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Phenotypic, proteomic, and functional analyses of cytokine-induced memory-like NK cells show two distinct subsets based on CD16 expression

Abstract NK cells are innate lymphoid cells that can acquire a memory-like phenotype in vitro when stimulated with IL-12, IL-15, and IL-18. These cytokine-induced memory-like (CIML) NK cells exhibit prolonged lifespan and increased cytotoxicity, making them ideal for immunotherapy. This study characterizes two CIML NK cell subsets based on CD16 expression. NK cells were isolated from the peripheral blood of healthy donors and stimulated overnight to induce a memory-like phenotype. After seven days, we analyzed the phenotype and degranulation potential of CD16−/CD56 + and CD16+/CD56 + cells. The subsets were purified by fluorescence-activated cell sorting (FACS) and examined using high-throughput multiplexed quantitative proteomics. CD16 − cells showed higher levels of activating receptors, increased Granulysin expression, and lower inhibitory receptor expression compared to CD16 + cells. Functionally, CD16 − cells exhibited greater degranulation capacity, as determined by CD107a/b expression, when co-incubated with K562 and melanoma cells. Proteomic profiling identified 35 differentially expressed proteins out of 4,750, with 22 downregulated and 13 upregulated in the CD16 − subset. Key proteins included Granzyme family proteins, NCAM1, CALM1, CD247, and Fc receptors. This study provides a detailed characterization of CIML NK cells based on CD16 expression. Our findings highlight the molecular and functional diversity of CIML NK cells and may guide improved cancer immunotherapy strategies.

Personalized learning assessment for secondary education using a hybrid model of circular intuitionistic fuzzy and Aczel–Alsina bonferroni aggregation operator

Detection of avermectin pesticide residues in pine trees based on magnetic Solid-Phase extraction combined technology

Phylodynamic and phylogeographic reconstruction of IBV lineages: diverse paths and determinants, one goal for control

Abstract Infectious bronchitis virus (IBV) is a genetically diverse avian coronavirus that significantly impacts global poultry production. While IBV evolution and spread have been widely studied, most analyses lack global scope and statistical evaluation of dispersal drivers. This study investigates the population dynamics, spatiotemporal diffusion, and determinants of spread for three major IBV lineages—GI-16, GI-19, and GI-23—using a phylodynamic framework integrated with a generalized linear model (GLM). All lineages likely originated between the 1960s and 1980s, circulating at low levels before expanding under favorable conditions, often linked to introduction into naïve or poorly managed poultry systems. Temporal trends suggested lineage competition and modulation by vaccination strategies. Phylogeographic analyses showed that local and regional circulation prevailed over long-distance migration. No statistical support was found for a role of migratory birds. Instead, chicken population size, agricultural investment and trade, were significant drivers. Interestingly, agricultural investment was negatively associated with viral migration in Europe—likely due to the protective effect of improved biosecurity and vaccination—yet positively associated with GI-23, reflecting rapid poultry sector expansion in some emerging economies, which was not matched by adequate animal health management. These findings highlight the complex and lineage-specific nature of IBV spread and the importance of science-based, coordinated control strategies, backed by international surveillance.

Network analysis of burnout, depression, and anxiety with occupational and personal outcomes among clinical nurses in China

CRISPR activation for SCN2A-related neurodevelopmental disorders

In situ light-field imaging of octopus locomotion reveals simplified control

Abstract Animals have developed many different solutions to survive, and these abilities are inspiring technological innovations in a wide range of fields including robotics 1–3 . However, biologically inspired robots, especially those mimicking octopus locomotion 4,5 , are based on limited in situ behavioural data owing to the complexity of collecting quantitative observations. Here we describe deployments of a remotely operated vehicle, equipped with a suite of imaging systems, to study the mechanics of locomotion in the octopus Muusoctopus robustus at the recently discovered 3,000-m deep Octopus Garden. Using a recently developed light-field imaging system called EyeRIS and an ultra-high-definition science camera, we were able to capture wide and zoomed-in views to characterize whole-animal gaits in a completely unconstrained environment across multiple individuals. Furthermore, the real-time volumetric data captured using EyeRIS yielded quantitative kinematics measurements of individual octopus arms during crawling, showing regions of high curvature and strain concentrated at distinct arm locations. Our results indicate that M.   robustus crawling patterns showed several elements of simplified control, with implications for the design of future octopus-inspired robots. Further developments and deployments of technologies such as EyeRIS, coupled with capable robotic vehicles, will enable mining of the deep ocean for biological inspiration.

Therapeutic genetic restoration through allogeneic brain microglia replacement

Microglia–neuron crosstalk through Hex–GM2–MGL2 maintains brain homeostasis

Abstract As tissue-resident macrophages of the central nervous system parenchyma, microglia perform diverse essential functions during homeostasis and perturbations 1 . They primarily interact with neurons by means of synaptic engulfment and through the rapid elimination of apoptotic cells and non-functional synapses 2 . Here, by combining unbiased lipidomics and high-resolution spatial lipid imaging, deep single-cell transcriptome analysis and novel cell-type-specific mutants, we identified a previously unknown mode of microglial interaction with neurons. During homeostasis, microglia deliver the lysosomal enzyme β-hexosaminidase to neurons for the degradation of the ganglioside GM2 that is integral to maintaining cell membrane organization and function. Absence of Hexb , encoding the β subunit of β-hexosaminidase, in both mice and patients with neurodegenerative Sandhoff disease leads to a massive accumulation of GM2 derivatives in a characteristic spatiotemporal manner 3 . In mice, neuronal GM2 gangliosides subsequently engage the macrophage galactose-type lectin 2 receptor on microglia through N -acetylgalactosamine residues, leading to lethal neurodegeneration. Notably, replacement of microglia with peripherally derived microglia-like cells is able to break this degenerative cycle and fully restore central nervous system homeostasis. Our results reveal a mode of bidirectional microglia–neuron communication centred around GM2 ganglioside turnover, identify a microgliopathy and offer therapeutic avenues for these maladies.

Microbial iron oxide respiration coupled to sulfide oxidation

Abstract Microorganisms have driven Earth’s sulfur cycle since the emergence of life 1–6 , yet the sulfur-cycling capacities of microorganisms and their integration with other element cycles remain incompletely understood. One such uncharacterized metabolism is the coupling of sulfide oxidation with iron( iii ) oxide reduction, a ubiquitous environmental process hitherto considered to be strictly abiotic 7,8 . Here we present a comprehensive genomic analysis of sulfur metabolism across prokaryotes, and reveal bacteria that are capable of oxidizing sulfide using extracellular solid phase iron( iii ). Based on a phylogenetic framework of over hundred genes involved in dissimilatory transformation of sulfur compounds, we recorded sulfur-cycling capacity in most bacterial and archaeal phyla. Metabolic reconstructions predicted co-occurrence of sulfur compound oxidation and iron( iii ) oxide respiration in diverse members of 37 prokaryotic phyla. Physiological and transcriptomic evidence demonstrated that a cultivated representative, Desulfurivibrio alkaliphilus , grows autotrophically by oxidizing dissolved sulfide or iron monosulfide (FeS) to sulfate with ferrihydrite as an extracellular iron( iii ) electron acceptor. The biological process outpaced the abiotic process at environmentally relevant sulfide concentrations. These findings expand the known diversity of sulfur-cycling microorganisms and unveil a biological mechanism that links sulfur and iron cycling in anoxic environments, thus highlighting the fundamental role of microorganisms in global element cycles.

A compressed hierarchy for visual form processing in the tree shrew

Abstract Our knowledge of the brain processes that govern vision is largely derived from studying primates, whose hierarchically organized visual system 1 inspired the architecture of deep neural networks 2 . This raises questions about the universality of such hierarchical structures. Here we examined the large-scale functional organization for vision in one of the closest living relatives to primates, the tree shrew. We performed Neuropixels recordings 3,4 across many cortical and thalamic areas spanning the tree shrew ventral visual system while presenting a large battery of visual stimuli in awake tree shrews. We found that receptive field size, response latency and selectivity for naturalistic textures, compared with spectrally matched noise 5 , all increased moving anteriorly along the tree shrew visual pathway, consistent with a primate-like hierarchical organization 6,7 . However, tree shrew area V2 already harboured a high-level representation of complex objects. First, V2 encoded a complete representation of a high-level object space 8 . Second, V2 activity supported the most accurate object decoding and reconstruction among all tree shrew visual areas. In fact, object decoding accuracy from tree shrew V2 was comparable to that in macaque posterior IT and substantially higher than that in macaque V2. Finally, starting in V2, we found strongly face-selective cells resembling those reported in macaque inferotemporal cortex 9 . Overall, these findings show how core computational principles of visual form processing found in primates are conserved, yet hierarchically compressed, in a small but highly visual mammal.

Publisher Correction: Multimodal cell maps as a foundation for structural and functional genomics

Artificially induced torpor during pregnancy impairs fetal growth in mice

Increasing canopy cover elevates vehicle collision risk for barbastelle bats (Barbastella barbastellus) at roads

Rate and noise in human amygdala drive increased exploration in aversive learning

A method for instrumental seismic intensity assessment in Western China based on RF and MLP

Prepupal diapause reduces adult lifespan in the solitary alfalfa leafcutter bee

Google Scholar-based tool gives extra credit to first and last authors

Automated parametrization of small molecules within the Martini 3 coarse-grained model guided by experimental log P values

Abstract Molecular dynamics simulations play an important role in investigating biological systems. However, simulating large-scale systems can be computationally expensive, which can be improved by the employment of a coarse-graining force field. This study focuses on the automated parametrization of small molecules within the CGCompiler framework. This optimization approach utilizes a mixed-variable particle swarm algorithm to avoid the manual tweaking of parameters. Particularly, the optimization focuses on matching experimentally known log P values of partitioning in water-octanol phases, reproducing atomistic density profiles in lipid bilayers, and optimizing overall shape and volume aspects of the modeled atomistic molecules. After the atomistic to coarse-grained mapping, the model’s accuracy is evaluated through a fitness function, which combines structural and dynamic targets, to accurately capture the shape and behavior of the small molecule in question. Through the investigation of the interactions between small molecules and cellular membranes, this optimization process supports the development of accurate coarse-grained models for small molecules relevant to drug discovery. Our work demonstrates promising results in automating the high-fidelity parametrization of small molecules using the Martini 3 force-field guided by experimental log P values.

This AI method could turbocharge the hunt for new medicines