Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

Evolutionary dynamics and comparative pathogenicity of clade 2.3.4.4b H5 subtype avian influenza viruses,China,2021–2022

The recent concurrent emergence of H5N1,H5N6,and H5N8 avian influenza viruses(AIVs)has led to significant avian mortality globally.Since 2020,frequent human-animal interactions have been documented.To gain insight into the novel H5 subtype AIVs(i.e.,H5N1,H5N6 and H5N8),we collected 6102 samples from various regions of China between January 2021 and September 2022,and identified 41 H5Nx strains.Comparative analyses on the evolution and biological properties of these isolates were conducted.Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b,with 13 related to H5N1,19 to H5N6,and 9 to H5N8.Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8,exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015–2022 worldwide.H5N1 showed a higher rate of evolution in 2021–2022 and more sites under positive selection pressure in 2015–2022.The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations.Further hemagglutination inhibition assay suggested that some A(H5N1)viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains.Mammalian challenge assays demonstrated that the H5N8 virus(21GD001_H5N8)displayed the highest pathogenicity in mice,followed by the H5N1 virus(B1557_H5N1)and then the H5N6 virus(220086_H5N6),suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts.Based on the above results,we speculate that A(H5N1)viruses have a higher risk of emergence in the future.Collectively,these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b,contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs.

Sodium intake:a double-edged sword wielded by the brain

Taste receptors on the tongue discriminate between five fundamental tastes:sour,sweet,bitter,salty,and umami(Chandrashekar et al.,2006).Typically,stimuli that evoke bitterness and acidity prompt aversive responses by animals,whereas sweet and umami flavors are appetitive and enjoyable.Saltiness is unique in that it transitions from an appetitive to an aversive stimulus with increasing concentrations.

Data mining-based detection of acupuncture treatment on juvenile myopia

OBJECTIVE:We applied data mining techniques to the study of acupuncture as a treatment for juvenile myopia,with the aim of identifying hidden patterns in the data.METHODS:Fifty patients with juvenile myopia were selected and treated with acupuncture,and data mining was used to analyze the effects of treatment and the influence of behavioral variables.Clustering analysis was used to divide myopia patients into two classifications before acupuncture treatment.Artificial neural network BP algorithm was adopted to analyze the roles of different factors in changes in diopters.An association algorithm was used to analyze factors associated with the subjective experience of acupuncture and average diopter.RESULTS:The two classification results were fully consistent with the understandings of the ophthalmic circles.The duration of using the Internet and watching TV every day was the main factor that affected vision.Acupuncture feelings and therapeutic effect have a strong correlativity.A good or above experience's score of acupuncture could slow the progression of juvenile myopia.CONCLUSION:Collecting data from patients with juvenile myopia by using data mining can extract hidden potential rules and knowledge from the research evidence.The decision support can be provided to improve the doctor's clinical acupuncture treatment effects.

Lateral Hypothalamus Calcium/Calmodulin-Dependent Protein Kinase IIα Neurons Encode Novelty-Seeking Signals to Promote Predatory Eating

Predatory hunting is an innate appetite-driven and evolutionarily conserved behavior essential for animal survival, integrating sequential behaviors including searching, pursuit, attack, retrieval, and ultimately consumption. Nevertheless, neural circuits underlying hunting behavior with different features remain largely unexplored. Here, we deciphered a novel function of lateral hypothalamus (LH) calcium/calmodulin-dependent protein kinase II α (CaMKIIα^(+)) neurons in hunting behavior and uncovered upstream/downstream circuit basis. LH CaMKIIα^(+) neurons bidirectionally modulate novelty-seeking behavior, predatory attack, and eating in hunting behavior. LH CaMKIIα^(+) neurons integrate hunting-related novelty-seeking information from the medial preoptic area (MPOA) and project to the ventral periaqueductal gray (vPAG) to promote predatory eating. Our results demonstrate that LH CaMKIIα^(+) neurons are the key hub that integrate MPOA-conveyed novelty-seeking signals and encode predatory eating in hunting behavior, which enriched the neuronal substrate of hunting behavior.