DataSheet_2_Performance Comparison of Three Data-Poor Methods With Various Types of Data on Assessing Southern Atlantic Albacore Fishery.docx

In the world, more than 80% of the fisheries by numbers and about half of the catches have not been formally analyzed and evaluated due to limited data. It has led to the fast growth of data-poor evaluation methods. There have been various studies carried out on the comparative performance of data-poor and data-moderate methods in evaluating fishery exploitation status. However, most studies to date have focused on coastal fish stocks with simple data sources. It is important to pay attention to high sea fisheries because they are exploited by multiple countries, fishing gears and data may be divrsified and inconsistent. Furthermore, a comparison of the performance of catch-based, length-based, and abundance-based methods to estimate fishery status is needed. This study is the first attempt to apply catch-based, length-based, and abundance-based data-poor methods to stock assessment for an oceanic tuna fishery and to compare the performance with a data-moderate model. Results showed that the three data-poor methods with various types of data did not produce an entirely consistent stock status of the southern Atlantic albacore (Thunnus alalunga) fishery in 2005, as the estimated B2005/BMSY ranged from 0.688 to 1.3 and F2005/FMSY ranged from 0.708 to 1.6. The Monte Carlo Catch maximum sustainable yield model (CMSY) produced a similar time series of B/BMSY and F/FMSY and stock status (recovering) to the Bayesian state-space Schaefer model (BSM). The abundance-based method (AMSY) gave the most conservative condition (overfished) of this fishery. Sensitivity analysis showed the results of the length-based Bayesian biomass estimation method (LBB) are sensitive to Linf settings, and the results with higher Linf were similar to those of other models. However, the LBB results with setting Linf at lower levels produced more optimistic conditions (healthy). Our results highlight that attention should be paid to the settings of model parameter priors and different trends implied in various types of data when using these data-poor methods.</p

DataSheet_3_Performance Comparison of Three Data-Poor Methods With Various Types of Data on Assessing Southern Atlantic Albacore Fishery.docx

In the world, more than 80% of the fisheries by numbers and about half of the catches have not been formally analyzed and evaluated due to limited data. It has led to the fast growth of data-poor evaluation methods. There have been various studies carried out on the comparative performance of data-poor and data-moderate methods in evaluating fishery exploitation status. However, most studies to date have focused on coastal fish stocks with simple data sources. It is important to pay attention to high sea fisheries because they are exploited by multiple countries, fishing gears and data may be divrsified and inconsistent. Furthermore, a comparison of the performance of catch-based, length-based, and abundance-based methods to estimate fishery status is needed. This study is the first attempt to apply catch-based, length-based, and abundance-based data-poor methods to stock assessment for an oceanic tuna fishery and to compare the performance with a data-moderate model. Results showed that the three data-poor methods with various types of data did not produce an entirely consistent stock status of the southern Atlantic albacore (Thunnus alalunga) fishery in 2005, as the estimated B2005/BMSY ranged from 0.688 to 1.3 and F2005/FMSY ranged from 0.708 to 1.6. The Monte Carlo Catch maximum sustainable yield model (CMSY) produced a similar time series of B/BMSY and F/FMSY and stock status (recovering) to the Bayesian state-space Schaefer model (BSM). The abundance-based method (AMSY) gave the most conservative condition (overfished) of this fishery. Sensitivity analysis showed the results of the length-based Bayesian biomass estimation method (LBB) are sensitive to Linf settings, and the results with higher Linf were similar to those of other models. However, the LBB results with setting Linf at lower levels produced more optimistic conditions (healthy). Our results highlight that attention should be paid to the settings of model parameter priors and different trends implied in various types of data when using these data-poor methods.</p

DataSheet_1_Performance Comparison of Three Data-Poor Methods With Various Types of Data on Assessing Southern Atlantic Albacore Fishery.csv

In the world, more than 80% of the fisheries by numbers and about half of the catches have not been formally analyzed and evaluated due to limited data. It has led to the fast growth of data-poor evaluation methods. There have been various studies carried out on the comparative performance of data-poor and data-moderate methods in evaluating fishery exploitation status. However, most studies to date have focused on coastal fish stocks with simple data sources. It is important to pay attention to high sea fisheries because they are exploited by multiple countries, fishing gears and data may be divrsified and inconsistent. Furthermore, a comparison of the performance of catch-based, length-based, and abundance-based methods to estimate fishery status is needed. This study is the first attempt to apply catch-based, length-based, and abundance-based data-poor methods to stock assessment for an oceanic tuna fishery and to compare the performance with a data-moderate model. Results showed that the three data-poor methods with various types of data did not produce an entirely consistent stock status of the southern Atlantic albacore (Thunnus alalunga) fishery in 2005, as the estimated B2005/BMSY ranged from 0.688 to 1.3 and F2005/FMSY ranged from 0.708 to 1.6. The Monte Carlo Catch maximum sustainable yield model (CMSY) produced a similar time series of B/BMSY and F/FMSY and stock status (recovering) to the Bayesian state-space Schaefer model (BSM). The abundance-based method (AMSY) gave the most conservative condition (overfished) of this fishery. Sensitivity analysis showed the results of the length-based Bayesian biomass estimation method (LBB) are sensitive to Linf settings, and the results with higher Linf were similar to those of other models. However, the LBB results with setting Linf at lower levels produced more optimistic conditions (healthy). Our results highlight that attention should be paid to the settings of model parameter priors and different trends implied in various types of data when using these data-poor methods.</p

Presentation_1_Dioscin Inhibits HSC-T6 Cell Migration via Adjusting SDC-4 Expression: Insights from iTRAQ-Based Quantitative Proteomics.PDF

Hepatic stellate cells (HSCs) migration, an important bioprocess, contributes to the development of liver fibrosis. Our previous studies have found the potent activity of dioscin against liver fibrosis by inhibiting HSCs proliferation, triggering the senescence and inducing apoptosis of activated HSCs, but the molecular mechanisms associated with cell migration were not clarified. In this work, iTRAQ (isobaric tags for relative and absolution quantitation)-based quantitative proteomics study was carried out, and a total of 1566 differentially expressed proteins with fold change ≥2.0 and p < 0.05 were identified in HSC-T6 cells treated by dioscin (5.0 μg/mL). Based on Gene Ontology classification, String and KEGG pathway assays, the effects of dioscin to inhibit cell migration via regulating SDC-4 were carried out. The results of wound-healing, cell migration and western blotting assays indicated that dioscin significantly inhibit HSC-T6 cell migration through SDC-4-dependent signal pathway by affecting the expression levels of Fn, PKCα, Src, FAK, and ERK1/2. Specific SDC-4 knockdown by shRNA also blocked HSC-T6 cell migration, and dioscin slightly enhanced the inhibiting effect. Taken together, the present work showed that SDC-4 played a crucial role on HSC-T6 cell adhesion and migration of dioscin against liver fibrosis, which may be one potent therapeutic target for fibrotic diseases.</p

Aggregation-Induced Emission Luminogen Catalyzed Photocontrolled Reversible Addition–Fragmentation Chain Transfer Polymerization in an Aqueous Environment

A robust aggregation-induced emission luminogen photocatalyst, 5,6-bis­(4′-(diphenylamino)-[1,1′-biphenyl]-4-yl)­pyrazine-2,3-dicarbonitrile (DCDPP-2TPA), for photoinduced electron transfer-reversible addition–fragmentation chain transfer (PET-RAFT) polymerization was investigated. A variety of well-defined polymers with narrow polydispersities (Đ < 1.20) were prepared using the donor–acceptor (D–A) type aggregation-induced emission luminogen as a photocatalyst (as low as 5 ppm with respect to monomers) under visible light at ambient temperature. The use of ppm level of metal- or organo-photocatalysts for PET-RAFT polymerization has been investigated before, but mainly in organic solvents, and very much fewer studies were reported in aqueous environments. The polymerization strategy was successfully demonstrated in water with or without oxygen-free conditions and resulted in structure-controlled polymers. We observed that the fluorescence of DCDPP-2TPA was intensified linearly with an increase in the degree of polymerization

Construction of (Dihydro)naphtho[1,8-<i>bc</i>]pyrans via Rh(III)-Catalyzed Twofold C–H Activation of Benzoylacetonitriles

Rh­(III)-catalyzed cascade C–H activation of benzoylacetonitriles and annulation with sulfoxonium ylides was realized, leading to selective synthesis of naphthols, 2,3-dihydronaphtho­[1,8-<i>bc</i>]­pyrans, and naphtho­[1,8-<i>bc</i>]­pyrans. This step-economic reaction proceeded efficiently under mild and redox-neutral conditions via multiple C–H activations

DataSheet_1_The current and future seasonal geographic distribution of largehead hairtail Trichiurus japonicus in the Beibu Gulf, South China Sea.zip

Largehead hairtail Trichiurus japonicus is a major commercial fish species in the Beibu Gulf of the northwestern South China Sea. Despite much effort to protect the fishery resource, the current stock of T. japonicus is overexploited. As the impacts of climate change unfold globally, seasonal changes in the distribution of largehead hairtail in the Beibu Gulf have not yet been clarified. Maximum entropy model based on mixed layer depth and salinity were projected onto seasonal habitat changes of T. japonicus in the Beibu Gulf under a current scenario and three different Representative Concentration Pathways (126, 370, 585) to evaluate geographic distribution changes under the different climate-change scenarios. The current geographic distribution results showed variation with seasonality, as the wintering population shifts toward the northeast. Under each of three SSP scenarios, there is higher risk to habitat suitability in the 2090s as compared with that in the 2050s. The disadvantage to T. japonicus distribution is greatest in winter under each of the three climate change scenarios, both in the short- and long-term. Potential suitable habitat distributions have a minor range extension in Representative Concentration Pathway 370–2050 winter, but in the rest of the scenes and years they contract to south of the Beibu Gulf. The overall results indicate that seasonal differences in suitable habitat should be considered to ensure effective planning of future management strategies for T. japonicus.</p

DataSheet_1_Stronger selective constraints on the mitochondrial genome in flying fishes.docx

Flying fishes, which use their wing-like pectoral fins and hypocercal caudal fin to glide through the air to avoid underwater predators, have independently evolved flight behavior, making them ideal for the study of adaptive evolution. To investigate the adaptation of flight behavior in flying fishes and the origin of Beloniformes fishes, this study obtained the complete mitochondrial genomes of Cheilopogon nigricans and Oxyporhamphus micropterus and constructed the DNA sequences extracted from these newly sequenced mitochondrial genomes with the DNA sequences of 32 previously published mitochondrial genomes into a dataset for reconstructing the phylogenetic relationships of Beloniformes fishes. The phylogeny that emerged strongly supported the possibility that flying fishes developed from halfbeaks and the progressive transition of flying fishes from two-wing to four-wing gliding. The divergence time analysis showed that the split between the suborder Belonidei and the family Adrianichthyidae occurred roughly 77.08 Mya, which fell within the period of evolution of the Indian plate in the late Cretaceous. Selection analyses revealed that flying fishes have a lower dN/dS ratio than the other members of Beloniformes, indicating that flying fishes experienced stronger purifying selection to eliminate deleterious mutations to maintain efficient energy metabolism to adapt to flight behavior. Moreover, this work found the positively selected signal in the ND4 gene, suggesting that different mitogenomic genes might have undergone different selective patterns during adaptive evolution.</p