Melatonin (N‐acetyl‐5‐methoxytryptamine) is an important biological hormone in many abiotic stress responses and developmental processes. In this study, the protective roles of melatonin were ...investigated by measuring the antioxidant defense system and photosynthetic characteristics in maize under salt stress. The results indicated that NaCl treatment led to the decrease in plant growth, chlorophyll contents and photochemical activity of photosystem II (PSII). However, the levels of reactive oxygen species increased significantly under salt stress. Meanwhile, we found that application of exogenous melatonin alleviated reactive oxygen species burst and protected the photosynthetic activity in maize seedlings under salt stress through the activation of antioxidant enzymes. In addition, 100 μM melatonin‐treated plants showed high photosynthetic efficiency and salinity. Immunoblotting analysis of PSII proteins showed that melatonin application alleviated the decline of 34 kDa PSII reaction center protein (D1) and the increase of PSII subunit S protein. Taken together, our study promotes more comprehensive understanding in the protective effects of exogenous melatonin in maize under salt stress, and it may be involved in activation of antioxidant enzymes and regulation of PSII proteins.
Summary
Sessile plants constantly experience environmental stresses in nature. They must have evolved effective mechanisms to balance growth with stress response. Here we report the MADS‐box ...transcription factor AGL16 acting as a negative regulator in stress response in Arabidopsis.
Loss‐of‐AGL16 confers resistance to salt stress in seed germination, root elongation and soil‐grown plants, while elevated AGL16 expression confers the opposite phenotypes compared with wild‐type. However, the sensitivity to abscisic acid (ABA) in seed germination is inversely correlated with AGL16 expression levels.
Transcriptomic comparison revealed that the improved salt resistance of agl16 mutants was largely attributed to enhanced expression of stress‐responsive transcriptional factors and the genes involved in ABA signalling and ion homeostasis. We further demonstrated that AGL16 directly binds to the CArG motifs in the promoter of HKT1;1, HsfA6a and MYB102 and represses their expression. Genetic analyses with double mutants also support that HsfA6a and MYB102 are target genes of AGL16.
Taken together, our results show that AGL16 acts as a negative regulator transcriptionally suppressing key components in the stress response and may play a role in balancing stress response with growth.
Summary
Nitrogen (N) is one of the key essential macronutrients that affects rice growth and yield. Inorganic N fertilizers are excessively used to boost yield and generate serious collateral ...environmental pollution. Therefore, improving crop N use efficiency (NUE) is highly desirable and has been a major endeavour in crop improvement. However, only a few regulators have been identified that can be used to improve NUE in rice to date. Here we show that the rice NIN‐like protein 4 (OsNLP4) significantly improves the rice NUE and yield. Field trials consistently showed that loss‐of‐OsNLP4 dramatically reduced yield and NUE compared with wild type under different N regimes. In contrast, the OsNLP4 overexpression lines remarkably increased yield by 30% and NUE by 47% under moderate N level compared with wild type. Transcriptomic analyses revealed that OsNLP4 orchestrates the expression of a majority of known N uptake, assimilation and signalling genes by directly binding to the nitrate‐responsive cis‐element in their promoters to regulate their expression. Moreover, overexpression of OsNLP4 can recover the phenotype of Arabidopsis nlp7 mutant and enhance its biomass. Our results demonstrate that OsNLP4 plays a pivotal role in rice NUE and sheds light on crop NUE improvement.
Nitrogen (N) is an essential macronutrient for crop growth and yield. Improving the N use efficiency (NUE) of crops is important to agriculture. However, the molecular mechanisms underlying NUE ...regulation remain largely elusive. Here we report that the OsNLP3 (NIN‐like protein 3) regulates NUE and grain yield in rice under N sufficient conditions. OsNLP3 transcript level is significantly induced by N starvation and its protein nucleocytosolic shuttling is specifically regulated by nitrate. Loss‐of‐function of OsNLP3 reduces plant growth, grain yield, and NUE under sufficient nitrate conditions, whereas under low nitrate or different ammonium conditions, osnlp3 mutants show no clear difference from the wild type. Importantly, under sufficient N conditions in the field, OsNLP3 overexpression lines display improved grain yield and NUE compared with the wild type. OsNLP3 orchestrates the expression of multiple N uptake and assimilation genes by directly binding to the nitrate‐responsive cis‐elements in their promoters. Overall, our study demonstrates that OsNLP3, together with OsNLP1 and OsNLP4, plays overlapping and differential roles in N acquisition and NUE, and modulates NUE and the grain yield increase promoted by N fertilizer. Therefore, OsNLP3 is a promising candidate gene for the genetic improvement of grain yield and NUE in rice.
Summary Statement
Crop nitrogen use efficiency (NUE) is an important agronomic trait. But the molecular mechanisms underlying NUE regulation are not well understood. This study reveals that rice NIN‐like protein 3 (OsNLP3) regulates NUE and grain yield especially under N sufficient conditions and is a promising candidate gene for improving grain yield and NUE in rice.
Summary
Rice panicles, a major component of yield, are regulated by phytohormones and nutrients. How mineral nutrients promote panicle architecture remains largely unknown.
Here, we report that ...NIN‐LIKE PROTEIN3 and 4 (OsNLP3/4) are crucial positive regulators of rice panicle architecture in response to nitrogen (N). Loss‐of‐function mutants of either
OsNLP3
or
OsNLP4
produced smaller panicles with reduced primary and secondary branches and fewer grains than wild‐type, whereas their overexpression plants showed the opposite phenotypes.
The OsNLP3/4‐regulated panicle architecture was positively correlated with N availability. OsNLP3/4 directly bind to the promoter of
OsRFL
and activate its expression to promote inflorescence meristem development. Furthermore, OsRFL activates
OsMOC1
expression by binding to its promoter.
Our findings reveal the novel N‐responsive OsNLP3/4‐OsRFL‐OsMOC1 module that integrates N availability to regulate panicle architecture, shedding light on how N nutrient signals regulate panicle architecture and providing candidate targets for the improvement of crop yield.
In this hydrological study, we developed a Transformer-based model to forecast urban river discharges and predict flood peaks, crucial for flood mitigation in urban areas prone to inundation. ...Utilizing daily precipitation data from 63 meteorological stations and flow data from hydrological stations, we established a correlation using the Random Forest method to determine the lag time between precipitation and flow. The model, enhanced with alternative loss functions – Weighted MSE Loss (WMSE), Huber Loss (Hloss), and Quantile Loss (Qloss) – instead of traditional Mean Squared Error (MSE), aims to project daily flow rates for seven days. Our findings indicate that Hloss significantly reduces absolute errors in peak value predictions, while WMSE improves linear correlation in forecasting. The accuracy remains stable for the initial four days, with a decrease from the fifth day. This approach, integrating diverse loss functions, presents a novel method for accurately predicting river discharges, offering vital insights for proactive flood management.
•Unique loss functions tailored to amplify peak flow event prediction accuracy.•Novel integration of DSW preprocessing with Transformer for hydrology forecasting.•Lag time optimization using Random Forest, enhancing input data synchronization.•Advanced seven-day flow forecasting leveraging data from 63 meteorological stations.•Dynamic model update strategy proposed for long-term hydrological shifts.
Traditional Chinese medicine (TCM) is considered a valuable asset in China's medical tradition. YPF is a classic prescription that has been derived from the "Jiu Yuan Fang" formula and consists of ...three herbs: Huangqi (Astragalus membranaceus Bunge), Baizhu (Atractylodes rubra Dekker), and Fangfeng (Saposhnikovia divaricata (Turcz.) Schischk). This prescription is widely acclaimed for its exceptional pharmacological properties, including potent antioxidant effects, hormone regulation, and immune modulation effects.
Previous research provides evidence suggesting that YPF may have therapeutic effects on pulmonary fibrosis. Further exploration is essential to confirm its effectiveness and elucidate the fundamental processes.
First, the active components and target genes of YPF were extracted from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Next, the GSE53845 dataset, which contains information on pulmonary fibrosis, was downloaded from the GEO database. Network informatics methods was then be utilized to identify target genes associated with pulmonary fibrosis. A YPF-based network of protein-protein interactions was constructed to pinpoint possible target genes for pulmonary fibrosis treatment. Additionally, an in vitro model of pulmonary fibrosis induced by bleomycin (BLM) was established to further investigate and validate the possible mechanisms underlying the effectiveness of YPF.
In this study, a total of 24 active ingredients of YPF, along with 178 target genes associated with the treatment, were identified. Additionally, 615 target genes related to pulmonary fibrosis were identified. Functional enrichment analysis revealed that 18 candidate genes (CGs) exhibited significant responses to tumor necrosis factor, NF-kB survival signaling, and positive regulation of apoptosis processes. Among these CGs, CAV1, VCAM1, and TP63 were identified as key target genes. Furthermore, cell experiments confirmed that the expression of CAV1 protein and RNA expression was increased in pulmonary fibrosis, but significantly decreased after treatment with YPF. Additionally, the expression of pSmad2, α-SMA, TGF-β1, and TNF-α was also decreased following YPF treatment.
Network pharmacology analysis revealed that YPF exhibits significant potential as a therapeutic intervention for pulmonary fibrosis by targeting various compounds and pathways. This study emphasizes that the efficacy of YPF in treating pulmonary fibrosis may be attributed to its ability to up-regulate CAV1 expression and inhibiting pulmonary fibrosis via modulation of the TGF-β1/Smad2 signaling pathway. These findings underscore the promising role of YPF and its ability to potentially alleviate pulmonary fibrosis.
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•YPF has significant potential as a therapeutic intervention for pulmonary fibrosis.•CAV1 may contribute to the therapeutic effects of YPF in treating pulmonary fibrosis.•YPF can inhibit pulmonary fibrosis by modulating the TGF-β1/Smad2 signaling pathway.
Crop yield plays a critical role in global food security. For optimal plant growth and maximal crop yields, nutrients must be balanced. However, the potential significance of balanced nitrogen–iron ...(N–Fe) for improving crop yield and nitrogen use efficiency (NUE) has not previously been addressed. Here, we show that balanced N–Fe sufficiency significantly increases tiller number and boosts yield and NUE in rice and wheat. NIN-like protein 4 (OsNLP4) plays a pivotal role in maintaining the N–Fe balance by coordinately regulating the expression of multiple genes involved in N and Fe metabolism and signaling. OsNLP4 also suppresses OsD3 expression and strigolactone (SL) signaling, thereby promoting tillering. Balanced N–Fe sufficiency promotes the nuclear localization of OsNLP4 by reducing H2O2 levels, reinforcing the functions of OsNLP4. Interestingly, we found that OsNLP4 upregulates the expression of a set of H2O2-scavenging genes to promote its own accumulation in the nucleus. Furthermore, we demonstrated that foliar spraying of balanced N–Fe fertilizer at the tillering stage can effectively increase tiller number, yield, and NUE of both rice and wheat in the field. Collectively, these findings reveal the previously unrecognized effects of N–Fe balance on grain yield and NUE as well as the molecular mechanism by which the OsNLP4–OsD3 module integrates N–Fe nutrient signals to downregulate SL signaling and thereby promote rice tillering. Our study sheds light on how N–Fe nutrient signals modulate rice tillering and provide potential innovative approaches that improve crop yield with reduced N fertilizer input for benefitting sustainable agriculture worldwide.
This study characterizes the OsNLP4–OsD3 module that integrates N–Fe nutrient signals to downregulate SL signaling and thereby promote rice tillering. The results also show that the balanced N–Fe fertilizer can significantly improve grain yield and NUE in both rice and wheat under field conditions.
Diagnosis of lung cancer at an early disease stage is important for successful treatment and improving the outcome of patients. To improve its prognosis, we attempted to explore novel tools for ...screening serum biomarkers to distinguish lung cancer from healthy individuals by serum protein profiles and a classification tree algorithm.
Serum samples were applied to metal affinity protein chips to generate mass spectra by surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry. Protein peak identification and clustering were performed using the Biomarker Wizard software. Proteomic spectra of serum samples from 89 lung cancer patients and age- and sex-matched 68 healthy individuals were used as a training set and a classification tree with 3 distinct protein masses was generated by using Biomarker Pattern software. The validity of the classification tree was then challenged with a blind test set including another 62 lung cancer patients and 34 healthy individuals. We additionally determined Cyfra21-1 and carcinoembryonic antigen in all the serum samples included in this study using an electrochemiluminescent immunoassay.
The software identified an average of 48 mass peaks/spectrum and 3 of the identified peaks at 5808, 5971, and 7779 d were used to construct the classification tree. The classification tree separated effectively lung cancer from healthy individuals, achieving a sensitivity of 91% (81 of 89) and a specificity of 97% (66 of 68). The blind test challenged the model with a sensitivity of 89% (55 of 62) and a specificity of 91% (31 of 34), and a positive predictive value of 90% (86 of 96), respectively. The specificity of Cyfra21-1 and the sensitivity provided by Cyfra21-1 and carcinoembryonic antigen used individually or in combination were significantly lower than that of the SELDI marker pattern (P < 0.05 or P < 0.005, respectively).
The results suggest that SELDI time-of-flight mass spectrometry technique can correctly distinguish lung cancer patients from healthy individuals and shows great potential for the development of a screening test for the detection of lung cancer.
Human papillomavirus (HPV) infection has been implicated as a causative of cervical cancer. In the present study, a total of 578 samples from females attending the gynecological outpatient clinic in ...Henan province, China, were collected and the HPV genotypes were detected by gene chip and flow-through hybridization. Overall, 44.5% (257/578) females were found to be HPV DNA positive, and the high risk HPV (HR-HPV) rate was 35.1% (203/578). The first peak of HR-HPV infection appeared in the >60 year-old group (55.0%), and the second was within the 51-55 year-old group (50.0%) (χ2=19.497, p<0.05). HPV 16 was the most prevalent genotype (9.2%), followed by HPV 52 (7.8%), HPV 6 (6.9%), HPV 11 (5.9%) and HPV 42 (5.0%). The single type HPV infection was 30.4%, with the five majority prevalent genotype HPV 16 (16.5%), HPV 52 (14.3%), HPV 6 (12.6%), HPV 42 (8.6%), HPV 31 (5.1%). The multiple-type HPV infections were 14.0%, and HPV 16 was the most prevalent type (29.6%), followed by HPV 52 (24.7%), HPV 6 (22.2%), HPV 11 (22.2%), HPV 42 (17.3%) and HPV 39 (17.3%).
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