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Cells in organ primordia undergo active proliferation at an early stage to generate sufficient number, before exiting proliferation and entering differentiation. However, how the actively proliferating cells are developmentally reprogrammed to acquire differentiation potential during organ maturation is unclear. Here, we induced a microRNA-resistant form of TCP4 at various developmental stages of Arabidopsis leaf primordium that lacked the activity of TCP4 and its homologues and followed its effect on growth kinematics. By combining this with spatio-temporal gene expression analysis, we show that TCP4 commits leaf cells within the transition zone to exit proliferation and enter differentiation. A 24-hour pulse of TCP4 activity was sufficient to impart irreversible differentiation competence to the actively dividing cells. A combination of biochemical and genetic analyses revealed that TCP4 imparts differentiation competence by promoting auxin response as well as by directly activating HAT2, a HD-ZIP II transcription factor-encoding gene that also acts downstream to auxin response. Our study offers a molecular link between the two major organ maturation factors, CIN-like TCPs and HD-ZIP II transcription factors and explains how TCP activity restricts the cell number and final size in a leaf.

As the world’s attention turns to cleaner, more dependable, and sustainable resources, the renewable energy sector is rising quickly. The decline in world energy use and climate change are the two most significant factors nowadays. PV forecasting was essential to enhancing the efficiency of the real-time control system and preventing any undesirable effects. The smart energy management systems of distributed energy resources, the forecasting model of irradiation received from the sun, and therefore PV energy production might mitigate the impact of uncertainty on PV energy generation, improve system dependability, and increase the incursion level of solar power generation. Smart sensors and Internet of Things technologies are essential for monitoring and controlling applications in a broad range of fields. As a result, solar power generation forecasting was essential for microgrid stability and security, as well as solar photovoltaic integration in a strategic approach. This paper examines how to use IoT, a solar photovoltaic system being monitored, and shows the proposed monitoring system is a potentially viable option for smart remote and in-person monitoring of a solar PV system.

Cell expansion is an essential process in plant morphogenesis and is regulated by the coordinated action of environmental stimuli and endogenous factors, such as the phytohormones auxin and brassinosteroid. Although the biosynthetic pathways that generate these hormones and their downstream signaling mechanisms have been extensively studied, the upstream transcriptional network that modulates their levels and connects their action to cell morphogenesis is less clear. Here, we show that the miR319-regulated TCP (TEOSINTE BRANCHED1, CYCLODEA, PROLIFERATING CELL FACTORS) transcription factors, notably TCP4, directly activate YUCCA5 transcription and integrate the auxin response to a brassinosteroid-dependent molecular circuit that promotes cell elongation in Arabidopsis thaliana hypocotyls. Furthermore, TCP4 modulates the common transcriptional network downstream to auxin-brassinosteroid signaling, which is also triggered by environmental cues, such as light, to promote cell expansion. Our study links TCP function with the hormone response during cell morphogenesis and shows that developmental and environmental signals converge on a common transcriptional network to promote cell elongation.

Background Enteric methane emissions from dairy cows are an environmental problem as well as a gross feed energy loss to the animal. Methane is generated in the rumen by methanogenic archaea from hydrogen (H 2 ) + carbon dioxide and from H 2 + methanol or methylamines. The methanogenic substrates are provided by non-methanogens during feed fermentation. Methane mitigation approaches have yielded variable results, partially due to an incomplete understanding of the contribution of hydrogenotrophic and methylotrophic archaea to methanogenesis. Research indicates that 3-nitrooxypropanol (3-NOP) reduces enteric methane formation in dairy cows by inhibiting methyl-coenzyme M reductase (MCR), the enzyme responsible for methane formation. The purpose of this study was to utilize metagenomic and metatranscriptomic approaches to investigate the effect of 3-NOP on the rumen microbiome and to determine the fate of H 2 that accumulates less than expected under inhibited methanogenesis. Results The inhibitor 3-NOP was more inhibitory on Methanobrevibacter species than methanol-utilizing Methanosphaera and tended to reduce the gene expression of MCR. Under inhibited methanogenesis by 3-NOP, fluctuations in H 2 concentrations were accompanied by changes in the expression of [FeFe] hydrogenases in H 2 -producing bacteria to regulate the amount of H 2 production. No previously reported alternative H 2 sinks increased under inhibited methanogenesis except for a significant increase in gene expression of enzymes involved in the butyrate pathway. Conclusion By taking a metatranscriptomic approach, this study provides novel insights on the contribution of methylotrophic methanogens to total methanogenesis and regulation of H 2 metabolism under normal and inhibited methanogenesis by 3-NOP in the rumen. -iX6YPbp4qKjzQQ25nvbCQ Video Abstract

This paper presents the implementation of a real-time optimal load scheduling system for an IoT-based intelligent smart energy management system (SEMS) using a novel decisive algorithm. The increasing use of electrical equipment by consumers often leads to a mismatch between demand and supply, posing significant challenges to the energy sector. The proposed system addresses these challenges by optimizing load distribution and enhancing energy efficiency through advanced demand-side management techniques. By leveraging real-time data from IoT sensors and incorporating user preferences, the new algorithm dynamically adjusts power consumption to avoid peak-hour overloads, thus preventing widespread power outages. Experimental results demonstrate that the system effectively reduces overall energy consumption while maintaining user comfort and optimizing costs. The innovative approach of controlled partial load shedding based on consumer priorities ensures a balanced and resilient energy supply. This study highlights the potential of IoT and advanced algorithms in transforming energy management practices and providing sustainable solutions for the future.

Customers of energy, both in residential and commercial structures, are now more interested in lowering their energy usage as an effect of the feed-in tariffs for renewable resources and the recent rise in electricity rates. The central control system and smart power Plug proposed in this study use the XBee communication protocol to manage energy use. Smart energy management systems are used to measure and optimize power use at the consumer premises level. The design and development of wireless smart Plugs that can assess several power characteristics and gather data on the real-time power use of individual consumer appliances is the main goal of this paper. An XBee transmitter and receiver node aids in the formation of the Consumer Area Network, which is created by the SEMS setup. The central node’s real-time data collection allows for the scheduling and prioritization of the appliances. Consumer appliance datasets may be created using the SEMS setup, and additional datasets can be utilized for load disaggregation. The configuration of the system allows for wireless data transfer from smart outlets to a central controller. The connected devices to the smart Plug are then turned on or off by the system using control instructions generated by the data analysis. According to test findings, the suggested smart Plug can assess the power consumption of wirelessly connected devices up to 18 meters away with accuracy and without compromising data. Based on a planned user program code, the central controller is capable of successfully controlling several Plugs. The proposed Smart Energy Management algorithm demonstrates that using smart Plugs as load controllers results in a decrease in energy consumption of 0.811 kW min (0.0134 kWh) with the right scheduling algorithm, the suggested smart Plug technology may, therefore, be used to its full potential in a smart energy management system. The data’s findings show how much better the proposed approach is than the standard ones in use now.

Angiosperm leaves show extensive shape diversity and are broadly divided into two forms; simple leaves with intact lamina and compound leaves with lamina dissected into leaflets. The mechanistic basis of margin dissection and leaflet initiation has been inferred primarily by analysing compound-leaf architecture, and thus whether the intact lamina of simple leaves has the potential to initiate leaflets upon endogenous gene inactivation remains unclear. Here, we show that the CINCINNATA-like TEOSINTE BRANCHED1, CYCLOIDEA, PROLIFERATING CELL FACTORS (CIN-TCP) transcription factors activate the class II KNOTTED1-LIKE ( KNOX-II ) genes and the CIN-TCP and KNOX-II proteins together redundantly suppress leaflet initiation in simple leaves. Simultaneous downregulation of CIN-TCP and KNOX-II in Arabidopsis leads to the reactivation of the stemness genes KNOX-I and CUPSHAPED COTYLEDON ( CUC ) and triggers ectopic organogenesis, eventually converting the simple lamina to a super-compound form that appears to initiate leaflets indefinitely. Thus, a conserved developmental mechanism promotes simple leaf architecture in which CIN-TCP–KNOX-II forms a strong differentiation module that suppresses the KNOX-I-CUC network and leaflet initiation. Do simple leaves have the potential to become compound leaves? In Arabidopsis , the combined action of CINCINNATA-like TEOSINTE BRANCHED1, CYCLOIDEA, PROLIFERATING CELL FACTORS (CIN-TCP) transcription factors and class II KNOTTED1-LIKE ( KNOX-II ) transcription factors suppresses leaflet initiation in simple leaves. Downregulation of these genes leads to super-compound leaves.

Post-mitotic cell growth is a key process in plant growth and development. Cell expansion drives major growth during morphogenesis and is influenced by both endogenous factors and environmental stimuli. Though both isotropic and anisotropic cell growth can contribute to organ size and shape at different degrees, anisotropic cell growth is more likely to contribute to shape change. While much is known about the mechanisms that increase cellular turgor and cell-wall biomass during expansion, the genetic factors that regulate these processes are less studied. In the past quarter of a century, the role of the CINCINNATA-like TCP (CIN-TCP) transcription factors has been well documented in regulating diverse aspects of plant growth and development including flower asymmetry, plant architecture, leaf morphogenesis, and plant maturation. The molecular activity of the CIN-TCP proteins common to these biological processes has been identified as their ability to suppress cell proliferation. However, reports on their role regulating post-mitotic cell growth have been scanty, partly because of functional redundancy among them. In addition, it is difficult to tease out the effect of gene activity on cell division and expansion since these two processes are linked by compensation, a phenomenon where perturbation in proliferation is compensated by an opposite effect on cell growth to keep the final organ size relatively unaltered. Despite these technical limitations, recent genetic and growth kinematic studies have shown a distinct role of CIN-TCPs in promoting cellular growth in cotyledons and hypocotyls, the embryonic organs that grow solely by cell expansion. In this review, we highlight these recent advances in our understanding of how CIN-TCPs promote cell growth.

The leaf surface usually stays flat, maintained by coordinated growth. Growth perturbation can introduce overall surface curvature, which can be negative, giving a saddle-shaped leaf, or positive, giving a cup-like leaf. Little is known about the molecular mechanisms that underlie leaf flatness, primarily because only a few mutants with altered surface curvature have been isolated and studied. Characterization of mutants of the likeCINCINNATA-like TCP genes in Antirrhinum and Arabidopsis have revealed that their products help maintain flatness by balancing the pattern of cell proliferation and surface expansion between the margin and the central zone during leaf morphogenesis. On the other hand, deletion of two homologous PEAPOD genes causes cup-shaped leaves in Arabidopsis due to excess division of dispersed meristemoid cells. Here, we report the isolation and characterization of an Arabidopsis mutant, tarani (tni), with enlarged, cup-shaped leaves. Morphometric analyses showed that the positive curvature of the tni leaf is linked to excess growth at the centre compared to the margin. By monitoring the dynamic pattern of CYCLIN D3;2 expression, we show that the shape of the primary arrest front is strongly convex in growing tni leaves, leading to excess mitotic expansion synchronized with excess cell proliferation at the centre. Reduction of cell proliferation and of endogenous gibberellic acid levels rescued the tni phenotype. Genetic interactions demonstrated that TNI maintains leaf flatness independent of TCPs and PEAPODs.

Many plants naturally synthesize and secrete secondary metabolites that exert an allelopathic effect, offering compelling alternatives to chemical herbicides. These natural herbicides are highly important for sustainable agricultural practices. Ailanthone is the chemical responsible for the herbicidal effect of Ailanthus altissima, or “tree of heaven”. The molecular studies involving ailanthone’s effect on plant growth are limited. In the current study, we combined whole-transcriptome and physiology analysis of three Arabidopsis thaliana ecotypes treated with ailanthone to identify the effect of this allelopathic chemical on genes and plant growth. Our physiology results showed 50% reduced root growth, high proline accumulation, and high reactive-oxygen-species accumulation in response to ailanthone stress. Deep transcriptome analysis revealed 528, 473, and 482 statistically significant differentially expressed genes for Col-0, Cvi-0, and U112-3 under ailanthone stress, including 131 genes shared among the three accessions. The common genes included 82 upregulated and 42 downregulated genes and varied in expression at least twofold. The study also revealed that 34 of the 131 genes had a similar expression pattern when Arabidopsis seedlings were subjected to other herbicides. Differentially expressed genes significantly induced in response to ailanthone included DTXL1, DTX1, ABCC3, NDB4, UGT74E2, and AZI1. Pathways of stress, development and hormone metabolism were significantly altered under ailanthone stress. These results suggest that ailanthone triggers a significant stress response in multiple pathways similar to other herbicides.