Cistanche deserticola(Orobanchaceae) has both medicinal and dietary properties and is cultivated on a large scale in Inner Mongolia, Ningxia, Gansu, Qinghai, and Xinjiang. In this study, 37 batches of cultivated C. deserticola samples were collected from five production areas. All samples were identified and differentiated based on the internal transcribed spacer 2(ITS2) sequence. An ultra-performance liquid chromatography( UPLC) method was established to simultaneously determine seven phenylethanoid glycosides, one iridoid glycoside, and two phenolic acids. This method was subsequently applied to the quality analysis and fingerprint comparison of the samples. The results of DNA barcoding identification showed that all 37 samples were authenticated as C. deserticola by the ITS2 sequence, and two single-nucleotide polymorphism(SNP) loci were identified for the first time, which may serve as potential molecular markers to distinguish samples from Inner Mongolia from those originating in other production areas, reflecting the genetic characteristics of the geo-authentic medicinal materials. The results of UPLC determination showed that the content of seven phenylethanoid glycosides in the 37 batches of cultivated C. deserticola was as follows: echinacoside, 0. 31-72. 56 mg·g~(-1); cistanoside A, 0-5. 55 mg·g~(-1); tubuloside A, 0-3. 74 mg·g~(-1); acteoside, 0-45. 34 mg·g~(-1); isoacteoside, 0. 07-5. 60 mg·g~(-1); 2'-acetylacteoside, 0-73. 89 mg·g~(-1); and tubuloside B, 0-11. 82 mg·g~(-1). The content of the iridoid glycoside, geniposidic acid, ranged from 0. 04 to 2. 72 mg·g~(-1), and the content of two phenolic acids, chlorogenic acid and caffeic acid, ranged from 0. 17 to 3. 29 mg·g~(-1) and 0. 28 to 1. 93 mg·g~(-1), respectively. The chemical composition of samples from different batches fluctuated significantly and did not show a consistent correlation with the production area. Moreover, the total content of echinacoside and acteoside in one batch from each of Inner Mongolia, Gansu and Qinghai was lower than the standard specified in the Chinese Pharmacopoeia. The postharvest processing methods might be one of the reasons for this phenomenon. The standardization of production procedures for C. deserticola is crucial for achieving stable and controllable quality for both medicinal and dietary use. This study provides guidance for the formulation of relevant quality standards and promotes the development of the C. deserticola comprehensive health industry.

To accurately detect early mechanical faults, a novel fault feature extraction method named Arnoldi mode decomposition (AMD) is proposed in this paper. First, AMD method constructs a numerically stable operator based on the output variance, projects the large-scale matrix formed from the signal onto a Krylov subspace via the Arnoldi process, and builds a set of low-dimensional orthogonal bases. The multi-parameter coupled filter optimization problem is then projected into the subspace for refined solution. Second, by exploiting the numerical stability of the orthogonal bases and the low-dimensional approximation capability of the Krylov subspace, numerical errors are effectively suppressed, thereby enhancing the stability of the feature extraction process. Finally, a nonlinear optimization is performed within the subspace using the reweighted kurtosis (RK) as the criterion, and a subspace sparse constraint strategy is adopted to update the filter along as few critical directions as possible, suppressing noise components and improving interpretability. Simulation signals and experimental bearing fault data demonstrate that the proposed AMD significantly improves the extraction ability of weak fault impulses, feature distinctiveness, and numerical stability, while maintaining low computational cost.

Genealogical ties leave traces beyond shared genetic material: relatives tend to share environmental exposures and cultural practices that persist across generations. Here, using genomic and electronic health record data from 13,143 individuals in the Biorepository and Integrative Genomics, we apply a hierarchical community detection algorithm that groups individuals into four major communities and 17 subcommunities based on the proportion of their genome shared identity-by-descent (IBD). This approach captures a fine-scale demographic structure beyond traditional ancestry classifications. By integrating neighborhood-level geographic data with census-derived environmental metrics, we reveal unequal exposure to environmental stressors between subcommunities, which correlates with differential rates of health conditions, including elevated respiratory condition prevalence in subcommunities under greater pollution burden. Through an interventional mediation analysis we find that a substantial part of the excess subcommunity-level risk remains unexplained by measured environmental factors alone, consistent with a contribution of unmeasured shared exposures captured by IBD-based grouping. Subcommunity-level disparities persist in sensitivity analyses adjusting for self-reported race, indicating that IBD-based clustering captures health-relevant information beyond demographic categories commonly used as proxies for social determinants of health. We implement an open-source dashboard for interactive exploration of IBD-defined communities, disease prevalence, and environmental exposures. Together, we demonstrate that IBD-based clustering jointly captures genetic and environmental determinants of health, offering a scalable framework for precision health and population genetics that translates biobank data into actionable insights.

As a core region for ecological security, food production, and energy supply in China, the hydrological cycle of the Yellow River Basin is being profoundly altered by climate change and intensive human activities, leading to growing systemic water scarcity and increasingly heterogeneous hydrological processes. However, the lack of long-term and high-resolution hydrological data has constrained the accurate characterization of multilayer water exchange processes among the atmosphere, surface water, and groundwater at the basin scale, thereby limiting the development of sustainable water resource management strategies. This study integrates multisource remote sensing data with hydrological models to reveal the spatiotemporal evolution of the basin water cycle and to develop a resilience-oriented water network for sustainable management. By integrating remote sensing products such as GRACE and ETMonitor with distributed hydrological models, the study systematically evaluated the multilevel water balance dynamics of the Yellow River Basin from atmospheric precipitation to groundwater storage during 1991-2020. The results show that the remotely sensed groundwater storage anomaly (GWSA) agrees well with in situ groundwater-level observations at the regional scale. The ETMonitor model performs well in estimating evapotranspiration over vegetated areas, with a validation root mean square error (RMSE) of 0.93 mm/day. The study revealed a pronounced spatiotemporal pattern of "water surplus in the west and water deficit in the east" across the Yellow River Basin, with the polarization intensifying under the combined effects of upstream climatic warming and humidification and intensive water consumption in the middle and lower reaches. Based on improved intelligent algorithms and channel topology constraints, this study proposed an optimized basin water network scheme. After optimization, the areal extent of water-deficient regions decreased substantially, water stress in the middle and lower reaches was alleviated, and both the balance and the efficiency of basin-wide water allocation improved. This research provides a quantitative basis for refined water resource management, water-saving irrigation retrofitting, and optimized planning of the national water network in the Yellow River Basin.

This article highlights the growing role of digital medicine in transforming the diagnosis and management of dizziness, vertigo, and other vestibular disorders. Advances such as video-oculography, video head impulse testing, smartphone-based diagnostic tools, and artificial intelligence (AI)-driven clinical decision support systems have created opportunities to deliver expert vestibular care at scale. The authors emphasize that current clinical practice often fails vestibular patients because of high diagnostic error rates, missed strokes, inappropriate testing, and low treatment rates for common conditions. While digital innovations hold great promise, challenges related to validation, regulation, data quality, and AI reliability still must be addressed.

Major histocompatibility complex (MHC) genes are central to pathogen recognition by the adaptive immune system of jawed vertebrates, with MHC classes I and II (henceforth referred to as MHC-I and MHC-II, respectively) primarily mediating responses to intracellular and extracellular pathogens, respectively. Here, we tested the hypothesis that MHC-II genes show stronger population differentiation, reflecting spatially heterogeneous selection by extracellular pathogens. We compiled a global dataset comprising >3500 pairwise estimates of MHC differentiation across approximately 120 tetrapod species. Phylogenetically informed analyses revealed consistently stronger differentiation at MHC-II than at MHC-I genes, supporting stronger local adaptation to spatially variable selection by extracellular pathogens. Isolation by distance contributed broadly to MHC differentiation, indicating that balancing selection is insufficient to homogenize MHC variation over large geographical scales. Differentiation varied markedly among tetrapod lineages, reflecting the differences in dispersal capacity. We further showed that differentiation was modulated by the genomic architecture of the MHC region, and our theoretical simulations demonstrated that variation in MHC gene copy number can have contrasting effects on population differentiation, depending on the strength of balancing selection acting on each MHC class. Together, these findings elucidate the global patterns of immunogenetic differentiation and advance the mechanistic understanding of how extraordinary MHC variation is structured across space.

Freshwater fish have evolved to forage in a range of habitats, from open water in lakes to benthic shorelines and streams. Much research has focused on how prey differences, such as zooplankton versus benthic macroinvertebrates, might select for divergence in predator traits across this habitat gradient. However, major structural components of this habitat contrast, such as aquatic vegetation, may fundamentally constrain foraging success. Here, we used a mesocosm experiment to test for interactive effects of vegetated habitat and fish density on the survival and growth of phenotypically variable juvenile sticklebacks. We investigated two scales of phenotypic variation: distinct lake and stream ecotypes and F2 lake-stream hybrids. We found that macrophytes strongly increased invertebrate biomass and functional richness, which increased average fish condition. Surprisingly, the relative performance of contrasting ecotypes and genotypes depended only on fish density. Stream ecotypes had higher survival than lake ecotypes, as well as higher condition. In parallel, F2 hybrids had higher growth when homozygous for stream alleles at three quantitative trait loci. Together, these findings suggest that adaptive divergence among habitats depends on the ways that prey type, habitat structure, and genetic variation for feeding and growth traits combine with competition to limit the abundance of accessible prey.

Ecological succession is shaped by multiple processes that operate simultaneously across spatial and temporal scales. While classical succession theory generally focuses on a single trophic level within a single location, often in plants or other macroscopic organisms, recent efforts have extended this framework to microorganisms across multiple ecological dimensions. The aquatic micro-ecosystem within the pitcher plant, Sarracenia purpurea, provides a natural model of primary succession replicated across a continental latitudinal gradient. Using this model system, we investigated how biogeography, food web structure and resource availability influenced bacterial succession. Over 12 weeks, we repeatedly sampled bacterial communities from seven sites spanning the latitudinal range of S. purpurea and characterized communities using 16S rRNA gene sequencing. Both taxonomic and phylogenetic diversity increased over succession. These diversity patterns were not explained by temporal changes in food web composition, resources or environmental conditions, although pH, water volume, latitude and midge abundance, each influenced diversity independently of time. Latent Dirichlet allocation models identified six compositional groups with distinct temporal and biogeographic signatures. Early-successional groups were enriched in putative diazotrophs, while late-successional groups contained metabolically diverse taxa adapted to low-oxygen conditions. Our findings show that microbial primary succession in S. purpurea is shaped by time, biogeography and pitcher-scale environmental filters.

Host and parasite body size frequently scale positively (often referred to as Harrison's rule), potentially as a result of fundamental constraints on large parasite species simply being morphologically incapable of infecting small host species, or through a variety of alternative proposed mechanisms. Regardless of mechanism, Harrison's rule does have some empirical support. Here, we leverage several trait databases and a large set of host-helminth parasite interactions to gauge support for Harrison's rule in parasitic helminths. We fit generalized additive models from both the host perspective (do larger host species tend to have larger average parasites?) and the parasite perspective (do larger parasite species tend to infect larger average host species?) across a range of host taxa including mammals, birds and fish. We find support for both relationships in mammals, moderate support in fish and very limited support in birds, relative to a null model. Together, we demonstrate positive host-parasite body size scaling in parasitic helminths, suggesting the potential for fundamental morphological constraints on host-parasite interactions, while also highlighting the clear differences in body size scaling across host taxa.