Biology subjects

Hao, Z.

Publications and source records attributed to Hao, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Urban planning leaves an audible legacy in a megacity's bird soundscape

Cities are planned for people, yet planning also determines where wildlife persists and where residents hear it. How can this acoustic footprint guide planning and monitoring? We combined AI-powered passive acoustic monitoring at 31 stations with detection-corrected models and spatial validation to map Asian Koel activity across Shenzhen. Koel acoustic opportunity declined with tree and built cover and increased with starling and myna opportunity; host information improved prediction at unmonitored sites. Weekly opportunity expanded in spring and varied across the city; sampled-minute exposure concentrated around dawn. Supported predictions intersected planning-sensitive places, while 51.5% of the city grid remained a monitoring gap. We translated these boundaries into monitoring priorities for underrepresented environments and uncertain spring predictions. This reproducible workflow reveals the acoustic imprint of the present-day urban landscape and connects ecological diagnosis, prediction boundaries and adaptive monitoring to inform urban coexistence.

ecology↗

bioRxiv2026

Evidence Scaling for Zero-Shot Protein Reasoning with Large Language Models

Large language models (LLMs) show emerging zero-shot capability for protein variant prediction, yet still lag behind specialized protein models. We ask whether this gap can be reduced by scaling access to biological evidence rather than adapting model parameters. We introduce BioEvidence, a training-free and model-agnostic interface that converts structural and evolutionary information from standard biological tools into compact evidence for frozen LLMs. On the ProteinGym benchmark, we observe evidence scaling: performance improves as evidence becomes richer. Structural and evolutionary evidence each improve performance, and combining them yields further gains, while mismatching the same evidence to the wrong variants degrades performance below the no-evidence baseline. Notably, BioEvidence enables zero-shot ranking to reach strong specialized protein predictors on matched evaluations, and the improvement persists on post-cutoff data released after the model's knowledge cutoff. Evidence also interacts with conventional scaling: for GPT-5.6 Sol, evidence at low reasoning effort outperforms the no-evidence condition at medium effort, while a six-model analysis associates stronger no-evidence performance with larger margins over evolutionary rank fusion. These results identify external evidence as a complementary scaling axis for scientific prediction alongside model capability and inference effort.

bioinformatics↗

bioRxiv2026

π-MNovo improves de novo peptide sequencing through microbial-domain adaptation and evidence-guided candidate selection

The high taxonomic and strain-level diversity of microbial communities makes it difficult for reference databases to fully represent the protein sequences present in metaproteomic samples, limiting database-dependent peptide identification. De novo peptide sequencing can recover peptide sequences directly from tandem mass spectra without relying on reference databases, providing complementary peptide evidence for metaproteomics. However, most existing de novo sequencing models were developed largely from non-microbial proteomic data and lack specific adaptation to microbial spectra. Here, we established a dedicated microbial spectral resource comprising more than 10 million annotated high-quality tandem mass spectra from 72 cultured microbial isolates, with peptide digests from each isolate separated into five high-pH reversed-phase fractions to increase the opportunity for deeper and more diverse peptide sampling. Using this resource, we developed {pi}-MNovo, which combines adaptation to microbial spectra with evidence-guided candidate selection to improve full-length peptide sequencing precision. On a seven-species external benchmark, {pi}-MNovo achieved 66.30% complete-peptide recall under the same residue-mass-based complete-peptide matching criterion applied to all models, exceeding four published models by 6.9-21.7% in relative recall, with consistent gains across species and peptide-length groups. In two independent metaproteomic datasets, {pi}-MNovo increased reference-supported taxonomic coverage, while synthetic-community analysis recapitulated the designed abundance ranking. From pFind-unidentified spectra, {pi}-MNovo recovered 1,587 pFind-unreported, reference-matched peptides that passed spectrum-evidence filtering. These results show that {pi}-MNovo expands recoverable peptide evidence and enhances the utility of de novo sequencing for metaproteomic analysis.

bioinformatics↗

bioRxiv2026

Accelerated lung evolution associated with end-Permian and end-Triassic mass extinctions

The end-Permian and end-Triassic mass extinctions, driven by massive catastrophic volcanism and prolonged hypoxia, fundamentally reshaped life on Earth. However, the genomic impacts of these two biodiversity crises on living organisms remain largely unknown. Here, we performed a genome-wide screening to identify accelerated evolved regions in the ancestral lineage of mammals that survived both extinction events. Nearly all (20/21) of these accelerated regions were located in protein-coding sequences, and 81% (17/21) were found to be associated with lung function. We further extended our analysis to three additional vertebrate lineages that experienced either one or both of the mass extinctions. Similar genomic signatures, involving accelerated evolution of lung-related genes, were also observed in these non-mammalian lineages. Collectively, these findings suggest that adaptation of lung-related genes to prolonged hypoxia may have occurred during the two mass extinction events, potentially driving a second evolutionary stage of the lung following the vertebrate transition to land.

evolutionary biology↗

bioRxiv2026

Enkephalin constrains fear learning via volume transmission to the lateral amygdala

Fear learning involves the formation of associations between cues and aversive outcomes, a process that must be tightly regulated to prevent excessive or generalised fear. Dopamine release in the lateral amygdala (LA) drives fear acquisition, whereas endogenous opioids constrain it. However, whether opioids are dynamically released within the amygdala circuits during learning, and how they exert this control remain unclear. Here we show that met-enkephalin is locally released within the amygdala during auditory fear conditioning, with signals shifting from the aversive outcome to its predictive cue as learning progresses. The amygdalo-striatal transition zone (ASt), is the principal source of this enkephalin, released from medium spiny neurons receiving strong auditory thalamic input. This enkephalin spreads from the ASt to the LA via volume transmission. Selective knockdown in the ASt abolished opioid signals and enhanced fear learning, demonstrating that this diffuse signal constrains fear memory formation. We further show that enkephalin suppresses dopamine release in both the ASt and LA via {micro}-opioid receptors, identifying the ASt as a neuromodulator hub coordinating opioid and dopaminergic signalling across amygdala fear circuits. Although demonstrated here for auditory fear learning, the ASt receives multimodal sensory input, suggesting a broader mechanism through which sensory experience recruits enkephalin release to gate associative learning

neuroscience↗

bioRxiv2026

Vegetation change and functional composition shifts in southwestern China during late MIS 3 to LGM

The climatic transition from Marine Isotope Stage 3 (MIS3) to the Last Glacial Maximum (LGM) had caused widespread vegetation change. Despite the dynamic equilibrium between vegetation and climate, the specific role of functional composition in vegetations response to climate change was inadequately understood. Here, we analyzed the long-term trajectories of palynological diversity, vegetation coverage and community-weighted-mean (CWM) functional traits based on EH22 pollen record (35-18 cal ka BP) from Erhai Lake, southwestern China. The results disclosed a vegetation transition from temperate deciduous broadleaf forest dominance in late MIS3 to cold coniferous and mixed broadleaved/coniferous forests in LGM. This vegetation dynamic involved functional composition shifts from competitive-driven functional convergence to partial recovery via niche differentiation during the late MIS3, and finally to a low-diversity but functional differentiation state through trait complementarity and diversification strategies during the cold LGM. Our results likely support a function-mediated climate filtering process whereby climate change regulated long-term vegetation dynamics during the MIS3-LGM transition primarily through shifts in CWM functional composition. These findings underscore the potential of pollen-based trait approaches to reconstruct ecosystem properties and advance our understanding of ecosystem change over decadal to millennial time-scales.

ecology↗

bioRxiv2026

Rapid vegetation reorganization in Hengduan Mountains driven by high climatic oscillations

The accelerating global climate change has been triggering large-scale vegetation reorganizations, yet our understanding of how mountain ecosystems respond to rapid climatic oscillations is critically constrained. Here, we present a high-resolution palynological record from Erhai Lake, southwestern China, revealing eight episodes of rapid vegetation reorganizations in the Hengduan Mountains (HMs) over the past 35,200 years. These reorganizations closely tracked the rhythms of rapid climate oscillations, particularly during the Last Glacial Maximum and the Last Deglacial Period. We find that while the timing of rapid vegetation reorganizations were synchronous with Atlantic Meridional Overturning Circulation (AMOC) anomalies that modulated global climate variability, the magnitude of these reorganizations did not exhibit a linear correlation with AMOC strength; instead, they were governed by local heat and moisture availability mediated through teleconnections. This demonstrates a strong natural regulatory capacity of mountain vegetation in HMs, enabling resilience to intense climatic fluctuations. However, when using the Erhai record as a benchmark, we project that rapid reorganizations under the high-emission pathway (SSP585) will likely surpass the intensities observed during historical events. These findings reveal the high climatic sensitivity and strong natural regulatory capacity of mountain ecosystems, highlighting the critical necessity of climate mitigation actions and nature-based solutions to safeguard subalpine and alpine biodiversity against unprecedented future climate change.

ecology↗

bioRxiv2026

EZH1/2 inhibition improves immunotherapy response through MHC Class II de-repression and neutrophil reprogramming

Squamous cell carcinoma of the lung is a difficult-to-treat cancer with high prevalence in the US, and particularly in Kentucky. Here, we sought to test if the EZH1/2 inhibitor valemetostat improves anti-PD1 responses in squamous cell lung cancer models, and to develop ex vivo models to test immunotherapy drug combinations. We found that valemetostat augmented anti-tumor responses to anti-PD1 therapy, led to up-regulation of tumor cell specific Major Histocompatibility Complex Class II (MHC Class II), and drove systemic neutrophil maturation. Likewise, Ezh2 knock-out mice produced neutrophils that were more apoptotic, less migratory, and less able to produce extracellular nets, but had similar ability to kill bacteria as Ezh2-WT neutrophils. To test tumor responses to differing neutrophil populations, we engineered three-dimensional air-liquid interface cultures with tumoroids, lung mesenchymal cells, and T cells, with and without bone marrow containing neutrophils and myeloid progenitors from distinct donors. Bone marrow from tumor-naive or mice with actively growing untreated tumors boosted tumoroid growth, while bone marrow from spontaneously tumor-rejected or mice with tumors treated with valemetostat was anti-tumor. MHC Class II blockade lowered the ability of bone marrow to boost tumor growth, and reduced the ability of valemetostat with anti-PD1 to reduce tumoroid growth. Patient samples revealed a strong negative correlation between EZH2 and MHC Class II, suggesting that targeting EZH2 activity could lead to marked increase in MHC Class II and improve treatment responses in lung squamous cell carcinomas.

cancer biology↗

bioRxiv2026

Gut Microbiota Dysbiosis Drives Myocardial Hypertrophy Through GBP2b/GBP1-Mediated Immune Reprogramming and Exosomal Signaling in Chronic Colitis

BACKGROUNDPatients with inflammatory bowel disease (IBD) are at increased risk of cardiovascular disease, yet the mechanisms linking chronic intestinal inflammation to cardiac dysfunction remain poorly understood. IBD is characterized by profound gut microbiota dysbiosis, which we hypothesize drives systemic immune dysregulation and contributes to cardiac dysfunction. METHODSA chronic colitis mouse model was used to assess gut microbiota dysbiosis, systemic immune cell metabolism, and cardiac remodeling. Cardiac outcomes were evaluated by echocardiography, histology, and molecular analyses. Mechanisms were examined using fecal microbiota transplantation, immune cell depletion, exosome transfer, bone marrow chimeras, RNA-seq, co-immunoprecipitation, confocal microscopy, and siRNA-mediated gene silencing. RESULTSChronic DSS colitis induced cardiac dysfunction, hypertrophy, and fibrosis in mice. These changes were accompanied by sustained gut microbiota dysbiosis, metabolic reprogramming, and mitochondrial dysfunction in circulating immune cells. Fecal microbiota transfer experiments demonstrated that colitis-associated microbiota were sufficient to reprogram systemic immune cells and promote cardiac dysfunction. Immune cell depletion studies identified macrophages as key mediators of colitis-associated cardiac injury. Colitis increased systemic lipopolysaccharide (LPS) translocation, bone marrow chimera experiments demonstrated that hematopoietic TLR4 signaling was required for immune cell metabolic remodeling and cardiac dysfunction during chronic colitis. Transcriptomic analysis identified guanylate-binding protein 2b (GBP2b/GBP1, hereafter referred to as GBP1) as a key downstream effector of LPS-TLR4 signaling. Upon LPS stimulation, GBP1 localized to mitochondria, where it interacted with DRP1 and FIS1 to promote mitochondrial fission, oxidative stress, and enhanced immune cell migration into the heart. In addition, GBP1 was secreted via exosomes, which were taken up by cardiomyocytes and contributed to hypertrophic remodeling, and cardiac dysfunction. CONCLUSIONSThese findings establish the LPS-TLR4-GBP1 axis as a key driver of colitis-associated cardiovascular dysfunction and highlight this pathway as a promising therapeutic target for reducing cardiovascular risk in patients with IBD. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIPatients with inflammatory bowel disease have an increased risk of cardiovascular dysfunction that cannot be fully explained by traditional cardiovascular risk factors. C_LIO_LIGut microbiota dysbiosis and chronic innate immune activation are hallmarks of inflammatory bowel disease, but their direct contribution to cardiac remodeling remains unclear. C_LI What New Information Does This Article Contribute?O_LIChronic colitis-associated gut microbiota dysbiosis induces systemic immune cell metabolic and mitochondrial reprogramming that is sufficient to drive cardiomyocyte hypertrophy and cardiac dysfunction. C_LIO_LIHematopoietic Toll-like receptor 4 signaling links colitis associated gut microbiota to immune metabolic dysfunction and cardiac impairment, establishing a causal gut-immune-heart axis. C_LIO_LIGuanylate-binding protein 2b (GBP2b/GBP1) is identified as a critical downstream effector that promotes mitochondrial fission, oxidative stress, immune cell cardiac infiltration, and exosome-mediated cardiac remodeling. C_LI

pathology↗

bioRxiv2026

A nucleolar stress gene signature for quantitative scoring across multi-omics contexts

The nucleolus is essential for ribosome biogenesis and cellular homeostasis, and its dysfunction can induce nucleolar stress, which has been implicated in cancer and other diseases. However, nucleolar stress is commonly inferred from morphological alterations or a limited set of functional assays, and quantitative approaches based on gene expression profiles remain lacking. Here, we integrate literature curation with multi-dataset screening to define a nucleolar stress gene signature and develop a nucleolar stress score (NuS) that is applicable across bulk transcriptomics, single-cell transcriptomics, proteomics, and spatial transcriptomics. Using this framework, we show in colorectal cancer models that oxaliplatin induces nucleolar stress, suppresses nascent rRNA synthesis, and activates p53 signalling, whereas these responses are attenuated in oxaliplatin-resistant cells. In combination with a ribosome biogenesis activity score (RiboSis), NuS captures related yet distinct dimensions of nucleolar function and stratifies tumors into functional states associated with distinct clinical outcomes. Furthermore, NuS-based analysis of perturbational transcriptomes enables prioritization of compounds with putative nucleolar stress-inducing activity. Collectively, this study establishes a quantitative framework for evaluating nucleolar stress and illustrates its applications in disease stratification and drug mechanism discovery.

cell biology↗

bioRxiv2026

CEACAM5/6+ Tumor Cells and IL-1β+ Macrophages Drive Resistance to Chemo-immunotherapy in Gastric Cancer

Chemo-immunotherapy is a first-line treatment for advanced gastric cancer, yet response rates remain limited and resistance mechanisms are poorly defined. Here we generate a single-cell atlas of 542,121 cells from 35 patients treated with anti-PD-1 plus chemotherapy, profiling pre- and post-treatment tumors linked to clinical response. Integrating spatial transcriptomics, immunohistochemistry, and bulk RNA sequencing, we identify two temporally distinct resistance programs. Intrinsic resistance in pre-treatment non-responders is marked by enrichment of CEACAM5/6 tumor cells that form immune-excluded spatial niches characterized by macrophage recruitment and CD8 T-cell exhaustion. Acquired resistance in post-treatment non-responders is driven by expansion of IL-1{beta} macrophages, which induces coordinated NF-{kappa}B activation across tumor and stromal compartments, promoting PD-L1 upregulation, epithelial-mesenchymal transition, and chronic inflammation. These findings delineate an evolutionary trajectory of resistance and nominate CEACAM5/6 and IL-1{beta} as predictive biomarkers and therapeutic targets to improve anti-PD-1-based combination strategies.

cancer biology↗

bioRxiv2025

Plant litter chemistry and associated changes in microbial decomposition under drought

Drought has consequences for microbial decomposition rates, including indirect effects through changes in plant litter chemistry. Here we studied the impact of a decade-long drought on plant litter chemistry and microbial decomposition traits in a semi-arid ecosystem during an 18-month litter bag experiment. We investigated litter sourced from four conditions: grass and shrub vegetation under ambient and reduced precipitation. We hypothesized that litter chemistry drives microbial decomposition capabilities and enzyme activity, either due to vegetation differences or drought effects on litter chemistry. Fourier Transform Infrared Spectroscopy was used to characterize litter chemistry; we found that carbohydrate-rich grass litter decomposed faster than more recalcitrant shrub litter which was richer in lignin and lipids. There were significant changes in litter chemistry under drought but no increase in lignin fraction suggesting that drought does not make litter more recalcitrant. Metagenomics-derived decomposition genes and extracellular enzyme activity were higher in grass litter; patterns related to differences in substrate supply. Genes linked to lignin depolymerization decreased in abundance under drought. However, most decomposition genes and enzyme activities were not significantly affected by drought thereby maintaining decomposition rates. Microbial community succession with higher abundance of fungi at early and bacteria at later stages of decomposition corresponded with genes for fungal and bacterial necromass recycling along with protein accumulation over time. We demonstrate minimal litter chemistry-mediated effects of drought but show significant changes in community composition and their decomposition capabilities over time highlighting that complex microbial-chemical interactions under climate change can influence ecosystem-scale processes. ImportanceClimate change is causing more severe and frequent droughts in semi-arid ecosystems, affecting soil microbes breaking down plant litter. Our research focusses on understanding the less studied pathway of drought impact on microbes via changes in plant litter chemistry. Drought can alter the plant litter chemistry, by changing the composition and physiology of plants, which can alter microbial decomposition and ecosystem-level carbon cycling. We investigated litter decomposition traits of microbial communities in grass and shrub litter under long-term drought. There were significant changes in litter chemistry under drought but no increase in lignin fraction. Despite this, microbial communities maintained their decomposition capabilities under drought highlighting ability of microbes to adapt and continue functioning. We also demonstrate unique microbial community succession patterns and dead biomass recycling which can have implications for carbon cycling rates in the ecosystem. This study sheds light on the complex microbial interactions that affect ecosystem functioning under climate change.

ecology↗

bioRxiv2025

Transgenerational polarity axis inheritance during Ceratopteris embryogenesis

For sexually reproducing organisms to pass on their genetic information, progeny must successfully establish. Various life history strategies have evolved, using either dispersal of large numbers of progeny or intensive nurturing of a few. Most plants use the former strategy, but ferns generate a single embryo in the exact same location as the mother, and it is unknown how progeny success is promoted, or how embryogenesis is adapted. By studying Ceratopteris richardii embryogenesis, we find that maternal tissues guide orientation of the early embryo body axis, thus aligning its root pole towards the homologous maternal rhizoids. We find that axis polarity inheritance is mediated by maternal tissue mechanical patterns, and thus identify a robust mechanism for progeny establishment as a nurturing strategy in plants.

plant biology↗

bioRxiv2025

Structural and Functional Insights into GGCX-FIX Interaction: Implications for Vitamin K-Dependent Bleeding Disorders

Gamma-carboxylation, catalyzed by {gamma}-glutamyl carboxylase (GGCX), is a critical post-translational modification essential for the biological activity of vitamin K-dependent proteins (VKDPs). Mutations in GGCX, depending on their specific location, result in vitamin K-dependent coagulation factor deficiency type 1 (VKCFD1), which encompasses a broad spectrum of clinical manifestations ranging from mild to severe, including bleeding disorders, osteoporosis, and vascular calcification. The limited knowledge of GGCXs structure and functional regions hinders our understanding of the consequences of GGCX mutations and the treatment for VKCFD1. This study aimed to identify key functional regions of GGCX and their interactions with VKDPs to better elucidate the molecular mechanisms underlying these diverse clinical symptoms. Using AlphaFold 3 and molecular dynamics simulations, we developed a complex binding model of GGCX, FIX, and reduced vitamin K, which revealed critical regions and residues involved in their interaction. Site-directed mutagenesis and cell-based assays further validated the model, confirming that multisite and regional cooperative binding of FIX to GGCX plays a key role in modulating {gamma}-carboxylation efficiency. Additionally, novel residues (I296, M303, M401, M402) were identified as essential for GGCXs dual enzymatic activities: carboxylation and vitamin K epoxidation. We further demonstrated that the spatial proximity of these active sites supports the hypothesis that GGCXs carboxylation and vitamin K epoxidation centers are interconnected, ensuring the efficient coupling of these processes. Our GGCX-FIX binding and carboxylation model aligns with known pathogenic GGCX mutations, providing valuable insights into the molecular basis of coagulation disorders caused by GGCX mutants.

pathology↗

bioRxiv2025

Ancient human extinction risk: Implications from high-precision computation and fossil evidence

Reconstructing ancient population size history is essential for understanding the evolutionary origin of Homo sapiens. Using the fast infinitesimal time coalescent process (FitCoal), which precisely computes the expected site frequency spectrum (SFS), we revisited the debated population bottleneck that occurred approximately 930 thousand years ago. By benchmarking FitCoal against mushi and ten billion coalescent simulations, we demonstrate that FitCoal achieves both superior speed and accuracy in expected SFS estimation. Analyses of simulated datasets confirmed that FitCoal reliably recovered the bottleneck, whereas mushi failed under identical conditions. Independent fossil and paleoclimate evidence further corroborates the timing and evolutionary impact of this bottleneck, linking it to hominin dispersals, speciation events, and a subsequent increase in brain size. These findings refine the demographic history of Homo during the Pleistocene and highlight the importance of high-precision SFS computation for revealing critical evolutionary transitions that shaped modern human ancestry.

evolutionary biology↗

bioRxiv2024

Rapid production of modified cattle and sheep from spermatid-like stem cells

Genome-modified ruminants, such as cattle and sheep, are important germplasm for agricultural applications. Haploid androgenetic stem cells (haSCs) can support the full-term development of embryos upon intracytoplasmic haSCs injection (iCHI) into intact oocytes. Thus, haSCs are invaluable resources for studying economic traits and significantly impact livestock breeding; however, ruminant haSCs have yet to be obtained. Here, we report the derivation of cattle and sheep haSCs using a recombinant FACE medium. These cells display characteristics of formative-state pluripotency and can differentiate into three germ layers, both in vitro and in vivo. Interestingly, the ectopic expression of protamine in haSCs converts their nuclei into a spermatid-like structure and synergistic enhancement of full-term development of iCHI embryos, named as Pro-iCHI approach. Furthermore, gene-modified cattle and sheep can be efficiently produced through the combinatorial use of the CRISPR and Pro-iCHI approach. Overall, Pro-iCHI provides an easy-to-manipulate agrobiotechnology tool for rapidly producing genetically modified livestock.

bioengineering↗

bioRxiv2024

The kinematics and aerodynamics of hinged wing of honeybees during takeoff

In this study, we utilize a high-speed camera array to meticulously capture the intricate wing kinematics of honeybees during free voluntary takeoffs. This allows us to investigate the variation in kinematic parameters over time. According to the variation of Euler angles, the takeoff process can be categorized into three stages: initial, adjusting, and stable. Our analysis reveals that honeybees typically execute at least 15 wingbeats before taking off, with wing stroke amplitudes exceeding 100 degrees and wingbeat frequencies ranging from 180 to 260 Hz. Significantly, the hinged wing mechanism, connecting the forewing and hindwing via hamuli, undergoes considerable chordwise deformation during this process, with the angle between the fore- and hind-wings surpassing 50 degrees. Notably, the forewing and hindwing maintain a positive camber throughout the wingbeat cycle during takeoff, contributing to the enhanced thrust generation instead of lift, comparing to the flat wings. The positive camber can be passively formed at beginning and ending of each half stroke, but should be actively maintained around middle half-stroke.This study provides valuable insights for aeronautical engineers in the design of flapping wing micro air vehicles, specifically in the effective implementation of hinged wings inspired by the wing motion of honeybees.

biophysics↗

bioRxiv2024

Threshold-Free Network-Oriented Statistics in Neuroscience

Network neuroscience has emerged as an indispensable tool for studying brain structure and function. Currently, the network-based statistic (NBS) procedure is widely used for dealing with massive multiple testing/comparison problems in brain networks. However, the NBS requires choosing a hard cluster-forming threshold, lacking objective rules. A powerful and flexible statistical framework is urgently needed with growing interest in finer-grained network explorations across modalities and scales. Here, we introduce a permutation-based framework--"Threshold-Free Network-Oriented Statistics" (TFNOS). It integrates two "threshold-free" pathways: traversing all cluster-forming thresholds (TT) and using predefined clusters (PC). The TT procedure, building upon the threshold-free network-based statistics, requires setting additional parameters. The PC procedures comprise six variants given the degree of freedom in pooling data, null distribution construction, and controlled error rate. Using numerical simulations, we evaluated the performance of the TT procedure under 600 parameter combinations, then benchmarked TFNOS procedures and baselines across different topologies of effects, sample sizes, and effect sizes, and finally provided illustrative examples with real data. We offer recommended parameter values that allow the TT procedure to stably maintain leading power, while empirically controlling the false discovery rate (FDR) beyond only weakly controlling the familywise error rate (FWER). Notably, the relevant parameters commonly employed in the field appear overly liberal. Furthermore, for the PC procedures, FDR-controlling variants showed improved power compared to FWER-controlling variants, and some of them are simple but do not compromise power. The nonparametric PC procedures allow the selection of any test statistics considered appropriate. Overall, the TFNOS is a generalized framework for inference on edges/nodes of undirected/directed brain networks. We provide empirical and principled criteria for selecting appropriate procedures and may enhance the reproducibility and sensitivity of future brain research.

neuroscience↗