Nuclear medicine imaging plays a critical role in early diagnosis, treatment planning, and monitoring by enabling real-time, non-invasive visualization of molecular processes. Conventional radiotracers, such as [18F]F-FDG, often suffer from limited specificity and unfavorable pharmacokinetics. Nanobodies, with their small size, high affinity, deep tissue penetration, and low immunogenicity, have emerged as valuable tools for molecular imaging. Nanobody-based radiotracers have shown promise across oncology, neurology, and immune-related diseases, supporting precision diagnostics and individualized treatment monitoring. However, challenges such as renal retention and short plasma half-life still hinder clinical translation. In this review, we present the structural and functional advantages of nanobodies and summarize the key advances, challenges, and future prospects of nanobody-based radiopharmaceuticals in nuclear medicine imaging.

For over a century, polyclonal antivenom has been the cornerstone of snakebite therapy, saving countless lives. However, the current production method, based on immunizing large animals, has inherent limitations in terms of safety, stability, and supply reliability, thereby creating a pressing need for alternative technologies. This review charts the rise of next-generation antivenoms built on recombinant antibody engineering. We systematically survey the strategies for discovering and developing these molecules, from humanized monoclonal antibodies and VHHs to computationally designed proteins. Our central thesis is that achieving broad-spectrum neutralization against complex venoms requires a shift from single-agent approaches to rationally designed, oligoclonal "cocktail" therapies (defined mixtures of a few select therapeutic antibodies). Finally, we analyze the critical challenges in bioprocessing, formulation, and regulatory science that must be overcome to translate these promising candidates from the laboratory into globally accessible medicines, and we explore the role of emerging technologies in accelerating this transition.

The era of antibody therapeutics, while transformative, has reached a therapeutic plateau. We posit this stagnation stems from a central, unresolved conflict: the Paradox of Specificity, where the exquisite molecular-level targeting of antibodies is systematically nullified by the indiscriminate nature of their systemic administration. This review argues for a fundamental paradigm shift from the prevailing antibody-centric model to the rational design of Antibody-Carrier Integrated Systems (ACIS). Within this framework, the delivery system is no longer a passive carrier but is reconceptualized as a contextual intelligence layer-an engineered interface capable of sensing biological cues to strictly govern when and where the drug is active. We systematically analyze key strategies to achieve this vision, from fortifying the antibody's core stability and programming its spatiotemporal release kinetics, to redefining the localized therapeutic environment via localized delivery. By critically evaluating translational hurdles and envisioning a future of computational co-design, this review provides a strategic roadmap to finally resolve the paradox, thereby unlocking the full, unrealized potential of antibody-based precision medicine.

Organoid technology has emerged as a promising platform for drug development by enabling the in vitro reconstruction of human tissue architecture, cellular heterogeneity, and key physiological functions. Compared with conventional two-dimensional cell cultures and animal models, organoids provide improved physiological relevance and translational potential. In this review, we systematically summarize the principles of organoid generation, including cell sources, construction strategies, and model classification, and discuss recent advances in integrating organoids with emerging technologies such as microfluidics, gene editing, artificial intelligence, and three-dimensional bioprinting. We further provide a comprehensive overview of organoid applications across the drug development pipeline, including target identification and drug discovery, pharmacodynamic evaluation, absorption, distribution, metabolism, and excretion (ADME) studies, and multi-organ toxicity assessment. Particular emphasis is placed on their expanding role in evaluating advanced drug delivery systems, including transdermal, pulmonary, and nanomedicine-based intelligent delivery platforms, where organoids enable systematic investigation of delivery–penetration–distribution–efficacy–toxicity processes under physiologically relevant conditions. In addition, current challenges, including model standardization, tissue maturation, vascularization, immune integration, and in vitro–in vivo extrapolation, are critically discussed together with future perspectives. Overall, organoid technology is evolving from an emerging experimental model into an integrated platform for drug discovery and translational research, providing new opportunities for more predictive, efficient, and personalized drug development.

Colorectal cancer is a prevalent and lethal malignancy, with histopathological examination serving as the diagnostic gold standard. Recent advances in deep learning have enabled the automated segmentation of medical histopathology images. However, pixel-level annotation of pathological images remains labor-intensive and time-consuming, which motivates the use of weakly supervised semantic segmentation (WSSS) as an alternative. Existing WSSS methods, however, often suffer from under-activation and over-activation due to the limited discriminative cues provided by categorical labels. As a result, they frequently fail to generate complete and high-quality Class Activation Maps (CAMs) suitable as pseudo-labels. Additionally, privacy concerns and barriers to inter-institutional data sharing hinder conventional centralized training approaches. To address these challenges, we propose FedCRT, a federated weakly supervised framework designed to comprehensively activate target regions while capturing fine-grained morphological features at tumor boundaries for high-precision segmentation. Specifically, we introduce a Class-Aware Spatial Reconstruction Module (CASRM), which guides the classification network to preserve spatial structures in input images and focus on non-discriminative regions, resulting in more complete target activation. We further develop a Triple-scale Consistency Constraint (TCC) that enforces feature consistency across global, neighborhood, and micro levels, enhancing boundary segmentation accuracy. Finally, we design a Bidirectional Trust Clustering (BTC) mechanism that uses cross-domain distance metrics, including Manhattan Distance and KL Divergence, to identify and eliminate Byzantine clients in decentralized federated training, thereby improving system stability and robustness. Experimental results on the CRAG, EBHI-seg, GLAS, and NDTH-CRC datasets demonstrate that FedCRT achieves the best overall performance, surpassing existing methods in both segmentation accuracy and robustness. Notably, FedCRT improves the Dice score by more than one percentage point over state-of-the-art models across all four datasets.

The clinical utility of nanobodies in solid tumor therapy is constrained by a fundamental biophysical trade-off: rapid renal clearance necessitates half-life extension, which in turn demands ultrahigh affinity to prevent dissociation from the target under systemic washout conditions. While generative artificial intelligence has substantially advanced structure prediction, it often fails to resolve the subtle energetic frustrations at protein–protein interfaces required for affinity maturation. Here, we present a physics-informed artificial intelligence framework that integrates AlphaFold 3 structural priors with molecular dynamics simulations to rationally design a picomolar anti-carcinoembryonic antigen nanobody. By employing variable dielectric molecular mechanics/generalized Born surface area decomposition, we identified interfacial residues that were structurally permissible but thermodynamically suboptimal. We subsequently constructed a focused library to resolve these bottlenecks through electrostatic optimization, desolvation penalty minimization, and van der Waals packing refinement. This strategy achieved a 99% binding positivity rate and yielded variants with picomolar affinity (KD ≈ 44 pM)—an ~306-fold improvement over the parental clone—without compromising thermal stability (Tm > 63 °C). To translate these biophysical gains into therapeutic efficacy, we engineered bispecific nanobodies fusing the affinity-matured domains with an anti-human serum albumin binder. In vivo longitudinal imaging of colorectal cancer xenografts revealed a “lock-and-hold” phenotype, characterized by deep intratumoral penetration and sustained retention (>168 h). This work demonstrates that coupling geometric deep learning with rigorous physical principles overcomes the inefficiencies of stochastic screening, providing a valuable framework that may be adapted for the rational development of high-potency biologics across various therapeutic targets.

Emerging and re-emerging infectious diseases ranging from the 1918 H1N1 influenza pandemic to the recent SARS-CoV-2 and monkeypox virus outbreaks continue to pose profound threats to global public health. These crises underscore the critical need for high-fidelity and human-relevant infection models. Organoid technology has emerged as a cornerstone platform for pathogen research by faithfully recapitulating the 3-dimensional architecture and physiological microenvironment of native human tissues in vitro. This review systematically examines the development and structural refinement of organoid-based infection models with an emphasis on evidence-based strategies for stem cell source selection, extracellular matrix optimization, and dynamic culture system engineering. Such advancements enable the robust generation of multi-organ models including respiratory, intestinal, and neural organoids tailored for investigating viral tropism, spatiotemporal infection kinetics, and host immune responses. Furthermore, we evaluate the translational utility of organoids in high-throughput antiviral drug screening and preclinical vaccine assessment. To further enhance physiological relevance and functional fidelity, organoid platforms are being increasingly combined with advanced engineering strategies, including coculture approaches, CRISPR-Cas9-mediated genetic perturbation, engineered microphysiological systems (such as organ-on-a-chip), and 3D bioprinting. These integrated technologies improve biomimicry while expanding experimental controllability and scalability. In addition, we critically examine the major bottlenecks limiting clinical translation and discuss emerging frontiers driven by artificial intelligence and synthetic biology. Through iterative technological refinement and cross-disciplinary convergence, organoids have evolved beyond reductionist in vitro surrogates into physiologically informed and mechanism-driven platforms that advance our understanding of host-pathogen interactions while enhancing global preparedness against emerging pathogens.

Currently, the storage and transportation of mRNA vaccines typically rely on ultra-low temperature conditions. To improve their stability and extend shelf life, recent studies have been devoted to converting liquid formulations into solid forms using drying technology. Among them, freeze-drying (lyophilization) is an effective strategy that freezes samples and removes moisture through primary (sublimation) and secondary (desorption) drying stages, maximally preserving the structural integrity and biological activity of mRNA vaccines. The significant reduction in moisture content effectively inhibits the rate of hydrolysis of mRNA, which is considered the primary factor contributing to the instability of mRNA vaccines. However, the freeze-drying process itself and its accompanying stresses pose key challenges, involving many critical variables closely related to formulation composition, process parameters, and manufacturing environment. This paper systematically reviews the application of different freeze-drying technologies in mRNA vaccines and the optimization strategies of lyophilized mRNA vaccines, aiming to provide theoretical foundation and guidance for optimizing freeze-drying processes, enhancing vaccine stability and expanding their application scope.

Zwitterionic polycarboxybetaines (PCBs), combining quaternary ammonium cations and carboxylate anions in their repeating units, have emerged as promising materials for drug delivery applications. Their exceptional hydration, biocompatibility, and antifouling properties make them attractive alternatives to polyethylene glycol (PEG), particularly given growing concerns about immunogenicity of PEG. PCBs can be functionalized through various methods, including modification of side-chain moieties, adjustment of spacer length between charged groups, and incorporation of responsive elements. When applied to delivery drug, PCBs have been successfully developed into multiple formats including micelles, hydrogels, liposomes, and nanoparticles. Notably, in protein drug delivery, PCBs demonstrate significant advantages such as enhancing protein stability, extending circulation time, improving penetration through biological barriers, and reducing immunogenicity. Despite these promising features, several challenges remain, including complex synthesis requirements, limited mechanical properties, and pending FDA approval as pharmaceutical excipients. This review provides a comprehensive analysis of PCBs from the structure-function relationship, synthesis methods, and applications in drug delivery systems, while examining current limitations and future prospects.

Aligned fibrous scaffolds are essential for directing soft-tissue regeneration, yet synthetic polymers lack native biochemical cues. To bridge this gap, bioactive and anisotropic scaffolds were developed by combining melt electrowriting (MEW) with decellularized extracellular matrix (dECM) decoration to enhance cell-scaffold interactions for soft tissue engineering. Porous polycaprolactone (PCL) scaffolds with aligned microfibers and tunable pore architectures (aspect ratios 1:1, 1:2, and 1:3) were fabricated via MEW and subsequently coated with porcine skeletal muscle dECM using a dip-gelation method. Comprehensive surface characterization confirmed the presence and robust adhesion of the dECM coating on the PCL scaffolds, which concurrently enhanced surface hydrophilicity. Furthermore, mechanical testing demonstrated that the resulting composite scaffold retained the structural integrity required to meet the mechanical demands of tissue regeneration. In vitro studies using L929 fibroblasts demonstrated that dECM decoration significantly improved cell adhesion, proliferation, and alignment along the fiber direction. Notably, scaffolds with 1:1 and 1:2 aspect ratios supported the highest cell density and guided morphological elongation most effectively. These findings highlight the synergistic potential of topographical cues and biochemical signaling in scaffold design for functional tissue regeneration.

Tumor necrosis factor alpha (TNF-alpha) is a key cytokine in inflammation and immune responses, making its rapid and accurate detection essential for disease diagnosis and management. In this study, we developed a highly sensitive chemiluminescence immunoassay (CLIA) using antibody-coated magnetic particles (Ab-MPs-CLIA) for TNF-alpha detection. From nine candidate antibodies, we identified an optimal pair through epitope competition and affinity assessments, significantly improving assay performance. The Ab-MPs-CLIA achieved a detection limit of 0.25 pg/mL, 6.8 times more sensitive than Siemens commercial kits, with a broad linear range of 9.2-1077 pg/ mL. The method demonstrated excellent stability, both under accelerated conditions at 37 degrees C for 7 days and longterm storage at 4 degrees C for 12 months. It showed no cross-reactivity with common interfering substances in human serum, ensuring high specificity. Notably, the entire process, from sample preparation to result, takes just 25 min, compared to 3-4 h for both ELISA and RIA, and CLIA typically offers 10-100 times higher sensitivity than these methods. These advantages make the Ab-MPs-CLIA an ideal option for clinical laboratories, providing superior sensitivity, specificity, broader dynamic range, and greater operational efficiency than existing TNF-alpha detection technologies.

The effective treatment of nasopharyngeal carcinoma (NPC) is challenged by an immunosuppressive tumor microenvironment (TME) and insufficient immune effector cell activation. Herein, we design a synergistic tri-modal therapeutic strategy to overcome these barriers. This platform integrates: (1) a CD109-targeted liposomal doxorubicin (S3-Lip-DOX) for precise chemotherapy and induction of immunogenic cell death (ICD); (2) non-genetically engineered natural killer (NK) cells armed with dual aptamers (targeting CD109 and PD-L1) via bio-orthogonal chemistry for enhanced tumor recognition (S3-P-NK); and (3) an Fc-engineered anti-PD-L1 antibody (Atezolizumab/IgG1) that restores antibody-dependent cellular cytotoxicity (ADCC). Crucially, we uncovered a key mechanistic synergy: S3-Lip-DOX treatment, as a stress-adaptive response, upregulates PD-L1 expression on NPC cells. This finding provides a compelling rationale for the integration, turning a potential immune escape mechanism into a therapeutic vulnerability. The complete regimen, comprising S3-Lip-DOX, S3-P-NK, and Atezolizumab/IgG1, demonstrated potent synergistic antitumor effects in vitro and in vivo. This triple-combination therapy not only achieved significant tumor regression but also robustly reprogrammed the innate tumor microenvironment, evidenced by enhanced dendritic cell (DC) maturation and pro-inflammatory macrophage activation. This work establishes a mechanism-driven, modular therapeutic platform that effectively coordinates targeted chemotherapy with innate immunotherapy, holding significant translational potential for solid tumors.

Nanodrug delivery systems (NDDS) have demonstrated outstanding performance in drug delivery due to their efficient delivery capacity, targeting ability, and biocompatibility. However, the development of nanomedicines still heavily relies on the expertise of formulation scientists and extensive trial-and-error experiments. Despite the abundance of data in nanoscience, traditional biological research often struggles to effectively process, analyze, and utilize these datasets, limiting nanomedicine studies to a “one-to-one” approach. Against this backdrop, the rapid growth of artificial intelligence (AI) and machine learning (ML) offers a new paradigm for nanomedicine research. Unlike traditional statistical analyses and mathematical models, AI and ML provide deeper insights into big data, enhancing the efficiency of nanomedicine development while steering the field toward more intelligent and more precise research approaches. This review focuses on milestone studies that use ML to reshape nanomedicine research from a pharmaceutics perspective, highlighting how data-driven ML models can guide new directions in nanomedicine development.

The global morbidity and mortality associated with viral diseases pose a major threat to public health security and cause significant economic losses worldwide. Developing novel prophylactic and therapeutic interventions remains an urgent priority in contemporary virology research. Immunotherapy, initially developed for cancer treatment, has shown satisfactory efficacy in the management of viral infections. However, the clinical application of immunotherapy is still constrained by its inherent limitations, including poor stability, inadequate targeting ability, and systemic toxicity. Nanocarriers have emerged as a promising platform to address these challenges, with features such as protecting active substances from enzymatic degradation, delivering active substances specifically to the site of infection via ligand modification, and controlling the release behavior of active substances so as to maintain their controlled and therapeutic concentrations. Therefore, the combination of immunotherapy and nanocarriers is expected to overcome the shortcomings of immunotherapy and significantly improve their therapeutic efficacy. In this review, the classification, application, and combination of immunotherapy with nanocarriers in viral diseases are summarized. The challenges and the future prospects of this combination are also discussed.

Bispecific antibodies (BsAbs) targeting PD-1 and LAG-3 offer a promising strategy in cancer immunotherapy by enhancing antitumor immunity and overcoming resistance to PD-1 blockade. Despite the growing interest in PD-1/LAG-3 BsAbs, a systematic comparison of different BsAbs formats remains lacking, leaving a gap in the rational design of optimized therapeutics. In this study, we systematically compared three BsAb formats-YG-003D1 (Ab-ScFv format), YG-003D2 (DVD format), and YG-003D3 (Knob-into-Hole (KIH) format)-to evaluate their structural, functional, and pharmacokinetic properties, providing critical insights into their therapeutic potential. YG-003D1 exhibited the strongest binding and blocking activity due to its tetravalent Ab-ScFv structure, which facilitated dual-target engagement with minimal steric hindrance. However, it had relatively low expression yields and a tendency to form aggregates, which could impact manufacturability and long-term stability. YG-003D2, utilizing a DVD format, exhibited mild steric hindrance in dual-target engagement, leading to a moderate reduction in blocking efficiency, particularly in LAG-3 inhibition. Nonetheless, its bivalency for both PD-1 and LAG-3 may provide advantages in specific therapeutic contexts. In contrast, YG-003D3, with its asymmetric KIH format, demonstrated the most favorable balance of manufacturability, stability, and pharmacokinetics. It had high expression yields, minimal aggregation, and a half-life comparable to IgG, making it the most promising candidate for clinical development. However, its monovalent binding per target resulted in slightly reduced blocking potency compared to YG-003D1. While YG-003D3 demonstrated the best overall balance of properties, alternative formats such as YG-003D1 could be refined through Fc engineering or linker optimization to enhance manufacturability and reduce aggregation. Similarly, YG-003D2's steric hindrance could be mitigated by introducing flexible linkers to improve dual-target engagement. Further modifications to YG-003D3, such as affinity tuning or Fc engineering, could enhance its blocking potency while retaining its favorable pharmacokinetics. These insights not only provide a rational framework for PD-1/LAG-3 bispecific inhibitor design but also serve as a reference for broader applications of BsAbs in immunotherapy.

Organophosphorus compounds (OPs) poisoning poses a significant health risk as an insecticide, and its potent toxicity is characterized by rapid onset and a very narrow window for intervention. Prophylactic medication is crucial for managing OPs poisoning, yet effective and safe drugs are still lacking. The enzyme Organophosphorus hydrolase (OPH) shows promise as a bioscavenger but faces challenges due to its short half-life and strong immunogenicity. Our research reveals that N-terminal PEGylation of OPH significantly extends its pharmacokinetic half-life, reduces immunogenicity, and, surprisingly, enhances its catalytic activity for ethyl paraoxon. Intravenous administration of PEGY40kDa-OPH at a dose of 1 mg/kg effectively protected the rats against 4 doses of 2 ×LD50 ethyl paraoxon challenge with neither death nor toxic symptoms observed. Molecular dynamics simulations suggest that this enhancement is due to increased flexibility and stronger hydrogen bonding between the active site of PEGylated OPH and the substrate. This leads to more stable binding and higher catalytic rate. The study offers a strategy for a rapid and enduring prophylactic against organophosphorus poisoning and introduces a new analytical approach to understand the impact of PEGylation on enzymatic function.

The management of the acute bacterial infections in the traumatic skin remains a significant challenge in clinical. The application of antibiotics on wounds is typically avoided due to antimicrobial resistance risks. Antisense therapeutics, like antisense oligonucleotides (ASOs), present a selective, low-resistance alternative, but effective bacterial uptake is still a major obstacle. In this work, we developed a novel microneedle-based delivery system (MNDS) distinguished by its distinctive multifunctional hydrogels and a "Tripartite Delivery" mechanism. The MNDS was designed with a bionic mushroom-shaped multilayered structure. Upon application, the MNDS enabled an initial rapid release and sustained release of the encapsulated nanocomplexes (ASO@GP-SiNPs). The needle body layer hydrogels can respond to hyaluronidase and continuously release hyaluronic acid and epsilon-polylysine for several days. These ASO@GP-SiNPs were effectively uptaken by E. coli (46.4 %) and S. aureus (37.1 %), subsequently releasing ASOs that target the acpP and ftsZ genes to effectively eliminate bacteria. The system exhibits significant antibacterial activity and effectively inhibits biofilm formation, while also inducing the polarization of macrophages toward an M2-like phenotype. Additionally, the system demonstrates excellent biocompatibility. In conclusion, this paper presents a novel strategy for addressing the challenges of acute bacterial infections in traumatic skin by utilizing the advanced functionalities of MNDS.

Clostridium perfringens alpha toxin (CPA), a zinc-dependent phospholipase C, is a key virulence factor in gas gangrene. While its membrane-disrupting cytotoxicity is well characterized, its capacity to modulate neutrophil function and promote pathological inflammation is poorly defined. Here, we show that CPA induces neutrophil extracellular trap (NETs) formation by mobilizing and functionally reprogramming immature neutrophils. In a murine model, CPA challenge caused dose-dependent mortality and multi-organ injury, driven by a dramatic expansion of a pro-NETotic immature neutrophil subset identified by single-cell RNA sequencing. This was confirmed by elevated systemic NETs markers and extensive NETs deposition in damaged tissues. Mechanistically, CPA directly triggered reactive oxygen species (ROS)-dependent, peptidylarginine deiminase 4 (PAD4)-mediated NETosis in both murine and human neutrophils, revealing a conserved pathogenic mechanism. Importantly, therapeutic targeting of the NETotic pathway-via PAD4 inhibition, (Deoxyribonuclease I) DNase I treatment, or neutrophil depletion-significantly reduced tissue damage and improved survival. These findings identify a CPA-neutrophil-NETs axis as a central driver of immunopathology. Our study reframes CPA from a classical cytolysin to a potent immunomodulatory toxin that hijacks neutrophil fate. Our findings validate the NETotic pathway as a critical therapeutic target, providing a strong rationale for developing host-directed therapies-potentially in combination with toxin-neutralizing agents-to combat severe toxin-driven diseases.

SARS-CoV-2 Omicron sublineages escape most preclinical/clinical neutralizing antibodies in development, suggesting that previously employed antibody screening strategies are not well suited to counteract the rapid mutation of SARS-CoV-2. Therefore, there is an urgent need to screen better broad-spectrum neutralizing antibody. In this study, a comprehensive approach to design broad-spectrum inhibitors against both SARS-CoV-1 and SARS-CoV-2 by leveraging the structural diversity of nanobodies is proposed. This includes the de novo design of a fully human nanobody library and the camel immunization-based nanobody library, both targeting conserved epitopes, as well as the development of multivalent nanobodies that bind nonoverlapping epitopes. The results show that trivale B11-E8-F3, three nanobodies joined tandemly in trivalent form, have the broadest spectrum and efficient neutralization activity, which spans from SARS-CoV-1 to SARS-CoV-2 variants. It is also demonstrated that B11-E8-F3 has a very prominent preventive and some therapeutic effect in animal models of three authentic viruses. Therefore, B11-E8-F3 has an outstanding advantage in preventing SARS-CoV-1/SARS-CoV-2 infections, especially in immunocompromised populations or elderly people with high-risk comorbidities.