Multiview clustering (MVC) has garnered extensive attention across diverse domains due to its ability to integrate complementary information from multiple perspectives. A primary challenge in Incomplete Multiview Clustering (IMVC) is to maintain the consistent knowledge shared across all views while maximally extracting unique, complementary information from each view. Additionally, addressing potential data loss or inconsistencies within individual views is crucial. However, tackling these issues through point-by-point data alignment across views can be prohibitively expensive. This study proposes a local probabilistic-manifold learning-enhanced approach for IMVC, where we integrate manifold structures rather than aligning raw data across views. First, local manifold learning captures intrinsic data structures within each view, and a mutual information maximization (MIM) module extracts distinctive, low-noise information. The learned probabilistic manifolds enhance the consistent information shared across views while mitigating the impact of point loss and noise in any single view. Second, to integrate partially consistent information, we use view-wise attention and consistent learning modules to align the manifolds across all views. This alignment bypasses the need for explicit space mapping and point-by-point data alignment, harmonizing the data and effectively addressing inconsistencies within individual views. Finally, the model undergoes fine-tuning, supervised by an indicator and target clustering distribution, to optimize the learned representations specifically for clustering tasks. Compared with eight state-of-the-art baselines, the proposed method significantly outperforms the best baseline in terms of accuracy, normalized mutual information (NMI), adjusted rand index (ARI), and F1-score by 3.23%, 3.65%, 4.88%, and 7.95%, respectively, on average.

Segmentation of breast ultrasound images is crucial but challenging due to the limited labeled data and low image contrast, which can mislead transformer attention mechanisms and reduce segmentation accuracy. The recent emergence of large models like the Segment Anything Model (SAM) offers new opportunities for segmentation tasks. However, SAM’s reliance on expert-provided prompts and its limitations in handling the low-contrast ultrasound images reduce its effectiveness in medical imaging applications. To address these limitations, we propose Auto-BUSAM, a YOLO-guided adaptation of SAM designed for precise and automated segmentation of low-contrast breast ultrasound images. Our framework introduces two lightweight yet effective innovations: (i) an Automatic Prompt Generator, based on YOLOv8, that automatically detects and generates bounding box prompts that guide SAM’s focus to relevant regions within ultrasound images, minimizing reliance on expert knowledge and reducing manual effort; and (ii) a Low-Rank Approximation attention module that improves feature discrimination and noise filtering by refining SAM’s attention mechanisms in the Mask Decoder. Importantly, our method preserves SAM’s pre-trained generalization ability by freezing the original encoder while fine-tuning only the Mask Decoder with the lightweight modules. Experimental results demonstrate a significant improvement in segmentation accuracy on the BUSI and Dataset B datasets, compared to SAM’s default mode. Our model also significantly outperforms both classical deep learning baselines and other SAM-based frameworks. The code is available at https://github.com/aI-area/Auto-BUSAM.

Modern machine learning models leveraging multi-omics data face significant privacy challenges due to the sensitive nature of patient information. Communication overhead and missing features in each institution can lead to a substantial decline in federated learning performance. In response to these concerns, we propose VFLING—Federated Learning for Multi-Omics Data Integration with Graphs—a secure one-shot communication federated learning framework. We note that medical data reflects disease characteristics from different omics, while the relationships between samples exhibit relative stability across these omics. To minimize data transmission while maximizing the utilization of each participant’s feature information we develop a strategy that transmits not only the local features but also the relationships or topology in one-shot communication. By fusing the omics based on the locally learned graph structure instead of features, VFLING enables improved performance even when some features are missing from individual parties. Extensive experiments demonstrate that VFLING outperforms existing frameworks, paving the way for applications in the medical field. Local features and graph topology are shared to the trainable server in a single communication, enhancing model accuracy through integrated data. This approach improves robustness despite incomplete information. Local Parties and Server Integration: Local parties learn and transmit both local features and graph topology to the server in a single communication, maximizing effective information transfer. The trainable server then integrates data across parties using graph relationships, enhancing model robustness and accuracy despite incomplete feature sets.

Learning directed acyclic graphs (DAGs) from observational data that involve a set of variables carrying intrinsic noise is a crucial yet challenging task. Recent approaches frame the DAG learning task as minimizing a reconstruction-based objective function, i.e., reconstructing observed data by learning a DAG, while adhering to an acyclic constraint. However, optimizing this objective does not always guarantee the correctness of the learned graphs. One reason for this is that the intrinsic noise entangled with the variables is inadvertently absorbed in the reconstruction process at the expense of inferring incorrect DAG structures.To address this issue, we propose a novel DAG learner that first injects artificial noise into observational variables that are contaminated by fixed intrinsic noise. The next step involves reconstructing these perturbed variables using a weighted structure estimator and a weighted noise estimator, instead of reconstructing the observational variables solely with the fixed intrinsic noise. This strategy effectively reduces the sensitivity of the structure estimator to the fixed intrinsic noise. Additionally, we observe a strong similarity between the proposed DAG learner and diffusion models. This similarity motivates us to replicate the well-known denoising capabilities of diffusion models in our DAG learner. We reformulate and adapt the denoising process in denoising diffusion probabilistic models (DDPMs), which allows us to derive a specific weight schedule for the weighted structure and noise estimators of our DAG learner. Extensive experiments conducted on synthetic and real datasets with varying scales demonstrate the outstanding performance of our proposed method.

This study compared light-driven physiological adaptations between floating and benthic Sargassum horneri ecotypes using five light intensities (50, 100, 150, 300, and 600 μmol photons m-2 s-1). Both ecotypes showed bell-shaped relative growth rate (RGR) curves, with floating S. horneri peaking at 6.74 % day-1 at 150 μmol photons m-2 s-1 and benthic ecotype reached its highest RGR of 6.90 % day-1 at 300 μmol photons m-2 s-1. At 600 μmol photons m-2 s-1, both the maximum photochemical efficiency (Fv/Fm) and the maximum relative electron transfer rate (rETRmax) of the two ecotypes were observed to be inhibited. Notably, the inhibition was more pronounced in the floating S. horneri. Simultaneously, both ecotypes exhibited resilience to elevated light stress by curtailing pigments synthesis, enhancing the light saturation point (Ik) and tissue carbon storage, and elevating catalase (CAT) and glutathione reductase (GR). The concentrations of soluble proteins and UV-absorbing compounds in benthic S. horneri were significantly greater than those found in floating S. horneri at light intensities of ≥300 μmol photons m-2 s-1. The results highlight ecotypes-specific physiological adaptations of S. horneri to varying light intensities. In comparison to the floating S. horneri, the benthic S. horneri collected during the same period exhibited a greater resilience and photosynthetic performance under higher light conditions. The study suggests that benthic S. horneri, if dislodged to surface waters, could proliferate rapidly under transient high-light exposure due to its robust photosynthetic plasticity.

Microcystis aeruginosa is a common cyanobacterium leading to algal blooms. Coupled effects of temperature increase and UV radiation increase will affect its photosynthesis performance, which may in turn will affect its proliferation and distribution, and change the environmental health of the water body. In this study, M. aeruginosa FACHB 469 was incubated at 25 °C and 30 °C and subjected to photosynthetically active radiation (PAR) and UV radiation (PAR + UVR) to monitor the relevant physiological responses. Exposure to both PAR and PAR + UVR resulted in a decline in PSII maximum quantum yield of M. aeruginosa, with UVR having more significant inhibitory effect. Meanwhile, UVR significantly increased the PSII photoinactivation rate constant (Kpi) and decreased the PSII repair rate constant (Krec), whereas the warming did not have a significant effect on it, and no significant interaction effect between warming and UVR was observed. Further analysis of the strategies of algal cells to cope with UVR at different temperatures revealed that at 25 °C, algal cells mainly relied on the repair cycle of PSII, and reduced the content of phycocyanin to lower light energy capture, and increased superoxide dismutase (SOD) and catalase (CAT) activities to alleviate the damage of UVR; whereas under warming conditions, algal cells, while relying on PSII repair, mainly photoprotect by strengthening the NPQ mechanism, thus improving their tolerance to UVR. These findings suggest that the differential strategies employed by M. aeruginosa to cope with UVR under varying temperature conditions may influence the resilience of cyanobacterial blooms to environmental stressors in the future.

Over the past few decades, the accumulation of micro- and nanoplastics (MNPs) have identified as enduring contaminants, posing significant risks to aquatic organisms. However, the interplay of MNPs and environmental stressors (e.g. nutrient etc.) is not well understood. In this study, Sargassum horneri, a typical benthic macroalgae, was cultured with two sizes of plastic particles (MPs (5 μm), NPs (0.05 μm) and nitrogen concentrations (LN (30 μM), HN (120 μM)) for 20 days to investigate the interactive effects between MNPs and nitrogen levels by measuring different physiological and biochemical parameters. The results demonstrated that both MPs and NPs decrease growth rate, non-photochemical quenching (NPQ), and catalase (CAT) activity, but increased the chlorophyll a and c, carotenoid, and soluble protein contents at low nitrogen level. Notably, the inhibitory effect on growth rate was more pronounced in the NPs conditions. Compared to low nitrogen groups, high nitrogen concentration increased the growth rate, NPQ, the ratio of carotenoids to chlorophyll a, the energy absorbed by each reaction center (ABS/RC), the energy dissipated by each reaction center (DI0/RC), superoxide dismutase (SOD), and CAT levels at same MPs or NPs treatment, respectively. Meanwhile, there was no significant difference among different sizes of plastic particle treatment groups in high nitrogen conditions. These results imply that NPs may exhibit potentially greater detrimental effects than MPs, when the algae were cultured under low nitrogen conditions. However, increased nitrogen availability appears to alleviate the toxic effects of MNPs by enhancing the algal photoprotective and antioxidant capacities. These findings highlight the potential for nutrient enrichment to mitigate the toxic impacts of micro- and nanoplastics on benthic macroalgae, providing valuable insights into future ecosystem response to increasing MNPs pollution in nutrient-variable coastal environments.

Continual learning, the ability of a model to learn over time without forgetting previous knowledge and, therefore, be adaptive to new data, is paramount in dynamic fields such as disease outbreak prediction. Deep neural networks, i.e., LSTM, are prone to error due to catastrophic forgetting. This study introduces a novel CEL model for continual learning by leveraging domain adaptation via Elastic Weight Consolidation (EWC). This model aims to mitigate the catastrophic forgetting phenomenon in a domain incremental setting. The Fisher Information Matrix (FIM) is constructed with EWC to develop a regularization term that penalizes changes to important parameters, namely, the important previous knowledge. CEL's performance is evaluated on three distinct diseases, Influenza, Mpox, and Measles, with different metrics. The high R-squared values during evaluation and reevaluation outperform the other state-of-the-art models in several contexts, indicating that CEL adapts to incremental data well. CEL's robustness and reliability are underscored by its minimal 65% forgetting rate and 18% higher memory stability compared to existing benchmark studies. This study highlights CEL's versatility in disease outbreak prediction, addressing evolving data with temporal patterns. It offers a valuable model for proactive disease control with accurate, timely predictions.

The Sargassum golden tide has resulted in severe ecological impacts, and the eutrophication of seawater is considered as a major trigger for it. To explore the physiological responses of reproductive S. horneri, a golden tide species, to increased light and nitrogen levels, two light intensities (LL and HL) and two nitrate concentrations (LN and HN) were set in this study. The results of two-factor interaction experiment showed that light and nitrate interactively influenced the photosynthesis of reproductive S. horneri. In LN treatment, a significant photoinhibition caused by high light was found, reflected by decreased maximum photochemical quantum yield (Fv/Fm) and photosynthetic rate, enhanced non-photochemical quenching (NPQ), and reduced Chla and Chlc contents. However, the HN culture remarkably alleviated such photoinhibition, even exhibited a higher photosynthetic rate in HL treatment, with the elevated Chla and Chlc contents. The increments of Car and ultraviolet-absorbing compounds (UVACs) contents, electron transport efficiency (alpha), and dark respiration rate in HN treatment may contribute to protecting and repairing the photodamage. Additionally, HL and HN treatments significantly increased the C and N contents in the branches and receptacles of alga. The HLHN treatment significantly enhanced the relative growth rate (RGR) at initial culture, and increased the number of reproductive receptacle and reproductive effort. Based on these findings, we hypothesize that under eutrophic conditions, reproductive S. horneri, after detachment and floating to the sea surface, is more likely to maintain rapid growth and reproduction and form golden tide after adapting to high light conditions.

Research has consistently indicated that long non-coding RNAs (lncRNAs) significantly influence the development of numerous diseases. Predicting lncRNA-disease associations (LDAs) will contribute to the prevention and treatment of diseases. However, most existing computational models suffer from several challenges: (i) difficulty in capturing complex higher-order relationships among nodes; (ii) limited number of known associations and neglect of consistency of representations across views; (iii) inadequate fusion of multi-view data. In this research, we introduce an innovative end-to-end method named HGCMLDA for LDA prediction. Firstly, HGCMLDA constructs hypergraphs of lncRNAs and diseases based on integrated similarity matrices utilizing Gaussian mixture model and k-nearest neighbor methods and utilizes hypergraph convolutional network to extract high-order representations of lncRNAs and diseases, followed by contrastive learning to capture information interaction between different views that can alleviate the dependence on limited known associations and enhance the node representations in an unsupervised way. Then, HGCMLDA utilizes multi-scale attentional feature fusion, which considers importance weights of different views and aggregates both global and local context to achieve achieve effective and adequate feature fusion. Subsequently, disease features and lncRNA features are also extracted by using variational autoencoder on the association matrix, so that prior knowledge is effectively incorporated for prediction. Finally, the features of these two parts are concatenated, and matrix completion is performed to predict LDA scores. The results of the comparison experiments indicate that HGCMLDA outperforms five state-of-the-art models for LDA prediction. Case studies for specific diseases demonstrate that HGCMLDA can identify novel associations with high accuracy.

This experiment investigated the effects of seaweed polysaccharide (SP) and seaweed enzymatic hydrolysate (SEH) on the growth performance, serum biochemical indices, antioxidant capacity, and intestinal function of Muscovy ducks. A total of 240 healthy 1 day female Muscovy ducks (48.85 ± 0.45 g) were randomly divided into 3 treatment groups, with 4 replicates per group and 20 ducks per replicate. The control (CON) group received a basic diet supplemented with 20 mL/kg of water, the SP group received a basic diet supplemented with 20 mL/kg of SP, and the SEH group received a basic diet supplemented with 20 mL/kg of SEH. The experimental period lasted for 28 d. The results indicate that, compared to the CON group, the average daily feed intake (ADFI) and feed to gain (F/G) of the SP and SEH groups of ducks significantly decreased at 28 d (p < 0.05). In the SP group, serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), as well as the concentrations of glucose (GLU), triglycerides (TG), total cholesterol (TCHO), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), were significantly reduced (p < 0.05). In the SEH group, the activities of ALT and AST were also significantly lower (p < 0.05). Additionally, serum total antioxidant capacity (T-AOC) levels and superoxide dismutase (SOD) activity in the SEH group were significantly higher than those in the CON group (p < 0.05), while the malondialdehyde (MDA) content was significantly reduced (p < 0.05). Compared to the CON group, serum levels of immunoglobulin A (IgA), immunoglobulin G (IgG), interleukin-4 (IL-4), and interleukin-10 (IL-10) in the SP group were significantly increased (p < 0.05), whereas the levels of tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6) were significantly decreased (p < 0.05). In the SP and SEH groups, the villus height (VH) and the villus height to crypt depth (V/C) of the Muscovy ducks significantly increased (p < 0.05), while the crypt depth (CD) significantly decreased (p < 0.05). A significant increase in the abundance of Barnesiella was observed in the SP and SEH groups (p < 0.05), whereas the abundances of UCG-005 and Romboutsia significantly decreased (p < 0.05). LEfSe analysis indicated that g__Bacillus and g__Veillonella were significantly abundant in the SP group (p < 0.05), while g__Coriobacteriaceae_UCG_002 was significantly abundant in the SEH group (p < 0.05). In summary, the addition of SP and SEH to the feed can promote the healthy growth of ducks by improving intestinal morphology, regulating the structure of intestinal microbiota, enhancing antioxidant capacity and immune function, and optimizing metabolic indicators. This occurs while reducing feed intake and feed-to-weight ratio, and there is a certain specificity in their mechanisms of action.

In recent years, the periodic outbreak of green tides in the coastal areas of China, caused by the combined effects of environmental changes and human activities, has been attracting extensive attention due to the serious negative impacts on the coastal marine ecosystem. In the study, the samples of Ulva linza, a green tide species, were cultivated under two light intensities (LL: 80 μmol photons m-2 s-1; HL: 300 μmol photons m-2 s-1) and three stocking densities (LD: 0.2 g L-1; MD:1 g L-1; HD:2 g L-1) to explore the photosynthetic physiological responses and nutrients absorption capacity. The results showed that high light and low density significantly increased the growth rate of U. linza. Under the HLLD, the maximum growth rate of U. linza was 43.13% day-1 and the energy captured per unit reaction center for electron transfer (ET0/RC) was the highest. The higher density significantly decreased the maximum relative electron transfer rate (rETRmax) of U. linza, especially among groups subjected to high-light condition. Under HL condition, HD also significantly decreased light utilization efficiency (α) in U. linza. The contents of chlorophyll a, b and carotenoids of U. linza were significantly lower in HLLD group compared to other treatment groups. The P uptake of U. linza was prominently inhibited by higher density, and the maximum P uptake and minimum P uptake was 17.94 μM g-1 FW day-1 in LLLD group and 2.74 μM g-1 FW day-1 in LLHD group, respectively. Lower density improved N uptake of U. linza, but high light had no effect on it. These results suggest that high light and lower density synergistically promote the growth of U. linza, which is likely due to enhanced photosynthetic efficiency and nutrient uptake. And the inhibitory effects of higher densities on growth, particularly under high-light conditions, may be due to increased competition for light and nutrients. In the late stage of the green tides outbreak, an increase in accumulation density could help to suppress the sustained outbreak of the green tides, particularly in high-light condition.

Sargassum muticum, , an invasive seaweed, has colonized many parts of the world along the coast. Marine environment invaded by this species is aggravated the complexity by CO2-induced 2-induced ocean acidification (OA) and coastal eutrophication. However, the coupling effects of seawater acidification and eutrophication on this invasive species remain unclear. In this study, we cultured Sargassum muticum at two concentrations of p CO 2 (420 ppmv, LC and 1000 ppmv, HC) and nitrate (10 mu M, LN and 200 mu M, HN) for 16 days, to investigate the coupling effects of CO2-induced 2-induced seawater acidification and nitrate enrichment on growth and photosynthesis of Sargassum muticum. . The results showed that high CO2 2 increased the relative growth rate (RGR) of alga by 58.9% under LN condition, while such increment was not found under HN condition. Thus, the highest RGR was emerged in the HCLN treatment. The photosynthetic rate curve under different inorganic carbon concentrations (P-C - C curve) presented that high CO2 2 increased the maximum inorganic carbon utilization rate (Vmax) V max ) by 8.1% under HN condition; while inhibited it by 29.8% under LN condition. The affinity to inorganic carbon, reflected by the half- saturation constant (K0.5), K 0.5 ), was improved significantly by high CO2 2 and/or high nitrate, compared with LCLN treatment. The photosynthetic rate curves under different irradiances (P-I - I curve) suggested that the maximum photosynthetic rate (Pmax) P max ) of alga was enhanced remarkably by high N, and kept unaffected by high CO2. 2 . The lowest value of dark respiration rate (Rd) R d ) was found in HCLN treatment, and there was no significant difference among the other three treatments. Additionally, an increase chlorophyll a content caused by high N was only found in HC treatment. After 16 d culture, nitrate reductase activity (NRA) of algae in HN treatments decreased significantly, compared with those in LN treatments. Furthermore, high CO2 2 enhanced NRA dramatically only in algae grown at LN level. Correspondingly, the lowest nitrate uptake rate (NUR) was found in LCHN treatment, and there was no significant difference among the other three treatments. In conclusion, our results showed that elevated CO2 2 enhanced the RGR, and the coupling of high CO2 2 and nitrate affected the photosynthesis and NUR, however did not synergistically promote growth of S. muticum. . Therefore, we speculate that the future OA may exacerbate the invasiveness of S. muticum; ; nevertheless, the eutrophication of seawater would not amplify this effect.

Background: The traits of the time to flowering and maturity and other important agronomic traits, e.g., plant height, the numbers of nodes and branches are key factors for the adaptability of soybean cultivars to a certain photoperiodic length and ecological environment. Correlation analysis of these traits will facilitate fine-tuning of phenotyping procedure for each trait. Methods: In this field investigation during 2017-2020 at two experimental stations in Heilongjiang Province, northern China, a total of 1133 cultivars or accessions were phenotyped for traits related to maturity, architecture, e.g. plant height, the numbers of nodes and branches and yield. Statistical analysis was performed to reveal the correlation between different traits, years and locations. Result: R1 (days to the first flowering stage) and R2 (days to the fully flowering stage) are strongly stable traits among different years and different locations in this study. Significant correlations were identified between maturity trait, plant height, the numbers of nodes and branches. However, the traits of the height of the first effective node and the pod number per plant demonstrated some weak correlation among different years or with these maturity traits. Therefore, phenotyping procedures in this study can be directly applicable for accurate evaluation of maturity and plant architecture-related traits e.g. plant height, the numbers of nodes and branches.

The retransmissions of SARS-CoV-2 from several mammals - primarily mink and white-tailed deer - to humans have raised concerns for the emergence of a new animal-derived SARS-CoV-2 variant to worsen the pandemic. Here, we discuss animal species that are susceptible to natural or experimental infection with SARS-CoV-2 and can transmit the virus to mates or humans. We describe cutting-edge techniques to assess the impact of a mutation in the viral spike (S) protein on its receptor and on antibody binding. Our review of spike sequences of animal-derived viruses identified nine unique amino acid exchanges in the receptor-binding domain (RBD) that are not present in any variant of concern (VOC). These mutations are present in SARS-CoV-2 found in companion animals such as dogs and cats, and they exhibit a higher frequency in SARS-CoV-2 found in mink and white-tailed deer, suggesting that sustained transmissions may contribute to maintaining novel mutations. Four of these exchanges, such as Leu452Met, could undermine acquired immune protection in humans while maintaining high affinity for the human angiotensin-converting enzyme 2 (ACE2) receptor. Finally, we discuss important avenues of future research into animal-derived viruses with public health risks.

In recent years, golden tides caused by floating Sargassum have induced severe ecological disasters globally. Eutrophication is a significant factor contributing to the massive spread of Sargassum golden tides. Furthermore, the thalli of Sargassum that float on the ocean surface are subjected to more ultraviolet radiation (UVR). The coupled impact of eutrophication and UVR on the photosynthetic physiology of golden tide species remains unclear. In this study, the thalli of Sargassum horneri, known to cause golden tide, were cultured and acclimated to three distinct nitrogen (N) conditions (natural seawater, NSW; NH4+-N enrichment; and NO3–N enrichment) for 6 days. Subsequently, the thalli were exposed to two different radiation treatments (photosynthetically active radiation (150 W m-2), PAR, 400–700 nm; PAR (150 W m-2) + UVR (28 W m-2), 280–700 nm) for 120 min, to investigate the photosynthetic effects of UVR and N on this alga. The findings demonstrated that exposure to UVR impeded the photosynthetic capacity of S. horneri, as evidenced by a decrease in the maximum photochemical quantum yield (Fv/Fm), photosynthetic efficiency (α) and chlorophyll content. Under diverse N-enrichment conditions, the alga tended to adopt various strategies to mitigate the adverse effects of UVR. NH4+-enrichment dissipated excess UVR energy through a greater increase in non-photochemical quenching (NPQ). While NO3–enrichment protected alga by enhancing N assimilation (higher nitrate reductase activity (NRA) and soluble protein content), and maintained a stable energy captured per unit reaction center for electron transfer (ET0/RC) and a higher net photosynthetic rate. Although different N enrichments could not completely offset the damage caused by UV radiation, they secured the photoprotective ability of S. horneri in several ways.

Sargassum muticum, an invasive seaweed, has colonized many parts of the world along the coast. Marine environment invaded by this species is aggravated the complexity by CO2-induced ocean acidification (OA) and coastal eutrophication. However, the coupling effects of seawater acidification and eutrophication on this invasive species remain unclear. In this study, we cultured Sargassum muticum at two concentrations of pCO2 (420 ppmv, LC and 1000 ppmv, HC) and nitrate (10 μM, LN and 200 μM, HN) for 16 days, to investigate the coupling effects of CO2-induced seawater acidification and nitrate enrichment on growth and photosynthesis of Sargassum muticum. The results showed that high CO2 increased the relative growth rate (RGR) of alga by 58.9% under LN condition, while such increment was not found under HN condition. Thus, the highest RGR was emerged in the HCLN treatment. The photosynthetic rate curve under different inorganic carbon concentrations (PC curve) presented that high CO2 increased the maximum inorganic carbon utilization rate (Vmax) by 8.1% under HN condition; while inhibited it by 29.8% under LN condition. The affinity to inorganic carbon, reflected by the half-saturation constant (K0.5), was improved significantly by high CO2 and/or high nitrate, compared with LCLN treatment. The photosynthetic rate curves under different irradiances (PI curve) suggested that the maximum photosynthetic rate (Pmax) of alga was enhanced remarkably by high N, and kept unaffected by high CO2. The lowest value of dark respiration rate (Rd) was found in HCLN treatment, and there was no significant difference among the other three treatments. Additionally, an increase chlorophyll a content caused by high N was only found in HC treatment. After 16 d culture, nitrate reductase activity (NRA) of algae in HN treatments decreased significantly, compared with those in LN treatments. Furthermore, high CO2 enhanced NRA dramatically only in algae grown at LN level. Correspondingly, the lowest nitrate uptake rate (NUR) was found in LCHN treatment, and there was no significant difference among the other three treatments. In conclusion, our results showed that elevated CO2 enhanced the RGR, and the coupling of high CO2 and nitrate affected the photosynthesis and NUR, however did not synergistically promote growth of S. muticum. Therefore, we speculate that the future OA may exacerbate the invasiveness of S. muticum; nevertheless, the eutrophication of seawater would not amplify this effect.

The aim was to determine the response of a bloom-forming Microcystis aeruginosa to climatic changes. Cultures of M. aeruginosa FACHB 905 were grown at two temperatures (25°C, 30°C) and exposed to high photosynthetically active radiation (PAR: 400–700 nm) alone or combined with UVR (PAR + UVR: 295–700 nm) for specified times. It was found that increased temperature enhanced M. aeruginosa sensitivity to both PAR and PAR + UVR as shown by reduced PSII quantum yields (Fv/Fm) in comparison with that at growth temperature (25°C), the presence of UVR significantly exacerbated the photoinhibition. M. aeruginosa cells grown at high temperature exhibited lower PSII repair rate (Krec) and sustained nonphotochemical quenching (NPQs) induction during the radiation exposure, particularly for PAR + UVR. Although high temperature alone or worked with UVR induced higher SOD and CAT activity and promoted the removal rate of PsbA, it seemed not enough to prevent the damage effect from them showing by the increased value of photoinactivation rate constant (Kpi). In addition, the energetic cost of microcystin synthesis at high temperature probably led to reduced materials and energy available for PsbA turnover, thus may partly account for the lower Krec and the declination of photosynthetic activity in cells following PAR and PAR + UVR exposure. Our findings suggest that increased temperature modulates the sensitivity of M. aeruginosa to UVR by affecting the PSII repair and defense capacity, thus influencing competitiveness and abundance in the future water environment.

A novel splice-site mutation in the P. vulgarisgene for TETRAKETIDE α-PYRONE REDUCTASE 2 impairs male fertility, and parthenocarpic pod development can be improved by external application of IAA. Snap bean (Phaseolus vulgaris L.) is an important vegetable crop in many parts of the world, and the main edible part is the fresh pod. Here, we report the characterization of the genic male sterility (ms-2) mutant in common bean. Loss of function of MS-2 accelerates degradation of the tapetum, resulting in a complete male sterility. Through fine-mapping, co-segregation, and re-sequencing analysis, we identified Phvul.003G032100, which encodes the TETRAKETIDE α-PYRONE REDUCTASE 2 (PvTKPR2) protein in common bean, as the causal gene for MS-2. PvTKPR2 is predominantly expressed at the early stages of flower development. A novel 7-bp (+ 6028 bp to + 6034 bp) deletion mutation spans the splice site between the fourth intron and fifth exon, leading to a 9-bp deletion in transcribed mRNA and a 3-amino acid (G210M211V212) deletion in the protein coding sequence of the PvTKPR2ms−2 gene. The 3-D structural changes in the protein due to the mutation may impair the activities of NAD-dependent epimerase/dehydratase and the NAD(P)-binding domains of PvTKPR2ms−2 protein. The ms-2 mutant plants produce many small parthenocarpic pods, and the size of the pods can be doubled by external application of 2 mM indole-3-acetic acid (IAA). Our results demonstrate that a novel mutation in PvTKPR2 impairs male fertility through premature degradation of the tapetum.

Aims As the ocean warms,the upper mixed layer becomes shallower,increasing nutrient limitation and sunlight exposure for diatoms.The photosynthetic yield of diatoms was affected by the dual stress of high light and nutrient limitation.This study mainly explored the photophysiological regulation of diatoms in response to phosphorus starvation and high light stress to further understand the effects of marine environmental changes on diatom photosynthesis. Methods We cultured the two different-sized diatom species Thalassiosira pseudonana and T.weissflogii under the condition of phosphorus starvation to monitor the changes of photosystem Ⅱ(PSII)function and to investigate their photophysiological responses to high light. Important findings Under the condition of phosphorus starvation,the PSII activity of smaller T.pseudonana gradually declined,the electron transport efficiency from plastoquinone QA-which binds to D2 protein to plastoquinone QB which binds to D1 protein descended.Thus,the energy captured for electron transport per unit reaction center decreased,and the non-photoquenched was induced,while the PSII activity of larger T.weissflogii could be maintained for a longer time;T.pseudonana had higher value of PSII photoinactivation cross section(σi)under phosphorus sufficient condition than T.weissflogii,which was prone to photoinhibition and exhibited a higher repair rate for PSII.Phosphorus starvation had no significant effect on its sensitivity to photoinhibition,while T.weissflogii had significantly higher σi under phosphorus starvation condition,and its tolerance to high light intensity was significantly reduced.Under the condition of nutrient limitation and increased light exposure,the larger T.weissflogii may tend to distribute in the lower euphotic layer.In summary,this study suggests that marine environmental changes may change the niche of diatoms with different cell sizes and affect their contribution to primary production.