A rational designed multi-epitope vaccine elicited robust protective efficacy against Klebsiella pneumoniae lung infection.

BACKGROUND: The emergence of drug-resistant strains of Klebsiella pneumoniae (K. pneumoniae) has become a significant challenge in the field of infectious diseases, posing an urgent need for the development of highly protective vaccines against this pathogen. METHODS AND RESULTS: In this study, we identified three immunogenic extracellular loops based on the structure of five candidate antigens using sera from K. pneumoniae infected mice. The sequences of these loops were linked to the C-terminal of an alpha-hemolysin mutant (mHla) from Staphylococcus aureus to generate a heptamer, termed mHla-EpiVac. In vivo studies confirmed that fusion with mHla significantly augmented the immunogenicity of EpiVac, and it elicited both humoral and cellular immune responses in mice, which could be further enhanced by formulation with aluminum adjuvant. Furthermore, immunization with mHla-EpiVac demonstrated enhanced protective efficacy against K. pneumoniae channeling compared to EpiVac alone, resulting in reduced bacterial burden, secretion of inflammatory factors, histopathology and lung injury. Moreover, mHla fusion facilitated antigen uptake by mouse bone marrow-derived cells (BMDCs) and provided sustained activation of these cells. CONCLUSIONS: These findings suggest that mHla-EpiVac is a promising vaccine candidate against K. pneumoniae, and further validate the potential of mHla as a versatile carrier protein and adjuvant for antigen design.

Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis.

BACKGROUND: Long-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to diagnose arrhythmias, and this is a particular issue in more remote and underdeveloped areas. The development of digital ECG and AI methods could assist clinicians who need to diagnose arrhythmias outside of the hospital setting. METHODS: We constructed a large-scale Chinese ECG benchmark dataset using data from 272,753 patients collected from January 2017 to December 2021. The dataset contains ECG recordings from all common arrhythmias present in the Chinese population. Several experienced cardiologists from Shanghai First People's Hospital labeled the dataset. We then developed a deep learning-based multi-label interpretable diagnostic model from the ECG recordings. We utilized Accuracy, F1 score and AUC-ROC to compare the performance of our model with that of the cardiologists, as well as with six comparison models, using testing and hidden data sets. RESULTS: The results show that our approach achieves an F1 score of 83.51%, an average AUC ROC score of 0.977, and 93.74% mean accuracy for 6 common arrhythmias. Results from the hidden dataset demonstrate the performance of our approach exceeds that of cardiologists. Our approach also highlights the diagnostic process. CONCLUSIONS: Our diagnosis system has superior diagnostic performance over that of clinicians. It also has the potential to help clinicians rapidly identify abnormal regions on ECG recordings, thus improving efficiency and accuracy of clinical ECG diagnosis in China. This approach could therefore potentially improve the productivity of out-of-hospital ECG diagnosis and provides a promising prospect for telemedicine.

Arrhythmia, also known as an irregular heartbeat, is a common cardiovascular disease. Sometimes the presence of an arrhythmia can increase the risk of more serious heart conditions. Long-term monitoring of the heartbeat enables arrhythmia to be more easily diagnosed. To accurately detect arrhythmia, we developed a computational model that was able to detect six common types of arrhythmias from readings of the heart rate obtained using a device connected to a mobile phone. We showed that our model could diagnose these arrhythmias in over 270,000 people living in China. Our diagnostic system could enable arrhythmias to be diagnosed more easily outside of hospitals and therefore improve access to healthcare, particularly for those in remote settings.

Antibody-antibiotic conjugate targeted therapy for orthopedic implant-associated intracellular S. aureus infections.

INTRODUCTION: Treating orthopedic implant-associated infections, especially those caused by Staphylococcus aureus (S. aureus), remains a significant challenge. S. aureus has the ability to invade host cells, enabling it to evade both antibiotics and immune responses during infection, which may result in clinical treatment failures. Therefore, it is critical to identify the host cell type of implant-associated intracellular S. aureus infections and to develop a strategy for highly targeted delivery of antibiotics to the host cells. OBJECTIVES: Introduced an antibody-antibiotic conjugate (AAC) for the targeted elimination of intracellular S. aureus. METHODS: The AAC comprises of a human monoclonal antibody (M0662) directly recognizes the surface antigen of S. aureus, Staphylococcus protein A, which is conjugated with vancomycin through cathepsin-sensitive linkers that are cleavable in the proteolytic environment of the intracellular phagolysosome. AAC, vancomycin and vancomycin combined with AAC were used in vitro intracellular infection and mice implant infection models. We then tested the effect of AAC in vivo and in vivo by fluorescence imaging, in vivo imaging, bacterial quantitative analysis and bacterial biofilm imaging. RESULTS: In vitro, it was observed that AAC captured extracellular S. aureus and co-entered the cells, and subsequently released vancomycin to induce rapid elimination of intracellular S. aureus. In the implant infection model, AAC significantly improved the bactericidal effect of vancomycin. Scanning electron microscopy showed that the application of AAC effectively blocked the formation of bacterial biofilm. Further histochemical and micro-CT analysis showed AAC significantly reduced the level of bone marrow density (BMD) and bone volume fraction (BV/TV) reduction caused by bacterial infection in the distal femur of mice compared to vancomycin treatment alone. CONCLUSIONS: The application of AAC in an implant infection model showed that it significantly improved the bactericidal effects of vancomycin and effectively blocked the formation of bacterial biofilms, without apparent toxicity to the host.

The prolyl isomerase Pin1 stabilizes NeuroD during differentiation of mechanoreceptors.

The peptidyl prolyl cis-trans isomerase Pin1 plays vital roles in diverse cellular processes and pathological conditions. NeuroD is a differentiation and survival factor for a subset of neurons and pancreatic endocrine cells. Although multiple phosphorylation events are known to be crucial for NeuroD function, their mechanisms remain elusive. In this study, we demonstrate that zebrafish embryos deficient in Pin1 displayed phenotypes resembling those associated with NeuroD depletion, characterized by defects in formation of mechanosensory hair cells. Furthermore, zebrafish Pin1 interacts with NeuroD in a phosphorylation-dependent manner. In Pin1-deficient cell lines, NeuroD is rapidly degraded. However, the protein stability of NeuroD is restored upon overexpression of Pin1. These findings suggest that Pin1 functionally regulates NeuroD protein levels by post-phosphorylation cis-trans isomerization during neuronal specification.

S-nitrosylation of RABG3E positively regulates vesicle trafficking to promote salt tolerance.

Nitric oxide (NO) is a key signaling molecule affecting the response of plants to salt stress; however, the underlying molecular mechanism is poorly understood. In this study, we conducted a phenotype analysis and found that the small GTPase RABG3E (RAB7) promotes salt tolerance in Arabidopsis thaliana. NO promotes the S-nitrosylation of RAB7 at Cys-171, which in turn helps maintain the ion balance in salt-stressed plants. Furthermore, the S-nitrosylation of RAB7 at Cys-171 enhances the enzyme's GTPase activity, thereby promoting vesicle trafficking and increasing its interaction with phosphatidylinositol phosphates-especially phosphatidylinositol-4-phosphate (PI4P). Exogenously applied PI4P increases vesicle trafficking and promotes salt tolerance depending on the S-nitrosylation of RAB7 at Cys-171. These findings illustrate a unique mechanism in salt tolerance, by which NO regulates vesicle trafficking and ion homeostasis through the S-nitrosylation of RAB7 and its interaction with PI4P.

rFSAV promotes Staphylococcus aureus-infected bone defect healing via IL-13- mediated M2 macrophage polarization.

Staphylococcus aureus (S. aureus) contamination commonly occurs in orthopedic internal fixation operations, leading to a delayed healing of the defected bone tissue. However, antibiotic treatments are ineffective in dealing with S. aureus bone infections due to the rise in multiple antimicrobial resistances. Here, we reported the protective effects of a recombinant five-antigen S. aureus vaccine (rFSAV) in an S. aureus infected bone defect model. In this study, we found the number of M2 macrophages markedly increased in the defect site and played a critical role in the healing of defected bone mediated by rFSAV. Mechanistically, rFSAV mediated increased level of IL-13 in bone defect site predominant M2 macrophage polarization. In summary, our study reveals a key role of M2 macrophage polarization in the bone regeneration process in S. aureus infection induced bone defect, which provide a promising application of rFSAV for the treatment of bone infection for orthopedic applications.

Calcium Signaling and the Response to Heat Shock in Crop Plants.

Climate change and the increasing frequency of high temperature (HT) events are significant threats to global crop yields. To address this, a comprehensive understanding of how plants respond to heat shock (HS) is essential. Signaling pathways involving calcium (Ca2+), a versatile second messenger in plants, encode information through temporal and spatial variations in ion concentration. Ca2+ is detected by Ca2+-sensing effectors, including channels and binding proteins, which trigger specific cellular responses. At elevated temperatures, the cytosolic concentration of Ca2+ in plant cells increases rapidly, making Ca2+ signals the earliest response to HS. In this review, we discuss the crucial role of Ca2+ signaling in raising plant thermotolerance, and we explore its multifaceted contributions to various aspects of the plant HS response (HSR).

Multiple high-regional-incidence cardiac disease diagnosis with deep learning and its potential to elevate cardiologist performance.

Currently, due to lack of large-scale datasets containing multiple arrhythmias and acute coronary syndrome-related diseases, AI-aided diagnosis for cardiac diseases is limited in clinical scenarios. Whether AI-based ECG diagnosis can assist cardiologists to improve performance has not been reported. We constructed a large-scale dataset containing multiple high-regional-incidence arrhythmias and ACS-related diseases, including 162,622 12-lead ECGs collected between January 2018 and March 2021. We presented a deep learning model for clinical ECG diagnosis of multiple cardiac diseases. Results show that our model for diagnosing 15 cardiac abnormalities achieved 88.216% accuracy, and its average AUC ROC score reached 0.961. On the board-certified re-annotated dataset, its performance surpasses that of cardiologists in non-reference group. Moreover, with aid of labels given by our model, accuracy and efficiency for cardiologist increased by 13.5% and 69.9% than non-reference group. Our approach provides solutions for AI-aided diagnosis systems of cardiac diseases in applications.

A novel P-QRS-T wave localization method in ECG signals based on hybrid neural networks.

As the number of people suffering from cardiovascular diseases increases every year, it becomes essential to have an accurate automatic electrocardiogram (ECG) diagnosis system. Researchers have adopted different methods, such as deep learning, to investigate arrhythmias classification. However, the importance of ECG waveform features is generally ignored when deep learning approaches are applied to classification tasks. P-wave, QRS-wave, and T-wave, containing plenty of physiological information, are three critical waves in the ECG heartbeat. The accurate localization of these critical ECG wave components is a prerequisite for ECG classification and diagnosis. In this study, a novel P-QRS-T wave localization method based on hybrid neural networks is proposed. The raw ECG signal is preprocessed sequentially by filtering, heartbeat extraction, and data standardization. The hybrid neural network is constructed by combining the residual neural network (ResNet) and the Long Short-Term Memory (LSTM). It predicts the relative positions of the P-peak, QRS-peak, and T-peak for each heartbeat. The proposed algorithm was validated on four ECG databases with input noise of different signal-to-noise ratio (SNR) levels. The results show that the proposed method can accurately predict the positions of the three key waves. The proposed P-QRS-T localization approach can improve the efficiency of ECG delineation. Integrated with cardiac disease classification methods, it can contribute to the development of advanced automatic ECG diagnosis systems.

A review of arrhythmia detection based on electrocardiogram with artificial intelligence.

INTRODUCTION: With the widespread availability of portable electrocardiogram (ECG) devices, there will be a surge in ECG diagnoses. Traditional computer-aided diagnosis of arrhythmia mainly relies on the rules of medical knowledge, which are insufficient due to the limitations of data quality and human expert knowledge. The research of arrhythmia detection methods based on artificial intelligence (AI) techniques can assist physicians in high-precision arrhythmia diagnosis. AI algorithms can also be embedded in smart ECG devices to help more people perform early screening for arrhythmia. AREAS COVERED: The primary objective of this paper is to describe the application of AI methods in the process of arrhythmia detection. Meanwhile, the advantages and limitations of various approaches in different applications are summarized to provide guidance and reference for future research work. EXPERT OPINION: Machine learning (ML) and deep learning (DL) algorithms can be more effectively employed to handle ECG signal denoising and quality assessment, wave detection and delineation, and arrhythmia classification problems. The DL approach can automatically learn deep representation features and temporal features of the ECG signal for heartbeat or rhythm classification. The application of AI methods for arrhythmia detection systems will significantly relieve the pressure on physicians to analyze ECGs.

The Role of Nitric Oxide in Plant Responses to Salt Stress.

The gas nitric oxide (NO) plays an important role in several biological processes in plants, including growth, development, and biotic/abiotic stress responses. Salinity has received increasing attention from scientists as an abiotic stressor that can seriously harm plant growth and crop yields. Under saline conditions, plants produce NO, which can alleviate salt-induced damage. Here, we summarize NO synthesis during salt stress and describe how NO is involved in alleviating salt stress effects through different strategies, including interactions with various other signaling molecules and plant hormones. Finally, future directions for research on the role of NO in plant salt tolerance are discussed. This summary will serve as a reference for researchers studying NO in plants.

OsWAK112, A Wall-Associated Kinase, Negatively Regulates Salt Stress Responses by Inhibiting Ethylene Production.

The wall-associated kinase (WAK) multigene family plays critical roles in various cellular processes and stress responses in plants, however, whether WAKs are involved in salt tolerance is obscure. Herein, we report the functional characterization of a rice WAK, WAK112, whose expression is suppressed by salt. Overexpression of OsWAK112 in rice and heterologous expression of OsWAK112 in Arabidopsis significantly decreased plant survival under conditions of salt stress, while knocking down the OsWAK112 in rice increased plant survival under salt stress. OsWAK112 is universally expressed in plant and associated with cell wall. Meanwhile, in vitro kinase assays and salt tolerance analyses showed that OsWAK112 possesses kinase activity and that it plays a negative role in the response of plants to salt stress. In addition, OsWAK112 interacts with S-adenosyl-L-methionine synthetase (SAMS) 1/2/3, which catalyzes SAM synthesis from ATP and L-methionine, and promotes OsSAMS1 degradation under salt stress. Furthermore, in OsWAK112-overexpressing plants, there is a decreased SAMS content and a decreased ethylene content under salt stress. These results indicate that OsWAK112 negatively regulates plant salt responses by inhibiting ethylene production, possibly via direct binding with OsSAMS1/2/3.

Cyclic Nucleotide-Gated Ion Channel 6 Mediates Thermotolerance in Arabidopsis Seedlings by Regulating Hydrogen Peroxide Production via Cytosolic Calcium Ions.

We previously reported the involvement of cyclic nucleotide-gated ion channel 6 (CNGC6) and hydrogen peroxide (H2O2) in plant responses to heat shock (HS). To demonstrate their relationship with plant thermotolerance, we assessed the effect of HS on several groups of Arabidopsis (Arabidopsis thaliana) seedlings: wild-type, cngc6 mutant, and its complementation line. Under exposure to HS, the level of H2O2 was lower in the cngc6 mutant seedlings than in the wild-type (WT) seedlings but obviously increased in the complementation line. The treatment of Arabidopsis seeds with calcium ions (Ca2+) increased the H2O2 levels in the seedlings under HS treatment, whereas treatment with a Ca2+ chelator (EGTA) inhibited it, indicating that CNGC6 may stimulate the accumulation of H2O2 in a manner dependent on an increase in cytosolic Ca2+ ([Ca2+]cyt). This point was verified by phenotypic observations and thermotolerance testing with transgenic plants overexpressing AtRbohB and AtRbohD (two genes involved in HS-responsive H2O2 production), respectively, in a cngc6 background. Real-time reverse transcription-polymerase chain reactions and Western blotting suggested that CNGC6 enhanced the gene transcription of HS factors (HSFs) and the accumulation of HS proteins (HSPs) via H2O2. These upon results indicate that H2O2 acts downstream of CNGC6 in the HS signaling pathway, increasing our understanding of the initiation of plants responses to high temperatures.

A novel self-assembled epitope peptide nanoemulsion vaccine targeting nasal mucosal epithelial cell for reinvigorating CD8+ T cell immune activity and inhibiting tumor progression.

Epitope peptides are not suitable for nasal administration immunity due to their poor immunogenicity and low delivery efficiency. Here, we reported an intranasal self-assembled nanovaccine (I-OVA NE), which was loaded with the peptides IKVAV-OVA257-264 (I-OVA), a laminin peptide (Ile-Lys-Val-ala-Val, IKVAV) and OVA257-264 epitope conjugated peptide. This nanovaccine with I-OVA at a concentration of 4 mg/mL showed the average particle size of 30.37 ± 2.49 nm, zeta potential of -16.67 ± 1.76 mV, and encapsulation rate of 84.07 ± 7.59%. Moreover, the mucin did not alter its stability (size, PdI and zeta potential). And it also had no obvious acute pathological changes neither in the nasal mucosa nor lung tissues after nasal administration. Meanwhile, the antigen uptake of I-OVA NE was promoted, and the nasal residence time was also prolonged in vivo. Besides, the uptake rate of this nanovaccine was obviously higher than that of free I-OVA (P < 0.001) after blocking by the integrin antibody, suggesting that the binding of IKVAV to integrin is involved in the epitope peptide uptake. Importantly, this nanovaccine enhanced peptide-specific CD8+T cells exhibiting OVA257-264-specific CTL activity and Th1 immune response, leading to the induction of the protective immunity in E.G7-OVA tumor-bearing mice. Overall, these data indicate that I-OVA NE can be an applicable strategy of tumor vaccine development.

Rictor, an essential component of mTOR complex 2, undergoes caspase-mediated cleavage during apoptosis induced by multiple stimuli.

Caspase-mediated cleavage of proteins ensures the irreversible commitment of cells to undergo apoptosis, and is thus a hallmark of apoptosis. Rapamycin-insensitive companion of mTOR (rictor) functions primarily as a core and essential component of mTOR complex 2 (mTORC2) to critically regulate cellular homeostasis. However, its role in the regulation of apoptosis is largely unknown. In the current study, we found that rictor was cleaved to generate two small fragments at ~ 50 kD and ~ 130 kD in cells undergoing apoptosis upon treatment with different stimuli such as the death ligand, TRAIL, and the small molecule, AZD9291. This cleavage was abolished when caspases were inhibited and could be reproduced when directly incubating rictor protein and caspase-3 in vitro. Furthermore, the cleavage site of caspase-3 on rictor was mapped at D1244 (VGVD). These findings together robustly demonstrate that rictor is a substrate of caspase-3 and undergoes cleavage during apoptosis. These results add new information for understanding the biology of rictor in the regulation of cell survival and growth.

[A heart sound classification method based on joint decision of extreme gradient boosting and deep neural network].

Heart sound is one of the common medical signals for diagnosing cardiovascular diseases. This paper studies the binary classification between normal or abnormal heart sounds, and proposes a heart sound classification algorithm based on the joint decision of extreme gradient boosting (XGBoost) and deep neural network, achieving a further improvement in feature extraction and model accuracy. First, the preprocessed heart sound recordings are segmented into four status, and five categories of features are extracted from the signals based on segmentation. The first four categories of features are sieved through recursive feature elimination, which is used as the input of the XGBoost classifier. The last category is the Mel-frequency cepstral coefficient (MFCC), which is used as the input of long short-term memory network (LSTM). Considering the imbalance of the data set, these two classifiers are both improved with weights. Finally, the heterogeneous integrated decision method is adopted to obtain the prediction. The algorithm was applied to the open heart sound database of the PhysioNet Computing in Cardiology(CINC) Challenge in 2016 on the PhysioNet website, to test the sensitivity, specificity, modified accuracy and F score. The results were 93%, 89.4%, 91.2% and 91.3% respectively. Compared with the results of machine learning, convolutional neural networks (CNN) and other methods used by other researchers, the accuracy and sensibility have been obviously improved, which proves that the method in this paper could effectively improve the accuracy of heart sound signal classification, and has great potential in the clinical auxiliary diagnosis application of some cardiovascular diseases.

An Immunodominant Epitope-Specific Monoclonal Antibody Cocktail Improves Survival in a Mouse Model of Staphylococcus aureus Bacteremia.

To date, no vaccine or monoclonal antibody (mAb) against Staphylococcus aureus has been approved for use in humans. Our laboratory has developed a 5-antigen S. aureus vaccine (rFSAV), which is now under efficacy evaluation in a phase 2 clinical trial. In the current study, using overlapping peptides and antiserum from rFSAV-immunized volunteers, we identified 7 B-cell immunodominant epitopes on 4 antigens in rFSAV, including 5 novel epitopes (Hla48-65, IsdB402-419, IsdB432-449, SEB78-95, and MntC7-24). Ten immunodominant epitope mAbs were generated against these epitopes, and all of them exhibited partial protection in a mouse sepsis model. Four robust mAbs were used together as an mAb cocktail to prevent methicillin-resistant S. aureus strain 252 infection. The results showed that the mAb cocktail was efficient in combating S. aureus infection and that its protective efficacy correlated with a reduced bacterial burden and decreased infection pathology, which demonstrates that the mAb cocktail is a promising S. aureus vaccine candidate.

Upregulation of Tubulointerstitial nephritis antigen like 1 promotes gastric cancer growth and metastasis by regulating multiple matrix metallopeptidase expression.

BACKGROUND AND AIM: Tubulointerstitial nephritis antigen-like 1 (TINAGL1), as a novel matricellular protein, has been demonstrated to participate in cancer progression, whereas the potential function of TINAGL1 in gastric cancer (GC) remains unknown. METHODS: The expression pattern of TINAGL1 in GC was examined by immunohistochemistry, ELISA, real-time polymerase chain reaction, and Western blot. Correlation between TINAGL1 and matrix metalloproteinases (MMPs) was analyzed by the GEPIA website and Kaplan-Meier plots database. The lentivirus-based TINAGL1 knockdown, CCK-8, and transwell assays were used to test the function of TINAGL1 in vitro. The role of TINAGL1 was confirmed by subcutaneous xenograft, abdominal dissemination, and lung metastasis model. Microarray experiments, ELISA, real-time polymerase chain reaction, and Western blot were used to identify molecular mechanism. RESULTS: TINAGL1 was increased in GC tumor tissues and associated with poor patient survival. Moreover, TINAGL1 significantly promoted GC cell proliferation and migration in vitro as well as facilitated GC tumor growth and metastasis in vivo. TINAGL1 expression in GC cells was accompanied with increasing MMPs including MMP2, MMP9, MMP11, MMP14, and MMP16. GEPIA database revealed that these MMPs were correlated with TINAGL1 in GC tumors and that the most highly expressed MMP was MMP2. Mechanically, TINAGL1 regulated MMP2 through the JNK signaling pathway activation. CONCLUSIONS: Our data highlight that TINAGL1 promotes GC growth and metastasis and regulates MMP2 expression, indicating that TINAGL1 may serve as a therapeutic target for GC.

Application of dexmedetomidine combined with sufentanil in colon cancer resection and its effect on immune and coagulation function of patients.

Application of dexmedetomidine combined with sufentanil in colon cancer resection and its effect on immune and coagulation function of patients was studied. Colon cancer cases (n=176) admitted to Xiangya Hospital Central South University were selected into the study. They were divided into group A (n=92) and group B (n=84). In group A, patients underwent surgery anesthesia with dexmedetomidine combined with sufentanil. In group B, patients underwent surgery anesthesia only with sufentanil. The anesthesia induced intubation, operation time and incidence of postoperative adverse reaction of patients were compared between the two groups. Heart rate (HR), systolic blood pressure (SBP) and diastolic blood pressure (DBP) were observed and recorded before induction, before intubation and after intubation. Blood coagulation analyzer was used to detect four items of coagulation before and after operation. FACSCalibur flow cytometry was used to detect T lymphocyte subsets in peripheral blood of patients in the two groups. The pain scores (VAS) of patients in the two groups were measured and recorded after surgery at 4, 24 and 48 h. There was a difference in anesthesia induced intubation and operation time of patients in both groups (P<0.05). There were differences in HR, SBP and DBP of patients in both groups after intubation (P<0.05), in postoperative coagulation function (P<0.05), and in postoperative immune function of patients in both groups (P<0.05). The VAS scores of patients in both groups were different at different time-points after operation (P<0.05). There were differences in postoperative adverse reactions of patients in both groups (P<0.05). Dexmedetomidine combined with sufentanil is a viable anesthetic regimen for colon cancer resection. The coagulation function and immune function have certain improvement effect for patients.

Water Retention Mechanism of HPMC in Cement Mortar.

In this paper, the effect of HPMC (hydroxypropyl methyl cellulose ether) on the cement mortar water retention (WR) and composition was studied. The relationship between the plastic viscosity and water retention of cement mortar was revealed. The results showed that HPMC formed a colloidal film with a 3D network structure in water, which changed the ability of water to migrate. The HPMC colloid adsorbed on the surface of cement and sand particles and played a bridging role due to the influence of the spatial network structure of the thin film. Fine particles formed a grid-like distribution, and the hydration products formed a unique fibrous tree-like structure. A positive correlation was observed between the plastic viscosity and the water holding capacity of cement mortar. Finally, the mechanism responsible for the improved water retention of cement mortar by HPMC was analyzed using the changing water migration capacity, migration channels, and mortar cohesion.