Anti-IL-17 Inhibits PINK1/Parkin Autophagy and M1 Macrophage Polarization in Rheumatic Heart Disease.

Rheumatic heart disease (RHD) is an important and preventable cause of cardiovascular death and disability, but the lack of clarity about its exact mechanisms makes it more difficult to find alternative methods or prevention and treatment. We previously demonstrated that increased IL-17 expression plays a crucial role in the development of RHD-related valvular inflammatory injury. Macrophage autophagy/polarization may be a pro-survival strategy in the initiation and resolution of the inflammatory process. This study investigated the mechanism by which IL-17 regulates autophagy/polarization activation in macrophages. A RHD rat model was generated, and the effects of anti-IL-17 and 3-methyladenine (3-MA) were analyzed. The molecular mechanisms underlying IL-17-induced macrophage autophagy/polarization were investigated via in vitro experiments. In our established RHD rat model, the activation of the macrophage PINK1/Parkin autophagic pathway in valve tissue was accompanied by M1 macrophage infiltration, and anti-IL-17 treatment inhibited autophagy and reversed macrophage inflammatory infiltration, thereby attenuating endothelial-mesenchymal transition (EndMT) in the valve tissue. The efficacy of 3-MA treatment was similar to that of anti-IL-17 treatment. Furthermore, in THP-1 cells, the pharmacological promotion of autophagy by IL-17 induced M1-type polarization, whereas the inhibition of autophagy by 3-MA reversed this process. Mechanistically, silencing PINK1 in THP-1 blocked autophagic flux. Moreover, IL-17-induced M1-polarized macrophages promoted EndMT in HUVECs. This study revealed that IL-17 plays an important role in EndMT in RHD via the PINK1/Parkin autophagic pathway and macrophage polarization, providing a potential therapeutic target.

Demethylation C-C coupling reaction facilitated by the repulsive Coulomb force between two cations.

Carbon chain elongation (CCE) is normally carried out using either chemical catalysts or bioenzymes. Herein we demonstrate a catalyst-free approach to promote demethylation C-C coupling reactions for advanced CCE constructed with functional groups under ambient conditions. Accelerated by the electric field, two organic cations containing a methyl group (e.g., ketones, acids, and aldehydes) approach each other with such proximity that the energy of the repulsive Coulomb interaction between these two cations exceeds the bond energy of the methyl group. This results in the elimination of a methyl cation and the coupling of the residual carbonyl carbon groups. As confirmed by high-resolution mass spectrometry and isotope-labeling experiments, the C-C coupling reactions (yields up to 76.5%) were commonly observed in the gas phase or liquid phase, for which the mechanism was further studied using molecular dynamics simulations and stationary-point calculations, revealing deep insights and perspectives of chemistry.

Sparse Wasserstein stationary subspace analysis for fault detection and diagnosis of nonstationary industrial processes.

Fault detection and diagnosis of nonstationary processes are crucial for ensuring the safety of industrial production systems. However, the nonstationarity of process data poses multifaceted challenges to them. First, conventional stationary fault detection methods encounter difficulties in discerning evolving trends within nonstationary data. Secondly, the majority of current nonstationary fault detection methods directly extract features from all variables, rendering them susceptible to redundant interference. Moreover, nonstationary trends possess the capacity to conceal and modify the correlations among variables. Coupled with the smearing effect of faults, it is challenging to achieve accurate fault diagnosis. To address these challenges, this paper proposes sparse Wasserstein stationary subspace analysis (SWSSA). Specifically, a ℓ2,p-norm constraint is introduced to endow the stationary subspace model with excellent sparse representation capability. Furthermore, recognizing that fault variables within the sparse stationary subspace influence only a limited subset of stationary sources, this paper proposes a novel contribution analysis method based on local dynamic preserving projection (LDPP), termed LDPPBC, which can effectively mitigate the smearing effect on nonstationary fault diagnosis. LDPPBC establishes a LDPP matrix by extracting the latent positional information of fault variables within the stationary subspace. This allows LDPPBC to selectively analyze the contributions of variables within the latent fault subspace to achieve precise fault diagnosis while avoiding the interference of variable contributions from the fault-free subspace. Finally, the superiority of the proposed method is thoroughly validated through a numerical simulation, a continuous stirred tank reactor, and a real industrial roaster.

Multifunctional nano-in-micro delivery systems for targeted therapy in fundus neovascularization diseases.

Fundus neovascularization diseases are a series of blinding eye diseases that seriously impair vision worldwide. Currently, the means of treating these diseases in clinical practice are continuously evolving and have rapidly revolutionized treatment opinions. However, key issues such as inadequate treatment effectiveness, high rates of recurrence, and poor patient compliance still need to be urgently addressed. Multifunctional nanomedicine can specifically respond to both endogenous and exogenous microenvironments, effectively deliver drugs to specific targets and participate in activities such as biological imaging and the detection of small molecules. Nano-in-micro (NIM) delivery systems such as metal, metal oxide and up-conversion nanoparticles (NPs), quantum dots, and carbon materials, have shown certain advantages in overcoming the presence of physiological barriers within the eyeball and are widely used in the treatment of ophthalmic diseases. Few studies, however, have evaluated the efficacy of NIM delivery systems in treating fundus neovascular diseases (FNDs). The present study describes the main clinical treatment strategies and the adverse events associated with the treatment of FNDs with NIM delivery systems and summarizes the anatomical obstacles that must be overcome. In this review, we wish to highlight the principle of intraocular microenvironment normalization, aiming to provide a more rational approach for designing new NIM delivery systems to treat specific FNDs.

Manipulating the Spin State of Spinel Octahedral Sites via a π-π Type Orbital Coupling to Boost Water Oxidation.

Spin state is often regarded as the crucial valve to release the reactivity of energy-related catalysts, yet it is also challenging to precisely manipulate, especially for the active center ions occupied at the specific geometric sites. Herein, a π-π type orbital coupling of 3d (Co)-2p (O)-4f (Ce) was employed to regulate the spin state of octahedral cobalt sites (CoOh) in the composite of Co3O4/CeO2. More specifically, the equivalent high-spin ratio of CoOh can reach to 54.7% via tuning the CeO2 content, thereby triggering the average eg filling (1.094) close to the theoretical optimum value. The corresponding catalyst exhibits a superior water oxidation performance with an overpotential of 251 mV at 10 mA cm-2, rivaling most cobalt-based oxides state-of-the-art. The π-π type coupling corroborated by the matched energy levels between Ce t1u/t2u-O and CoOh t2g-O π type bond in the calculated crystal orbital Hamilton population and partial density of states profiles, stimulates a π-donation between O 2p and π-symmetric Ce 4fyz2 orbital, consequently facilitating the electrons hopping from t2g to eg orbital of CoOh. This work offers an in-depth insight into understanding the 4f and 3d orbital coupling for spin state optimization in composite oxides.

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Strengthening the Synergy between Oxygen Vacancies in Electrocatalysts for Efficient Glycerol Electrooxidation.

Defect-engineered bimetallic oxides exhibit high potential for the electrolysis of small organic molecules. However, the ambiguity in the relationship between the defect density and electrocatalytic performance makes it challenging to control the final products of multi-step multi-electron reactions in such electrocatalytic systems. In this study, controllable kinetics reduction is used to maximize the oxygen vacancy density of a Cu─Co oxide nanosheet (CuCo2O4 NS), which is used to catalyze the glycerol electrooxidation reaction (GOR). The CuCo2O4-x NS with the highest oxygen-vacancy density (CuCo2O4-x-2) oxidizes C3 molecules to C1 molecules with selectivity of almost 100% and a Faradaic efficiency of ≈99%, showing the best oxidation performance among all the modified catalysts. Systems with multiple oxygen vacancies in close proximity to each other synergistically facilitate the cleavage of C─C bonds. Density functional theory calculations confirm the ability of closely spaced oxygen vacancies to facilitate charge transfer between the catalyst and several key glycolic-acid (GCA) intermediates of the GOR process, thereby facilitating the decomposition of C2 intermediates to C1 molecules. This study reveals qualitatively in tuning the density of oxygen vacancies for altering the reaction pathway of GOR by the synergistic effects of spatial proximity of high-density oxygen vacancies.

Electron Accumulation Induced by Electron Injection-Incomplete Discharge on NiFe LDH for Enhanced Oxygen Evolution Reaction.

Optimizing the local electronic structure of electrocatalysts can effectively lower the energy barrier of electrochemical reactions, thus enhancing the electrocatalytic activity. However, the intrinsic contribution of the electronic effect is still experimentally unclear. In this work, the electron injection-incomplete discharge approach to achieve the electron accumulation (EA) degree on the nickel-iron layered double hydroxide (NiFe LDH) is proposed, to reveal the intrinsic contribution of EA toward oxygen evolution reaction (OER). Such NiFe LDH with EA effect results in only 262 mV overpotential to reach 50 mA cm-2, which is 51 mV-lower compared with pristine NiFe LDH (313 mV), and reduced Tafel slope of 54.8 mV dec-1 than NiFe LDH (107.5 mV dec-1). Spectroscopy characterizations combined with theoretical calculations confirm that the EA near concomitant Vo can induce a narrower energy gap and lower thermodynamic barrier to enhance OER performance. This study clarifies the mechanism of the EA effect on OER activity, providing a direct electronic structure modulation guideline for effective electrocatalyst design.

MSRB2 Ameliorates H2O2-induced Chondrocyte Oxidative Stress and Suppresses Apoptosis in Osteoarthritis.

BACKGROUND: Chondrocyte oxidative stress and apoptosis are critical factors contributing to the pathogenesis of osteoarthritis (OA). Methionine sulfoxide reductase B2 (MSRB2) is a mitochondrial protein that protects cells from oxidative stress and is involved in apoptosis. This study aimed to investigated the expression of MSRB2 in articular cartilage tissues and elucidated its effect on H2O2-stimulated chondrocytes. METHODS: Human chondrocytes were cultured in Dulbecco's modified Eagle's medium (DMEM)/F12. MSRB2 overexpression in chondrocytes was achieved by transfecting with an MSRB2 overexpression plasmid. Western blot, quantitative RT-PCR, Immunofluorescence staining, and TUNEL assay were employed in this study. RESULTS: MSRB2 expression was found to be reduced in OA patients. Furthermore, overexpression of MSRB2 in H2O2-induced chondrocytes mitigated apoptosis and enhanced cell viability. Elevated MSRB2 expression diminished chondrocyte ROS contents, decreased cytochrome C (Cyc) in the cytoplasm, and regulated mitochondrial membrane potential to maintain mitochondrial homeostasis. Interestingly, knockdown of charged multivesicular body protein 5 (CHMP5) led to a decreased inMSRB2 expression in chondrocytes. Additionally, protein levels of CHMP5 and MSRB2 were reduced in H2O2-stimulated chondrocytes, and silencing CHMP5 reduced MSRB2 expression. Knockdown of CHMP5 increased cleaved caspase-3 expression in H2O2-induced chondrocytes and elevated TUNEL-positive chondrocytes. CONCLUSION: MSRB2 decreased in OA, and overexpression of MSRB2 alleviated oxidative stress and apoptosis of chondrocyte.

A spatiotemporal atlas of mouse liver homeostasis and regeneration.

The mechanism by which mammalian liver cell responses are coordinated during tissue homeostasis and perturbation is poorly understood, representing a major obstacle in our understanding of many diseases. This knowledge gap is caused by the difficulty involved with studying multiple cell types in different states and locations, particularly when these are transient. We have combined Stereo-seq (spatiotemporal enhanced resolution omics-sequencing) with single-cell transcriptomic profiling of 473,290 cells to generate a high-definition spatiotemporal atlas of mouse liver homeostasis and regeneration at the whole-lobe scale. Our integrative study dissects in detail the molecular gradients controlling liver cell function, systematically defining how gene networks are dynamically modulated through intercellular communication to promote regeneration. Among other important regulators, we identified the transcriptional cofactor TBL1XR1 as a rheostat linking inflammation to Wnt/ß-catenin signaling for facilitating hepatocyte proliferation. Our data and analytical pipelines lay the foundation for future high-definition tissue-scale atlases of organ physiology and malfunction.

CHMP5 attenuates osteoarthritis via inhibiting chondrocyte apoptosis and extracellular matrix degradation: involvement of NF-κB pathway.

BACKGROUND: Osteoarthritis (OA), the most common joint disease, is linked with chondrocyte apoptosis and extracellular matrix (ECM) degradation. Charged multivesicular body protein 5 (CHMP5), a member of the multivesicular body, has been reported to serve as an anti-apoptotic protein to participate in leukemia development. However, the effects of CHMP5 on apoptosis and ECM degradation in OA remain unclear. METHODS: In this study, quantitative proteomics was performed to analyze differential proteins between normal and OA patient articular cartilages. The OA mouse model was constructed by the destabilization of the medial meniscus (DMM). In vitro, interleukin-1 beta (IL-1ß) was used to induce OA in human chondrocytes. CHMP5 overexpression and silencing vectors were created using an adenovirus system. The effects of CHMP5 on IL-1ß-induced chondrocyte apoptosis were investigated by CCK-8, flow cytometry, and western blot. The effects on ECM degradation were examined by western blot and immunofluorescence. The potential mechanism was explored by western blot and Co-IP assays. RESULTS: Downregulated CHMP5 was identified by proteomics in OA patient cartilages, which was verified in human and mouse articular cartilages. CHMP5 overexpression repressed cell apoptosis and ECM degradation in OA chondrocytes. However, silencing CHMP5 exacerbated OA chondrocyte apoptosis and ECM degradation. Furthermore, we found that the protective effect of CHMP5 against OA was involved in nuclear factor kappa B (NF-κB) signaling pathway. CONCLUSIONS: This study demonstrated that CHMP5 repressed IL-1ß-induced chondrocyte apoptosis and ECM degradation and blocked NF-κB activation. It was shown that CHMP5 might be a novel potential therapeutic target for OA in the future.

The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML.

Differentiation therapy based on ATRA almost cured acute promyelocytic leukemia (APL). However, it is disappointing that ATRA is not effective against other acute myeloid leukemia (AML) subtypes. Developing new and effective anti-AML therapies that promote leukemia differentiation is necessary. The CDK4/6-cyclin D pathway is a key initiator of the G1-S phase transition, which determines cell fate. Herein, we investigated whether the CDK4/6 inhibitor palbociclib would synergize with ATRA to promote leukemia differentiation in vitro and in vivo. Our findings revealed that CDK4/6-cyclin D pathway genes were aberrantly expressed in AML, and we observed that palbociclib sensitized AML cells to ATRA-induced morphologic, biochemical, and functional changes indicative of myeloid differentiation. The combination of palbociclib and ATRA attenuated AML cell expansion in vivo. These enhanced differentiation effects may be associated with the regulation of transcription factors, including RARα, E2F1, and STAT1. Overall, our findings demonstrate that CDK4/6 inhibition sensitizes AML cells to ATRA and could guide the development of novel therapeutic strategies for patients with AML.

Antibody Nanotweezer Constructing Bivalent Transistor-Biomolecule Interface with Spatial Tolerance.

Establishing a multivalent interface between the biointerface of a living system and electronic device is vital to building intelligent bioelectronic systems. How to achieve multivalent binding with spatial tolerance at the nanoscale remains challenging. Here, we report an antibody nanotweezer that is a self-adaptive bivalent nanobody enabling strong and resilient binding between transistor and envelope proteins at biointerfaces. The antibody nanotweezer is constructed by a DNA framework, where the nanoscale patterning of nanobodies along with their local spatial adaptivity enables simultaneous recognition of target epitopes without binding stress. As such, effective binding affinity increases by 1 order of magnitude compared with monovalent antibody. The antibody nanotweezer operating on transistor offers enhanced signal transduction, which is implemented to detect clinical pathogens, showing ∼100% overall agreement with PCR results. This work provides a perspective of engineering multivalent interfaces between biosystems with solid-state devices, holding great potential for organoid intelligence on a chip.

Spatially and Temporally Resolved Dynamic Response of Co-Based Composite Interface during the Oxygen Evolution Reaction.

Interfacial interaction dictates the overall catalytic performance and catalytic behavior rules of the composite catalyst. However, understanding of interfacial active sites at the microscopic scale is still limited. Importantly, identifying the dynamic action mechanism of the "real" active site at the interface necessitates nanoscale, high spatial-time-resolved complementary-operando techniques. In this work, a Co3O4 homojunction with a well-defined interface effect is developed as a model system to explore the spatial-correlation dynamic response of the interface toward oxygen evolution reaction. Quasi in situ scanning transmission electron microscopy-electron energy-loss spectroscopy with high spatial resolution visually confirms the size characteristics of the interface effect in the spatial dimension, showing that the activation of active sites originates from strong interfacial electron interactions at a scale of 3 nm. Multiple time-resolved operando spectroscopy techniques explicitly capture dynamic changes in the adsorption behavior for key reaction intermediates. Combined with density functional theory calculations, we reveal that the dynamic adjustment of multiple adsorption configurations of intermediates by highly activated active sites at the interface facilitates the O-O coupling and *OOH deprotonation processes. The dual dynamic regulation mechanism accelerates the kinetics of oxygen evolution and serves as a pivotal factor in promoting the oxygen evolution activity of the composite structure. The resulting composite catalyst (Co-B@Co3O4/Co3O4 NSs) exhibits an approximately 70-fold turnover frequency and 20-fold mass activity than the monomer structure (Co3O4 NSs) and leads to significant activity (η10 ∼257 mV). The visual complementary analysis of multimodal operando/in situ techniques provides us with a powerful platform to advance our fundamental understanding of interfacial structure-activity relationships in composite structured catalysts.

Prevention and treatment of HPV-related cancer through a mRNA vaccine expressing APC-targeting antigen.

Persistent human papillomavirus (HPV) infection is associated with multiple malignancies. Developing therapeutic vaccines to eliminate HPV-infected and malignant cells holds significant value. In this study, we introduced a lipid nanoparticle encapsulated mRNA vaccine expressing tHA-mE7-mE6. Mutations were introduced into E6 and E7 of HPV to eliminate their tumourigenicity. A truncated influenza haemagglutinin protein (tHA), which binds to the CD209 receptor on the surface of dendritic cells (DCs), was fused with mE7-mE6 in order to allow efficient uptake of antigen by antigen presenting cells. The tHA-mE7-mE6 (mRNA) showed higher therapeutic efficacy than mE7-mE6 (mRNA) in an E6 and E7+ tumour model. The treatment resulted in complete tumour regression and prevented tumour formation. Strong CD8+ T-cell immune response was induced, contributing to preventing and curing of E6 and E7+ tumour. Antigen-specific CD8+ T were found in spleens, peripheral blood and in tumours. In addition, the tumour infiltration of DC and NK cells were increased post therapy. In conclusion, this study described a therapeutic mRNA vaccine inducing strong anti-tumour immunity in peripheral and in tumour microenvironment, holding promising potential to treat HPV-induced cancer and to prevent cancer recurrence.

Efficient catalyst-free N2 fixation by water radical cations under ambient conditions.

The growth and sustainable development of humanity is heavily dependent upon molecular nitrogen (N2) fixation. Herein we discover ambient catalyst-free disproportionation of N2 by water plasma which occurs via the distinctive HONH-HNOH+• intermediate to yield economically valuable nitroxyl (HNO) and hydroxylamine (NH2OH) products. Calculations suggest that the reaction is prompted by the coordination of electronically excited N2 with water dimer radical cation, (H2O)2+•, in its two-center-three-electron configuration. The reaction products are collected in a 76-needle array discharge reactor with product yields of 1.14 µg cm-2 h-1 for NH2OH and 0.37 µg cm-2 h-1 for HNO. Potential applications of these compounds are demonstrated to make ammonia (for NH2OH), as well as to chemically react and convert cysteine, and serve as a neuroprotective agent (for HNO). The conversion of N2 into HNO and NH2OH by water plasma could offer great profitability and reduction of polluting emissions, thus giving an entirely look and perspectives to the problem of green N2 fixation.

A Dynamics-Learning Multirate Estimation Approach for the Feeding Condition Perception of Complex Industry Processes.

In this study, we propose a dynamics-learning multirate estimation approach to perceive the quality-related indices (QRIs) of the feeding solution of a unit process. A quality-related index for estimation is an intermediate technical indicator between a unit process and a proceeding unit process; hence, the estimation problem is formulated as a two-stage estimation problem utilizing the production data of both unit processes. Dynamics-learning bidirectional long short-term memory (BiLSTM) with different inputs for the forward and backward layers is proposed to manage the input data from the different unit processes. In the dynamics-learning BiLSTM, a cycle control gate is added in the memory cell to learn the dynamics of the QRIs, thereby enabling a high-rate estimation under multirate conditions. A Bayesian estimation model is then combined with the dynamics-learning BiLSTM model to manage the process delay. Ablation and comparative experiments are conducted to evaluate the feasibility and effectiveness of the proposed estimation approach. The experimental results illustrate the performance and high-rate estimation ability of the proposed approach.

Error-Triggered Adaptive Sparse Identification for Predictive Control and Its Application to Multiple Operating Conditions Processes.

With the digital transformation of process manufacturing, identifying the system model from process data and then applying to predictive control has become the most dominant approach in process control. However, the controlled plant often operates under changing operating conditions. What is more, there are often unknown operating conditions such as first appearance operating conditions, which make traditional predictive control methods based on identified model difficult to adapt to changing operating conditions. Moreover, the control accuracy is low during operating condition switching. To solve these problems, this article proposes an error-triggered adaptive sparse identification for predictive control (ETASI4PC) method. Specifically, an initial model is established based on sparse identification. Then, a prediction error-triggered mechanism is proposed to monitor operating condition changes in real time. Next, the previously identified model is updated with the fewest modifications by identifying parameter change, structural change, and combination of changes in the dynamical equations, thus achieving precise control to multiple operating conditions. Considering the problem of low control accuracy during the operating condition switching, a novel elastic feedback correction strategy is proposed to significantly improve the control accuracy in the transition period and ensure accurate control under full operating conditions. To verify the superiority of the proposed method, a numerical simulation case and a continuous stirred tank reactor (CSTR) case are designed. Compared with some state-of-the-art methods, the proposed method can rapidly adapt to frequent changes in operating conditions, and it can achieve real-time control effects even for unknown operating conditions such as first appearance operating conditions.

A novel human single-domain antibody-drug conjugate targeting CEACAM5 exhibits potent in vitro and in vivo antitumor activity.

Leveraging the specificity of antibody to deliver cytotoxic agent into tumor, antibody-drug conjugates (ADCs) have become one of the hotspots in the development of anticancer therapies. Although significant progress has been achieved, there remain challenges to overcome, including limited penetration into solid tumors and potential immunogenicity. Fully human single-domain antibodies (UdAbs), with their small size and human nature, represent a promising approach for addressing these challenges. Carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) is a glycosylated cell surface protein that rarely expressed in normal adult tissues but overexpressed in diverse cancers, taking part in tumorigenesis, progression, and metastasis. In this study, we investigated the therapeutic potential of UdADC targeting CEACAM5. We performed biopanning in our library and obtained an antibody candidate B9, which bound potently and specifically to CEACAM5 protein (KD = 4.84 nM) and possessed excellent biophysical properties (low aggregation tendency, high homogeneity, and thermal stability). The conjugation of B9 with a potent cytotoxic agent, monomethyl auristatin E (MMAE), exhibited superior antitumor efficacy against CEACAM5-expressing human gastric cancer cell line MKN-45, human pancreatic carcinoma cell line BxPC-3 and human colorectal cancer cell line LS174T with IC50 values of 38.14, 25.60, and 101.4 nM, respectively. In BxPC-3 and MKN-45 xenograft mice, administration of UdADC B9-MMAE (5 mg/kg, i.v.) every 2 days for 4 times markedly inhibited the tumor growth without significant change in body weight. This study may have significant implications for the design of next-generation ADCs.