Adaptive Changes Research Articles

A novel quinazoline derivative exhibits potent anticancer cytotoxicity via apoptosis and inhibition of angiogenesis in DMBA-induced mammary gland carcinoma.

Mammary gland carcinoma is one of the most prevalent and deadly diseases among women globally. It is a type of solid malignant tumor. In this malignant tumor, the microenvironment becomes hypoxic in rapidly proliferating cancer cells. These cells undergo adaptive changes through the expression of hypoxia-inducible factor-1alpha (HIF-1α) which is regulated by factor inhibiting HIF-1α (FIH-1). Considering this, we hypothesized that the chemical activation of FIH-1 would inhibit the hypoxic activity of HIF-1α in mammary gland carcinoma. A library of 67,609 chemical compounds was virtually screened against FIH-1 based on Lipinski's rule from the ZINC database. The BBAP-8 has been selected based on an excellent docking score (-8.352 Kcal/mol), favorable ADMET, and potential FIH-1 activator profile. Further, its in-vitro cytotoxicity and apoptotic activity were scrutinized against MCF-7 cells and in-vivo activity against 7,12-dimethylbenz[a]anthracene (DMBA) induced mammary gland carcinoma in Wistar rats. It exhibited significant cytotoxicity (IC50 = 16.59 ± 0.49 μM) and activated apoptosis when scrutinized through DAPI, AO/EB, and JC-1 staining. Also, oral administration of BBAP-8 restored hemodynamic changes, normalized tissue architecture, and corrected metabolic abnormalities. The western blot analysis and mRNA expression analysis validated that BBAP-8 has the potential to activate FIH-1 with the downregulation of GLUT-1, VEGF, and Twist-1. Moreover, BBAP-8 fostered apoptosis, when evaluated through BCL-2, BAX, Caspase-8, and Caspase-3. Based on research findings, this implies that BBAP-8 activates FIH-1 and can be effective in chemotherapeutic treatment of mammary gland carcinoma.

Detection of Incidents and Anomalies in Software-Defined Network – Based Implementations of Critical Infrastructure Resulting in Adaptive System Changes

Detection of Incidents and Anomalies in Software-Defined Network – Based Implementations of Critical Infrastructure Resulting in Adaptive System Changes

Mutant Huntingtin Drives Development of an Advantageous Brain Early in Life: Evidence in Support of Antagonistic Pleiotropy.

Huntington's disease (HD) is a neurodegenerative disease caused by a triplet repeat expansion within the gene huntingtin (HTT). Antagonistic pleiotropy is a theory of aging that posits that some genes, facilitating individual fitness early in life through adaptive evolutionary changes, also augment detrimental aging-related processes. Antagonistic pleiotropy theory may explain a positive evolutionary pressure toward functionally advantageous brain development that is vulnerable to rapid degeneration. The current study investigated antagonistic pleiotropy in HD using a years-to-onset paradigm in a unique sample of children and young adults at risk for HD. Cognitive, behavioral, motor, and brain structural measures from premanifest gene-expanded (n = 79) and gene nonexpanded (n = 112) participants (6-21 years) in the Kids-HD study were examined. All measures in the gene-expanded group were modeled using a mixed-effects regression approach to assess years-to-onset-based changes while controlling for normal growth. Simultaneously, structure-function associations were also examined. Decades from motor onset, gene-expanded participants showed significantly better cognitive, behavioral, and motor scores versus gene nonexpanded controls, along with larger cerebral volumes and cortical features. After this initial peak, a prolonged deterioration was observed in both functional and structural measures. Far from onset, brain measures were positively correlated with functional measures, supporting the view that functional advantages were mediated by structural differences. Mutant HTT may drive the development of a larger than normal brain that subserves superior early-life function. These findings support the antagonistic pleiotropy theory of HTT in HD, where this gene drives early advantage followed by accelerated aging processes. ANN NEUROL 2024;96:1006-1019.

Anticipating prosperity: a systemic analysis of long-term economic trajectories

PurposeThis study introduces an innovative approach to long-term economic forecasting by integrating anticipatory governance (AG) and causal layered analysis methodologies. Focussing on emerging economies, with Vietnam as a case study, we explore potential economic trajectories to 2050.Design/methodology/approachThe research employs a mixed-method approach, combining quantitative economic projections with qualitative scenario building and analysis.FindingsOur findings reveal four distinct future scenarios, ranging from low growth to transformative change. The preferred scenario, characterized by adaptive change, projects a Gross National Income (GNI) per capita of $30,684 by 2050, with significant reductions in agricultural labour and improvements in human development indicators.Originality/valueThis study contributes to theoretical and practical domains by demonstrating the value of integrated foresight methodologies in economic planning. It offers policymakers a comprehensive framework for navigating complex, long-term economic challenges and opportunities. This research underscores the importance of adaptive governance and systemic thinking in achieving sustainable, inclusive economic growth in an increasingly uncertain global environment.

Expanding the Triangle of U: Comparative analysis of the Hirschfeldia incana genome provides insights into chromosomal evolution, phylogenomics and high photosynthesis-related traits.

The Brassiceae tribe encompasses many economically important crops and exhibits high intraspecific and interspecific phenotypic variation. After a shared whole-genome triplication (WGT) event (Br-α, ~15.9 million years ago), differential lineage diversification and genomic changes contributed to an array of divergence in morphology, biochemistry, and physiology underlying photosynthesis-related traits. Here, the C3 species Hirschfeldia incana is studied as it displays high photosynthetic rates under high-light conditions. Our aim was to elucidate the evolution that gave rise to the genome of H. incana and its high-photosynthesis traits. We reconstructed a chromosome-level genome assembly for H. incana (Nijmegen, v2.0) using nanopore and chromosome conformation capture (Hi-C) technologies, with 409Mb in size and an N50 of 52Mb (a 10× improvement over the previously published scaffold-level v1.0 assembly). The updated assembly and annotation was subsequently employed to investigate the WGT history of H. incana in a comparative phylogenomic framework from the Brassiceae ancestral genomic blocks and related diploidized crops. Hirschfeldia incana (x=7) shares extensive genome collinearity with Raphanus sativus (x=9). These two species share some commonalities with Brassica rapa and B. oleracea (A genome, x=10 and C genome, x=9, respectively) and other similarities with B. nigra (B genome, x=8). Phylogenetic analysis revealed that H. incana and R. sativus form a monophyletic clade in between the Brassica A/C and B genomes. We postulate that H. incana and R. sativus genomes are results of hybridization or introgression of the Brassica A/C and B genome types. Our results might explain the discrepancy observed in published studies regarding phylogenetic placement of H. incana and R. sativus in relation to the "Triangle of U" species. Expression analysis of WGT retained gene copies revealed sub-genome expression divergence, likely due to neo- or sub-functionalization. Finally, we highlighted genes associated with physio-biochemical-anatomical adaptive changes observed in H. incana which likely facilitate its high-photosynthesis traits under high light. The improved H. incana genome assembly, annotation and results presented in this work will be a valuable resource for future research to unravel the genetic basis of its ability to maintain a high photosynthetic efficiency in high-light conditions and thereby improve photosynthesis for enhanced agricultural production.

Multiscale X-ray phase-contrast CT uncovers adaptive changes and compensatory mechanisms of circulatory pathways during acute liver injury

Intrahepatic circulation is essential for the repair of acute liver injury (ALI); however, very limited information is available concerning changes in the circulatory pathways during ALI. Therefore, multi-scale X-ray phase-contrast CT combined with three-dimensional (3D) visualization is used to quantitatively analyze the intrahepatic circulation pathway (including the hepatic vein, portal vein and hepatic sinusoid) in the mouse model via the intraperitoneal injection of carbon tetrachloride (CCl4) from acute injury to recovery. The results demonstrate that the liver still preserves some vessel-like channels accessed to the central vein when the injury causes the severe collapse of the hepatic sinusoids that cannot be observed in two-dimensional pathologic slices. Moreover, angiogenesis is observed in the terminal branches of the hepatic vein and portal vein. Additionally, we extend the two-dimensional primary lobule to a 3D model and find that the sinusoids in zone III have the most severe injury. The sinusoids in different zones also show changes in parameters such as density and mean diameter during the ALI. In conclusion, phase-contrast CT can reveal the intact vascular system within the liver lobes, thus providing critical information for studying the mechanisms involved in the evolution of circulatory structures from damage to repair.

The Involvement of GABA in the Modulation of the Rhythm of Electrical Activity in the Small Intestine during Food Deprivation.

In experiments on male Wistar rats, the stages of adaptive changes in the rhythm of periodic electrical activity in the small intestine during food deprivation were identified and the effect of GABA on changes of the rhythm under these conditions was assessed. It was found that on days 1-3 of food deprivation, the migrating myoelectric complex (MMC) in the small intestine is preserved, but the cycle becomes rarer. On days 4-6, MMC disappears, irregular and regular activity with no periods of quiescence is recorded. On days 7-9, predominantly irregular activity of the small intestine with short quiescence periods is observed. Enteral administration of GABA at different stages of food deprivation modulates electrical activity and preserves small intestinal MMC.

Exploring low- and high-order functional connectivity in chronic ankle instability through resting-state fMRI.

The functional connectivity (FC) has emerged as a valuable tool for comprehending the cerebral operational mechanism. Understanding the FC changes in patients with chronic ankle instability (CAI) helps reveal the underlying central nervous system mechanisms of the disease and provides clues for developing personalized treatment plans. To explore differences between low- and high-order FC in patients with CAI and healthy controls, as well as the correlation among the feature connections and clinical data. In our study, we recruited 40 patients with CAI and 42 healthy individuals who had not experienced ankle injuries. All participants underwent clinical assessments of ankle joints, collected the number of ankle sprains within the past 6 months, and performed resting-state functional magnetic resonance imaging (rs-fMRI) scans. Pearson correlation and matrix variate normal distribution (MVND) were used to construct low-order and high-order FC networks, respectively. Feature selections between groups were performed by two-sample t-tests, and a multi-kernel support vector machine (MK-SVM) was subsequently applied to combine the multiple connection patterns for the classification. Using leave-one-out cross-validation (LOOCV) to assess classification performance and identify the consensus connections contributing most to classification. FC was reduced in certain brain regions of CAI patients. More consensus connections were recognized in low-order FC network than in high-order FC network. The highest classification accuracy of 91.30% was achieved by combining three connection patterns. The most discriminating functional connections were primarily centered on the default mode network and spanned the visual network, sensorimotor network, ventral attention network, and central executive network. In addition, FC strength in the left cingulate and paracingulate gyrus (DCG.L) and right superior temporal gyrus (STG.R) was negatively correlated with the number of ankle sprains in the past 6 months in all FC networks (p<0.05). Abnormalities in connectivity in patients with CAI were observed in both low- and high-order FC networks. The adaptive changes in the brain related to CAI may extend beyond the sensorimotor networks, primarily involving higher-level default mode networks associated with attention. Moreover, the FC strength between DCG.L and STG.R may predict the risk of ankle re-sprains and help clinicians develop personalized treatment plans.

Physiological and Genetic Basis of High-Altitude Indigenous Animals' Adaptation to Hypoxic Environments.

Adaptation is one of the fundamental characteristics of life activities; humans and animals inhabiting high altitudes are well adapted to hypobaric hypoxic environments, and studies on the mechanisms of this adaptation emerged a hundred years ago. Based on these studies, this paper reviews the adaptive changes in hypoxia-sensitive tissues and organs, as well as at the molecular genetic level, such as pulmonary, cardiovascular, O2-consuming tissues, and the hemoglobin and HIF pathway, that occur in animals in response to the challenge of hypobaric hypoxia. High-altitude hypoxia adaptation may be due to the coordinated action of genetic variants in multiple genes and, as a result, adaptive changes in multiple tissues and organs at the physiological and biochemical levels. Unraveling their mechanisms of action can provide a reference for the prevention and treatment of multiple diseases caused by chronic hypoxia.

Assessment of Condylar Changes in Patients with Degenerative Joint Disease of the TMJ After Stabilizing Splint Therapy: A Retrospective CBCT Study.

Degenerative joint disease (DJD) of the TMJ can impact patients' quality of life and complicate orthodontic treatment. Stabilizing splints are a common conservative treatment in managing TMDs symptoms, although their long-term effects on condylar morphology are poorly studied. This study aimed to assess the impact of stabilizing splints on condyle morphology using cone-beam computed tomography (CBCT) in patients with various stages of DJD. Forty-two condyles with pre- (T1) and post- (T2) splint therapy scans were analyzed. CBCT scans were sectioned into sagittal and coronal slices for condyle classification and measurement. T1 and T2 CBCTs were superimposed before linear and area measurements at different poles. Our results indicate that condyles in the normal group remain unchanged after splint therapy. The majority of subjects in the degenerative groups remained in the same classification group: six out of fourteen degenerative-active patients became degenerative-repair, while three out of twenty-two degenerative-repair patients progressed to degenerative-active. There is no significant remodeling of condylar width pre- and post-splint therapy. On average, there is more bone deposition than reduction in condylar height after splint therapy, although individual variation exists. Stabilizing splints offer a low-risk intervention for managing DJD and may contribute to favorable adaptive changes in the condyles.

Stabilizing selection and adaptation shape cis and trans gene expression variation in C. elegans.

An outstanding question in the evolution of gene expression is the relative influence of neutral processes versus natural selection, including adaptive change driven by directional selection as well as stabilizing selection, which may include compensatory dynamics. These forces shape patterns of gene expression variation within and between species, including the regulatory mechanisms governing expression in cis and trans . In this study, we interrogate intraspecific gene expression variation among seven wild C. elegans strains, with varying degrees of genomic divergence from the reference strain N2, leveraging this system's unique advantages to comprehensively evaluate gene expression evolution. By capturing allele-specific and between-strain changes in expression, we characterize the regulatory architecture and inheritance mode of gene expression variation within C. elegans and assess their relationship to nucleotide diversity, genome evolutionary history, gene essentiality, and other biological factors. We conclude that stabilizing selection is a dominant influence in maintaining expression phenotypes within the species, and the discovery that genes with higher overall expression tend to exhibit fewer expression differences supports this conclusion, as do widespread instances of cis differences compensated in trans . Moreover, analyses of human expression data replicate our finding that higher expression genes have less variable expression. We also observe evidence for directional selection driving expression divergence, and that expression divergence accelerates with increasing genomic divergence. To provide community access to the data from this first analysis of allele-specific expression in C. elegans , we introduce an interactive web application, where users can submit gene-specific queries to view expression, regulatory pattern, inheritance mode, and other information: https://wildworm.biosci.gatech.edu/ase/ .

Phylogenomic analysis of the Lake Kronotskoe species flock of Dolly Varden charr reveals genetic and developmental signatures of sympatric radiation.

Recent adaptive radiations provide experimental opportunities to parse the relationship between genomic variation and the origins of distinct phenotypes. Sympatric radiations of the charr complex (genus Salvelinus) present a trove for phylogenetic analyses as charrs have repeatedly diversified into multiple morphs with distinct feeding specializations. However, charr species flocks normally comprise only two to three lineages. Dolly Varden charr inhabiting Lake Kronotskoe represent the most extensive radiation described for the genus, containing at least seven lineages, each with defining morphological and ecological traits. Here, we perform the first genome-wide analysis of this species flock to parse the foundations of adaptive change. Our data support distinct, reproductively isolated lineages within the clade. We find that changes in genes associated with thyroid signaling and craniofacial development provided a foundational shift in evolution to the lake. The thyroid axis is further implicated in subsequent lineage partitioning events. These results delineate a genetic scenario for the diversification of specialized lineages and highlight a common axis of change biasing the generation of specific forms during adaptive radiation.

Temperature-responsive solvation enabled by dipole-dipole interactions towards wide-temperature sodium-ion batteries

Rechargeable batteries with high durability over wide temperature is needed in aerospace and submarine fields. Unfortunately, Current battery technologies suffer from limited operating temperatures due to the rapid performance decay at extreme temperatures. A major challenge for wide-temperature electrolyte design lies in restricting the parasitic reactions at elevated temperatures while improving the reaction kinetics at low temperatures. Here, we demonstrate a temperature-adaptive electrolyte design by regulating the dipole-dipole interactions at various temperatures to simultaneously address the issues at both elevated and subzero temperatures. This approach prevents electrolyte degradation while endowing it with the ability to undergo adaptive changes as temperature varies. Such electrolyte favors to form solvation structure with high thermal stability with rising temperatures and transits to one that prevents salt precipitation at lower temperatures. This ensures stably within a wide temperature range of ‒60 −55 °C. This temperature-adaptive electrolyte opens an avenue for wide-temperature electrolyte design, highlighting the significance of dipole-dipole interactions in regulating solvation structures.

Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China

Leaf-trait variation has traditionally been focused on both within and among species along environmental gradients, while leaf age has received less attention. By measuring leaf morphological, stomatal, and stoichiometric traits of 40 coexisting woody species in temperate forest in northern China, we analyzed their variation pattern and the correlations among different plant life forms and leaf age. We found that leaf age has significant effects on leaf functional traits. The young leaves of both shrub and tree species revealed a lower stoma density (SD) and a higher stoma length (SL), stoma width (SW), and leaf N content (LNC) than mature leaves. Shrub species have a higher SLA and SD than tree species for both young and mature leaves. The traits of young leaves generally revealed a higher variation than those of mature leaves. Although correlations between traits are similar between young leaves and mature leaves, the slopes of the SLA–SD and SD–LNC relationships were significantly affected by leaf age. These findings elucidate the adaptive changes of leaf traits during leaf maturation and underscore the trade-off between stomatal safety and efficiency, as well as the trade-off between leaf hydraulic and economic traits in temperate woody species during leaf development. We conclude that variation in leaf traits with age may play a potentially important role in understanding the ecological function of woody species in temperate forests.

A fault diagnosis method for bearings and gears in rotating machinery based on data fusion and transfer learning

Abstract Rotating machinery is a crucial component of industrial equipment, and the fault diagnosis of bearings and gears, as vital elements of rotating machinery, is essential since they often fail under harsh working conditions, leading to significant property losses and serious personal safety problems. However, fault data for gears and bearings are often sparse in actual condition, and it is a challenge to ensure the reliability and stability of fault diagnosis results by extracting the features of a single data. To solve the above problems, this paper proposes a fault diagnosis method that combines Transfer Learning and data fusion techniques. Firstly, in this method, two kinds of fault signals are transformed into Gramian Angular Difference Fields and Recurrence Plot. Next, a U-shaped feature fusion dual discriminator generative adversarial network is used to fuse two-dimensional images from multiple sensor data. Its feature fusion module deeply integrates the features of the two images, thereby solving the impact of single data on the reliability and stability of fault diagnosis. Moreover, open-source datasets are used for Transfer Learning training to tackle the small sample problem. Finally, a decision-level information fusion classifier, the Dual-Branch Dempster-Shafer Classifier (DB-DSC), classifies the fused images. This classifier incorporates an improved soft threshold function and D-S evidence theory to achieve adaptive gradient changes and improve the robustness and accuracy of classification results. The experimental results show the effectiveness and stability of the proposed method, and the generated images get high score in several metrics. The average classification accuracy of the classification network reaches 93% and 92.5% on the two datasets, Therefore, the proposed method exhibits strong fault diagnosis capabilities under the small sample conditions of bearings and gears.

Environmental Driving of Adaptation Mechanism on Rumen Microorganisms of Sheep Based on Metagenomics and Metabolomics Data Analysis.

Natural or artificial selection causes animals to adapt to their environment. The adaptive changes generated by the rumen population and metabolism form the basis of ruminant evolution. In particular, the adaptive drive for environmental adaptation reflects the high-quality traits of sheep that have migrated from other places or have been distant from their origins for a long time. The Hu sheep is the most representative sheep breed in the humid and low-altitude environments (Tai Lake region) in East Asia and has been widely introduced into the arid and high-altitude environments (Tibetan Plateau and Hotan region), resulting in environmental adaptive changes in the Hu sheep. In this study, a joint analysis of the rumen microbial metagenome and metabolome was conducted on Hu sheep from different regions (area of origin and area of introduction) with the objective of investigating the quality traits of Hu sheep and identifying microorganisms that influence the adaptive drive of ruminants. The results demonstrated that the growth performance of Hu sheep was altered due to changes in rumen tissue and metabolism following their introduction to the arid area at relatively high altitude. Metagenomic and metabolomic analyses (five ramsper area) revealed that 3580 different microorganisms and 732 different metabolites were identified in the rumen fluid of arid sheep. Among these, the representative upregulated metabolites were 4,6-isocanedione, methanesulfonic acid and N2-succinyl-L-arginine, while the dominant microorganism was Prevotella ruminicola. The downregulated metabolites were identified as campesterol, teprenone and dihydroclavaminic acid, while the disadvantaged microorganisms were Dialister_succinatiphilus, Prevotella_sp._AGR2160, Prevotella_multisaccharivorax and Selenomonas_bovis. The results of the Pearson analysis indicated that the rumen microbiota and metabolite content of sheep were significantly altered and highly correlated following their relocation from a humid lowland to an arid upland. In particular, the observed changes in rumen microorganisms led to an acceleration of body metabolism, rendering sheep highly adaptable to environmental stress. Prevotella_ruminicola was identified as playing an important role in this process. These findings provide insights into the environmental adaptation mechanisms of sheep.

Supporting risk management through cyberspace: An adaptive network model simulating AI coach effects by inducing adherence to guidelines in neonatal medical protocols

In this article, it is shown how second-order adaptive agent-based network models can be used to support a medical team in healthcare institutions to adhere to specific Neonatal Hypoglycemia and Neonatal Hyperbilirubinemia treatment guidelines through the integration of an Artificial Intelligence (AI) Virtual Coach. The proposed AI Coach is designed to provide timely interventions and correct deviations when lapses in the health care practitioner’s internal mental model occur. Through simulating three different scenarios, the internal dynamics of these mental models, adaptive changes of these mental models (learning and forgetting), and the interaction between health care practitioners and the world is shown when: (1) There is perfect adherence to guidelines, (2) There is imperfect adherence to guidelines and (3) There is both perfect and imperfect adherence to guidelines alongside interventions of the AI Coach in the latter case.

Understanding of Plant Salt Tolerance Mechanisms and Application to Molecular Breeding.

Soil salinization is a widespread hindrance that endangers agricultural production and ecological security. High salt concentrations in saline soils are primarily caused by osmotic stress, ionic toxicity and oxidative stress, which have a negative impact on plant growth and development. In order to withstand salt stress, plants have developed a series of complicated physiological and molecular mechanisms, encompassing adaptive changes in the structure and function of various plant organs, as well as the intricate signal transduction networks enabling plants to survive in high-salinity environments. This review summarizes the recent advances in salt perception under different tissues, physiological responses and signaling regulations of plant tolerance to salt stress. We also examine the current knowledge of strategies for breeding salt-tolerant plants, including the applications of omics technologies and transgenic approaches, aiming to provide the basis for the cultivation of salt-tolerant crops through molecular breeding. Finally, future research on the application of wild germplasm resources and muti-omics technologies to discover new tolerant genes as well as investigation of crosstalk among plant hormone signaling pathways to uncover plant salt tolerance mechanisms are also discussed in this review.

EEG microstate transition cost correlates with task demands.

The ability to solve complex tasks relies on the adaptive changes occurring in the spatio-temporal organization of brain activity under different conditions. Altered flexibility in these dynamics can lead to impaired cognitive performance, manifesting for instance as difficulties in attention regulation, distraction inhibition, and behavioral adaptation. Such impairments result in decreased efficiency and increased effort in accomplishing goal-directed tasks. Therefore, developing quantitative measures that can directly assess the effort involved in these transitions using neural data is of paramount importance. In this study, we propose a framework to associate cognitive effort during the performance of tasks with electroencephalography (EEG) activation patterns. The methodology relies on the identification of discrete dynamical states (EEG microstates) and optimal transport theory. To validate the effectiveness of this framework, we apply it to a dataset collected during a spatial version of the Stroop task, a cognitive test in which participants respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. The Stroop task is a cognitive test where participants must respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. Our findings reveal an increased cost linked to cognitive effort, thus confirming the framework's effectiveness in capturing and quantifying cognitive transitions. By utilizing a fully data-driven method, this research opens up fresh perspectives for physiologically describing cognitive effort within the brain.

Ecological adaptations of amphibians to environmental changes along an altitudinal gradient (Case Study: Bufo gargarizans) from phenotypic and genetic perspectives

BackgroundOrganisms have evolved a range of phenotypic and genetic adaptations to live in different environments along an altitudinal gradient. Herein, we studied the widely distributed Chinese toad, Bufo gargarizans, as a model and used an integrated phenotype-genotype approach to assess adaptations to different altitudinal environments.ResultsComparison of populations from four altitudes (50 m, 1200 m, 2300 m, and 3400 m) showed more effective defenses among high-altitude toads. These included thickened epidermis, more epidermal capillaries and granular glands, greater gland size in skin, and higher antioxidant enzyme activities in plasma. High-altitude toads also showed increased erythrocytes and hematocrit and elevated hemoglobin concentration, potentially improving oxygen delivery. Elevated altitude led to a metabolic shift from aerobic to anaerobic metabolism, and high-altitude populations favored carbohydrates over fatty acids to fuel for energy metabolism. Differentially expressed genes were associated with adaptive phenotypic changes. For instance, expression of genes associated with fatty acid metabolism showed greater suppression at high altitude (3400 m), consistent with decreased flux of β-hydroxybutyric acid and lower free fatty acids levels. Moreover, down-regulation of genes involved in carbon metabolism processes at high altitude (3400 m) were coincident with reduced TCA cycle flux. These results suggest that high-altitude toads adopt a metabolic suppression strategy for survival under harsh environmental conditions. Moreover, the hypoxia-inducible factor signaling cascade was activated at high altitude.ConclusionsCollectively, these results advance our comprehension of adaptation to high-altitude environments by revealing physiological and genetic mechanisms at work in Chinese toads living along altitudinal gradients.