Technologies to differentiate human pluripotent stem cells into three-dimensional organized structures that resemble in vivo organs are pushing the frontiers of human disease modeling and drug development. In response to the global health emergency posed by the Zika virus (ZIKV) outbreak, brain organoids engineered to mimic the developing human fetal brain have been employed to model ZIKV-induced microcephaly. Here, we discuss the advantages of brain organoids over other model systems to study development and highlight recent advances in understanding ZIKV pathophysiology and its underlying pathogenesis mechanisms. We further discuss perspectives on overcoming limitations of current organoid systems for their future use in ZIKV research.

Remotely sensed ocean color data and numerical modeling have been used to study the phenology of both spring and fall phytoplankton blooms (FPBs) in the Nova Scotian Shelf (NSS)–Gulf of Maine (GoM) region. The ocean color data reveal a general pattern of westward progression of the spring phytoplankton bloom (SPB), and an eastward progression of the FPB in the NSS–GoM region. The spatial pattern of mean chlorophyll concentration in spring is similar to that in fall, with a lower concentration in the NSS and higher in the GoM. Interannually, there is a weak but significant tendency for years with earlier (delayed) SPBs to be followed by delayed (earlier) FPBs, but the mean chlorophyll concentrations during SPBs are not correlated with those during FPBs. The interannual variability of SPB timing is significantly correlated with sea surface salinity (SSS), but the FPB timing is correlated with both SSS and sea surface temperature. The process-oriented numerical modeling experiments suggest that (i) salinity is the main factor influencing the bloom timing and magnitude in the NSS–GoM region, especially for the timing of SPBs; (ii) compared to buoyancy forcing induced by vertical salinity gradients, the impact of surface heating and surface wind stress on the blooms variability is much weaker; and (iii) the nutrient level controls the bloom magnitude, but only has a minor effect on bloom timing. This study provides a quantitative estimation of relationship between changes in local/remote environmental forcing and phytoplankton phenological shifts, thus improving our understanding on the possible impact of climate change on coastal/shelf ecosystems.

Recent rapid sea‐ice changes in the Arctic Ocean have been widely considered to alter phytoplankton bloom timing and primary production, but the magnitude and regionality of this effect remain unclear. Here, we examined the spatial patterns in bloom timing, bloom magnitude, and primary productivity in relation to ice‐retreat timing, using a combination of satellite observations and numerical modeling. We found distinct regional differences in how the phytoplankton bloom relates to ice‐retreat timing. In the Arctic shelf regions, earlier and stronger blooms follow earlier annual ice retreats and enhanced light availability. By contrast, in some parts of the central Arctic, especially in the Canada Basin, there have been weakened blooms and reduced primary production in recent years. This reduction is largely due to a chain reaction triggered by earlier ice‐melt and enhanced haline stratification, which further suppress vertical nutrient exchange and reduce surface nutrients in an already nutrient‐limited system. Recognizing and quantifying strong and regionally distinct links between sea‐ice retreat and primary production will improve spatiotemporal projections of biogeochemical cycles and trophic flows in Arctic marine ecosystems.

The Yellow River Estuary and its adjacent waters serve as crucial spawning, foraging, and nursery areas for marine organisms, possessing abundant biological resources. Monitoring fish communities provides a baseline for implementing the sustainable utilization of marine resources. In this study, data were collected from 15 spring surface and bottom sites and 17 summer surface sites using eDNA and trawl surveys. The results showed that 37, 40, and 35 fish species were detected using eDNA in the spring (surface and bottom) and summer (surface), respectively, with 38 fish species caught during summer trawling. The dominant species mainly belonged to Engraulidae of Clupeiformes in the spring and Gobiidae of Perciformes in the summer, characterized by smaller-sized, short-lived, and pelagic fish species. The summer surface communities exhibited higher diversity than the spring surface and bottom communities. NMDS analysis revealed a degree of seasonal differences in fish communities and that there may be a lack of vertical stratification in the spring communities. The pH and DO were identified as the key environmental factors affecting the fish community. Additionally, the combination of eDNA and trawl surveys was regarded as a superior survey method. Our study provides valuable information for understanding seasonal fish communities in the Yellow River Estuary and its adjacent waters, contributing to fishery resource management and conservation in the region.

The Arctic Ocean has experienced significant sea ice loss over recent decades, shifting towards a thinner and more mobile seasonal ice regime. However, the impacts of these transformations on the upper ocean dynamics of the biologically productive Pacific Arctic continental shelves remain underexplored. Here, we quantified the summer upper mixed layer depth and analyzed its interannual to decadal evolution with sea ice and atmospheric forcing, using hydrographic observations and model reanalysis from 1996 to 2021. Before 2006, a shoaling summer mixed layer was associated with sea ice loss and surface warming. After 2007, however, the upper mixed layer reversed to a generally deepening trend due to markedly lengthened open water duration, enhanced wind-induced mixing, and reduced ice meltwater input. Our findings reveal a shift in the primary drivers of upper ocean dynamics, with surface buoyancy flux dominant initially, followed by a shift to wind forcing despite continued sea ice decline. These changes in upper ocean structure and forcing mechanisms may have substantial implications for the marine ecosystem, potentially contributing to unusual fall phytoplankton blooms and intensified ocean acidification observed in the past decade.

The integrated assessment of ecological quality in estuarine ecosystems holds significant importance for environmental management. Previous monitoring programs predominantly focused on environmental data, lacking a comprehensive quality assessment approach. To address this gap, this study aimed to integrate environmental factors with macrofaunal community information to evaluate the ecological quality status of the Yellow River Estuary. A total of 13 stations were routinely monitored in August for four consecutive years to collect environmental and biological data. Candidate indicators were screened based on variation coefficients, distribution ranges, and redundancy analysis, identifying 16 indicators belonging to three categories (i.e., seawater, sediment, and biology). The model fit and the interrelationship of the components were determined using structural equation modelling (SEM). The main results were as follows. (1) A total of 144 macrofaunal taxa, belonging to eight animal phyla and 98 families, were identified, with a dominance of Annelida (37.8%) and Mollusca (33.3%). The environmental variables most strongly correlated with the macrofaunal community were TOC, DO, Cd, and Md. (2) NO₂ and heavy metals represented the two most direct factors of environmental pollution, while the factor load of biodiversity indices (H’, J, and D) was large in the biology category. (3) The evaluation results indicated that 78.85% of the total samples were between the average and upper levels of ecological quality, but only 7.69% of samples were at the “high” level. The framework system for the evaluation of ecological quality constructed in this study provides a theoretical and practical basis for the evaluation of the effectiveness of conservation management of the Yellow River Estuary.