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Atopic dermatitis (AD) is a chronic inflammatory skin disease, driven by barrier and immune dysregulation, which causes significant impairment in quality of life. The introduction of biologics and oral small molecules has substantially improved treatment outcomes. However, achieving complete and durable clinical clearance for most patients remains challenging, and concerns related to long-term safety and healthcare burden persist as key unmet needs. These limitations have catalyzed a new phase of therapeutic innovation in AD. Next-generation biologics targeting type 2 cytokines are being refined through advances in antibody bioengineering, including high binding affinity and fragment crystallizable modification, with the aim of enhancing efficacy while achieving extended dosing intervals. In parallel, bispecific and multispecific antibodies, designed to simultaneously engage multiple epitopes on the same or distinct antigens, are increasingly being evaluated in inflammatory skin diseases after initial development in oncology, offering the potential for synergistic immunomodulatory effects. This evolving landscape is further complemented by evidence from T-cell rebalancing strategies that showed durable off-treatment responses, positioning these approaches as potential game changers in long-term disease control. Lastly, emerging oral small-molecule agents that inhibit intracellular signaling downstream of multiple cytokines are supported by favorable safety profiles in early-phase trials. Overall, this review synthesizes current translational and clinical advances shaping the evolving pipeline, highlighting how both novel ways of modulating established pathways and the identification of new targets may transform the future management of AD.

Cervical lymph node metastases in oral cancer patients are a frequent occurrence and important prognostic factor. Anatomical and molecular imaging modalities can identify neck metastases with varying sensitivity and specificity but perform poorly in clinically negative neck nodes with microscopic disease. Herein we investigate the use of porphyrin-lipid nanotheranostics (PS) for multimodal detection of neck disease in preclinical models of oral cancer. Xenograft models of tongue cancer were established in nude rats using MOC2 mouse oral squamous cells. PS nanoparticles were radiolabelled with positron-emitting Copper-64 (64Cu-PS) and administered either IT (100 MBq 64Cu, 0.5 mg) or IV (250-500 MBq 64Cu/kg, 0.5-1.0 mg/kg). Uptake in the tumour and cervical lymph nodes was measured with serial PET/MR imaging and at endpoint with in situ fluorescence (FL) imaging. In the IV cohort, 64Cu-PS uptake was compared to 18F-FDG (46 MBq 18F/kg) PET performed prior to nanoparticle injection. After imaging, neck nodes were harvested for pathological staging. Receiver operating characteristics were compared in the IV cohort between 18F-FDG vs 64Cu-PS PET imaging vs FL imaging. The tongue tumour model yielded micrometastases to 54% of neck nodes by 14 d post-implantation. Following IT injection, sentinel and metastatic lymph nodes were visible with 64Cu-PS PET for 72 h. Following IV injection, 64Cu-PS PET signal in the tumour and neck nodes was clearest at 24 h and significant differences in the pooled SUVs of benign vs metastatic nodes were obtained. On FL imaging, metastatic neck nodes had significantly higher fluorescent signal (S/B) compared to benign nodes. Overall, FL S/Bmean gave the best prediction of nodal disease with 75% SEN, 79% SPC, and 71% NPV. 64Cu-PS PET (SUVmax: 77% SEN, 68% SPC, 68% NPV) performed slightly worse than FL imaging for identifying metastatic nodes but still better compared to 18F-FDG PET (SUVmax: 81% SEN, 43% SPC, 59% NPV). Inflamed nodes were the commonest source of false positives for both 64Cu-PS PET and FL imaging modalities. Nanotheranostic 64Cu-PS permitted more accurate multimodal detection of microscopic neck disease in preclinical oral cancer models and can offer valuable guidance for planning and performing neck dissections.

Digital health is emerging as a powerful tool in rheumatology, yet routine implementation remains limited. This study aimed to assess the needs and preferences of patients with immune-mediated inflammatory diseases and rheumatology healthcare professionals regarding the implementation of digital health. We conducted 2 parallel online cross-sectional surveys, 1 targeting adults with immune-mediated inflammatory diseases and another rheumatology professionals, featuring questions rated on a scale of 1 to 10 (1 = lowest and 10 = highest level of agreement) covering domains on contacting rheumatologists, app use, teleconsultations, digital health experience, digital assessment, app features, and impediments to digital health. We analysed responses from 135 patients (86.7% women, mean age 48.6 ± 12.5 years) and 53 professionals (88.7% rheumatologists, 9.4% nurses). Overall, 24.7% of patients reported difficulties contacting their rheumatologist during flares, and disease-related app use was low (3.3 ± 2.6/10). More than half had limited digital health experience, and improving communication with professionals was the highest rated item regarding digital evaluation (8.1 ± 2.8/10). Among professionals, 75% considered digital health beneficial, but only 26.9% reported substantial training (≥7/10), and 53.9% reported minimal use of digital health tools (≤2/10). Treatment adherence showed the greatest agreement for remote monitoring (7.6 ± 2.2/10). Key barriers were poor integration of digital tools with electronic health records (EHR) (8.5 ± 2.1/10) and increased workload (7.7 ± 2.8/10), whereas lack of interest was the least relevant (5.1 ± 2.6/10). Patients and professionals show a high perceived value of digital health in rheumatology, but limited real-world adoption. Improving training, user-centred app design, and EHR integration may help bridge the gap between perceived usefulness and routine implementation.

Echinocandin B (ECB), a fungal non-ribosomal lipopeptide, serves as the exclusive natural precursor of the front-line antifungal anidulafungin. Despite its clinical importance, ECB production remains suboptimal due to incomplete understanding of its biosynthesis mechanism. The global regulator LaeA has been implicated in secondary metabolite production, yet its specific role in ECB biosynthesis remains unexplored. To address this, we successfully constructed laeA deletion and overexpression strains, and demonstrated that LaeA functionally couples morphological development with ECB productivity. Transcriptomic analysis revealed LaeA directly activated the sterigmatocystin cluster via pathway-specific regulator AflR, but indirectly influenced ECB through iron-heme cofactor synchronization rather than direct gene cluster activation. LaeA overexpression upregulated siderophore iron transporters and heme biosynthetic genes, with supplementation of Fe2 + or 5-ALA further boosting titers to 2487 ± 123 and 2697 ± 16 mg/L, respectively. To overcome P450s catalytic constraints, we screened out a novel cytochrome P450 reductase CPR2 as the optimal redox partner. Co-expression of CPR2 with bacterial hemoglobin VHb achieved synergistic enhancement, improving the ECB titer to 3170 ± 41 mg/L. This study provided a practical strategy for improving ECB production and offering insights into the versatile regulatory modes of global secondary metabolite regulators.

Droplet interface bilayers (DIBs) offer a tunable platform for probing the electromechanical properties of lipid and lipid-peptide membranes under controlled electrical stimulation. DIBs enable both single-channel and ensemble ion conductance measurements over membrane areas orders of magnitude larger than those accessible by traditional patch clamp techniques, thereby allowing membrane-level analyses of electromechanical deformation and its influence on ion-conducting peptides. By systematically tuning membrane structure through the bulk hydrocarbon oil phase (e.g., hexadecane [C16] vs. dodecane/hexadecane [C12/C16] [25%/75%, v/v]), this bottom-up platform enables systematic variation of membrane composition and oil environment, which influence membrane viscoelasticity and structural reorganization, and thereby peptide ion conduction. Detailed procedures are provided for the assembly of gramicidin A-doped 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhPC) membranes using different hydrocarbon oil compositions and for the application of voltage-pulse protocols that drive membranes into metastable electromechanical states. Adaptive membrane ion conduction is characterized, including short-term plasticity-like (STP-like) and long-term potentiation- and depression-like (LTP-like/LTD-like) responses in a model membrane system. More broadly, this protocol provides a robust, reproducible approach for systematically investigating composition-dependent, membrane-level electromechanical contributions to synaptic-like conductive behavior and for understanding how lipid membrane environments modulate ion channel function.

We report the draft genome sequence of the methicillin-resistant Staphylococcus aureus (MRSA) strain MRSA_GSTU_PS9_BD, isolated from a patient's wound infection in Bangladesh. The genome harbors 123 and 22 predicted virulence factors and antimicrobial resistance genes, respectively, with a 91.86% probability of being a human pathogen.

Certain peptoids designed as mimics of host defense peptides such as LL-37 exhibit potent, broad-spectrum antibacterial, antifungal, antiparasitic, and antiviral activity with minimal cytotoxicity. Previous fixed-cell studies have suggested that the peptoids can pass through bacterial membranes and rapidly kill bacteria by aggregating intracellular macroanions, including ribosomes and DNA. However, the dynamic mechanisms of action of these biomimetic peptoids have remained elusive. We employed single-bacterial-cell, time-resolved fluorescence microscopy, and single-particle tracking methods to investigate the effects of the 12mer peptoid TM1, along with shorter alkylated and brominated analogues, on cytoplasmic membrane permeabilization and DNA and ribosome rigidification of Escherichia coli. Our results demonstrate that TM1 and several of its analogues permeabilize the cytoplasmic membrane within five minutes of flowing the peptoid solution over the cells-faster than seen for the important human antimicrobial peptide LL-37-and rigidify DNA and ribosomes as effectively as LL-37. Detailed biophysical structural and dynamical studies show that TM1 binds to both DNA (double-stranded and single-stranded) and single-stranded RNA in a similar manner to LL-37, which is well known to display strong nucleic acid binding. These results support our hypothesis that TM1 and its analogues exert their antimicrobial effects through intracellular aggregation of biomacromolecules such as ribosomes, RNA, and DNA. TM1 displays a higher affinity for RNA compared to DNA, suggesting it will preferentially bind in vivo to bacterial ribosomes. Our study yields insight into the dynamic effects of antimicrobial peptoids, facilitating their future development as biomimetic anti-infectives, with the additional advantage of protease invulnerability.

We investigated whether bobcats ( Lynx rufus) and domestic cats ( Felis catus ) exhibit distinct daily activity patterns or use different habitats in the Houston, Texas metropolitan area. Motion-activated cameras were deployed at 33 sites for 16 one-month sampling periods from 2020 - 2024. Bobcats exhibited primarily nocturnal activity wherever they were present. Domestic cats were primarily nocturnal at sites where no bobcats were detected. Bobcats and domestic cats overlapped at sites with a mixture of forest and developed land and domestic cats shifted to more daytime activity. Both temporal and spatial niche partitioning appear to facilitate predator coexistence in urban landscapes.

This study aims to develop a spatio-temporal predictive model for the luminous intensity distribution of the laser welding molten pool-a key visual indicator of process stability and quality-to overcome the limitations of conventional analytical models in handling complex multi-physical interactions. A data-driven framework based on a nonparametric artificial neural network architecture is proposed. Gaussian functions are employed as radial basis functions to capture localized spatio-temporal variations in the light field. The root mean square error is adopted as the evaluation metric and integrated into a systematic hyperparameter optimization procedure to enhance model fidelity and robustness. The optimized model successfully predicts two distinct molten pool luminous patterns under different welding conditions. Predictions show strong agreement with synchronized high-speed experimental images, confirming the model's accuracy and generalization capability. This method effectively reconstructs the molten pool's luminous signature, demonstrating significant potential for real-time process monitoring, online anomaly detection, and non-destructive quality assessment in advanced laser welding operations.

2,4-Dihydroxybenzoic acid is an important intermediate in agricultural and food chemistry. Salicylic acid decarboxylase catalyzes the carboxylation of resorcinol with CO2 to yield 2,4-dihydroxybenzoic acid. However, this process suffers from poor regioselectivity and low carboxylation activity. Here, we propose that the unique microenvironment created by the enzyme's substrate-binding pocket, referred to here as the enzyme field, induces charge redistribution in resorcinol, thus altering the enzymatic regioselectivity. Charge distributions at carbon atoms were calculated under 14 different enzyme fields, and catalytic assays revealed the correlation between regioselectivity and the electronegativity of the corresponding carbon atom. Furthermore, K23A/Y64T/E291D/Y27A was obtained with 99% C4-carboxylation selectivity from 20%, and a 69-fold increase in kcat/Km. The SAD-catalyzed carboxylation mechanism involving HCO3--mediated proton transfer was proposed on the basis of QM/MM metadynamics simulations. This work elucidates the repurposing of regioselectivity by enzyme-induced substrate charge distribution and proposes the mechanism of the SAD-catalyzed carboxylation of resorcinol.

Social recognition, the ability to distinguish between individuals, is essential for cognitively demanding social behaviors. The anterior olfactory nucleus (AON), a primary olfactory cortical region, is implicated in this process, but the underlying neurocircuitry remains poorly understood. Here, we generated a novel mouse line to enable genetic access to AON pyramidal neurons and mapped their whole-brain synaptic inputs and outputs. The medial prefrontal cortex (mPFC), a crucial hub for social cognition, is the primary neocortical target of AON neurons, which form monosynaptic excitatory connections with a substantial fraction of mPFC neurons. The AON→mPFC pathway is activated during social investigation, and chemogenetic inhibition of this pathway impairs social recognition. Moreover, an analogous AON-prefrontal pathway is present in humans, as supported by resting-state functional magnetic resonance imaging (fMRI) functional connectivity analyses. Taken together, these findings reveal a conserved olfactory-prefrontal circuit spanning mice to humans, potentially linking olfactory dysfunction to neuropsychiatric disorders.

Superelastic Nickel Titanium (NiTi) exhibits nonlinear and path-dependent behavior that complicates accurate simulation of orthodontic appliances. Standard iterative finite element (FE) formulations often fail to maintain realistic stress evolution during simulations, leading to non-physiologic force predictions. This study introduced an Element-Iteration-Specific (EIS) material model implemented within the FE framework to incorporate the behavior of superelastic NiTi alloy into an iterative simulation, aiming to investigate the biomechanics of a molar uprighting spring and estimate the clinical treatment duration. A two-dimensional (2D) model was constructed representing a 30° mesially tilted mandibular second molar uprighted using a prefabricated superelastic NiTi spring. At each iteration, the EIS algorithm redefines the element specific material parameters of the spring according to the stress-strain state inherited from the preceding iteration, thereby preserving the continuity of its behavior and enabling realistic stress evolution and load transfer between the wire, brackets, and teeth. The simulation achieved 23.3° of molar uprighting with 3.0 mm of tangential distal and 2.4 mm of normal extrusive displacements, over an equivalent of 14-week clinical duration. The NiTi spring generated an initial 12.4 N·mm (~ 1265 g·mm) counter-clockwise moment and 0.9 N normal extrusive force. The mean PDL stress remained physiologic, decreasing from 20.3 KPa at wire activation to 13.3 KPa at the end of the simulation. The model successfully tracked the spatial and temporal evolution of the superelastic NiTi's stress-induced martensitic transformation during activation and uprighting. The EIS framework effectively reproduced the nonlinear and history-dependent response of superelastic NiTi, offering clinically representative predictions and establishing a validated computational foundation for optimizing NiTi-based orthodontic appliances and improving treatment outcomes.

Thrombotic disorders are a leading cause of cardiovascular mortality worldwide; however, real-time, point-of-care monitoring technologies for timely detection of evolving coagulopathies remain inaccessible. Wearable, minimally invasive tracking of thrombo-inflammatory activity could enable earlier risk assessment and more effective therapy monitoring than conventional episodic blood tests. Here, we present a reagent-free, wearable electrochemical platform that integrates an on-chip Prussian Blue (PB) redox transducer with a signal-off molecularly imprinted polymer (MIP) layer and a biocompatible hydrogel microneedle (HMN) array for interstitial fluid (ISF) sampling, enabling direct electrochemical detection of thrombo-inflammatory biomarkers. The electrochemical PB/MIP (e-MIP) biosensor was configured to quantify thrombin (thrombotic biomarker) as well as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) (inflammatory biomarkers) directly in dermal ISF extracted via the integrated HMNs. The wearable e-MIP was characterized in vitro and ex vivo, where porcine skin tests preserved linearity and achieved limits of detection (LODs) of 0.26 ng mL- 1 for thrombin and ≤ 0.41 pg mL- 1 for IL-6 and TNF-α, confirming sensitive performance in a skin model. Also, selectivity studies against potential interferents (e.g., prothrombin or cardiac troponins) were conducted to assess the possible cross-reactivity. in vivo, HMN-integrated patches applied to lipopolysaccharide (LPS)-challenged rats sampled ISF and delivered it to the e-MIP, which captured the rise-and-fall kinetics of thrombin and IL-6 over 0-24 h. The results were validated against parallel enzyme-linked immunosorbent assays (ELISAs) performed on plasma collected at corresponding time points. Its versatile architecture and demonstrated in vivo performance position it as a promising platform that can enable early thrombotic risk assessment and therapeutic monitoring, with potential applications in personalized cardiovascular management following clinical validation.

It remains unclear which patient subgroups benefit most from intensive rehabilitation therapy. This study aimed to examine the heterogeneity in the effects of intensive postacute rehabilitation after hip fracture surgery on activities of daily living and to identify its potential sources. A retrospective observational study. Patients aged 50 years or older who underwent hip fracture surgery within 2 days of admission and were transferred to a rehabilitation ward between 7 and 30 days after surgery. Exposure was defined as the average daily rehabilitation time within 30 days posttransfer, dichotomized as &#x2265;120 versus <120 minutes/day. The outcome was the motor domain score of the Functional Independence Measure (FIM) at 60 days posttransfer. Heterogeneity of treatment effects was assessed using conditional average treatment effects (CATEs) estimated through the causal forest approach. The models were adjusted for relevant covariates, including age, sex, and FIM score at the time of transfer to the rehabilitation ward. The causal forest approach revealed heterogeneous effects-the estimated CATE for the top 20% high-benefit subgroup was 3.89 (95% CI: 2.32-5.46). The high-benefit subgroup was older and had lower FIM scores for the self-care, mobility, transfers, and excretion control domains at the time of transfer, compared with the low-benefit subgroup (the bottom 20% of the estimated CATEs). Heterogeneity exists in the association between intensive in-hospital rehabilitation therapy and functional status among older patients undergoing early hip fracture surgery during the postacute rehabilitation phase.

Most conventional alkene synthesis reactions (e.g., elimination et al.) inherently favor the formation of thermodynamically more stable E-isomers, posing a long-standing challenge for direct access to Z-alkenes. Here, we report the reprogramming of a thiamine diphosphate (ThDP)-dependent enzyme to catalyze a formal dehalogenative elimination that overrides this intrinsic thermodynamic bias, enabling the direct and selective synthesis of Z-&#x3b1;,&#x3b2;-unsaturated carboxylic acids. In contrast to classical approaches that rely on substrate control, directing groups, or complex ligand architectures, our strategy harnesses the enzyme's confined active site to achieve kinetic control exclusively via noncovalent interactions&#x2500;representing a fundamentally distinct and more sustainable approach to stereochemical programming. This transformation diverts the enzyme from its native function in C-C bond formation by channeling the Breslow intermediate toward a homoenolate-mediated pathway, wherein specific noncovalent interactions stabilize the syn-periplanar geometry required for Z-selective dehalogenative elimination. Through rational active-site engineering, the stereochemical trajectory can be inverted to furnish the complementary E-isomer, enabling stereodivergent synthesis from a common scaffold. This work establishes a biocatalytic platform that addresses a critical gap in Z-alkene synthesis, expands the catalytic repertoire of ThDP-dependent enzymes, and provides a sustainable alternative to conventional methodologies.

Type 1 diabetes mellitus (T1DM) results from autoimmune-mediated destruction of pancreatic &#x3b2;-cells, leading to absolute insulin deficiency. Current treatments rely on insulin replacement and do not prevent &#x3b2;-cell loss. 4-Methylumbelliferone (4-MU), an inhibitor of hyaluronan synthesis, has shown anti-inflammatory and cytoprotective effects, but its therapeutic potential and mechanisms in T1DM remain unclear. A streptozotocin (STZ)-induced mouse model of T1DM was treated with 4-MU for three weeks. Blood glucose levels and glucose tolerance were evaluated. Pancreatic islet morphology and cell composition were assessed by immunofluorescence. In parallel, STZ -injured MIN6 and &#x3b2;TC6 &#x3b2;-cells were used to investigate the effects of 4-MU on cell viability, oxidative stress, intracellular Ca&#xb2;&#x207a; homeostasis, and glucose-stimulated insulin secretion. Network pharmacology, molecular docking, qPCR, and Western blot analyses were conducted to explore the underlying mechanisms. 4-MU significantly reduced hyperglycemia and improved glucose tolerance in T1DM mice, accompanied by preservation of &#x3b2;-cell mass, normalization of the &#x3b2;/&#x3b1;-cell ratio, and reduced islet inflammation. In vitro, 4-MU protected &#x3b2;-cells from STZ-induced injury by decreasing reactive oxygen species (ROS) accumulation, restoring intracellular Ca&#xb2;&#x207a; balance, and improving insulin secretion. Network pharmacology identified 48 shared targets between 4-MU and T1DM, with KEGG pathway enrichment highlighting the PI3K/Akt signaling pathway. Molecular docking revealed stable binding of 4-MU to key regulators, including EGFR, Akt, ESR1, INSR, and IGF1R. Consistently, 4-MU enhanced the phosphorylation of EGFR, PI3K, and Akt in injured &#x3b2;-cells. 4-MU exerts protective effects in T1DM by preserving pancreatic &#x3b2;-cells survival and function, potentially through activation of the EGFR/PI3K/Akt signaling pathway.

Quantum dot single-particle tracking (QD-SPT), a powerful tool for analyzing membrane domains that are critical to various cellular processes, is widely used in membrane molecular dynamics research. QDs, which possess both a broad excitation range and a narrow emission bandwidth, are inherently suited for multicolor imaging at various wavelengths. However, applying multicolor QD-SPT with multiple biomolecular targets has been challenging due to the limited methods for specifically conjugating QDs to biomolecules. Here, we propose a DNA hybridization-based QD labeling method that generates several specific interactions based on sequence. QD fused with 20-mer oligo DNA specifically labeled membrane lipid 1,2-dipalmitoyl-sn-glycero-3-phosphatidylethanolamine (DPPE) covalently bound to complementary oligo DNA, forming a stable label that is suitable for SPT. The combination of polyA-polyT sequence as the linker oligo caused more QDs to fuse to DPPE compared with a random sequence linker. Oligo DNA-based QD-SPT accurately reflected the diffusion dynamics of DPPE measured using the single-fluorescence tracking technique and was compatible with conventional QD-SPT utilizing secondary antibody Fab. Using different pairs of oligo DNA sequences, we successfully achieved multicolor QD-SPT that distinguishes the lateral diffusion of DPPE and a membrane protein, GABAA receptor (GABAAR), within the same cell. The oligo DNA-based QD labeling method developed in this study is anticipated to substantially advance simultaneous multicolor QD-SPT of different living cell membrane molecules specific to DNA sequences.

Harm reduction vending machines (HRVMs) can expand low-barrier access to overdose prevention, sexual health, safer-use, and basic self-care supplies; however, practical guidance for implementing HRVMs in health system and supportive housing settings is limited. This practice report describes a clinical pharmacist practitioner (CPP)-led deployment of 15 HRVMs across a Veterans Affairs (VA) system and Veterans supportive housing in California. Beginning in December 2021, the CPP conducted site engagement, market research, and funding applications; convened cross-departmental stakeholders (logistics, engineering, biomedical, environmental management, information security/technology); and completed contracting. Contracts were awarded to VendNovation, LLC, for HRVMs which were placed in 7 community-based outpatient clinics, 6 supportive-housing sites, and 2 hospital locations. The CPP designed the HRVM wrap and interior layout; curated product assortments (eg, fentanyl/xylazine test strips, syringes, safer-sex supplies, wound-care, and hygiene items; naloxone added after launch) based on prior quality improvement interventions and Veteran feedback surveys; and established barcode-based user access and software-enabled inventory management. Implementation challenges included staff concerns (eg, stigma, not in my backyard attitudes), connectivity barriers (eg, Wi-Fi requirements), and added costs for deliveries to non-VA locations. HRVMs within VA clinics were accessible during business hours; supportive-housing HRVMs operate 24/7. Planning and installation required nearly 2 years, underscoring the need for dedicated staffing (CPP plus logistics technician), braided funding for start-up and recurring costs, and standardized purchasing and installation pathways. HRVMs seem feasible and acceptable in VA clinical and housing settings and may increase anonymous, low-barrier access to harm-reduction supplies. Implications for scale-up include development of centralized or prevetted procurement pathways, clearer implementation guidance, and operational supports to reduce site-level contracting burden.

Predicting Herb-Disease Associations (HDA) is pivotal for modernizing Traditional Chinese Medicine (TCM); however, this is impeded by data heterogeneity and the complex, multi-component mechanisms of herbal medicines. Existing drug-disease prediction models often struggle to capture high-order structural patterns and resolve semantic inconsistencies intrinsic to herbs. To overcome these limitations, we present HData, a standardized benchmark dataset that integrates herbal medicinal properties, chemical compositions, and disease associations. We further propose GHF-ACL, a novel multi-order graph contrastive learning framework designed for HDA prediction. Specifically, GHF-ACL explicitly models low-order functional similarities via a herb-disease similarity graph while capturing high-order component interactions through a herb-chemical hypergraph. Furthermore, an adaptive gating-guided structural interaction module aligns heterogeneous graph representations into a unified latent space, and hierarchical contrastive learning enforces consistency across structural views. Extensive experiments on five datasets demonstrate that GHF-ACL achieves superior or competitive performance over six state-of-the-art models across most metrics, with significant improvements over the best-performing baseline model in AUPR (+4.8% on LRSSL,&#x2009;+&#x2009;3.81% on Cdata), F1 score, and Recall. These results underscore the model's superior capability in detecting true positive associations within imbalanced biomedical data. By synergizing multi-view graph modeling, semantic fusion, and contrastive regularization, this work establishes a unified framework for HDA prediction, offering valuable insights for computational TCM and data-driven drug discovery.