Objective To explore enteral nutrition support and analyze its influencing factors in elderly patients with ischemic stroke. Methods A total of 328 patients with ischemic stroke in General Hospital of Western Theater Command were enrolled for nutritional screening between July 2020 and February 2024. Corresponding nutritional support plans were selected to investigate the compliance of patients with enteral nutrition support. Patients were divided into a standard group (n=140) and a non-standard group (n=97) based on whether their calorie intake met the standard. The effects of different clinical characteristics on enteral nutrition support were explored, and logistic analysis was used to analyze the influencing factors of non-standard enteral nutrition support. Results In the 328 patients with ischemic stroke, proportions of total parenteral nutrition support, total enteral nutrition support, and parenteral/enteral nutrition support were 25.30%, 27.74% and 46.95%, respectively. The proportions of vomiting or regurgitation, gastric residual volume >100 mL, mechanical ventilation and use of antibiotics >2 in the non-standard group were higher than those in the standard group (P<0.05). Logistic analysis showed that the above clinical characteristics were risk factors influencing patients with enteral nutrition support and parenteral/enteral nutrition support. Conclusion Vomiting or regurgitation , gastric residual volume, mechanical ventilation, and amount of antibiotics used are important influencing factors of enteral nutrition support in patients. Clinicians should pay attention to the above clinical characteristics.

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.

By analyzing the current application of multi-modal data in the diagnosis of gastric "inflammation-cancer" transformation， this study explored the feasibility and strategies for constructing a disease-syndrome integrated diagnosis and treatment system. Based on traditional Chinese medicine （TCM） phenomics， we proposed utilizing multi-modal data from literature research， cross-sectional studies， and cohort follow-ups， combined with artificial intelligence technology， to establish a multi-dimensional diagnostic and treatment index system. This approach aims to uncover the complex pathogenesis and transformation patterns of gastric "inflammation-cancer" progression. Additionally， by dynamically collecting TCM four-diagnostic information and modern medical diagnostic information through a long-term follow-up system， we developed three major modules including information extraction， multi-modal phenotypic modeling， and information output， to make it enable real-world clinical data-driven long-term follow-up and treatment of chronic atrophic gastritis. This system can provide technical support for clinical diagnosis， treatment evaluation， and research， while also offering insights and methods for intelligent TCM diagnosis.

Twelve compounds were isolated from the rice fermentation extracts of Penicillium expansum GY618 by silica column chromatography, Sephadex gel column chromatography, ODS column chromatography and semi preparative HPLC methods. They were determined as 11-hydroxyl-penicitrinone F (1), penicitrinone F (2), betulin (3), erythrodiol (4), ergosterol (5), ergost-5α,8α-epidioxy-6,22-dien-3β-ol (6), (5α,8α-epidioxy-(22E,24R)-ergosta-6,9(11),22-trien-3β-ol) (7), 5α,8α-epidioxy-(22E,24R)-23-methylergosta-6,22-dien-3β-ol (8), 5α,8α-epidioxy- 23,24(R)-dimethylcholesta-6,9(11),22-trien-3β-ol (9), dankasterone A (10), (17R)-4-hydroxy-17-methylincisterol (11) and ergosta-4,6,8(14),22-tetraen-3-one (12), through mass spectrometer, nuclear magnetic resonance (NMR) and comparison with the literature. Compound 1 was a new compound and compounds 2-4, 6-12 were isolated from Penicillium expansum fungus for the first time. The tyrosinase inhibitory activity experiment showed that compounds 1, 3 and 12 showed certain inhibitory activity against tyrosinase with IC₅₀ values of (75 ± 9), (69 ± 8) and (64 ± 2) μmol·L^-1, respectively. The IC₅₀ of other compounds were all greater than 100 μmol·L^-1, while IC₅₀ of the positive control kojic acid was (46 ± 4) μmol·L^-1.

BACKGROUND:Acupoint embedding and floating needle therapy are two methods for the treatment of knee osteoarthritis,but there are few reports on the combined treatment of the two methods. OBJECTIVE:To investigate the therapeutic effect of acupoint embedding combined with floating needle therapy on different stages of knee osteoarthritis using generalized estimating equations. METHODS:A total of 436 patients with knee osteoarthritis admitted to Dongguan Hospital of Traditional Chinese Medicine from February 2019 to February 2023 were selected as the research subjects.All patients were randomly divided into a control group with floating needle therapy(n=218)and an observation group with acupoint embedding method combined with floating needle therapy(n=218).Staging was performed according to the K-L staging method.In the control group,there were 57 cases in stage Ⅰ,62 in stage Ⅱ,49 in phase Ⅲ,and 50 in stage Ⅳ,while in the observation group,there were 48 cases in stage Ⅰ,66 in stage Ⅱ,63 in phase Ⅲ,and 41 in stage Ⅳ.The levels of indexes and clinical efficacy were compared between groups before and after treatment.Generalized estimating equation model was used to analyze the influencing factors of clinical efficacy and the interaction effect of different time points,different methods and different stages on therapeutic efficacy. RESULTS AND CONCLUSION:There was no significant difference in baseline data between the observation group and the control group,as well as between the patients of different stages(P>0.05).After treatment,the cure rate of stage Ⅰ patients was the highest after treatment,and the total improvement rate in the observation group was significantly higher than that in the control group.There were significant differences in the cure rate among different stages in each group(P<0.05).After treatment,all indicators in the two groups were significantly decreased.In the control group,there were significant differences in various indicators of patients at different stages after 4 weeks of treatment(P<0.05).In the observation group,after 2 weeks of treatment,there were significant differences in various indicators of patients at different stages(P<0.05),and all the indexes in the observation were lower than those in the control group after 4 weeks of treatment(P<0.05)and the therapeutic effect in the observation group was better than that in the control group.Generalized estimating equation model analysis showed that trauma history,interleukin-6 level,treatment method,treatment time and K-L stage all significantly affected the clinical efficacy in patients.In the interaction effect analysis,after 2 weeks of treatment,there was a significant difference in the visual analogue scale score between the two groups in stages Ⅲ and Ⅳ(P<0.05).After 4 weeks of treatment,there was a significant difference in the visual analogue scale score between the two groups in stages Ⅱ,Ⅲ,and Ⅳ(P<0.05).To conclude,acupoint embedding combined with floating needle therapy is superior to floating needle therapy alone in the treatment of different stages of knee osteoarthritis.Trauma history,interleukin-6 level,treatment method,treatment time and K-L stage significantly influence the therapeutic effect.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

To guide transfusion practice in critically ill children who often need plasma and platelet transfusions, the Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding (TAXI-CAB) developed Recommendations and Expert Consensus for Plasma and Platelet Transfusion Practice in Critically Ill Children. This guideline addresses 53 recommendations related to plasma and platelet transfusion in critically ill children with 8 kinds of diseases, laboratory testing, selection/treatment of plasma and platelet components, and research priorities. This paper introduces the specific methods and results of the recommendation formation of the guideline.

The shaoyang meridian is an important pivot between the internal organs and meridians system， with the functions of regulating qi and blood， balancing yin and yang， and coordinating the ascending and descending movement of qi. Dysfunction of the shaoyang pivot can lead to spleen and kidney deficiency， impaired liver and gallbladder qi regulation， and stagnation of qi and blood. It is believed that the onset and progression of Crohn's disease are closely related to shaoyang pivot dysfunction， with the core pathogenesis characterized by shaoyang disharmony， spleen deficiency， dampness retention， and blood stasis. Based on this understanding， the treatment principle centers on harmonizing the shaoyang pivot， supplemented by methods such as warming and nourishing the spleen and stomach， tonifying shaoyang， and soothing the liver and benefiting the gallbladder. Acupuncture is employed to target key acupoints along the shaoyang meridian to restore its regulatory functions， improve spleen and stomach transformation and transportation， facilitate liver and gallbladder qi flow， and promote the circulation of qi and blood. This provides a practical therapeutic approach for acupuncture-based treatment of Crohn's disease.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.