Understanding spatial variation in species distribution and community structure is at the core of community ecology. Nevertheless, the effect of distance on metacommunity structure remains little studied. We examine how plant-pollinator community structure changes across geographical distances at a regional scale and disentangle its underlying local and regional processes. We use a multilayer network to represent linked plant-pollinator communities as a metacommunity in the Canary Islands. We used modularity (i.e. the extent to which the community is partitioned into groups of densely interacting species) to quantify distance decay in structure across space. In multilayer modularity, the same species can belong to different modules in different communities, and modules can span communities. This enabled quantifying how similarity in module composition varied with distance between islands. We developed three null models, each controlling for a separate component of the multilayer network, to disentangle the role of species turnover, interaction rewiring and local factors in driving distance decay in structure. We found a pattern of distance decay in structure, indicating that islands tended to share fewer modules with increasing distance. Species turnover (but not interaction rewiring) was the primary regional process triggering distance decay in structure. Local interaction structure also played an essential role in determining the structure similarity of communities at a regional scale. Therefore, local factors that determine species interactions occurring at a local scale drive distance decay in structure at a regional scale. Our work highlights the interplay between local and regional processes underlying community structure. The methodology, and specifically the null models, we developed provides a general framework for linking communities in space and testing different hypotheses regarding the factors generating spatial structure.

Atmospheric cold plasma (ACP) presents a promising method for the sterilization of coconut milk and exhibits a modifying effect on coconut globulin (CG), the primary allergen in coconut milk. This study investigated the potential role of ACP treatment in mitigating the allergenic properties of coconut milk by examining changes in protein structure. ACP treatment induced structural alterations in CG, disrupting binding sites with immunoglobulin E (IgE). Consequently, this led to a reduction in the affinity between CG and IgE, evidenced by a decrease in Ka from 2.17 × 104/M to 0.64 × 104/M, thereby diminishing IgE-mediated allergic reactions. The findings from allergenic and cellular models further corroborated that ACP treatment decreased the allergenicity of CG by 55.18%, while inhibiting degranulation and the release of allergic mediators. This study presents an innovative methodology for producing hypoallergenic coconut milk, thereby expanding the applicability of ACP technology within the food industry.

We analyzed age structure and dynamics, spatial distribution patterns, and reproductive capabilities of four Rosa persica populations in Xinjiang, to evaluate the survival status of the species and explore the reasons behind its endangerment. The results showed that the populations had fewer individuals in the youngest (Ⅰ) and oldest (Ⅵ-Ⅷ) age classes, with a predominance of middle-aged individuals, resulting in an irregular pyramid-shaped distribution, described as \"high in the middle, low on both sides\". The populations were generally growing, but were susceptible to external environmental disturbances (Vpi\'＞0, Pmax＞0). The mortality rate (qx) and vanish rate (Kx) peaked at age Ⅴ, leading to a sharp decline in plant abundance. The life expectancy (ex) decreased progressively with the increases of age class, reaching its lowest at age Ⅷ, which indicated minimal vitality at this stage. A time sequence analysis predicted a future dominance of individuals at age Ⅴ-Ⅷ, suggesting an aging trend. Spatially, the four populations were predominantly clumped, with the intensity of clumping ranked from highest to lowest as P4, P3, P1, and P2. P3 and P4 exhibited better reproductive capabilities than P1 and P2. There was a significant positive correlation between hundred-fruit weight and plant height and crown width, and between total seed number and crown width and hundred-fruit weight.
以4个单叶蔷薇种群为研究对象,对年龄结构与动态、空间分布类型、结实能力3个方面进行分析,评价生存状况,探讨单叶蔷薇致危机理。结果表明: 单叶蔷薇种群第Ⅰ、Ⅵ～Ⅷ龄级个体数量较少,中间龄级个体数量较多,总体呈“中间高、两侧低”的不规则金字塔型分布。虽然4个单叶蔷薇种群整体上为增长型,但易受外部环境干扰(Vpi′＞0,Pmax＞0),死亡率(qx)和消失率(Kx)均在第Ⅴ龄级时达到最大值,植株数量锐减;期望寿命(ex)随龄级增加呈递减趋势,且均在第Ⅷ龄级时出现最小值,说明在此阶段植株活力最低。时间序列分析表明,未来4个单叶蔷薇种群的第Ⅰ～Ⅳ龄级个体数量缺乏,第Ⅴ～Ⅷ龄级将占主导地位,单叶蔷薇种群在未来会趋于老龄化。种群空间分布主要为聚集类型,4个种群的聚集强度大小排布为P4＞P3＞P1＞P2。P3、P4种群植株结实能力优于P1、P2种群。百果重与株高、冠幅,种子总数量与冠幅、百果重之间呈显著正相关。.

Social and spatial structures of host populations play important roles in pathogen transmission. For environmentally transmitted pathogens, the host space use interacts with both the host social structure and the pathogen\'s environmental persistence (which determines the time-lag across which two hosts can transmit). Together, these factors shape the epidemiological dynamics of environmentally transmitted pathogens. While the importance of both social and spatial structures and environmental pathogen persistence has long been recognized in epidemiology, they are often considered separately. A better understanding of how these factors interact to determine disease dynamics is required for developing robust surveillance and management strategies. Here, we use a simple agent-based model where we vary host mobility (spatial), host gregariousness (social) and pathogen decay (environmental persistence), each from low to high levels to uncover how they affect epidemiological dynamics. By comparing epidemic peak, time to epidemic peak and final epidemic size, we show that longer infectious periods, higher group mobility, larger group size and longer pathogen persistence lead to larger, faster growing outbreaks, and explore how these processes interact to determine epidemiological outcomes such as the epidemic peak and the final epidemic size. We identify general principles that can be used for planning surveillance and control for wildlife host-pathogen systems with environmental transmission across a range of spatial behaviour, social structure and pathogen decay rates. This article is part of the theme issue \'The spatial-social interface: a theoretical and empirical integration\'.

Intra-tumour immune infiltration is a crucial determinant affecting immunotherapy response in non-small cell lung cancer (NSCLC). However, its phenotype and related spatial structure have remained elusive. To overcome these restrictions, we undertook a comprehensive study comprising spatial transcriptomic (ST) data (28 712 spots from six samples). We identified two distinct intra-tumour infiltration patterns: immune exclusion (characterised by myeloid cells) and immune activation (characterised by plasma cells). The immune exclusion and immune activation signatures showed adverse and favourable roles in NSCLC patients\' survival, respectively. Notably, CD14+APOE+ cells were recognised as the main cell type in immune exclusion samples, with increased epithelial‒mesenchymal transition and decreased immune activities. The co-location of CD14+APOE+ cells and MMP7+ tumour cells was observed in both ST and bulk transcriptomics data, validated by multiplex immunofluorescence performed on 20 NSCLC samples. The co-location area exhibited the upregulation of proliferation-related pathways and hypoxia activities. This co-localisation inhibited T-cell infiltration and the formation of tertiary lymphoid structures. Both CD14+APOE+ cells and MMP7+ tumour cells were associated with worse survival. In an immunotherapy cohort from the ORIENT-3 clinical trial, NSCLC patients who responded unfavourably exhibited higher infiltration of CD14+APOE+ cells and MMP7+ tumour cells. Within the co-location area, the MK, SEMA3 and Macrophage migration inhibitory factor (MIF) signalling pathway was most active in cell‒cell communication. This study identified immune exclusion and activation patterns in NSCLC and the co-location of CD14+APOE+ cells and MMP7+ tumour cells as contributors to immune resistance.

The study presents a thorough and detailed analysis of bicalutamide\'s structural and conformational properties. Quantum chemical calculations were employed to explore the conformational properties of the molecule, identifying significant energy differences between conformers. Analysis revealed that hydrogen bonds stabilise the conformers, with notable variations in torsion angles. Conformers were classified into \'closed\' and \'open\' types based on the relative orientation of the cyclic fragments. NOE spectroscopy in different solvents (CDCl3 and DMSO-d6) was used to study the conformational preferences of the molecule. NOESY experiments provided the predominance of \'closed\' conformers in non-polar solvents and a significant presence of \'open\' conformers in polar solvents. The proportions of open conformers were 22.7 ± 3.7% in CDCl3 and 59.8 ± 6.2% in DMSO-d6, while closed conformers accounted for 77.3 ± 3.7% and 40.2 ± 6.2%, respectively. This comprehensive study underscores the solvent environment\'s impact on its structural behaviour. The findings significantly contribute to a deeper understanding of conformational dynamics, stimulating further exploration in drug development.

The microbial enrichment of traditional biocarriers is limited due to the inadequate consideration of spatial structure and surface charging characteristics. Here, capitalizing on the ability of 3D printing technology to fabricate high-resolution materials, we further designed a positively charged sodium alginate/ε-poly-l-lysine (SA/ε-PL) printing ink, and the 3D printed biocarriers with ideal pore structure and rich positive charge were constructed to enhance the microbial enrichment. The rheological and mechanical tests confirmed that the developed SA/ε-PL ink could simultaneously satisfy the smooth extrusion for printing process and the maintenance of 3D structure. The utilization of the ε-PL secondary cross-linking strategy reinforced the 3D mechanical structure and imparted the requisite physical properties for its application as a biocarrier. Compared with traditional sponge carriers, 3D printed biocarrier had a faster initial attachment rate and a higher biomass of 14.58 ± 1.18 VS/cm3, and the nitrogen removal efficiency increased by 53.9 %. Besides, due to the superior electrochemical properties and biocompatibility, the 3D printed biocarriers effectively enriched the electroactive denitrifying bacteria genus Trichococcus, thus supporting its excellent denitrification performance. This study provided novel insights into the development of new functional biocarriers in the wastewater treatment, thereby providing scientific guidance for practical engineering.

Coexistence of multiple strains of a pathogen in a host population can present significant challenges to vaccine development or treatment efficacy. Here we discuss a novel mechanism that can increase rates of long-lived strain polymorphism, rooted in the presence of social structure in a host population. We show that social preference of interaction, in conjunction with differences in immunity between host subgroups, can exert varying selection pressure on pathogen strains, creating a balancing mechanism that supports stable viral coexistence, independent of other known mechanisms. We use population genetic models to study rates of pathogen heterozygosity as a function of population size, host population composition, mutant strain fitness differences and host social preferences of interaction. We also show that even small periodic epochs of host population stratification can lead to elevated strain coexistence. These results are robust to varying social preferences of interaction, overall differences in strain fitnesses, and spatial heterogeneity in host population composition. Our results highlight the role of host population social stratification in increasing rates of pathogen strain diversity, with effects that should be considered when designing policies or treatments with a long-term view of curbing pathogen evolution.

Deciding where to forage must not only account for variations in habitat quality but also where others might forage. Recent studies have suggested that when individuals remember recent foraging outcomes, negative frequency-dependent learning can allow them to avoid resources exploited by others (indirect competition). This process can drive the emergence of consistent differences in resource use (resource partitioning) at the population level. However, indirect cues of competition can be difficult for individuals to sense. Here, we propose that information pooling through collective decision-making-i.e. collective intelligence-can allow populations of group-living animals to more effectively partition resources relative to populations of solitary animals. We test this hypothesis by simulating (i) individuals preferring to forage where they were recently successful and (ii) cohesive groups that choose one resource using a majority rule. While solitary animals can partially avoid indirect competition through negative frequency-dependent learning, resource partitioning is more likely to emerge in populations of group-living animals. Populations of larger groups also better partition resources than populations of smaller groups, especially in environments with more choices. Our results give insight into the value of long- versus short-term memory, home range sizes and the evolution of specialization, optimal group sizes and territoriality. This article is part of the theme issue \'Connected interactions: enriching food web research by spatial and social interactions\'.

Plants emit biogenic volatile organic compounds (BVOCs) as signaling molecules, playing a crucial role in inducing resistance against herbivores. Neighboring plants that eavesdrop on BVOC signals can also increase defenses against herbivores or alter growth patterns to respond to potential risks of herbivore damage. Despite the significance of BVOC emissions, the evolutionary rationales behind their release and the factors contributing to the diversity in such emissions remain poorly understood. To unravel the conditions for the evolution of BVOC emission, we developed a spatially explicit model that formalizes the evolutionary dynamics of BVOC emission and non-emission strategies. Our model considered two effects of BVOC signaling that impact the fitness of plants: intra-individual communication, which mitigates herbivore damage through the plant\'s own BVOC signaling incurring emission costs, and inter-individual communication, which alters the influence of herbivory based on BVOC signals from other individuals without incurring emission costs. Employing two mathematical models-the lattice model and the random distribution model-we investigated how intra-individual communication, inter-individual communication, and spatial structure influenced the evolution of BVOC emission strategies. Our analysis revealed that the increase in intra-individual communication promotes the evolution of the BVOC emission strategy. In contrast, the increase in inter-individual communication effect favors cheaters who benefit from the BVOCs released from neighboring plants without bearing the costs associated with BVOC emission. Our analysis also demonstrated that the narrower the spatial scale of BVOC signaling, the higher the likelihood of BVOC evolution. This research sheds light on the intricate dynamics governing the evolution of BVOC emissions and their implications for plant-plant communication.