Integrative spatial analysis reveals a multi-layered organization of glioblastoma.

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma.

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

Advancing primate surveillance with image recognition techniques from unmanned aerial vehicles.

Using unmanned aerial vehicles (UAVs) for surveys on thermostatic animals has gained prominence due to their ability to provide practical and precise dynamic censuses, contributing to developing and refining conservation strategies. However, the practical application of UAVs for animal monitoring necessitates the automation of image interpretation to enhance their effectiveness. Based on our past experiences, we present the Sichuan snub-nosed monkey (Rhinopithecus roxellana) as a case study to illustrate the effective use of thermal cameras mounted on UAVs for monitoring monkey populations in Qinling, a region characterized by magnificent biodiversity. We used the local contrast method for a small infrared target detection algorithm to collect the total population size. Through the experimental group, we determined the average optimal grayscale threshold, while the validation group confirmed that this threshold enables automatic detection and counting of target animals in similar datasets. The precision rate obtained from the experiments ranged from 85.14% to 97.60%. Our findings reveal a negative correlation between the minimum average distance between thermal spots and the count of detected individuals, indicating higher interference in images with closer thermal spots. We propose a formula for adjusting primate population estimates based on detection rates obtained from UAV surveys. Our results demonstrate the practical application of UAV-based thermal imagery and automated detection algorithms for primate monitoring, albeit with consideration of environmental factors and the need for data preprocessing. This study contributes to advancing the application of UAV technology in wildlife monitoring, with implications for conservation management and research.

Advancements in enhancing resistant starch type 3 (RS3) content in starchy food and its impact on gut microbiota: A review.

Resistant starch type 3 (RS3), often found in cooked starchy food, has various health benefits due to its indigestible properties and physiological functions such as promoting the abundance of gut beneficial microbial flora and inhibiting the growth of intestinal pathogenic bacteria. However, it is challenging to develop starchy food with high RS3 content. This review aims to provide a detailed overview of current advancements to enhance RS3 content in starchy food and its effects of RS3 on gut microbiota. These approaches include breeding high-amylose cereals through gene editing techniques, processing, enzyme treatments, storage, formation of RS3 nanoparticles, and the incorporation of bioactive compounds. The mechanisms, specific conditions, advantages, and disadvantages associated with each approach and the potential effects of RS3 prepared by different methods on gut microbiota are summarized. In conclusion, this review contains important information that aims to provide guidelines for developing an efficient RS3 preparation process and promote the consumption of RS3-enriched starchy foods to improve overall health outcomes.

Unveiling the potential of novel recyclable deep eutectic solvent pretreatment: Effective separation of lignin from poplar hydrolyzed residue.

To effectively convert the fermentable sugars present in lignocellulosic biomass into biofuels and additional value-added products, it is crucial to remove lignin from the biomass. With the intention of expeditiously remove lignin from poplar wood and improve cellulose saccharification, an innovative ternary deep eutectic solvent (DES) benzyl triethyl ammonium chloride-ethylene glycol-FeCl3 (T-EG-F) was studied for the pretreatment of poplar hydrolyzed residue (PHR). The results revealed that following T-EG-F DES pretreatment at 130 °C for 4 h, the lignin removal rate reached 91.88 %. The effect of DES on PHR and regenerated lignin was comprehensively investigated using X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), Thermogravimetric (TG) and other characterization methods, providing valuable insights into the mechanism of this innovative biomass pretreatment. Moreover, there was a significant improvement in the enzyme digestibility of the DES pretreatment residue. At 48 h, the enzyme load of 30 FPU/g cellulose achieved a remarkable enzyme digestibility of 97.31 %, and this value exhibited a notable increase of 6.56 times compared to the untreated poplar sample. In addition, the T-EG-F could be recycled and reused. This study demonstrates that the potential of T-EG-F DES pretreatment as a green and efficient method for lignin dissociation from lignocellulosic biomass, offering a promising approach for biomass component separation.

Maternal dietary fat during lactation shapes single nucleus transcriptomic profile of postnatal offspring hypothalamus in a sexually dimorphic manner in mice.

Maternal overnutrition during lactation predisposes offspring to develop metabolic diseases and exacerbates the relevant syndromes in males more than females in later life. The hypothalamus is a heterogenous brain region that regulates energy balance. Here we combined metabolic trait quantification of mother and offspring mice under low and high fat diet (HFD) feeding during lactation, with single nucleus transcriptomic profiling of their offspring hypothalamus at peak lacation to understand the cellular and molecular alterations in response to maternal dietary pertubation. We found significant expansion in neuronal subpopulations including histaminergic (Hdc), arginine vasopressin/retinoic acid receptor-related orphan receptor ß (Avp/Rorb) and agouti-related peptide/neuropeptide Y (AgRP/Npy) in male offspring when their mothers were fed HFD, and increased Npy-astrocyte interactions in offspring responding to maternal overnutrition. Our study provides a comprehensive offspring hypothalamus map at the peak lactation and reveals how the cellular subpopulations respond to maternal dietary fat in a sex-specific manner during development.

Mass spectrometry imaging-based metabolomics highlights spatial metabolic alterations in three types of liver injuries.

Liver's distinctive function renders it highly susceptible to diverse damage sources. Characterizing the metabolic profiles and spatial signatures in different liver injuries is imperative for early diagnosis and etiology-oriented treatment. In this comparative study, we conducted whole-body spatial metabolomics on zebrafish with liver injury induced by ethanol (EtOH), acetaminophen (APAP), and thioacetamide (TAA). The two specific levels, the whole-body and liver-specific metabolic profiles, as well as their regional distributions, were systematically mapped in situ by mass spectrometry imaging, which is distinct from conventional LC-MS and GC-MS methods. We found that liver injury regions exhibited more pronounced metabolic reprogramming than the entire organism, leading to significant alterations in eight fatty acids, three phospholipids, and four low-molecular-weight metabolites. More importantly, fatty acids as well as small molecule metabolites including glutamine, glutamate, taurine and malic acid displayed contrasting changes between alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD). In addition, phospholipids, including Lyso PC (16:0) and Lyso PE (18:0), demonstrated notable down-regulation in all damaged liver, whereas PC (34:1) underwent upregulation. This study not only deepens insights into distinct potential biomarkers for liver injuries, but also underscores spatial metabolomics as a powerful tool to elucidate possible pathogenic mechanisms in other metabolic diseases.

Variation in placentophagy in golden snub-nosed monkeys (Rhinopithecus roxellana) reflects nutritional constraints.

Golden snub-nosed monkeys show inconsistent frequency of placentophagy between wild and captive populations, with almost all births in the wild but around half of the births in captivity accompanied by the female's consumption of placenta. This aligns with nutritional demands-driven placentophagy, as captive populations are generally under less nutritional constraints for breeding females than the wild population. Placentophagy is probably adaptive in the wild and under positive selection due to nutritional benefits to both mothers and infants.

Moderate Genetic Diversity of MHC Genes in an Isolated Small Population of Black-and-White Snub-Nosed Monkeys (Rhinopithecus bieti).

Genetic diversity is an essential indicator that echoes the natural selection and environmental adaptation of a species. Isolated small populations are vulnerable to genetic drift, inbreeding, and limited gene flow; thus, assessing their genetic diversity is critical in conservation. In this study, we studied the genetic diversity of black-and-white snub-nosed monkeys (Rhinopithecus bieti) using neutral microsatellites and five adaptive major histocompatibility complex (MHC) genes. Two DQA1 alleles, two DQB1 alleles, two DRB1 alleles, two DRB5 alleles, and three DPB1 alleles were isolated from a population. The results indicate that neutral microsatellites demonstrate a high degree of heterozygosity and polymorphism, while adaptive MHC genes display a high degree of heterozygosity and moderate polymorphism. The results also show that balancing selection has prominently influenced the MHC diversity of the species during evolution: (1) significant positive selection is identified at several amino acid sites (primarily at and near antigen-binding sites) of the DRB1, DRB5, and DQB1 genes; (2) phylogenetic analyses display the patterns of trans-species evolution for all MHC loci. This study provides valuable genetic diversity insights into black-and-white snub-nosed monkeys, which dwell at the highest altitude and have experienced the harshest environmental selection of all primates globally since the Pleistocene. Such results provide valuable scientific evidence and a reference for making or amending conservation strategies for this endangered primate species.

Dynamic foraging strategy adaptation to heterogeneous environments contributes to social aggregation in snub-nosed monkeys.

The dynamics of animal social structures are heavily influenced by environmental patterns of competition and cooperation. In folivorous colobine primates, prevailing theories suggest that larger group sizes should be favored in rainforests with a year-round abundance of food, thereby reducing feeding competition. Yet, paradoxically, larger groups are frequently found in high-altitude or high-latitude montane ecosystems characterized by a seasonal scarcity of leaves. This contradiction is posited to arise from cooperative benefits in heterogeneous environments. To investigate this hypothesis, we carried out a six-year field study on two neighboring groups of golden snub-nosed monkey ( Rhinopithecus roxellana), a species representing the northernmost distribution of colobine primates. Results showed that the groups adjusted their movement and habitat selection in response to fluctuating climates and spatiotemporal variability of resources, indicative of a dynamic foraging strategy. Notably, during the cold, resource-scarce conditions in winter, the large group occupied food-rich habitats but did not exhibit significantly longer daily travel distances than the smaller neighboring group. Subsequently, we compiled an eco-behavioral dataset of 52 colobine species to explore their evolutionary trajectories. Analysis of this dataset suggested that the increase in group size may have evolved via home range expansion in response to the cold and heterogeneous climates found at higher altitudes or latitudes. Hence, we developed a multi-benefits framework to interpret the formation of larger groups by integrating environmental heterogeneity. In cold and diverse environments, even smaller groups require larger home ranges to meet their dynamic survival needs. The spatiotemporal distribution of high-quality resources within these expanded home ranges facilitates more frequent interactions between groups, thereby encouraging social aggregation into larger groups. This process enhances the benefits of collaborative actions and reproductive opportunities, while simultaneously optimizing travel costs through a dynamic foraging strategy.

The hedonic overdrive model best explains high-fat diet-induced obesity in C57BL/6 mice.

OBJECTIVE: High-fat diets cause obesity in male mice; however, the underlying mechanisms remain controversial. Here, three contrasting ideas were assessed: hedonic overdrive, reverse causality, and passive overconsumption models. METHODS: A total of 12 groups of 20 individually housed 12-week-old C57BL/6 male mice were exposed to 12 high-fat diets with varying fat content from 40% to 80% (by calories), protein content from 5% to 30%, and carbohydrate content from 8.4% to 40%. Body weight and food intake were monitored for 30 days after 7 days at baseline on a standard low-fat diet. RESULTS: After exposure to the diets, energy intake increased first, and body weight followed later. Intake then declined. The peak energy intake was dependent on both dietary protein and carbohydrate, but not the dietary fat and energy density, whereas the rate of decrease in intake was only related to dietary protein. On high-fat diets, the weight of food intake declined, but despite this average reduction of 14.4 g in food intake, they consumed, on average, 357 kJ more energy than at baseline. CONCLUSIONS: The hedonic overdrive model fit the data best. The other two models were not supported.

Pregnancy diagnosis and sex identification with urinary glycopatterns of two mammal species.

Glycome in urine could be promising biomarkers for detecting pregnancy diagnosis and sex noninvasively for animals, especially for rare species. We explore the applicability of grouping golden snub-nosed monkeys by sex or diagnosing pregnancy based on their urinary glycopatterns, which are determined via lectin microarray combining mass spectrometry analysis. Sprague-Dawley rats are used to verify whether this approach and whether the glycomic biomarkers can be generalized to other mammalian species. The results show that, for both species, lectin microarray combining mass spectrometry can distinguish individuals' pregnancy status and sex; significant differences are found in the types, amounts, and terminal modification of glycans between pregnant and non-pregnant females and between females and males. This indicates the approach could be generalized to other mammalian species to group sex and detect pregnancy, yet the glycopatterns appear to be species-specific and markers developed from one species may not be directly applicable to another.