Objective This study aimed to explore the ability of ultrasonographic radiomics in predicting the occurrence of in-stent restenosis(ISR)after carotid artery stenting(CAS)by analyzing the correlation between radiomic features of responsible plaques in carotid artery stenosis and the incidence of ISR.Methods A retrospective collection was conducted on 206 cases that underwent CAS treatment at our hospital.The enrolled patients were randomly split into a training set(144 cases)and a test set(62 cases)at a 7∶3 ratio.We utilized the Darwin Intelligent Research Platform to extract radiomic features from each region of interest,and then screened 1125 ultrasonographic radiomic features.Different machine learning algorithms were employed to construct diagnostic models,and the best-performing classifier was selected.Various prediction models were established,including a clinical-ultrasonographic feature model,a radiomic model,and a combined clinical-ultrasonographic-radiomic model.Results Multivariate logistic regression analysis in the training set revealed that hypertension,hyperuricemia,triglycerides,and plaque location were independent risk factors for ISR after CAS.For the clinical-ultrasonographic model,the area under the curve(AUC)values for the training and validation sets were 0.896 and 0.644,respectively.The corresponding AUC values for the radiomic model were 0.961 and 0.715,while those for the combined model were 0.947 and 0.727.Conclusion The radiomic model demonstrates superior performance in predicting ISR compared to the traditional clinical-ultrasonographic model.The combined model exhibited an enhanced ability to predict ISR occurrence,thereby improving the diagnostic performance of traditional assessments.

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

OBJECTIVE: This study aims to elucidate the therapeutic potential of osthole for the treatment of atopic dermatitis (AD), focusing on its ability to alleviate chronic pruritus (CP) and the underlying molecular mechanisms. METHODS: In this study, we investigated the anti-inflammatory effects of osthole in both a 2,4-dichloronitrobenzene (DNCB)-induced AD mouse model and tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) stimulated huma immortalized epidermal (HaCaT) cells. The anti-itch effect of osthole was specifically assessed in the AD mouse model. Using methods such as hematoxylin and eosin (HE) staining, enzyme-linked immunosorbent assay (ELISA), western blot (WB), quantitative real-time PCR (qRT-PCR), and immunofluorescence staining. RESULTS: Osthole improved skin damage and clinical dermatitis scores, reduced scratching bouts, and decreased epidermal thickness AD-like mice. It also reduced the levels of interleukin (IL)-31 and IL-31 receptor A (IL-31 RA) in both skin tissues and HaCaT cells. Furthermore, Osthole suppressed the protein expression levels of phosphor-p65 (p-p65) and phosphor-inhibitor of nuclear factor kappa-Bα (p-IκBα). Meanwhile, it increased the protein expression levels of peroxisome proliferator-activated receptor α (PPARα) and PPARγ in HaCaT cells. CONCLUSION These findings indicated that osthole effectively inhibited CP in AD by activating PPARα, PPARγ, repressing the NF-κB signaling pathway, as well as the expression of IL-31 and IL-31 RA.

Aim To study the effect of p-benzoyl sali-droside(pOBz)on angiogenesis after ischemic stroke and to explore the underlying mechanism.Methods The MCAO model was prepared by suture method.Rats were divided into four groups:sham,MCAO,pOBz administration,and edaravone positive control,treated for seven days.The mNSS was used to assess the neurological impairment.Western blotting was em-ployed to detect CD31,NICD,and Hes-1 protein ex-pression,while immunofluorescence staining was ap-plies to quantify CD31-positive cells in ischemic brain tissue.In vitro an OGD/R model was established in HUVECs.Following treatment with varying pOBz con-centrations(0.01,0.1,1 μmol·L-1),the CCK-8 as-say was uses to measure cell viability,and in vitro tube formation assay was utilized to evaluate angiogenesis.Western blotting was employed again to assess CD31,NICD and Hes-1 protein levels.To further elucidate the mechanism,HUVEC were treated with the Notch inhibitor DAPT prior to grouping and pOBz administra-tion,and the same parameters were evaluated.Results pOBz significantly reduced the mNSS score of MCAO rats,increased CD31-positive cell counts,and upregu-lated CD31,NICD,and Hes-1 protein expression(P＜0.01).In vitro results further showed that pOBz could dose-dependently increase the survival rate and angio-genesis ability of HUVEC induced by OGD/R,and promote CD31,NICD and Hes-1 proteins(P＜0.01),and Notch inhibitor DAPT could reverse the above effects of pOBz.Conclusion pOBz promotes angio-genesis in HUVEC,and its mechanism involves activa-tion of the Notch signaling pathway.

The terminology and connotation changes of tongue coating are closely associated with the development of the theory of tongue inspection.Previous literature research on tongue inspection has primarily focused on tracing the origins;however,it lacks an analysis of the connotations of terminology changes.This article uses the theory of metaphorical cognition to elucidate the corresponding relationship between tongue coating terminology and its connotation changes.In the process of terminology change from"tongue fur"to"tongue moss,"tongue coating has evolved from a purely pathological concept to one with physiological significance.The relationship between tongue coating and body has changed from the attachment of tongue coating to the surface of the tongue body to the inseparability of tongue coating and body.The characteristic terminology"fur"used by ZHANG Zhongjing contains architectural metaphors,reflecting the characteristic of the tongue coating being flat and slightly higher than the tongue body.During the Ming and Qing dynasties,medical practitioners gradually used the term"moss"to illustrate the organic connection between tongue coating and the tongue body through plant metaphors.They constructed metaphors of water and fire,as well as plants,to explain how tongue coating forms in both physiological and pathological states.Therefore,compared to the"fur,"the"moss"has a richer metaphorical meaning,corresponding to the connotations of tongue coating terminology,which helps explain related physiological and pathological manifestations,and is a key factor affecting the evolution of tongue coating terminology.

The terminology and connotation changes of tongue coating are closely associated with the development of the theory of tongue inspection.Previous literature research on tongue inspection has primarily focused on tracing the origins;however,it lacks an analysis of the connotations of terminology changes.This article uses the theory of metaphorical cognition to elucidate the corresponding relationship between tongue coating terminology and its connotation changes.In the process of terminology change from"tongue fur"to"tongue moss,"tongue coating has evolved from a purely pathological concept to one with physiological significance.The relationship between tongue coating and body has changed from the attachment of tongue coating to the surface of the tongue body to the inseparability of tongue coating and body.The characteristic terminology"fur"used by ZHANG Zhongjing contains architectural metaphors,reflecting the characteristic of the tongue coating being flat and slightly higher than the tongue body.During the Ming and Qing dynasties,medical practitioners gradually used the term"moss"to illustrate the organic connection between tongue coating and the tongue body through plant metaphors.They constructed metaphors of water and fire,as well as plants,to explain how tongue coating forms in both physiological and pathological states.Therefore,compared to the"fur,"the"moss"has a richer metaphorical meaning,corresponding to the connotations of tongue coating terminology,which helps explain related physiological and pathological manifestations,and is a key factor affecting the evolution of tongue coating terminology.

Aim To study the effect of p-benzoyl sali-droside(pOBz)on angiogenesis after ischemic stroke and to explore the underlying mechanism.Methods The MCAO model was prepared by suture method.Rats were divided into four groups:sham,MCAO,pOBz administration,and edaravone positive control,treated for seven days.The mNSS was used to assess the neurological impairment.Western blotting was em-ployed to detect CD31,NICD,and Hes-1 protein ex-pression,while immunofluorescence staining was ap-plies to quantify CD31-positive cells in ischemic brain tissue.In vitro an OGD/R model was established in HUVECs.Following treatment with varying pOBz con-centrations(0.01,0.1,1 μmol·L-1),the CCK-8 as-say was uses to measure cell viability,and in vitro tube formation assay was utilized to evaluate angiogenesis.Western blotting was employed again to assess CD31,NICD and Hes-1 protein levels.To further elucidate the mechanism,HUVEC were treated with the Notch inhibitor DAPT prior to grouping and pOBz administra-tion,and the same parameters were evaluated.Results pOBz significantly reduced the mNSS score of MCAO rats,increased CD31-positive cell counts,and upregu-lated CD31,NICD,and Hes-1 protein expression(P＜0.01).In vitro results further showed that pOBz could dose-dependently increase the survival rate and angio-genesis ability of HUVEC induced by OGD/R,and promote CD31,NICD and Hes-1 proteins(P＜0.01),and Notch inhibitor DAPT could reverse the above effects of pOBz.Conclusion pOBz promotes angio-genesis in HUVEC,and its mechanism involves activa-tion of the Notch signaling pathway.

Objective This study aimed to explore the ability of ultrasonographic radiomics in predicting the occurrence of in-stent restenosis(ISR)after carotid artery stenting(CAS)by analyzing the correlation between radiomic features of responsible plaques in carotid artery stenosis and the incidence of ISR.Methods A retrospective collection was conducted on 206 cases that underwent CAS treatment at our hospital.The enrolled patients were randomly split into a training set(144 cases)and a test set(62 cases)at a 7∶3 ratio.We utilized the Darwin Intelligent Research Platform to extract radiomic features from each region of interest,and then screened 1125 ultrasonographic radiomic features.Different machine learning algorithms were employed to construct diagnostic models,and the best-performing classifier was selected.Various prediction models were established,including a clinical-ultrasonographic feature model,a radiomic model,and a combined clinical-ultrasonographic-radiomic model.Results Multivariate logistic regression analysis in the training set revealed that hypertension,hyperuricemia,triglycerides,and plaque location were independent risk factors for ISR after CAS.For the clinical-ultrasonographic model,the area under the curve(AUC)values for the training and validation sets were 0.896 and 0.644,respectively.The corresponding AUC values for the radiomic model were 0.961 and 0.715,while those for the combined model were 0.947 and 0.727.Conclusion The radiomic model demonstrates superior performance in predicting ISR compared to the traditional clinical-ultrasonographic model.The combined model exhibited an enhanced ability to predict ISR occurrence,thereby improving the diagnostic performance of traditional assessments.

Aim To study the neuroprotective effects of Herba siegesbeckiae extract on cerebral ischemia/ reperfusion rats and its mechanism. Methods Sixty SD rats were randomly divided into model group, low, middle and high dose groups of Herba siegesbeckiae, and Sham operation group, and the drug was given continuously for seven days. The degree of neurologic impairment was evaluated by mNSS, and the infarct volume was measured by MRI. The number of Nissl-posi- tive cells was detected by Nissl staining, and the apop- tosis was accessed by Tunel staining. Furthermore, the expression of Bax, Bcl-2 and NeuN was observed by Western blot, and the expression of NeuN was detected by immunofluorescence staining. The expression of IL- 1β, TNF-α and IL-6 mRNA was performed by RT- qPCR. Results The mNSS score and the volume of ischemic cerebral infarction in the model group were significantly increased, and Herba siegesbeckiae extract treatment significantly decreased the mNSS score and infarct volume (P<0.05, P<0.01). Herba siegesbeckiae extract could increase the number of Nissl-pos- itive cells and the expression of NeuN (P<0.01), and reduce the number of Tunel-positive cells (P<0.01). Western blot showed that Herba siegesbeckiae extract inhibited the expression of Bax, increased Bcl-2 and NeuN in ischemic brain tissue (P<0.01). RT-qPCR showed that Herba siegesbeckiae extract inhibited the expression of IL-1 β, TNF-α and IL-6 mRNA in the is-chemic brain tissue (P<0.01). Conclusions Herba siegesbeckiae extract can reduce the cerebral infarction volume, improve the neurological function damage, inhibit the apoptosis of nerve cells and the expression of inflammatory factors and promote the expression of NeuN, there by exerting protective effects on MCAO rats.

Objective To explore the feasibility and effectiveness of the artificial intelligence(AI)diagnostic model for bone age imaging in the radiology information system-picture archiving and communication system(RIS-PACS)environment operation.Methods The optimized bone age AI model was integrated into the RIS-PACS platform.The bone age imaging data of 88 038 patients aged 0-18 years old were automatically evaluated.The reference bone age was determined by the consensus of two experienced radi-ologists based on GP map,with an error of±1.0 year old.The success rate,accuracy,system compatibility,stability,and influen-cing factors of results were further analyzed.Results The time for bone age AI evaluation of each case did not exceed 3 seconds,and the success rate of automatic evaluation reached 100%.AI model of bone age and RIS-PACS in hospital could be well integrated.Accord-ing to the readings evaluated by pediatric radiologists based on GP maps,the accuracy rate was 93.05%for girls and 89.53%for boys,with a mean absolute error(MAE)of(0.42±0.54)years old for girls and(0.45±0.60)years old for boys,respectively.The AI model could run efficiency in the RIS-PACS,which significantly reduced the burden of radiologists.The factors that affect the accuracy of the model were image position,exposures,multiple images in a single sequence and hand deformity,etc.Conclusion The bone age imaging AI diagnostic model can be seamlessly embedded into RIS-PACS in hospital,achieving one click bone age imaging diagnosis.