ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

The machine learning is used increasingly and widely in acupuncture prescription optimization, intelligent treatment and precision medicine, and has obtained a certain achievement. But, there are still some problems remained to be solved such as the poor interpretability of the model, the inconsistency of data quality of acupuncture research, and the clinical application of constructed models. Researches in future should focus on the acquisition of high-quality clinical and experimental data sets, take various machine learning algorithms as the basis, and construct professional models to solve various problems, so as to drive the high-quality development of acupuncture research.
Acupuncture Therapy/trends* ; Machine Learning ; Humans ; Algorithms

OBJECTIVE: To investigate whether auraptene (AUR) exerts a protective effect on acute diquat (DQ)-induced liver injury in mice and explore its underlying mechanisms. METHODS: Forty SPF-grade healthy male C57BL/6 mice were randomly divided into normal control group (Control group), DQ poisoning model group (DQ group), AUR treatment group (DQ+AUR group), and AUR control group (AUR group), with 10 mice in each group. The DQ poisoning model was established via a single intraperitoneal injection of 40 mg/kg DQ aqueous solution (0.5 mL); Control group and AUR group received an equal volume of pure water intraperitoneally. Four hours post-modeling, DQ+AUR group and AUR group were administered 0.5 mg/kg AUR aqueous solution (0.2 mL) by gavage once daily for 7 consecutive days, while Control group and DQ group received pure water. Blood and liver tissues were collected after anesthesia on day 7. Liver ultrastructure was observed by transmission electron microscopy. Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were measured via enzyme-linked immunosorbent assay (ELISA). Hepatic glutathione (GSH), superoxide dismutase (SOD), and malondialdehyde (MDA) levels were detected using WST-1, thiobarbituric acid (TBA), and enzymatic reaction methods, respectively. Protein expression of nuclear factor-erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), Kelch-like ECH-associated protein 1 (Keap1), and activated caspase-9 in liver tissues was analyzed by Western blotting. RESULTS: Transmission electron microscopy revealed that mitochondria in the Control group exhibited mild swelling, uneven distribution of matrix, and a small number of cristae fractures. In the AUR group, mitochondria showed mild swelling, with no obvious disruption of cristae structure. In the DQ group, mitochondria demonstrated marked swelling and increased volume, matrix dissolution, loss and fragmentation of cristae, and extensive vacuolization. In contrast, the DQ+AUR group showed significantly reduced mitochondrial swelling, volume increase, matrix dissolution, cristae loss and fragmentation, and vacuolization compared to the DQ group. Compared with the DQ group, the DQ+AUR group exhibited significantly lower serum AST levels (U/L: 173.45±23.60 vs. 255.33±41.51), ALT levels (U/L: 51.77±21.63 vs. 100.70±32.35), and hepatic MDA levels (μmol/g: 12.40±2.76 vs. 19.74±4.10), along with higher hepatic GSH levels (mmol/g: 37.65±14.95 vs. 20.58±8.52) and SOD levels (kU/g: 124.10±33.77 vs. 82.81±22.00), the differences were statistically significant (all P < 0.05). Western blotting showed upregulated Nrf2 expression (Nrf2/β-actin: 0.87±0.37 vs. 0.53±0.22) and HO-1 expression (HO-1/β-actin: 1.06±0.22 vs. 0.49±0.08), and downregulated Keap1 expression (Keap1/β-actin: 0.82±0.12 vs. 1.52±0.76) and activated caspase-9 expression (activated caspase-9/β-actin: 1.16±0.28 vs. 1.71±0.30) in the DQ+AUR group compared to the DQ group (all P < 0.05). CONCLUSION AUR attenuates DQ-induced acute liver injury in mice by activating the Keap1/Nrf2 signaling pathway.
Animals ; Male ; Mice ; Mice, Inbred C57BL ; Liver/pathology* ; Chemical and Drug Induced Liver Injury/drug therapy* ; Diquat/poisoning* ; NF-E2-Related Factor 2/metabolism* ; Oxidative Stress ; Apoptosis ; Coumarins

In recent years, the spread of clubroot disease caused by Plasmodiophora brassicae infection has seriously affected the yield and quality of Brassica juncea (L.) Czern.. The cascade of mitogen-activated protein kinases (MAPKs), a highly conserved signaling pathway, plays an important role in plant responses to both biotic and abiotic stress conditions. To mine the MAPK genes related to clubroot disease resistance in B. juncea, we conducted a genome-wide analysis on this vegetable, and we analyzed the phylogenetic evolution and gene structure of the MAPK gene family in mustard. The 66 BjuMAPK genes identified by screening the whole genome sequence of B. juncea were unevenly distributed on 17 chromosomes. At the genomic scale, tandem repeats led to an increase in the number of MAPK genes in B. juncea. It was found that members of the same subfamily had similar gene structures, and there were great differences among different subfamilies. These predicted cis-acting elements were related to plant hormones, stress resistance, and plant growth and development. The expression of BjuMAPK02, BjuMAPK15, BjuMAPK17, and BjuMAPK19 were down-regulated or up-regulated in response to P. brassicae infection. The above results lay a theoretical foundation for further studying the functions of BjuMAPK genes in B. juncea in response to the biotic stress caused by clubroot disease.
Mustard Plant/parasitology* ; Plasmodiophorida/pathogenicity* ; Plant Diseases/genetics* ; Mitogen-Activated Protein Kinases/metabolism* ; Phylogeny ; Disease Resistance/genetics* ; Gene Expression Regulation, Plant ; Genome, Plant ; Plant Proteins/genetics*

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Molecular Probes ; Molecular Imaging/methods* ; Magnetic Resonance Imaging ; Positron-Emission Tomography ; Tomography, Emission-Computed, Single-Photon ; Ultrasonography ; Optical Imaging ; Biomarkers, Tumor ; Precision Medicine/methods*

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

Evading host immunity killing is a critical step for virus survival. Inhibiting viral immune escape is crucial for the treatment of viral diseases. Serine/threonine kinase 39 (STK39) was reported to play an essential role in ion homeostasis. However, its potential role and mechanism in viral infection remain unknown. In this study, we found that viral infection promoted STK39 expression. Consequently, overexpressed STK39 inhibited the phosphorylation of interferon regulatory factor 3 (IRF3) and the production of type I interferon, which led to viral replication and immune escape. Genetic ablation or pharmacological inhibition of STK39 significantly protected mice from viral infection. Mechanistically, mass spectrometry and immunoprecipitation assays identified that STK39 interacted with PPP2R1A (a scaffold subunit of protein phosphatase 2A (PP2A)) in a kinase activity-dependent manner. This interaction inhibited DDB1 and CUL4 associated factor 1 (DCAF1)-mediated PPP2R1A degradation, maintained the stabilization and phosphatase activity of PP2A, which, in turn, suppressed the phosphorylation of IRF3, decreased the production of type I interferon, and then strengthened viral replication. Thus, our study provides a novel theoretical basis for viral immune escape, and STK39 may be a potential therapeutic target for viral infectious diseases.

Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.

Objective To investigate the feasibility of the spatiotemporal filtering model in analysis of reported schistosomiasis cases, so as to provide insights into analysis of complicated data pertaining to schistosomiasis control. Methods Demographic and epidemiological data of reported schistosomiasis cases in Anhui Province from 1997 to 2010 were collected from Anhui Provincial Center for Disease Control and Prevention, and the annual prevalence of Schistosoma japonicum human infections was calculated. The meteorological data were captured from meteorological stations in counties (cities, districts) of Anhui Province where schistosomiasis cases were reported from 1997 to 2010 at the National Meteorological Information Center, including monthly average air temperature and precipitation. Meteorological data were interpolated using the inverse-distance weighting method, and the annual average air temperature and annual precipitation were calculated in each county (city, district). The centroid of the county (city, district) where schistosomiasis cases were reported was extracted using the software ArcGIS 10.0, and the Euclidean distance from each centroid to the Yangtze River was calculated as the distance between that county (city, district) and the Yangtze River. The global Moran’s I of the prevalence of S. japonicum human infections in Anhui Province for each year from 1997 to 2010 were calculated to analyze the spatial autocorrelation. A spatial weight matrix was constructed using Rook adjacency, and a first-order temporal weight matrix was built to quantify the relationship between disease changes over time. Subsequently, a spatiotemporal structure matrix was constructed. A negative binomial model was built based on the spatiotemporal structure matrix and data pertaining to reported schistosomiasis cases, and a linear model was created between the residual of the model and candidate set feature vectors to determine the optimal subset composition of the spatiotemporal filter through stepwise regression. Then, a spatio-temporal filtering model was constructed using the negative binomial model. Negative binomial models, Bayesian spatial models, and Bayesian spatiotemporal models were constructed and compared with the spatiotemporal filtering model to validate the performance of the spatiotemporal filtering model, and cross-validation was conducted for each model. The goodness of fit was evaluated using the deviance information criterion (DIC) and Watanabe-Akaike information criterion (WAIC), and the effectiveness of model validation was assessed using mean squared error (MSE), while the accuracy of assessment results was assessed using coefficients and their 95% confidence intervals (CI), and the computational efficiency was assessed based on the running time of the model. The four feature vectors with the largest Moran’s I values were selected to identify regions with autocorrelation through their schematic diagrams to investigate the differences in spatiotemporal patterns of specific regions. Results Of all models created, the spatiotemporal filtering model exhibited the highest goodness of fit (DIC = 3 240.70, WAIC = 3 257.80), the best model validation effectiveness (MSE = 42 617.52), and the runtime was 3.18 s, exhibiting the optimal performance. Across all modeling results, the distance from the Yangtze River showed a negative correlation with the number of reported schistosomiasis cases (coefficient values = −4.93 to −3.78, none of the 95% CIs included 0), and annual average air temperature or average precipitation posed no significant effects on numbers of reported schistosomiasis cases (both of the 95% CIs included 0). Schematic diagrams of feature vectors showed that the transmission of schistosomiasis might be associated with water systems in Anhui Province, and localized clustering patterns were primarily concentrated in the northern and western parts of schistosomiasis-endemic areas in the province. Conclusion The spatiotemporal filtering model is an effective spatiotemporal analysis characterized by simple modeling, user-friendly operation, accurate results and good flexibility, which may serve as an efficient alternative to conventional complex spatiotemporal models for data analysis in schistosomiasis researches.