Photosynthetic performance of the red algae Gracilariopsis lemaneiformis under high seawater pH: Excess reactive oxygen production due to carbon limitation.

The red algae Gracilariopsis lemaneiformis is extensively cultivated at high densities, leading to significant increases in regional seawater pH due to its photosynthetic removal of inorganic carbon. We conducted a study on G. lemaneiformis cultured under various pH conditions (normal pH, pH 9.3, and pH 9.6) and light levels (dark and 100 µmol photons m-2 s-1) to investigate how high pH seawater environments affect the metabolic processes of G. lemaneiformis. The high pH did not directly damage the photosynthetic light reactions or the Calvin cycle. Instead, the observed reduction in photosynthetic rates was primarily due to CO2 limitation. However, under illuminated conditions, a high pH environment leads to a decrease in electron transport efficiency (ETo/RC) and reaction center density (RC/CSo), while simultaneously increasing the levels of hydrogen peroxide (H2O2), malondialdehyde (MDA), and the activity of antioxidant enzymes. Under illuminated conditions, the limitation of inhibit the photosynthetic electron transport process, leading to energy imbalance and excessive production of reactive oxygen species, which in turn resulted in lipid peroxidation of the cell membrane. This might be one of the inducing factors responsible for the bleaching in sea-farmed G. lemaneiformis plants.

Effectiveness of a socioecological model-guided, smart device-based, self-management-oriented lifestyle intervention in community residents: protocol for a cluster-randomized controlled trial.

BACKGROUND: Healthy lifestyles are crucial for preventing chronic diseases. Nonetheless, approximately 90% of Chinese community residents regularly engage in at least one unhealthy lifestyle. Mobile smart devices-based health interventions (mHealth) that incorporate theoretical frameworks regarding behavioral change in interaction with the environment may provide an appealing and cost-effective approach for promoting sustainable adaptations of healthier lifestyles. We designed a randomized controlled trial (RCT) to evaluate the effectiveness of a socioecological model-guided, smart device-based, and self-management-oriented lifestyles (3SLIFE) intervention, to promote healthy lifestyles among Chinese community residents. METHODS: This two-arm, parallel, cluster-RCT with a 6-month intervention and 6-month follow-up period foresees to randomize a total of 20 communities/villages from 4 townships in a 1:1 ratio to either intervention or control. Within these communities, a total of at least 256 community residents will be enrolled. The experimental group will receive a multi-level intervention based on the socioecological model supplemented with a multi-dimensional empowerment approach. The control group will receive information only. The primary outcome is the reduction of modifiable unhealthy lifestyles at six months, including smoking, excess alcohol consumption, physical inactivity, unbalanced diet, and overweight/obesity. A reduction by one unhealthy behavior measured with the Healthy Lifestyle Index Score (HLIS) will be considered favorable. Secondary outcomes include reduction of specific unhealthy lifestyles at 3 months, 9 months, and 12 months, and mental health outcomes such as depression measured with PHQ-9, social outcomes such as social support measured with the modified Multidimensional Scale of Perceived Social Support, clinical outcomes such as obesity, and biomedical outcomes such as the development of gut microbiota. Data will be analyzed with mixed effects generalized linear models with family and link function determined by outcome distribution and accounting for clustering of participants in communities. DISCUSSION: This study will provide evidence concerning the effect of a mHealth intervention that incorporates a behavioral change theoretical framework on cultivating and maintaining healthy lifestyles in community residents. The study will provide insights into research on and application of similar mHealth intervention strategies to promote healthy lifestyles in community populations and settings. TRIAL REGISTRATION NUMBER: ChiCTR2300070575. Date of registration: April 17, 2023. https://www.chictr.org.cn/index.aspx .

[Mechanism of Shikonin on spinal cord injury in rats based on TNFR/RIPK1 pathway].

OBJECTIVE: To explore the effect of shikonin on the recovery of nerve function after acute spinal cord injury(SCI) in rats. METHODS: 96 male Sprague-Dawley(SD)rats were divided into 4 groups randomly:sham operation group (Group A), sham operation+shikonin group (Group B), SCI+ DMSO(Group C), SCI+shikonin group (Group D).The acute SCI model of rats was made by clamp method in groups C and D . After subdural catheterization, no drug was given in group A. rats in groups B and D were injected with 100 mg·kg-1 of shikonin through catheter 30 min after modeling, and rats in group C were given with the same amount of DMSO, once a day until the time point of collection tissue. Basso-Beattie-Bresnahan(BBB) scores were performed on 8 rats in each group at 6, 12, and 3 d after moneling, and oblique plate tests were performed on 1, 3, 7 and 14 d after modeling, and then spinal cord tissues were collected. Eight rats were intraperitoneally injected with propidine iodide(PI) 1 h before sacrificed to detection PI positive cells at 24 h in each group. Eight rats were sacrificed in each group at 24 h after modeling, the spinal cord injury was observed by HE staining.The Nissl staining was used to observe survivor number of nerve cells. Western-blot technique was used to detect the expression levels of Bcl-2 protein and apoptosis related protein RIPK1. RESULTS: After modeling, BBB scores were normal in group A and B, but in group C and D were significantly higher than those in group A and B. And the scores in group D were higher than those in group C in each time point (P<0.05). At 12 h after modeling, the PI red stained cells in group D were significantly reduced compared with that in group C, and the disintegration of neurons was alleviated(P<0.05). HE and Nissl staining showed nerve cells with normal morphology in group A and B at 24h after operation. The degree of SCI and the number of neuronal survival in group D were better than those in group C, the difference was statistically significant at 24h (P<0.05). The expression of Bcl-2 and RIPK1 proteins was very low in group A and B;The expression of RIPK1 was significantly increased in Group C and decreased in Group D, with a statistically significant difference (P<0.05);The expression of Bcl-2 protein in group D was significantly higher than that in group C (P<0.05). CONCLUSION: Shikonin can alleviate the pathological changes after acute SCI in rats, improve the behavioral score, and promote the recovery of spinal nerve function. The specific mechanism may be related to the inhibition of TNFR/RIPK1 signaling pathway mediated necrotic apoptosis.

The additive effect of essential hypertension on coronary artery plaques in type 2 diabetes mellitus patients: a coronary computed tomography angiography study.

BACKGROUND: The effect of comorbid hypertension and type 2 diabetes mellitus (T2DM) on coronary artery plaques examined by coronary computed tomography angiography (CCTA) is not fully understood. We aimed to comprehensively assess whether comorbid hypertension and T2DM influence coronary artery plaques using CCTA. MATERIALS AND METHODS: A total of 1100 T2DM patients, namely, 277 normotensive [T2DM(HTN-)] and 823 hypertensive [T2DM(HTN +)] individuals, and 1048 normotensive patients without T2DM (control group) who had coronary plaques detected on CCTA were retrospectively enrolled. Plaque type, coronary stenosis, diseased vessels, the segment involvement score (SIS) and the segment stenosis score (SSS) based on CCTA data were evaluated and compared among the groups. RESULTS: Compared with patients in the control group, the patients in the T2DM(HTN-) and T2DM(HTN +) groups had more partially calcified plaques, noncalcified plaques, segments with obstructive stenosis, and diseased vessels, and a higher SIS and SSS (all P values < 0.001). Compared with the control group, T2DM(HTN +) patients had increased odds of having any calcified and any noncalcified plaque [odds ratio (OR) = 1.669 and 1.278, respectively; both P values < 0.001]; both the T2DM(HTN-) and T2DM(HTN +) groups had increased odds of having any partially calcified plaque (OR = 1.514 and 2.323; P = 0.005 and P < 0.001, respectively), obstructive coronary artery disease (CAD) (OR = 1.629 and 1.992; P = 0.001 and P < 0.001, respectively), multivessel disease (OR = 1.892 and 3.372; both P-values < 0.001), an SIS > 3 (OR = 2.233 and 3.769; both P values < 0.001) and an SSS > 5 (OR = 2.057 and 3.580; both P values < 0.001). Compared to T2DM(HTN-) patients, T2DM(HTN +) patients had an increased risk of any partially calcified plaque (OR = 1.561; P = 0.005), multivessel disease (OR = 1.867; P < 0.001), an SIS > 3 (OR = 1.647; P = 0.001) and an SSS > 5 (OR = 1.625; P = 0.001). CONCLUSION: T2DM is related to the presence of partially calcified plaques, obstructive CAD, and more extensive coronary artery plaques. Comorbid hypertension and diabetes further increase the risk of partially calcified plaques, and more extensive coronary artery plaques.

A comprehensive prognostic analysis of osimertinib treatment in advanced non-small cell lung cancer patients with acquired EGFR-T790M mutation: a real-world study.

PURPOSE: Osimertinib is the standard treatment for advanced non-small cell lung cancer (NSCLC) patients with T790M mutation after the failure of first-/second-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI). We comprehensively analyzed factors that affect the therapeutic efficacy of the osimertinib treatment in NSCLC patients. METHODS: 351 NSCLC patients with T790M mutation receiving osimertinib treatment were included. We investigated the value of different factors in predicting the clinical outcomes of the osimertinib therapy, including progression-free survival (PFS), overall survival (OS) and objective response rate (ORR). Logistic and COX regression were used to identify prognosticators. RESULTS: In osimertinib therapy, EGFR mutation status (19Del/L858R) at initial diagnosis and the therapeutic choice of prior EGFR-TKI agent was not associated with patients' prognosis. Notably, the PFS of the prior EGFR-TKI was independently related to ORR (OR, 95% CI 0.98, 0.96-1.00, p = 0.030), PFS (HR, 95% CI 0.98, 0.97-1.00, p = 0.009) and OS (HR, 95% CI 0.96, 0.93-0.98, p < 0.001) of osimertinib treatment. Among distinct organ metastases, only bone metastasis was related to the efficacy of osimertinib, in terms of ORR (OR, 95% CI 1.97, 1.27-3.06, p = 0.002), PFS (HR, 95% CI 1.55, 1.18-2.03, p = 0.001) and OS (HR, 95% CI 1.81, 1.27-2.59, p = 0.001). However, the therapeutic efficacy of osimertinib was not further impacted by the accumulation of metastatic organs. A performance status score of 2-4 was also an adverse prognosticator for the osimertinib therapy. CONCLUSION: PFS of the prior EGFR-TKI treatment, performance status score and bone metastasis were independent prognosticators of the osimertinib treatment. These findings may facilitate clinicians in the decision-making of osimertinib.

Multisurrogate-Assisted Ant Colony Optimization for Expensive Optimization Problems With Continuous and Categorical Variables.

As an effective optimization tool for expensive optimization problems (EOPs), surrogate-assisted evolutionary algorithms (SAEAs) have been widely studied in recent years. However, most current SAEAs are designed for continuous/ combinatorial EOPs, which are not suitable for mixed-variable EOPs. This article focuses on one kind of mixed-variable EOP: EOPs with continuous and categorical variables (EOPCCVs). A multisurrogate-assisted ant colony optimization algorithm (MiSACO) is proposed to solve EOPCCVs. MiSACO contains two main strategies: 1) multisurrogate-assisted selection and 2) surrogate-assisted local search. In the former, the radial basis function (RBF) and least-squares boosting tree (LSBT) are employed as the surrogate models. Afterward, three selection operators (i.e., RBF-based selection, LSBT-based selection, and random selection) are devised to select three solutions from the offspring solutions generated by ACO, with the aim of coping with different types of EOPCCVs robustly and preventing the algorithm from being misled by inaccurate surrogate models. In the latter, sequence quadratic optimization, coupled with RBF, is utilized to refine the continuous variables of the best solution found so far. By combining these two strategies, MiSACO can solve EOPCCVs with limited function evaluations. Three sets of test problems and two real-world cases are used to verify the effectiveness of MiSACO. The results demonstrate that MiSACO performs well in solving EOPCCVs.

Effect of Smoking on Coronary Artery Plaques in Type 2 Diabetes Mellitus: Evaluation With Coronary Computed Tomography Angiography.

Background: The effect of smoking on coronary artery plaques examined by coronary computed tomography angiography (CCTA) in type 2 diabetes mellitus (DM) patients is not fully understood. This study explored the effect of smoking on coronary artery plaques by comparing the characteristics of plaques between diabetes patients with and without a smoking history and among those with different smoking durations. Materials and Methods: In total, 1058 DM patients found to have coronary plaques on CCTA were categorized into the smoker (n=448) and nonsmoker groups (n=610). Smokers were stratified by smoking duration [≤20 years (n=115), 20~40 years (n=233) and >40 years (n=100)]. The plaque types, luminal stenosis [obstructive (<50%) or nonobstructive (≥50%) stenosis], segment involvement score (SIS), and segment stenosis score (SSS) of the CCTA data were compared among groups. Results: Compared to nonsmokers, smokers demonstrated increased odds ratios (ORs) of any noncalcified plaques (OR=1.423; P=0.014), obstructive plaques (OR=1.884; P<0.001), multivessel disease (OR=1.491; P=0.020), SIS≥4 (OR=1.662; P<0.001), and SSS≥7 (OR=1.562; P=0.001). Compared to diabetes patients with a smoking duration ≤20 years, those with a smoking duration of 20~40 years and >40 years had higher OR of any mixed plaques (OR=2.623 and 3.052, respectively; Ps<0.001), obstructive plaques (OR=2.004 and 2.098; P=0.003 and 0.008, respectively), multivessel disease (OR=3.171 and 3.784; P<0.001 and P=0.001, respectively), and SSS≥7 (OR=1.605 and 1.950; P=0.044 and 0.020, respectively). Diabetes with a smoking duration >40 years had a higher OR of SIS≥4 (OR=1.916, P=0.034). Conclusion: Smoking is independently associated with the presence of noncalcified, obstructive, and more extensive coronary artery plaques in diabetes patients, and a longer smoking duration is significantly associated with a higher risk of mixed, obstructive, and more extensive plaques.

Machine Learning-Based CT Radiomics Analysis for Prognostic Prediction in Metastatic Non-Small Cell Lung Cancer Patients With EGFR-T790M Mutation Receiving Third-Generation EGFR-TKI Osimertinib Treatment.

BACKGROUND AND PURPOSE: As a third-generation EGFR tyrosine kinase inhibitor (TKI), osimertinib is approved for treating advanced non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation after progression on first- or second-generation EGFR-TKIs such as gefitinib, erlotinib and afatinib. We aim at exploring the feasibility and effectiveness of using radiomic features from chest CT scan to predict the prognosis of metastatic non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation receiving second-line osimertinib therapy. METHODS: Contrast-enhanced and unenhanced chest CT images before osimertinib treatment were collected from 201 and 273 metastatic NSCLC patients with EGFR-T790M mutation, respectively. Radiomic features were extracted from the volume of interest. LASSO regression was used to preliminarily evaluate the prognostic values of different radiomic features. We then performed machine learning-based analyses including random forest (RF), support vector machine (SVM), stepwise regression (SR) and LASSO regression with 5-fold cross-validation (CV) to establish the optimal radiomic model for predicting the progression-free survival (PFS) of osimertinib treatment. Finally, a combined clinical-radiomic model was developed and validated using the concordance index (C-index), decision-curve analysis (DCA) and calibration curve analysis. RESULTS: Disease progression occurred in 174/273 (63.7%) cases. CT morphological features had no ability in predicting patients' prognosis in osimertinib treatment. Univariate COX regression followed by LASSO regression analyses identified 23 and 6 radiomic features from the contrast-enhanced and unenhanced CT with prognostic value, respectively. The 23 contrast-enhanced radiomic features were further used to construct radiomic models using different machine learning strategies. Radiomic model built by SR exhibited superior predictive accuracy than RF, SVR or LASSO model (mean C-index of the 5-fold CV: 0.660 vs. 0.560 vs. 0.598 vs. 0.590). Adding the SR radiomic model to the clinical model could remarkably strengthen the C-index of the latter from 0.672 to 0.755. DCA and calibration curve analyses also demonstrated good performance of the combined clinical-radiomic model. CONCLUSIONS: Radiomic features extracted from the contrast-enhanced chest CT could be used to evaluate metastatic NSCLC patients' prognosis in osimertinib treatment. Prognostic models combing both radiomic features and clinical factors had a great performance in predicting patients' outcomes.

Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study.

BACKGROUND: Tumor mutation burden (TMB) is an emerging prognostic biomarker of immunotherapy for bladder cancer (BLCA). We aim at investigating radiomic features' value in predicting the TMB status of BLCA patients. METHODS: Totally, 75 patients with BLCA were enrolled. Radiomic features extracted from the volume of interest of preoperative pelvic contrast-enhanced computed tomography (CECT) were obtained for each case. Unsupervised hierarchical clustering analysis was performed based on radiomic features. Sequential univariate Logistic regression, the least absolute shrinkage and selection operator (LASSO) regression and the backward stepwise regression were used to develop a TMB-predicting model using radiomic features. RESULTS: The unsupervised clustering analysis divided the total cohort into two groups, i.e., group A (32.0%) and B (68.0%). Patients in group A had a significantly larger proportion of having high TMB against those in group B (66.7% vs. 41.2%, p = 0.039), indicating the intrinsic ability of radiomic features in TMB-predicting. In univariate analysis, 27 radiomic features could predict TMB. Based on six radiomic features selected by logistic and LASSO regression, a TMB-predicting model was built and visualized by nomogram. The area under the ROC curve of the model reached 0.853. Besides, the calibration curve and the decision curve also revealed the good performance of the model. CONCLUSIONS: Our work firstly proved the feasibility of using radiomics to predict TMB for patients with BLCA. The predictive model based on radiomic features from pelvic CECT has a promising ability to predict TMB. Future study with a larger cohort is needed to verify our findings.

The Prognostic Value of Radiomics Features Extracted From Computed Tomography in Patients With Localized Clear Cell Renal Cell Carcinoma After Nephrectomy.

BACKGROUND AND PURPOSE: Radiomics is an emerging field of quantitative imaging. The prognostic value of radiomics analysis in patients with localized clear cell renal cell carcinoma (ccRCC) after nephrectomy remains unknown. METHODS: Computed tomography images of 167 eligible cases were obtained from the Cancer Imaging Archive database. Radiomics features were extracted from the region of interest contoured manually for each patient. Hierarchical clustering was performed to divide patients into distinct groups. Prognostic assessments were performed by Kaplan-Meier curves, COX regression, and least absolute shrinkage and selection operator COX regression. Besides, transcriptome mRNA data were also included in the prognostic analyses. Endpoints were overall survival (OS) and disease-free survival (DFS). Concordance index (C-index), decision curve analysis and calibration curves with 1,000 bootstrapping replications were used for model's validation. RESULTS: Hierarchical clustering groups from nephrographic features and mRNA can divide patients into different prognostic groups while clustering groups from corticomedullary or unenhanced phase couldn't distinguish patients' prognosis. In multivariate analyses, 11 OS-predicting and eight DFS-predicting features were identified in nephrographic phase. Similarly, seven OS-predictors and seven DFS-predictors were confirmed in mRNA data. In contrast, limited prognostic features were found in corticomedullary (two OS-predictor and two DFS-predictors) and unenhanced phase (one OS-predictors and two DFS-predictors). Prognostic models combining both nephrographic features and mRNA showed improved C-index than any model alone (C-index: 0.927 and 0.879 for OS- and DFS-predicting, respectively). In addition, decision curves and calibration curves also revealed the great performance of the novel models. CONCLUSION: We firstly investigated the prognostic significance of preoperative radiomics signatures in ccRCC patients. Radiomics features obtained from nephrographic phase had stronger predictive ability than features from corticomedullary or unenhanced phase. Multi-omics models combining radiomics and transcriptome data could further increase the predictive accuracy.

Features of family clusters of COVID-19 patients: A retrospective study.

BACKGROUND: To investigate and compare the clinical and imaging features among family members infected with COVID-19. METHODS: We retrospectively collected a total of 34 COVID-19 cases (15 male, 19 female, aged 48 ± 16 years, ranging from 10 to 81 years) from 13 families from January 17, 2020 through February 15, 2020. Patients were divided into two groups: Group 1 - part of the family members (first-generation) who had exposure history and others (second-generation) infected through them, and Group 2 - patients from the same family having identical exposure history. We collected clinical symptoms, laboratory findings, and high-resolution computed tomography (HRCT) features for each patient. Comparison tests were performed between the first- and second-generation patients in Group 1. RESULTS: In total there were 21 patients in Group 1 and 20 patients in Group 2. For Group 1, first-generation patients had significantly higher white blood cell count (6.5 × 109/L (interquartile range (IQR): 4.9-9.2 × 109/L) vs 4.5 × 109/L (IQR: 3.7-5.3 × 109/L); P = 0.0265), higher neutrophil count (4.9 × 109/L (IQR: 3.6-7.3 × 109/L) vs 2.9 × 109/L (IQR: 2.1-3.3 × 109/L); P = 0.0111), and higher severity scores on HRCT (3.9 ± 2.4 vs 2.0 ± 1.3, P = 0.0362) than the second-generation patients. Associated underlying diseases (odds ratio, 8.0, 95% confidence interval: 3.4-18.7, P = 0.0013) were significantly correlated with radiologic severity scores in second-generation patients. CONCLUSION: Analysis of the family cluster cases suggests that COVID-19 had no age or sex predominance. Secondarily infected patients in a family tended to develop milder illness, but this was not true for those with existing comorbidities.

A novel prognostic model predicting the long-term cancer-specific survival for patients with hypopharyngeal squamous cell carcinoma.

BACKGROUND: Hypopharyngeal squamous cell carcinoma (HSCC) is a rare type of head and neck cancer with poor prognosis. However, till now, there is still no model predicting the survival outcomes for HSCC patients. We aim to develop a novel nomogram predicting the long-term cancer-specific survival (CSS) for patients with HSCC and establish a prognostic classification system. METHODS: Data of 2021 eligible HSCC patients were retrieved from the Surveillance, Epidemiology and End Results database between 2010 and 2015. We randomly split the whole cases (ratio: 7:3) into the training and the validation cohort. Cox regression as well as the Least absolute shrinkage and selection operator (LASSO) COX were used to select significant predictors of CSS. Based on the beta-value of these predictors, a novel nomogram was built. The concordance index (C-index), the calibration curve and the decision curve analysis (DCA) were utilized for the model validation and evaluation using the validation cohort. RESULTS: In total, cancer-specific death occurred in 974/2021 (48.2%) patients. LASSO COX indicated that age, race, T stage, N stage, M stage, surgery, radiotherapy and chemotherapy are significant prognosticators of CSS. A prognostic model based on these factors was constructed and visually presented as nomogram. The C-index of the model was 0.764, indicating great predictive accuracy. Additionally, DCA and calibration curves also demonstrated that the nomogram had good clinical effect and satisfactory consistency between the predictive CSS and actual observation. Furthermore, we developed a prognostic classification system that divides HSCC patients into three groups with different prognosis. The median CSS for HSCC patients in the favorable, intermediate and poor prognosis group was not reached, 39.0-Mo and 10.0-Mo, respectively (p < 0.001). CONCLUSIONS: In this study, we constructed the first nomogram as well as a relevant prognostic classification system that predicts CSS for HSCC patients. We believe these tools would be helpful for clinical practice in patients' consultation and risk group stratification.

HRCT imaging features in representative imported cases of 2019 novel coronavirus pneumonia.

With the spread of novel coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the key diagnostic tools. To achieve early and accurate diagnostics, determining the radiological characteristics of the disease is of great importance. In this small scale research we retrospectively reviewed and selected six cases confirmed with 2019-nCoV infection in West China Hospital and investigated their initial and follow-up HRCT features, along with the clinical characteristics. The 2019-nCoV pneumonia basically showed a multifocal or unifocal involvement of ground-glass opacity (GGO), sometimes with consolidation and fibrosis. No pleural effusion or lymphadenopathy was identified in our presented cases. The follow-up CT generally demonstrated mild to moderate progression of the lesion, with only one case showing remission by the reducing extent and density of the airspace opacification.

Antioxidant responses and photosynthetic behaviors of Kappaphycus alvarezii and Kappaphycus striatum (Rhodophyta, Solieriaceae) during low temperature stress.

BACKGROUND: Kappaphycus are farmed in tropical countries as raw material for carrageenan, which is widely used in food industry. The sea area available for farming is one limiting factor in the production of seaweeds. Though cultivation is spreading into subtropical regions, the lower seawater temperature is an important problem encountered in subtropical regions for the farming of Kappaphycus. This research of physiological response to low temperature stress will be helpful for screening Kappaphycus strains for growth in a lower temperature environment. RESULTS: Responses of antioxidant systems and photosystem II (PSII) behaviors in Kappaphycus alvarezii and Kappaphycus striatum were evaluated during low temperature treatments (23, 20, 17 °C). Compared with the controls at 26 °C, the H2O2 concentrations increased in both species when the thalli were exposed to low temperatures (23, 20, 17 °C), but these increases were much greater in K. striatum than in K. alvarezii thalli, suggesting that K. striatum suffered more oxidative stress. The activities of some important antioxidant enzymes (e.g. superoxide dismutase and ascorbate peroxidase) and the hydroxyl free radical scavenging capacity were substantially higher at 23, 20 and 17 °C than at the control 26 °C in K. alvarezii, indicating that the antioxidant system of K. alvarezii enhanced its resistance to low temperature. However, no significant increases of antioxidant enzymes activities were observed at 20 and 17 °C in K. striatum. In addition, both the maximal efficiency of PSII photochemistry (FV/Fm) and the performance index (PIABS) decreased significantly in K. striatum at 23 °C, indicating that the photosynthetic apparatus was damaged at 23 °C. In contrast, no significant decreases of either FV/Fm or PIABS were observed in K. alvarezii at 23 °C. CONCLUSIONS: It is concluded that K. alvarezii has greater tolerance to low temperature than K. striatum.

Efficacy of binary combinations of botanical pesticides for rotifer elimination in microalgal cultivation.

Binary interactions of celangulin, matrine and toosendanin against the rotifer Brachionus plicatilis were studied. Types of interactions (antagonism, synergism and addition) were dependent on the biocides themselves and their ratios in combinations. Mixtures of matrine/toosendanin mainly produced addition owing to their similar modes of action aiming at the nervous system. Combinations of celangulin mixed with matrine or toosendanin at 1:9 exhibited synergism, which is attributed to the interference of matrine or toosendanin with the detoxification enzymes of celangulin. Both the synergistic combinations were inappropriate for rotifer extermination in Isochrysis sp. cultivation owing to the high phytotoxicity resulting from the absence of cell walls. However, the celangulin/toosendanin (1:9) mixture decreased rotifer reproduction without damaging cells of Chlorella and Nannochloropsis sp. Application of frequent, low doses of celangulin/toosendanin (1:9) mixture also reduced the dosage of biocides, thereby reducing the cost of exterminating rotifers, and indicating a considerable practical application in microalgal cultivation.

Changes of Photosynthetic Behaviors in Kappaphycus alvarezii Infected by Epiphyte.

Epiphytic filamentous algae (EFA) were noted as a serious problem to reduce the production and quality of K. alvarezii. The morphological studies revealed that the main epiphyte on K. alvarezii was Neosiphonia savatieri in China. Though the harmful effects of EFA on the production of K. alvarezii have been reported, the detailed mechanism of the N. savatieri in limiting the production of K. alvarezii has not been studied yet. The present paper studied the effects of N. savatieri infection on photosynthetic behaviors in K. alvarezii by detecting chlorophyll fluorescence transient in vivo. The results revealed that damage of oxygen-evolving complex (OEC), decrease of active reaction centers (RCs), and the plastoquinone (PQ) pool as well as significant reduction in the performance indexes (PI) of PSII were caused by the infection of N. savatieri. The influence of N. savatieri on photosynthetic activity of K. alvarezii should be one of the important reasons to reduce the production of K. alvarezii infected by N. savatieri.