Objective To propose a method for mass spectrometry imaging(MSI)super-resolution reconstruction based on a spatially multi-level and self-supervised deep learning network(SMSDL-Net),aiming to improve the resolution of mass spectrometry images.Methods SMSDL-Net firstly registered histological and mass spectrometry images using a nonlinear transformation.Then a multi-branch Vision Transformer(ViT)was utilized to extract hierarchical features of high-resolution histological images in a self-supervised manner.These features were subsequently combined with the paired low-resolution mass spectrometry data to construct a regression network,which could realize the prediction of high-resolution mass spectrometry information.To validate the performance of the proposed method,the results by the method were compared with those of the traditional bicubic interpolation(BI)methods based on interpolation processing and the deepFERE method based on convolution neural network(CNN)for super-resolution reconstruction of magnesium elemental image of metal mass spectrometry of human liver cancer samples,and the method was also applied to a mouse renal adenocarcinoma metabolite mass spectrometry imaging dataset.Results Compared with the traditional BI methods and the deepFERE multimodal method,the method proposed demonstrated the lowest root mean square error(RMSE=0.015),the highest structural similarity index measure(SSIM=0.84)and the highest R-squared value(R2=0.853)in reconstructing mass spectrometry images.The effectiveness of the method and its potential for precise tissue-specific distinction were validated using the mouse renal adenocarcinoma metabolite MSI dataset.Conclusion Compared with traditional single-modal and pixel-wise regression deep learning methods,the method proposed enhances the quality of high-resolution mass spectrometry image reconstruction and can serve as a novel method for super-resolution reconstruction in the field of mass spectrometry imaging.[Chinese Medical Equipment Journal,2025,46(4):1-8]

Endosomes are characterized by the presence of various phosphoinositides that are essential for defining the membrane properties. However, the interplay between endosomal phosphoinositides metabolism and innate immunity is yet to be fully understood. Here, our findings highlight the evolutionary continuity of RAB-10/Rab10's involvement in regulating innate immunity. Upon infection of Caenorhabditis elegans with Pseudomonas aeruginosa, an increase in RAB-10 activity was observed in the intestine. Conversely, when RAB-10 was absent, the intestinal diacylglycerols (DAGs) decreased, and the animal's response to the pathogen was impaired. Further research revealed that UNC-16/JIP3 acts as an RAB-10 effector, facilitating the recruitment of phospholipase EGL-8 to endosomes. This leads to a decrease in endosomal phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) and an elevation of DAGs, as well as the activation of the PMK-1/p38 MAPK innate immune pathway. It is noteworthy that the dimerization of UNC-16 is a prerequisite for its interaction with RAB-10(GTP) and the recruitment of EGL-8. Moreover, we ascertained that the rise in RAB-10 activity, due to infection, was attributed to the augmented expression of LET-413/Erbin, and the nuclear receptor NHR-25/NR5A1/2 was determined to be indispensable for this increase. Hence, this study illuminates the significance of endosomal PI(4,5)P2 catabolism in boosting innate immunity and outlines an NHR-25-mediated mechanism for pathogen detection in intestinal epithelia.
Animals ; Caenorhabditis elegans/genetics* ; Endosomes/immunology* ; Caenorhabditis elegans Proteins/immunology* ; Phosphatidylinositol 4,5-Diphosphate/immunology* ; Immunity, Innate ; Pseudomonas aeruginosa/immunology* ; rab GTP-Binding Proteins/genetics* ; Diglycerides/metabolism*

From the perspective of competitive endogenous RNA(ceRNA) constructed by metastasy-associated lung adenocarcinoma transcript 1(Malat1) and microRNA 16-5p(miR-16-5p), the improvement mechanism of Tonggu Xiaotong Capsules(TGXTC) on the imbalance and disorder of "cholesterol-iron" metabolism in chondrocytes of osteoarthritis(OA) was explored. In vivo experiments, 60 8-week-old C57BL/6 mice were acclimatized and fed for 1 week and then randomly divided into two groups: blank group(12 mice) and modeling group(48 mice). The animals in modeling group were anesthetized by 5% isoflurane inhalation, which was followed by the construction of OA model. They were then randomly divided into model group, TGXTC group, Malat1 overexpression group, and TGXTC+Malat1 overexpression(TGXTC+Malat1-OE) group, with 12 mice in each group. The structural changes of mouse cartilage tissues were observed by Masson staining after the intervention in each group. RT-PCR was employed to detect the mRNA levels of Malat1 and miR-16-5p in cartilage tissues. Western blot was used to analyze the protein expression of ATP-binding cassette transporter A1(ABCA1), sterol regulatory element-binding protein(SREBP), cytochrome P450 family 7 subfamily B member 1(CYP7B1), CCAAT/enhancer-binding protein homologous protein(CHOP), acyl-CoA synthetase long-chain family member 4(ACSL4), and glutathione peroxidase 4(GPX4) in cartilage tissues. In vitro experiments, mouse chondrocytes were induced by thapsigargin(TG), and the combination of Malat1 and miR-16-5p was detected by double luciferase assay. The fluorescence intensity of Malat1 in chondrocytes was determined by fluorescence in situ hybridization. The miR-16-5p inhibitory chondrocyte model was constructed. RT-PCR was used to analyze the levels of Malat1 and miR-16-5p in chondrocytes under the inhibition of miR-16-5p. Western blot was adopted to analyze the regulation of TG-induced chondrocyte proteins ABCA1, SREBP, CYP7B1, CHOP, ACSL4, and GPX4 by TGXTC under the inhibition of miR-16-5p. The results of in vivo experiments showed that,(1) compared with model group, TGXTC group exhibited a relatively complete cartilage layer structure. Compared with Malat1-OE group, TGXTC+Malat1-OE group showed alleviated cartilage surface damage.(2) Compared with model group, TGXTC group had a significantly decreased Malat1 mRNA level and an increased miR-16-5p mRNA level in mouse cartilage tissues(P<0.01).(3) Compared with the model group, the protein levels of ABCA1 and GPX4 in the cartilage tissue of mice in the TGXTC group increased, while the protein levels of SREBP, CYP7B1, CHOP and ACSL4 decreased(P<0.01). The results of in vitro experiments show that,(1) dual-luciferase was used to evaluate that miR-16-5p has a targeting effect on the Malat1 gene.(2)Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group had an increased mRNA level of miR-16-5p and an decreased mRNA level of Malat1(P<0.01).(3) Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group exhibited increased expression of ABCA1 and GPX4 proteins and decreased expression of SREBP, CYP7B1, CHOP, and ACSL4 proteins(P<0.01). The reasults showed that TGXTC can regulate the ceRNA of Malat1 and miR-16-5p to alleviate the "cholesterol-iron" metabolism disorder of osteoarthritis chondrocytes.
Animals ; MicroRNAs/metabolism* ; RNA, Long Noncoding/metabolism* ; Chondrocytes/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice, Inbred C57BL ; Mice ; Osteoarthritis/drug therapy* ; Iron/metabolism* ; Male ; Cholesterol/metabolism* ; Humans ; Capsules ; RNA, Competitive Endogenous

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Objective To propose a method for mass spectrometry imaging(MSI)super-resolution reconstruction based on a spatially multi-level and self-supervised deep learning network(SMSDL-Net),aiming to improve the resolution of mass spectrometry images.Methods SMSDL-Net firstly registered histological and mass spectrometry images using a nonlinear transformation.Then a multi-branch Vision Transformer(ViT)was utilized to extract hierarchical features of high-resolution histological images in a self-supervised manner.These features were subsequently combined with the paired low-resolution mass spectrometry data to construct a regression network,which could realize the prediction of high-resolution mass spectrometry information.To validate the performance of the proposed method,the results by the method were compared with those of the traditional bicubic interpolation(BI)methods based on interpolation processing and the deepFERE method based on convolution neural network(CNN)for super-resolution reconstruction of magnesium elemental image of metal mass spectrometry of human liver cancer samples,and the method was also applied to a mouse renal adenocarcinoma metabolite mass spectrometry imaging dataset.Results Compared with the traditional BI methods and the deepFERE multimodal method,the method proposed demonstrated the lowest root mean square error(RMSE=0.015),the highest structural similarity index measure(SSIM=0.84)and the highest R-squared value(R2=0.853)in reconstructing mass spectrometry images.The effectiveness of the method and its potential for precise tissue-specific distinction were validated using the mouse renal adenocarcinoma metabolite MSI dataset.Conclusion Compared with traditional single-modal and pixel-wise regression deep learning methods,the method proposed enhances the quality of high-resolution mass spectrometry image reconstruction and can serve as a novel method for super-resolution reconstruction in the field of mass spectrometry imaging.[Chinese Medical Equipment Journal,2025,46(4):1-8]

Objective To study the synergistic effects of gentiopicroside combined with pabolizumab on photodynamic therapy in mice with breast cancer.Methods MCF-7 cells were injected subcutaneously to establish a tumor bearing mouse model of breast cancer and were randomly divided into model group,control group,positive control group,experimental group and combination group,with 10 mice in each group.The control group was intraperitoneally injected with 50 mg·kg-1 of 5-aminolevulinic acid and irradiated with 200 J·cm-2 laser for 20 min,once a week.The positive control group was intraperitoneally injected with 100μg·kg-1 pabolizumab,twice a week,and photodynamic therapy once a week,the experimental group was intragastric given 100 mg·kg-1 gentiopicroside,once a day,and photodynamic therapy once a week,the combined group was intraperitoneally injected with pabolizumab(100 μg·kg-1),twice a week,and gavage of gentiopicroside(100 mg·kg-1)once a day and photodynamic therapy once a week.Five groups of mice were given the drug for 3 weeks.The tumor inhibition rate of each group was compared,and the levels of interleukin(IL)-12,interferon(INF)-γand tumor necrosis factor(TNF)-α were measured by enzyme-linked immunosorbent assay.The levels of B-cell lymphoma-2 associated gene(Bax),B-lymphoblastoma-2 gene(Bcl-2)and vascular endothelial growth factor(VEGF)protein in tumor tissues were determined by Western blot.Results The tumor inhibition rates of control,positive control,experimental and combined groups were(22.38±2.26)％,(42.27±3.21)％,(38.16±2.17)％and(60.24±2.84)％,respectively.The serum IL-12 levels of model,control,positive control,experimental and combined groups were(127.13±1.25),(132.29±2.31),(155.27±1.48),(163.31±2.67)and(185.24±1.71)pg·mL-1;INF-γ levels were(724.16±3.63),(891.12±4.45),(1 043.19±3.85),(1 082.34±4.51)and(1 492.13±6.57)pg·mL-1;TNF-α levels were(83.81±4.52),(65.26±3.77),(41.07±3.85),(43.59±3.94)and(27.12±3.93)pg·mL-1;the relative protein expression levels of Bax were 0.30±0.08,0.47±0.05,0.67±0.11,0.89±0.06 and 1.03±0.10;the relative protein expression levels of Bcl-2 were 0.99±0.04,0.86±0.06,0.71±0.05,0.46±0.06 and 0.31±0.08;the relative protein expression levels of VEGF were 1.06±0.04,0.92±0.03,0.76±0.04,0.49±0.04 and 0.29±0.08.The differences of above indexes between the combined group and the control,positive control group and experimental groups were statistically significant(all P＜0.05).Conclusion Gentiopicroside combined with pembrolizumab can significantly enhance the tumor inhibition effect of photodynamic therapy on breast cancer mice,promote the apoptosis of breast cancer cells,and then inhibit the tumor progression of breast cancer mice.

Spinal cord injury (SCI) is a devastating traumatic disease seriously impairing the quality of life in patients. Expectations to allow the hopeless central nervous system to repair itself after injury are unfeasible. Developing new approaches to regenerate the central nervous system is still the priority. Exosomes derived from mesenchymal stem cells (MSC-Exo) have been proven to robustly quench the inflammatory response or oxidative stress and curb neuronal apoptosis and autophagy following SCI, which are the key processes to rescue damaged spinal cord neurons and restore their functions. Nonetheless, MSC-Exo in SCI received scant attention. In this review, we reviewed our previous work and other studies to summarize the roles of MSC-Exo in SCI and its underlying mechanisms. Furthermore, we also focus on the application of exosomes as drug carrier in SCI. In particular, it combs the advantages of exosomes as a drug carrier for SCI, imaging advantages, drug types, loading methods, etc., which provides the latest progress for exosomes in the treatment of SCI, especially drug carrier.

Inertial microfluidics,as a microfluidic technology with the ability to precisely manipulate particles and cells with high throughput,has attracted widespread attention.However,challenges remain in achieving particle focusing with insensitivity to flow rates in large-scale channels,mainly due to the instability of secondary flows within the inertial microfluidic chip.This study developed a microstructure-assisted ultra-low aspect ratio spiral microchannel,which utilized the stability and acceleration of secondary flows to achieve inertial particle focusing.The research results demonstrated successful particle focusing within a 1 mm-wide spiral channel chip,for different diameter sizes(7.3 μm and 15.5 μm),within a wide range of flow rates(0.5-3 mL/min).The focusing efficiencies for these particles were measured to be above 94%and 99%,respectively.Additionally,it was observed that the particle focusing position was approximately 100 μm away from the channel walls,significantly larger than other inertial focusing chips.Consequently,by incorporating ordered microstructures within the spiral channel chip,the stability and enhancement of secondary flows were achieved,resulting in flow rate and particle size-insensitive inertial focusing.Compared to traditional methods of inertial focusing,this design had advantages of not requiring additional sheath flow operations,and boasted high throughput and ease of manufacturing.This innovative structure opened up vast prospects for the development of portable inertial microfluidic chips,and could be used in the fields such as cell analysis and detection,flow cytometry,and online sample processing.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.