ObjectiveTo analyze the current status, hotspot and development trends of rehabilitation technologies for post-stroke dysphagia (PSD). MethodsLiteratures related to rehabilitation technologies for PSD were retrieved from CNKI, VIP and Web of Science Core Collection from inception to July, 2025. Visualization analysis was conducted using CiteSpace 6.3.R1 and VOSviewer 1.2.20. ResultsA total of 1 265 articles were included, consisting of 794 Chinese and 471 English publications. The annual volume of Chinese literature peaked in 2019 (74 articles) and English literature peaked in 2022 (61 articles). Research hotspots included low-frequency surface neuromuscular electrical stimulation, repetitive transcranial magnetic stimulation, surface electromyography biofeedback and transcranial direct current stimulation. Keyword clustering and timeline analysis indicated that researches evolved from early traditional rehabilitation methods to the diversified and integrated application of combined rehabilitation technologies. ConclusionResearch on rehabilitation technologies for PSD is developing rapidly. Future efforts should focus on researches of multi-technology integration, individualized treatment protocols and long-term efficacy assessments.

ObjectiveTo analyze the current status, hotspot and development trends of rehabilitation technologies for post-stroke dysphagia (PSD). MethodsLiteratures related to rehabilitation technologies for PSD were retrieved from CNKI, VIP and Web of Science Core Collection from inception to July, 2025. Visualization analysis was conducted using CiteSpace 6.3.R1 and VOSviewer 1.2.20. ResultsA total of 1 265 articles were included, consisting of 794 Chinese and 471 English publications. The annual volume of Chinese literature peaked in 2019 (74 articles) and English literature peaked in 2022 (61 articles). Research hotspots included low-frequency surface neuromuscular electrical stimulation, repetitive transcranial magnetic stimulation, surface electromyography biofeedback and transcranial direct current stimulation. Keyword clustering and timeline analysis indicated that researches evolved from early traditional rehabilitation methods to the diversified and integrated application of combined rehabilitation technologies. ConclusionResearch on rehabilitation technologies for PSD is developing rapidly. Future efforts should focus on researches of multi-technology integration, individualized treatment protocols and long-term efficacy assessments.

ObjectiveTo analyze the current status, hotspot and development trends of rehabilitation technologies for post-stroke dysphagia (PSD). MethodsLiteratures related to rehabilitation technologies for PSD were retrieved from CNKI, VIP and Web of Science Core Collection from inception to July, 2025. Visualization analysis was conducted using CiteSpace 6.3.R1 and VOSviewer 1.2.20. ResultsA total of 1 265 articles were included, consisting of 794 Chinese and 471 English publications. The annual volume of Chinese literature peaked in 2019 (74 articles) and English literature peaked in 2022 (61 articles). Research hotspots included low-frequency surface neuromuscular electrical stimulation, repetitive transcranial magnetic stimulation, surface electromyography biofeedback and transcranial direct current stimulation. Keyword clustering and timeline analysis indicated that researches evolved from early traditional rehabilitation methods to the diversified and integrated application of combined rehabilitation technologies. ConclusionResearch on rehabilitation technologies for PSD is developing rapidly. Future efforts should focus on researches of multi-technology integration, individualized treatment protocols and long-term efficacy assessments.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.