ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

This study aims to investigate the protective effects and mechanisms of polysaccharide extract PCP1 from Polygonatum cyrtonema in ameliorating cerebral ischemia-reperfusion(I/R) injury in rats through modulation of the Toll-like receptor 4(TLR4)/NOD-like receptor protein 3(NLRP3) signaling pathway. In vivo, SD rats were randomly divided into the sham group, model group, PCP1 group, nimodipine(NMDP) group, and TLR4 signaling inhibitor(TAK-242) group. A middle cerebral artery occlusion/reperfusion(MCAO/R) model was established, and neurological deficit scores and infarct size were evaluated 24 hours after reperfusion. Hematoxylin-eosin(HE) and Nissl staining were used to observe pathological changes in ischemic brain tissue. Transmission electron microscopy(TEM) assessed ultrastructural damage in cortical neurons. Enzyme-linked immunosorbent assay(ELISA) was used to measure the levels of interleukin-1β(IL-1β), interleukin-6(IL-6), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), interleukin-10(IL-10), and nitric oxide(NO) in serum. Immunofluorescence was used to analyze the expression of TLR4 and NLRP3 proteins. In vitro, a BV2 microglial cell oxygen-glucose deprivation/reperfusion(OGD/R) model was established, and cells were divided into the control, OGD/R, PCP1, TAK-242, and PCP1 + TLR4 activator lipopolysaccharide(LPS) groups. The CCK-8 assay evaluated BV2 cell viability, and ELISA determined NO release. Western blot was used to analyze the expression of TLR4, NLRP3, and downstream pathway-related proteins. The results indicated that, compared with the model group, PCP1 significantly reduced neurological deficit scores, infarct size, ischemic tissue pathology, cortical cell damage, and the levels of inflammatory factors IL-1β, IL-6, IL-18, TNF-α, and NO(P<0.01). It also elevated IL-10 levels(P<0.01) and decreased the expression of TLR4 and NLRP3 proteins(P<0.05, P<0.01). Moreover, in vitro results showed that, compared with the OGD/R group, PCP1 significantly improved BV2 cell viability(P<0.05, P<0.01), reduced cell NO levels induced by OGD/R(P<0.01), and inhibited the expression of TLR4-related inflammatory pathway proteins, including TLR4, myeloid differentiation factor 88(MyD88), tumor necrosis factor receptor-associated factor 6(TRAF6), phosphorylated nuclear factor-kappaB dimer RelA(p-p65)/nuclear factor-kappaB dimer RelA(p65), NLRP3, cleaved-caspase-1, apoptosis-associated speck-like protein(ASC), GSDMD-N, IL-1β, and IL-18(P<0.05, P<0.01). The protective effects of PCP1 were reversed by LPS stimulation. In conclusion, PCP1 ameliorates cerebral I/R injury by modulating the TLR4/NLRP3 signaling pathway, exerting anti-inflammatory and anti-pyroptotic effects.
Animals ; Toll-Like Receptor 4/genetics* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Rats, Sprague-Dawley ; Rats ; Reperfusion Injury/genetics* ; Male ; Signal Transduction/drug effects* ; Polysaccharides/isolation & purification* ; Polygonatum/chemistry* ; Brain Ischemia/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Humans

Perceptual decision making refers to the process by which individuals make choices and judgments based on sensory information, serving as a fundamental ability for human adaptation to complex environments. While traditional research has focused on perceptual decision making in isolated contexts, growing evidence highlights the profound influence of social contexts prevalent in real-world scenarios. As a crucial factor supporting individual survival and development, social context not only provides rich information sources but also shapes perceptual decision making through top-down processing mechanisms, prompting researchers to recognize the inherently social nature of human decisions. Empirical studies have demonstrated that social information, such as others’ choices or group norms, can systematically bias individuals’ perceptual decisions, often manifesting as conformity behaviors. Social influence can also facilitate performance under certain conditions, particularly when individuals can accurately identify and adopt high-quality social information. The impact of social context on perceptual decisions is modulated by a variety of external and internal factors, including group characteristics(e.g., group size, response consistency), attributes of peers (e.g., familiarity, social status, distinctions between human and artificial agents), as well as individual differences such as confidence, personality traits, and developmental stage. The motivations driving social influence encompass three primary mechanisms: improving decision accuracy through informational influence, gaining social acceptance through normative influence, and maintaining positive self-concept. Recent computational approaches have employed diverse theoretical frameworks to provide valuable insights into the cognitive mechanisms underlying social influence in perceptual decision making. Reinforcement learning models demonstrate how social feedback shapes future choices through reward-based updating. Bayesian inference frameworks describe how individuals integrate personal beliefs with social information based on their respective reliabilities, dynamically updating beliefs to optimize decisions under uncertainty. Drift diffusion models offer powerful tools to decompose social influence into distinct cognitive components, allowing researchers to differentiate between changes in perceptual processing and shifts in decision criteria. Collectively, these models establish a comprehensive methodological foundation for disentangling the multiple pathways by which social context shapes perceptual decisions. Neuroimaging and electrophysiological studies provide converging evidence that social context influences perceptual decision making through multi-level neural mechanisms. At early perceptual processing stages, social influence modulates sensory evidence accumulation in parietal cortex and directly alters primary visual cortex activity, while guiding selective attention to stimulus features consistent with social norms through attentional alignment mechanisms. At higher cognitive levels, the reward system (ventral striatum, ventromedial prefrontal cortex) is activated during group-consistent decisions; emotion-processing networks (anterior cingulate cortex, insula, amygdala) regulate experiences of social acceptance and rejection; and mentalizing-related brain regions (dorsomedial prefrontal cortex, temporoparietal junction) support inference of others’ mental states and social information integration. These neural circuits work synergistically to achieve top-down multi-level modulation of perceptual decision making. Understanding the mechanisms by which social context shapes perceptual decision making has broad theoretical and practical implications. These insights inform the optimization of collective decision-making, the design of socially adaptive human-computer interaction systems, and interventions for cognitive disorders such as autism spectrum disorder and anorexia nervosa. Future studies should combine computational modeling and neuroimaging approaches to systematically investigate the multi-level and dynamic nature of social influences on perceptual decision making.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

OBJECTIVE: To construct a prediction model for the clinical effect of eye acupuncture combined with rehabilitation therapy on ischemic stroke based on interpretable machine learning. METHODS: From January 1st, 2020 to October 1st, 2024, the clinical data of 470 patients with ischemic stroke were collected in the the Second Department of Encephalopathy Rehabilitation of the Affiliated Hospital of Liaoning University of TCM. The modified Barthel index (MBI) score before and after treatment was used to divide the patients into an effect group (291 cases) and a non-effect group (179 cases). Random forest and recursive feature elimination with cross-validation were combined to screen the predictors of the therapeutic effect of patients. Seven representative machine learning models with different principles were established according to the screening results. The predictive effect of the best model was evaluated by receiver operating characteristics (ROC), calibration, and clinical decision-making (DCA) curves. Finally, the Shapley additive explanation (SHAP) framework was used to interpret the prediction results of the best model. RESULT: ①All the machine learning models presented the area under curve (AUC) to be above 85%. Of these models, the random forest model showed the best prediction ability, with AUC of 0.96 and the precision of 0.87. ②The prediction probability of calibration curve and the actual probability showed a good prediction consistency. ③The net benefit rate of DCA curve in the range of 0.1 to 1.0 was higher than the risk threshold, indicating a good effect of model. ④SHAP explained the characteristic values of variables that affected the prediction effect of the model, meaning, more days of treatment, lower MBI score before treatment, lower level of fibrinogen, shorter days of onset and younger age. These values demonstrated the better effect of eye acupuncture rehabilitation therapy. CONCLUSION The rehabilitation effect prediction model constructed in this study presents a good performance, which is conductive to assisting doctors in formulating targeted personalized rehabilitation programs, and identifying the benefit groups of eye acupuncture combined with rehabilitation therapy and finding the advantageous groups with clinical effect. It provides more ideas for the treatment of ischemic stroke with eye acupuncture combined with rehabilitation therapy.
Humans ; Acupuncture Therapy ; Machine Learning ; Male ; Female ; Middle Aged ; Ischemic Stroke/rehabilitation* ; Aged ; Stroke Rehabilitation ; Adult ; Eye

BACKGROUND:Hydrogels have become a research hotspot due to their unique advantages in the biomedical field due to their superior mechanical and biological properties.At present,related research involves tissue engineering,wound dressing and so on. OBJECTIVE:To review the advantages and properties of hydrogels and the research progress of their application in the repair of oral and maxillofacial defects,discuss the current limitations and challenges of hydrogels in application and promotion,and provide new ideas for future research directions. METHODS:Relevant literature was searched in PubMed,CNKI,and WanFang database by computer.The search terms were"hydrogel,oral and maxillofacial defects,mechanical properties,tissue engineering,wound dressing"in Chinese and"hydrogel,oral and maxillofacial defects,mechanical properties,guided tissue regeneration,wound dressing"in English.Preliminary screening was carried out by reading titles and abstracts,and articles not related to the topic of the article were excluded.According to the inclusion and exclusion criteria,108 articles were finally included for the result analysis. RESULTS AND CONCLUSION:(1)The hydrogel has good biological activity,mechanical controllability,and stimulation response.(2)Polymer,metal,and ceramic hydrogel composites have appropriate mechanical properties,biodegradability,and controlled release rate,which are suitable for maxillofacial bone tissue engineering.(3)Fibrin-based hydrogel could fill the hollow nerve conduit through the nerve defect area and promote the regeneration and growth of axons to restore the function of maxillofacial nerve.(4)Controlling the interaction between nanomaterials and hydrogels can improve the formation of muscle fiber oriented structure to promote maxillofacial muscle tissue regeneration.(5)Polysaccharide hydrogel has gradually become the first choice for repairing irregular periodontal defects due to its ability to control drug delivery,carry bioactive molecules,and combine with other materials to produce the best scaffold matching the extracellular matrix.(6)Calcium phosphate or calcium carbonate-based hydrogels can be used to fill irregular or fine tissue defects and remineralize hard tissues.The self-assembled hydrogels are simple to prepare and have good biological activity.(7)Salivary gland-derived extracellular matrix-like gel is expected to participate in the treatment of many salivary gland diseases.(8)Hydrogels can be used as wound dressings in combination with biological adhesives,acellular biomaterials,antimicrobials,antioxidants,or stem cells to treat various wounds.(9)Fibrin-based hydrogel has the most potential in the repair of oral and maxillofacial defects.It has excellent biocompatibility,flexibility,and plasticity.It can combine with cells,extracellular matrix proteins,and various growth factors,and promote the osteogenic differentiation of mesenchymal stem cells,axon regeneration and growth,angiogenesis,myotube differentiation,salivary gland tissue regeneration,and periodontal tissue regeneration.It has a broad prospect in the repair of oral and maxillofacial defects.However,its therapeutic effect depends on the function of the substance carried.The complex preparation process,its safety and long-term efficacy,and the special anatomical oral and maxillofacial structure is the problem that hinders its promotion,which also provides directions for future research.

Adrenocortical carcinoma（ACC）is a rare and highly aggressive malignant tumor. Currently，mitotane is the first-line treatment. However，reports on neoadjuvant therapy for ACC using mitotane combined with immune checkpoint inhibitors remain scarce. This article reports a case of ACC. The patient was asymptomatic，and a right adrenal mass was detected during examination. Diagnostic imaging and endocrine evaluation confirmed the diagnosis of ACC. Due to the large tumor size，radical resection was initially considered unfeasible. After 7 months of mitotane therapy and two courses of tislelizumab，significant tumor shrinkage was achieved，allowing for successful open resection of the large right adrenal tumor combined with right nephrectomy. Postoperative histopathological examination confirmed the diagnosis of ACC. During the 3-month postoperative follow-up，no evidence of recurrence or metastasis was observed.

Objective:To explore the differences in clinicopathological features and prognosis between conventional adrenocortical carcinoma（ACC）and oncocytic ACC.Methods:The clinical and pathological data of patients with conventional ACC and oncocytic ACC who were admitted to Peking Union Medical College Hospital from March 2012 to Fabruary 2025 were retrospectively analyzed. Differences in clinical and pathological characteristics between the two groups were compared. Survival curves were plotted using the Kaplan-Meier method，and differences in survival rates were compared using the log-rank test.Results:The conventional ACC group comprised 137 cases，with a mean age of（47.5 ± 12.6）years and 37.2%（51/137）being male. The oncocytic ACC group included 22 cases，with a mean age of（49.1 ± 15.3）years and 59.1%（13/22）being male. No statistically significant differences were observed in age or gender distribution between the two groups（ P > 0.05）. The conventional ACC group exhibited a significantly higher prevalence of classic Cushing’s syndrome symptoms compared to the oncocytic ACC group［35.2%（45/128）vs. 5.3%（1/19）； χ2 = 6.876， P < 0.01］. Additionally，the proportion of hypertension was higher in the conventional ACC group［49.2%（65/132）vs. 22.2%（4/18）； χ2 = 5.319， P < 0.05］，whereas the prevalence of adrenal sex characteristics was lower［22.0%（28/127）vs. 63.2%（12/19）； χ2 = 14.043， P < 0.01］. The Ki-67 proliferation index was significantly higher in conventional ACC patients［20%（10%，40%）vs. 12%（9%，20%）； Z = -2.113， P < 0.05］. Furthermore，the conventional ACC group demonstrated a lower 5-year overall survival rate than the oncocytic ACC group（44.5% vs. 67.3%， P < 0.05）. Conclusions:Conventional ACC patients have a higher proportion of Cushing’s symptoms and hypertension，and oncocytic ACC patients have a higher proportion of adrenal sexual characteristics abnormalities. The prognosis of oncocytic ACC is better than that of conventional ACC.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.