Neuroprotective effect of emodin on Aß25-35-induced cytotoxicity in PC12 cells involves Nrf2/GPX4 and TLR4/p-NF-κB/NLRP3 pathways.

The present study aims to investigate the neuroprotective effects of emodin in Alzheimer's disease (AD). PC12 cells were used to explore the underlying mechanism and were incubated with Aß25-35 for 24 h as the model group, incubated with emodin at different concentrations (2.5, 5, 10 µM) as the drug administration groups. The content of MDA and the enzymic activities of CAT, GSH-Px were detected by the corresponding commercial kits. The ROS level in Aß25-35 induced cells was decreased by emodin dose-dependently, but the MMP in these cells were elevated. The expressions of AChE, TLR4, p-NF-κB, NLRP3, IL-1ß, and TNF-α in PC12 cells were increased by Aß25-35 treatment, the expressions of Nrf2, HO-1, GPX4, xCT were decreased, all the levels of expressions were reversed by emodin. Besides, ultraviolet spectrophotometry and infrared spectrophotometry were ultilized to ascertain the production of emodin-Fe (Ⅱ) complex. The FerroOrange results showed that emodin reduced free Fe2+ in cells. The immunofluorescent intensities of Nrf2, GPX4, and p-NF-κB offered direct visible evidence for emodin's multi-targets in AD treatment. Collectively, emodin could inhibit the activity of AChE and exert neuroprotective effects against AD through antioxidant, anti-ferroptotic, anti-inflammatory properties via Nrf2/GPX4 and TLR4/p-NF-κB/NLRP3 pathways.

Neuroprotection of macamide in a mouse model of Alzheimer's disease involves Nrf2 signaling pathway and gut microbiota.

The underlying mechanisms of macamide's neuroprotective effects in Alzheimer's disease (AD) were investigated in the paper. Macamides are considered as unique ingredients in maca. Improvement effects and mechanisms of macamide on cognitive impairment have not been revealed. In this study, Vina 1.1.2 was used for docking to evaluate the binding abilities of 12 main macamides to acetylcholinesterase (AChE). N-benzyl-(9Z,12Z)-octadecadienamide (M 18:2) was selected to study the following experiments because it can stably bind to AChE with a strong binding energy. The animal experiments showed that M 18:2 prevented the scopolamine (SCP)-induced cognitive impairment and neurotransmitter disorders, increased the positive rates of Nrf2 and HO-1 in hippocampal CA1, improved the synaptic plasticity by maintaining synaptic morphology and increasing the synapse density. Moreover, the contents of IL-1ß, IL-6, and TNF-α in the hippocampus, serum, and colon were reduced by M 18:2. Furthermore, M 18:2 promoted colonic epithelial integrity and partially restored the composition of the gut microbiota to normal, including decreased genera Clostridiales_unclassified and Lachnospiraceae_unclassified, as well as increased genera Muribaculaceae_unclassified, Muribaculum, Alistipes, and Bacteroides, which may be the possible biomarkers of cognitive aging. In summary, M 18:2 exerted neuroprotective effects on SCP-induced AD mice possibly via activating the Nrf2/HO-1 signaling pathway and modulating the gut microbiota.

Innovative methods for microplastic characterization and detection: Deep learning supported by photoacoustic imaging and automated pre-processing data.

Plastic products' widespread applications and their non-biodegradable nature have resulted in the continuous accumulation of microplastic waste, emerging as a significant component of ecological environmental issues. In the field of microplastic detection, the intricate morphology poses challenges in achieving rapid visual characterization of microplastics. In this study, photoacoustic imaging technology is initially employed to capture high-resolution images of diverse microplastic samples. To address the limited dataset issue, an automated data processing pipeline is designed to obtain sample masks while effectively expanding the dataset size. Additionally, we propose Vqdp2, a generative deep learning model with multiple proxy tasks, for predicting six forms of microplastics data. By simultaneously constraining model parameters through two training modes, outstanding morphological category representations are achieved. The results demonstrate Vqdp2's excellent performance in classification accuracy and feature extraction by leveraging the advantages of multi-task training. This research is expected to be attractive for the detection classification and visual characterization of microplastics.

Nuclear RNA homeostasis promotes systems-level coordination of cell fate and senescence.

Understanding cellular coordination remains a challenge despite knowledge of individual pathways. The RNA exosome, targeting a wide range of RNA substrates, is often downregulated in cellular senescence. Utilizing an auxin-inducible system, we observed that RNA exosome depletion in embryonic stem cells significantly affects the transcriptome and proteome, causing pluripotency loss and pre-senescence onset. Mechanistically, exosome depletion triggers acute nuclear RNA aggregation, disrupting nuclear RNA-protein equilibrium. This disturbance limits nuclear protein availability and hinders polymerase initiation and engagement, reducing gene transcription. Concurrently, it promptly disrupts nucleolar transcription, ribosomal processes, and nuclear exporting, resulting in a translational shutdown. Prolonged exosome depletion induces nuclear structural changes resembling senescent cells, including aberrant chromatin compaction, chromocenter disassembly, and intensified heterochromatic foci. These effects suggest that the dynamic turnover of nuclear RNA orchestrates crosstalk between essential processes to optimize cellular function. Disruptions in nuclear RNA homeostasis result in systemic functional decline, altering the cell state and promoting senescence.

Advancing microplastic surveillance through photoacoustic imaging and deep learning techniques.

Microplastic contamination presents a significant global environmental threat, yet scientific understanding of its morphological distribution within ecosystems remains limited. This study introduces a pioneering method for comprehensive microplastic assessment and environmental monitoring, integrating photoacoustic imaging and advanced deep learning techniques. Rigorous curation of diverse microplastic datasets enhances model training, yielding a high-resolution imaging dataset focused on shape-based discrimination. The introduction of the Vector-Quantized Variational Auto Encoder (VQVAE2) deep learning model signifies a substantial advancement, demonstrating exceptional proficiency in image dimensionality reduction and clustering. Furthermore, the utilization of Vector Quantization Microplastic Photoacoustic imaging (VQMPA) with a proxy task before decoding enhances feature extraction, enabling simultaneous microplastic analysis and discrimination. Despite inherent limitations, this study lays a robust foundation for future research, suggesting avenues for enhancing microplastic identification precision through expanded sample sizes and complementary methodologies like spectroscopy. In conclusion, this innovative approach not only advances microplastic monitoring but also provides valuable insights for future environmental investigations, highlighting the potential of photoacoustic imaging and deep learning in bolstering sustainable environmental monitoring efforts.

A Palladium Catalyst Supported on Boron-Doped Porous Carbon for Efficient Dehydrogenation of Formic Acid.

Formic acid has emerged as a highly promising hydrogen storage material, and the development of efficient catalysts to facilitate its dehydrogenation remains imperative. In this study, a novel catalyst consisting of palladium nanoparticles supported on boron-doped porous carbon (Pd/BPC) was successfully synthesized to enable efficient hydrogen production through the dehydrogenation of formic acid. The impacts of the boron doping ratio, doping temperature, and palladium reduction temperature on the catalyst's performance were systemically investigated. The results demonstrated the Pd/BPC catalyst synthesized with a carbon-to-boron ratio of 1:5 by calcination at 900 °C and subsequent reduction at 60 °C exhibited superior formic acid dehydrogenation performance, being 2.9 and 3.8 times greater than that of the Pd/PC catalysts without boron doping and commercial Pd/C, respectively. Additionally, the catalyst showed excellent cycle stability with no significant activity reduction after five consecutive cycles. Experimental and theoretical results reveal that boron doping not only facilitates the homogenous distribution of Pd nanoparticles but also induces a stronger support-metal interaction, thereby reinforcing the catalytic performance. This research is expected to provide valuable insights into the economically viable and efficient production of environmentally friendly hydrogen energy.

Gas exchange and chlorophyll fluorescence responses of Camellia sinensis grown under various cultivations in different seasons.

Sod culture (SC) and conventional agriculture (CA) represent two distinct field management approaches utilized in the cultivation of tea plants in Taiwan. In this study, we employed gas exchange and chlorophyll fluorescence techniques to assess the impact of SC and CA methods on the photosynthetic machinery of Camellia sinensis cv. TTES No.12 (Jhinhsuan) in response to variable light intensities across different seasons. In spring, at photosynthetic photon flux densities (PPFD) ranging from 800 to 2,000 µmol photon m-2 s-1, the net photosynthesis rate (Pn, 10.43 µmol CO2 m-2 s-1), stomatal conductance (Gs, 126.11 mmol H2O m-2 s-1), electron transport rate (ETR, 137.94), and ΔF/Fm' and Fv/Fm (50.37) values for plants grown using SC were comparatively higher than those cultivated under CA. Conversely, the non-photochemical quenching (NPQ) values for SC-grown plants were relatively lower (3.11) compared to those grown under CA at 800 to 2,000 PPFD in spring. Additionally, when tea plants were exposed to PPFD levels below 1,500 µmol photon m- 2 s- 1, there was a concurrent increase in Pn, Gs, ETR, and NPQ. These photosynthetic parameters are crucial for devising models that optimize cultivation practices across varying seasons and specific tillage requirements, and for predicting photosynthetic and respiratory responses of tea plants to seasonally or artificially altered light irradiances. The observed positive impacts of SC on maximum photosynthetic rate (Amax), Fv/Fm, Gs, water-use efficiency (WUE), and ETR suggest that SC is advantageous for enhancing the productivity of tea plants, thereby offering a more adaptable management model for tea gardens.

Enhancing subcellular protein localization mapping analysis using Sc2promap utilizing attention mechanisms.

BACKGROUND: Aberrant protein localization is a prominent feature in many human diseases and can have detrimental effects on the function of specific tissues and organs. High-throughput technologies, which continue to advance with iterations of automated equipment and the development of bioinformatics, enable the acquisition of large-scale data that are more pattern-rich, allowing for the use of a wider range of methods to extract useful patterns and knowledge from them. METHODS: The proposed sc2promap (Spatial and Channel for SubCellular Protein Localization Mapping) model, designed to proficiently extract meaningful features from a vast repository of single-channel grayscale protein images for the purposes of protein localization analysis and clustering. Sc2promap incorporates a prediction head component enriched with supplementary protein annotations, along with the integration of a spatial-channel attention mechanism within the encoder to enables the generation of high-resolution protein localization maps that encapsulate the fundamental characteristics of cells, including elemental cellular localizations such as nuclear and non-nuclear domains. RESULTS: Qualitative and quantitative comparisons were conducted across internal and external clustering evaluation metrics, as well as various facets of the clustering results. The study also explored different components of the model. The research outcomes conclusively indicate that, in comparison to previous methods, Sc2promap exhibits superior performance. CONCLUSIONS: The amalgamation of the attention mechanism and prediction head components has led the model to excel in protein localization clustering and analysis tasks. GENERAL SIGNIFICANCE: The model effectively enhances the capability to extract features and knowledge from protein fluorescence images.

Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model.

In intraoperative brain cancer procedures, real-time diagnosis is essential for ensuring safe and effective care. The prevailing workflow, which relies on histological staining with hematoxylin and eosin (H&E) for tissue processing, is resource-intensive, time-consuming, and requires considerable labor. Recently, an innovative approach combining stimulated Raman histology (SRH) and deep convolutional neural networks (CNN) has emerged, creating a new avenue for real-time cancer diagnosis during surgery. While this approach exhibits potential, there exists an opportunity for refinement in the domain of feature extraction. In this study, we employ coherent Raman scattering imaging method and a self-supervised deep learning model (VQVAE2) to enhance the speed of SRH image acquisition and feature representation, thereby enhancing the capability of automated real-time bedside diagnosis. Specifically, we propose the VQSRS network, which integrates vector quantization with a proxy task based on patch annotation for analysis of brain tumor subtypes. Training on images collected from the SRS microscopy system, our VQSRS demonstrates a significant speed enhancement over traditional techniques (e.g., 20-30 min). Comparative studies in dimensionality reduction clustering confirm the diagnostic capacity of VQSRS rivals that of CNN. By learning a hierarchical structure of recognizable histological features, VQSRS classifies major tissue pathological categories in brain tumors. Additionally, an external semantic segmentation method is applied for identifying tumor-infiltrated regions in SRH images. Collectively, these findings indicate that this automated real-time prediction technique holds the potential to streamline intraoperative cancer diagnosis, providing assistance to pathologists in simplifying the process.

Solutal Marangoni force controls lateral motion of electrolytic gas bubbles.

Electrochemical gas-evolving reactions have been widely used for industrial energy conversion and storage processes. Gas bubbles form frequently at the electrode surface due to a small gas solubility, thereby reducing the effective reaction area and increasing the over-potential and ohmic resistance. However, the growth and motion mechanisms for tiny gas bubbles on the electrode remains elusive. Combining molecular dynamics (MD) and fluid dynamics simulations (CFD), we show that there exists a lateral solutal Marangoni force originating from an asymmetric distribution of dissolved gas near the bubble. Both MD and CFD simulations deliver a similar magnitude of the Marangoni force of ∼0.01 nN acting on the bubble. We demonstrate that this force may lead to lateral bubble oscillations and analyze the phenomenon of dynamic self-pinning of bubbles at the electrode boundary.

Einstein-Stokes relation for small bubbles at the nanoscale.

As the physicochemical properties of ultrafine bubble systems are governed by their size, it is crucial to determine the size and distribution of such bubble systems. At present, the size or size distribution of nanometer-sized bubbles in suspension is often measured by either dynamic light scattering or the nanoparticle tracking analysis. Both techniques determine the bubble size via the Einstein-Stokes equation based on the theory of the Brownian motion. However, it is not yet clear to which extent the Einstein-Stokes equation is applicable for such ultrafine bubbles. In this work, using atomic molecular dynamics simulation, we evaluate the applicability of the Einstein-Stokes equation for gas nanobubbles with a diameter less than 10 nm, and for a comparative analysis, both vacuum nanobubbles and copper nanoparticles are also considered. The simulation results demonstrate that the diffusion coefficient for rigid nanoparticles in water is found to be highly consistent with the Einstein-Stokes equation, with slight deviation only found for nanoparticle with a radius less than 1 nm. For nanobubbles, including both methane and vacuum nanobubbles, however, large deviation from the Einstein-Stokes equation is found for the bubble radius larger than 3 nm. The deviation is attributed to the deformability of large nanobubbles that leads to a cushioning effect for collision-induced bubble diffusion.

Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data.

This study presents the Fourier Decay Perception Generative Adversarial Network (FDP-GAN), an innovative approach dedicated to alleviating limitations in photoacoustic imaging stemming from restricted sensor availability and biological tissue heterogeneity. By integrating diverse photoacoustic data, FDP-GAN notably enhances image fidelity and reduces artifacts, particularly in scenarios of low sampling. Its demonstrated effectiveness highlights its potential for substantial contributions to clinical applications, marking a significant stride in addressing pertinent challenges within the realm of photoacoustic acquisition techniques.

Photo-protection and photo-inhibition during light induction in Barbula indica and Conocephalum conicum under different light gradients.

The objectives of this study were to measure the chlorophyll fluorescence (ChlF) parameters of Barbula indica (Hook.) Spreng and Conocephalum conicum (L.) Dumort subjected to various light intensities (LI) as a reflection of their adaptability to their habitats. The electron transport rate (ETR) of all plants under 500 µmol m-2 s-1 photosynthetic photon flux density (PPFD) was significantly higher than other LI treatments, implying that these plants could be grown under a specific and optimal light intensity adapted to 500 PPFD conditions. As LI increased from 50 to 2,000 PPFD, we observed in all plants increased non-photochemical quenching (NPQ) and photo-inhibitory quenching (qI) and decreased photosystem II efficiency (ΦPSII), potential quantum efficiency of PSII (Fv/Fm), actual PSII efficiency (ΔF/Fm'%), and Fv/Fm%. In addition, energy-dependent quenching (qE), the light protection system (qE + qZ + qT), and qI increased as ΦPSII decreased and photo-inhibition% increased under 1000, 1500, and 2000 PPFD conditions, suggesting that these plants had higher photo-protective ability under high LI treatments to maintain higher photosynthetic system performance. B. indica plants remained photochemically active and maintained higher qE under 300, 500, and 1000 PPFD, whereas C. conicum qZ + qT exhibited higher photo-protection under 500, 1000, and 1500 PPFD conditions. These ChlF indices can be used for predicting photosynthetic responses to light induction in different bryophytes and provide a theoretical basis for ecological monitoring.

Immunohistochemical Stain-Aided Annotation Accelerates Machine Learning and Deep Learning Model Development in the Pathologic Diagnosis of Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is an epithelial cancer originating in the nasopharynx epithelium. Nevertheless, annotating pathology slides remains a bottleneck in the development of AI-driven pathology models and applications. In the present study, we aim to demonstrate the feasibility of using immunohistochemistry (IHC) for annotation by non-pathologists and to develop an efficient model for distinguishing NPC without the time-consuming involvement of pathologists. For this study, we gathered NPC slides from 251 different patients, comprising hematoxylin and eosin (H&E) slides, pan-cytokeratin (Pan-CK) IHC slides, and Epstein-Barr virus-encoded small RNA (EBER) slides. The annotation of NPC regions in the H&E slides was carried out by a non-pathologist trainee who had access to corresponding Pan-CK IHC slides, both with and without EBER slides. The training process utilized ResNeXt, a deep neural network featuring a residual and inception architecture. In the validation set, NPC exhibited an AUC of 0.896, with a sensitivity of 0.919 and a specificity of 0.878. This study represents a significant breakthrough: the successful application of deep convolutional neural networks to identify NPC without the need for expert pathologist annotations. Our results underscore the potential of laboratory techniques to substantially reduce the workload of pathologists.

Bacillus velezensis SQR9 inhibition to fungal denitrification responsible for decreased N2O emissions from acidic soils.

Tropical and subtropical acidic soils are hotspots of global terrestrial nitrous oxide (N2O) emissions, with N2O produced primarily through denitrification. Plant growth-promoting microbes (PGPMs) may effectively mitigate soil N2O emissions from acidic soils, achieved through differential responses of bacterial and fungal denitrification to PGPMs. To test this hypothesis, we conducted a pot experiment and the associated laboratory trials to gain the underlying insights into the PGPM Bacillus velezensis strain SQR9 effects on N2O emissions from acidic soils. SQR9 inoculation significantly reduced soil N2O emissions by 22.6-33.5 %, dependent on inoculation dose, and increased the bacterial AOB, nirK and nosZ genes abundance, facilitating the reduction of N2O to N2 in denitrification. The relative contribution of fungi to the soil denitrification rate was 58.4-77.1 %, suggesting that the N2O emissions derived mainly from fungal denitrification. The SQR9 inoculation significantly inhibited the fungal denitrification and down-regulated fungal nirK gene transcript, dependent on the SQR9 sfp gene, which was necessary for secondary metabolite synthesis. Therefore, our study provides new evidence that decreased N2O emissions from acidic soils can be due to fungal denitrification inhibited by PGPM SQR9 inoculation.

Responses of photosynthesis and chlorophyll fluorescence during light induction in different seedling ages of Mahonia oiwakensis.

BACKGROUND: The aim of this study was to determine the actual state of the photosynthetic apparatus and exhibit distinguishable differences in the chlorophyll fluorescence (ChlF) components in different seedling ages of M. oiwakensis plants subjected to different light intensity (LI). Potted 6-month-old greenhouse seedlings and field collected 2.4-year-old seedlings with 5 cm heights were selected and randomly separated into seven groups for photosynthesis measurements illuminated with 50, 100 (assigned as low LI), 300, 500, 1,000 (as moderate LI), 1,500 and 2,000 (as high LI) µmol m-2 s-1 photosynthetic photon flux density (PPFD) treatments. RESULTS: n 6-month-old seedlings, as LI increased from 50 to 2,000 PPFD, the values of non-photochemical quenching and photo-inhibitory quenching (qI) increased but potential quantum efficiency of PSII (Fv/Fm) and photochemical efficiency of photosystem II (ΦPSII) values decreased. High electron transport rate and percentage of actual PSII efficiency by Fv/Fm values were observed in 2.4-year-old seedlings at high LI conditions. Furthermore, higher ΦPSII was detected under low LI conditions, with lower energy-dependent quenching (qE) and qI values and photo-inhibition % decreased as well. However, qE and qI increased as ΦPSII decreased and photo-inhibition% increased under high LI treatments. CONCLUSIONS: These results could be useful for predicting the changes in growth and distribution of Mahonia species grown in controlled environments and open fields with various combinations of varying light illuminations, and ecological monitoring of their restoration and habitat creation is important for provenance conservation and helps to formulate better conservation strategies for the seedlings.

Physiological responses and antioxidant properties of coriander plants (Coriandrum sativum L.) under different light intensities of red and blue lights.

Coriander (Coriandrum sativum L.) contains abundant antioxidants and essential oils which can provide antibacterial, antifungal, and antioxidant activities in the pharmaceutical, health and food production industry. To improve the economic values of coriander, the relationships between optimal light treatments for maximizing both plant growth and the antioxidant and essential oil content of coriander leaves need to be determined. Plants were exposed to five light-emitting diodes spectral color mixtures, high blue light (BL) intensity induced the levels of reducing power response. The light treatments were then adjusted for the analysis of secondary metabolite compounds of coriander leaves. Among 30 identified compounds, the amounts of decamethyl-cyclopentasiloxane and dodecane were significantly reduced in the R80 + G50 + B50 condition, whereas dodecamethyl-cyclohexasiloxane level was significantly reduced in R50 + G50 + B80 condition. Various light quality and intensity combinations influenced the accumulations of chlorophyll and phytochemical contents, mediated antioxidative properties, and secondary metabolites of coriander leaves, which may be useful in developing a new LED lighting apparatus optimized for coriander production in plant factories.

The mechanisms underlying the actions of Xuefu Zhuyu decoction pretreatment against neurological deficits after ischemic stroke in mice: The mediation of glymphatic function by aquaporin-4 and its anchoring proteins.

Ischemic stroke (IS) has been associated with an impairment in glymphatic function. Xuefu Zhuyu Decoction (XFZYD) is widely used in the prevention and treatment of ischemic stroke. We hypothesized that Xuefu Zhuyu decoction pretreatment could attenuate early neurological deficits after ischemic stroke by enhancing the function of the glymphatic system. To prove our hypothesis, we carried out temporary middle cerebral artery occlusion and reperfusion surgery on C57BL/6 mice and then measured neurological score, infarct size and performed hematoxylin-eosin staining to assess stroke outcomes after 24 h of reperfusion. Subsequently, we injected fluorescent tracers in to the cisterna magna and evaluated tracer distribution in coronal brain sections. The polarization of aquaporin-4 (AQP4), colocalization of aquaporin-4, α-dystroglycan, ß-dystroglycan and agrin were determined by immunofluorescence. Our research showed that pretreatment with Xuefu Zhuyu decoction significantly alleviated neurological scores, neurological deficits and pathological abnormalities in a mouse model of ischemic stroke. Importantly, Xuefu Zhuyu decoction pretreatment enhanced cerebrospinal fluid influx, protected aquaporin-4 depolarization and promoted the colocalization of aquaporin-4 with its anchoring proteins in the brain. Our findings highlight novel mechanisms underlying the neuroprotective effect of Xuefu Zhuyu decoction pretreatment on ischemic stroke-induced brain damage through the glymphatic system. Xuefu Zhuyu decoction pretreatment may offer a promising approach to slow the onset and progression of ischemic stroke.

Safety Assessment of 3S, 3'S Astaxanthin Derived from Metabolically Engineered K. marxianus.

Previous reviews have already explored the safety and bioavailability of astaxanthin, as well as its beneficial effects on human body. The great commercial potential in a variety of industries, such as the pharmaceutical and health supplement industries, has led to a skyrocketing demand for natural astaxanthin. In this study, we have successfully optimized the astaxanthin yield up to 12.8 mg/g DCW in a probiotic yeast and purity to 97%. We also verified that it is the desired free-form 3S, 3'S configurational stereoisomer by NMR and FITR that can significantly increase the bioavailability of astaxanthin. In addition, we have proven that our extracted astaxanthin crystals have higher antioxidant capabilities compared with natural esterified astaxanthin from H. pluvialis. We also screened for potential adverse effects of the pure astaxanthin crystals extracted from the engineered probiotic yeast by dosing SD rats with 6, 12, and 24 mg/kg/day of astaxanthin crystals via oral gavages for a 13-week period and have found no significant biological differences between the control and treatment groups in rats of both genders, further confirming the safety of astaxanthin crystals. This study demonstrates that developing metabolically engineered microorganisms provides a safe and feasible approach for the bio-based production of many beneficial compounds, including astaxanthin.

Photosynthesis in Response to Different Salinities and Immersions of Two Native Rhizophoraceae Mangroves.

Mangrove ecosystems are vulnerable to rising sea levels as the plants are exposed to high salinity and tidal submergence. The ways in which these plants respond to varying salinities, immersion depths, and levels of light irradiation are poorly studied. To understand photosynthesis in response to salinity and submergence in mangroves acclimated to different tidal elevations, two-year-old seedlings of two native mangrove species, Kandelia obovata and Rhizophora stylosa, were treated at different salinity concentrations (0, 10, and 30 part per thousand, ppt) with and without immersion conditions under fifteen photosynthetic photon flux densities (PPFD µmol photon·m-2·s-1). The photosynthetic capacity and the chlorophyll fluorescence (ChlF) parameters of both species were measured. We found that under different PPFDs, electron transport rate (ETR) induction was much faster than photosynthetic rate (Pn) induction, and Pn was restricted by stomatal conductance (Gs). The Pn of the immersed K. obovata plants increased, indicating that this species is immersed-tolerant, whereas the Pn level of the R. stylosa plants is salt-tolerant with no immersion. All of the plants treated with 30 ppt salinity exhibited lower Pn but higher non-photochemical quenching (NPQ) and heat quenching (D) values, followed by increases in the excess energy and photoprotective effects. Since NPQ or D can be easily measured in the field, these values provide a useful ecological monitoring index that may provide a reference for mangrove restoration, habitat creation, and ecological monitoring.