demonstrated consistency in synaptic gain evolution across different seizures from the individual patient. Furthermore, two patient groups were identified, each one corresponding to a specific synaptic gain evolution in the parameter space during a seizure. Results were validated by a bootstrapping approach based on comparison with random paths. The differences in the path revealed variations in EEG dynamics for patients despite showing identical seizure onset pattern. Our approach may have the potential to classify the epileptic patients into subgroups based on different mechanisms revealed by subtle changes in synaptic gains and further enable more robust decisions regarding treatment strategy.

Dynamics underlying interictal to ictal transition in temporal lobe epilepsy: insights from a neural mass model.

We propose an approach that combines a neural mass model and clinical intracranial electroencephalographic (iEEG) recordings to explore the potential pathophysiological mechanisms (at the neuronal population level) of ictogenesis. Thirty iEEG recordings from 10 temporal lobe epilepsy (TLE) patients around seizure onset were investigated. Physiologically meaningful parameters [average excitatory (Ae ), slow (B), and fast (G) inhibitory synaptic gain] were identified during interictal to ictal transition. Four ratios (Ae /G, Ae /B, Ae /(B + G), and B/G) were derived from these parameters, and their evolution over time was analyzed. The excitation/inhibition ratio increased around seizure onset and decreased before seizure offset, indicating the impairment and re-emergence of excitation/inhibition balance around seizure onset and before seizure offset, respectively. Moreover, the slow inhibition may have an earlier effect on excitation/inhibition imbalance. We confirm the decrease in excitation/inhibition ratio upon seizure termination in human temporal lobe epilepsy, as revealed by optogenetic approaches both in vivo in animal models and in vitro. The increase in excitation/inhibition ratio around seizure occurrence could be an indicator to detect seizures.

Generalization of the primary tone phase variation method: An exclusive way of isolating the frequency-following response components.

The primary tone phase variation (PTPV) technique combines selective sub-averaging with systematic variation of the phases of multitone stimuli. Each response component having a known phase relationship with the stimulus components phases can be isolated in the time domain. The method was generalized to the frequency-following response (FFR) evoked by a two-tone (f 1 and f 2) stimulus comprising both linear and non-linear, as well as transient components. The generalized PTPV technique isolated each spectral component present in the FFR, including those sharing the same frequency, allowing comparison of their latencies. After isolation of the envelope component f 2 - f 1 from its harmonic distortion 2f 2 - 2f 1 and from the transient auditory brainstem response, a computerized analysis of instantaneous amplitudes and phases was applied in order to objectively determine the onset and offset latencies of the response components. The successive activation of two generators separated by 3.7 ms could be detected in all (N = 12) awake adult normal subjects, but in none (N = 10) of the sleeping/sedated children with normal hearing thresholds. The method offers an unprecedented way of disentangling the various FFR subcomponents. These results open the way for renewed investigations of the FFR components in both human and animal research as well as for clinical applications.

An Energy-Efficient Wireless Power Receiver With One-Step Adiabatic-Bipolar-Supply Generating for Implantable Electrical Stimulation Applications.

This paper presents an energy-efficient wireless power receiver for implantable electrical stimulation applications, which can achieve one-step adiabatic bipolar-supply that is generated by a hybrid single-stage dual-output regulating (SSDOR) rectifiers. The structure using only four switches overcomes the disadvantages that the two output voltage values in the traditional dual-output rectifiers are close to each other. A constant-current (CC) controlled adiabatic dynamic voltage scaling (DVS) technique is proposed to minimize the voltage headroom of the stimulating drivers and improve the stimulation efficiency significantly. In addition, the receiver adopts only one general constant on-time (COT) low-frequency control to adjust the stimulation current, reducing both the power consumption and the complexity of the control circuits. The proposed receiver has been fabricated in a 0.18 µm BCD process with ±6 V voltage compliance and 2.5 mA maximum stimulating current. With a current range from ±1.5 mA to ±2.5 mA, the measured maximum average headroom voltage is only 80 mV and the peak total efficiency of the receiver is 85.6%. The functionalities of the proposed receiver have been successfully verified through in vitro experiments.

A 3-mV Precision Dual-Mode-Controlled Fast Charge Balancing for Implantable Biphasic Neural Stimulators.

This paper presents a novel charge balancing (CB) with a current-control (CC) mode and a voltage-control (VC) mode for implantable biphasic stimulators, which can achieve one-step accurate anodic pulse generating. Compared with the conventional short-pulse-injection-based CB, the proposed method could reduce the balancing time and avoid inducing undesired artifact. The CC operation compensates the majority stimulation charge at high speed, while the VC operation guarantees a high CB precision. In order to eliminate the oscillation during the mode transition, a smooth CC-VC transition method is adopted. In addition, a digital auxiliary monitoring loop is introduced against the variations of the tissue-electrode interface impedance during the stimulation process to meet long-term CB requirement. The proposed stimulator has been fabricated in a 0.18 µm BCD process with 10 V voltage compliance, and the measured CB precision is less than 3 mV. The functionalities of the proposed CB have been verified successfully through in vitro experiments.

Event-Related EEG Desynchronization Reveals Enhanced Motor Imagery From the Third Person Perspective by Manipulating Sense of Body Ownership With Virtual Reality for Stroke Patients.

Virtual reality (VR)-based rehabilitation training holds great potential for post-stroke motor recovery. Existing VR-based motor imagery (MI) paradigms mostly focus on the first-person perspective, and the benefit of the third-person perspective (3PP) remains to be further exploited. The 3PP is advantageous for movements involving the back or those with a large range because of its field coverage. Some movements are easier to imagine from the 3PP. However, the 3PP training efficiency may be unsatisfactory, which may be attributed to the difficulty encountered when generating a strong sense of ownership (SOO). In this work, we attempt to enhance a visual-guided 3PP MI in stroke patients by eliciting the SOO over a virtual avatar with VR. We propose to achieve this by inducing the so-called out-of-body experience (OBE), which is a full-body illusion (FBI) that people misperceive a 3PP virtual body as his/her own (i.e., generating the SOO to the virtual body). Electroencephalography signals of 13 stroke patients are recorded while MI of the affected upper limb is being performed. The proposed paradigm is evaluated by comparing event-related desynchronization (ERD) with a control paradigm without FBI induction. The results show that the proposed paradigm leads to a significantly larger ERD during MI, indicating a bilateral activation pattern consistent with that in previous studies. In conclusion, 3PP MI can be enhanced in stroke patients by eliciting the SOO through induction of the "OBE" FBI. This study offers more possibilities for virtual rehabilitation in stroke patients and can further facilitate VR application in rehabilitation.

High-efficiency electrocatalytic nitrite-to-ammonia conversion on molybdenum doped cobalt oxide nanoarray at ambient conditions.

Electrochemical conversion of nitrite (NO2-) contaminant to green ammonia (NH3) is a promising approach to achieve the nitrogen cycle. The slow kinetics of the complex multi-reaction process remains a serious issue, and there is still a need to design highly effective and selective catalysts. Herein, we report that molybdenum doped cobalt oxide nanoarray on titanium mesh (Mo-Co3O4/TM) acts as a catalyst to facilitate electroreduction of NO2- to NH3. Such a catalyst delivers an extremely high Faradaic efficiency of 96.9 % and a corresponding NH3 yield of 651.5 µmol h-1 cm-2 at -0.5 V with strong stability. Density functional theory calculations reveal that the introduction of Mo can induce the redistribution of electrons around Co atoms and further strengthen the adsorption of NO2-, which is the key to facilitating the catalytic performance. Furthermore, the assembled battery based on Mo-Co3O4/TM suggests its practical application value.