Esophageal cancer （EC） is a highly prevalent malignant tumor in China. The phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway， as one of the key oncogenic pathways， can promote the cell cycle progression， proliferation， migration， and invasion， induce chemoresistance， and inhibit apoptosis and autophagy of EC cells. Traditional Chinese medicine （TCM）， with the advantages of targeting multiple points with multiple components to delay cancer progression， can target the PI3K/Akt signaling pathway for EC treatment. This article preliminarily discusses the molecular mechanism and role of the PI3K/Akt signaling pathway in EC and elaborates on the specific targets and efficacy of TCM in treating EC through intervention in the PI3K/Akt signaling pathway in the past five years. TCM materials and extracts inhibiting the PI3K/Akt signaling pathway in EC include Borneolum， spore powder of Ganoderma lucidum without spore coat， extract of Celastrus orbiculatus， root extract of Taraxacum， and Bruceae Fructus oil emulsion. TCM active ingredients exerting the effect include flavonoids， terpenoids， saponins， phenols， polysaccharides， alkaloids， and other compounds. TCM compound prescriptions with such effect include Qige San， Huqi San， Xuanfu Daizhetang， Tongyoutang and its decomposed prescriptions， Liujunzi Tang， and Xishenzhi Formula. In addition， TCM injections such as Compound Kushen Injection and Kang'ai injection also inhibit the PI3K/Akt signaling pathway in EC. This paper summarizes the role of the PI3K/Akt signaling pathway in EC and the TCM interventions， aiming to provide reference for the research and clinical application of new drugs for EC.

ObjectiveTo investigate the potential mechanism of Danggui Shaoyaosan （DSS） in ameliorating renal injury in db/db mice. MethodsThirty 8-week-old specific pathogen-free （SPF）-grade male db/db mice and six db/m mice were acclimated for one week. Urinary microalbumin and blood glucose levels were measured weekly in both db/db and db/m mice. Successful modeling was determined by significantly higher microalbuminuria in db/db mice compared to db/m mice and a fasting blood glucose ≥16.7 mmol·L^-1. The 30 db/db mice were randomly divided into five groups： the model group， the irbesartan （IBN） group， and three DSS dose groups （low-， medium-， and high-dose DSS groups， administered at 16.77， 33.54， 67.08 g·kg^-1·d^-1， respectively）. Additionally， the six db/m mice served as the normal control group. The IBN group received irbesartan at 0.025 g·kg^-1·d^-1 by gavage， while the three DSS groups received DSS at 16.77， 33.54， and 67.08 g·kg^-1·d^-1 by gavage， respectively. The normal and model groups were administered with an equivalent volume of normal saline by gavage. All interventions lasted for 8 consecutive weeks. After intervention， serum creatinine （SCr）， blood urea nitrogen （BUN）， urinary total protein （UTP）， triglyceride （TG）， and low-density lipoprotein cholesterol （LDL-C） were measured to evaluate the therapeutic efficacy of the treatments. Renal histopathological changes were observed with hematoxylin-eosin （HE） staining. Western blot was used to detect the protein expression of silencing information regulator 1 （SIRT1）， hypoxia-inducible factor-1α （HIF-1α）， very low-density lipoprotein receptor （VLDLr）， and cluster of differentiation 31 （CD31）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA levels of HIF-1α and VLDLr. Immunohistochemistry was used to observe the expression and distribution of HIF-1α and Caspase-3. ResultsCompared to the normal group， the model group showed significantly increased SCr， BUN， UTP， TG， and LDL-C. HE staining revealed glomerulosclerosis， mesangial matrix hyperplasia， capillary loop distortion and thickening， with extensive inflammatory cell infiltration. Protein expression of SIRT1 and CD31 significantly decreased （P<0.05）， while HIF-1α and VLDLr protein and mRNA levels increased （P<0.05）. Immunohistochemistry showed increased expression of HIF-1α and Caspase-3 （P<0.05）， indicating hypoxia and apoptosis in renal cells. In all treatment groups， SCr， BUN， TG， and LDL-C were significantly reduced compared to the model group （P<0.05）， and UTP was significantly improved in the medium-dose DSS group （P<0.05）. Renal tissue structure and morphology were improved， inflammatory cells were reduced， and no vascular hyaline degeneration was observed. SIRT1 and CD31 protein expression was elevated to varying degrees compared to the model group （P<0.05）， while HIF-1α and VLDLr protein and mRNA levels decreased （P<0.05）. Immunohistochemistry showed reduced expression of HIF-1α and Caspase-3 in all treatment groups （P<0.05）， with the most significant improvement observed in the IBN group and medium-dose DSS group （P<0.05）. ConclusionDSS can effectively ameliorate glomerulosclerosis and lipid deposition in db/db mice， and its mechanism may involve the SIRT1/HIF-1α/VLDLr signaling pathway.

ObjectiveTo investigate the therapeutic efficacy of Danggui Shaoyaosan （DSS） on renal injury in db/db mice and its impact on endoplasmic reticulum stress （ERS） in renal tissues. MethodsThirty 8-week-old male db/db mice and six db/m mice were acclimated for one week， after which urinary microalbumin and blood glucose levels were monitored to establish a diabetic kidney disease （DKD） model. The model mice were randomly divided into a model group， an irbesartan group， and three DSS treatment groups with different doses （16.77， 33.54， and 67.08 g·kg^-1·d^-1）. A normal group was set as control. Each group was intragastrically administered with the corresponding drugs or saline for 8 weeks. After the intervention， general conditions were observed. Serum cystatin C （Cys-C）， 24-hour urinary total protein （24 h-UTP）， 24-hour urinary microalbumin （24 h-UMA）， urinary creatinine （Ucr）， and urea nitrogen （UUN） were measured. Transmission electron microscopy （TEM） was used to observe glomerular basement membrane （GBM） and ultrastructural changes of the endoplasmic reticulum （ER） in glomerular endothelial cells. Western blot， real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， and immunohistochemistry were used to analyze renal tissue structure and the expression of GRP78， CHOP， and related markers. ResultsCompared with the normal group， the mice in the model group showed curled posture， sluggish response， poor fur condition， increased levels of Cys-C， 24 h-UTP， 24 h-UMA， and UUN （P<0.05）， while Ucr decreased （P<0.05）. The GBM was significantly thickened， with podocyte and foot process fusion. The protein expressions of GRP78， CHOP， and ATF6 were significantly upregulated （P<0.05）， the mRNA levels of GRP78 and CHOP increased （P<0.05）， and immunohistochemistry showed an enhanced GRP78 signal （P<0.05）. After treatment， the mice exhibited improved behavior， normalized GBM and podocyte structure， improved ER morphology and markedly better biochemical indicators. Western blot， Real-time PCR， and immunohistochemistry indicated that the ERS-related markers were downregulated in the DSS treatment groups （P<0.05）， suggesting alleviated ERS and improved renal function. ConclusionDSS can effectively ameliorate renal pathological damage in db/db mice， possibly by regulating ERS in glomerular endothelial cells， although the underlying signaling mechanisms require further investigation.

This article systematically reviews and verifies the name， origin， production area， quality evaluation， harvesting， processing and other aspects of Cynanchi Atrati Radix et Rhizoma（CARR） by consulting relevant ancient and modern literature， in order to provide a basis for the development and utilization of famous classical formulas containing this herb. Through textual research， Baiwei has been the official name for CARR， though it also bears alternative names such as Chuncao， Popo Zhenxianbao， Longdan Baiwei. The mainstream base is the roots and rhizomes of Cynanchum atratum. Historical records indicate primary producing areas include Shandong， Anhui， Jiangsu， Shaanxi and Shanxi. Since the late Ming dynasty， varieties from Juxian， Yishui and Rizhao in Shandong have been highly regarded as authentic， commonly known as eastern Baiwei. Since modern times， its quality has been summarized as fine， slender， and straight fibrous roots， pale yellow exterior， whiter interior， and dryness with easy breakability are considered superior. The harvesting time before the Song dynasty was on the third day of the third lunar month， but after the Song dynasty， harvesting was possible in both spring and autumn. The initial processing methods of CARR in ancient times included drying in the shade， removing Lu（the little rhizomes which are on tap of roots）， and removing mustaches， modern methods involve washing and sun-drying. During the Northern and Southern dynasties， processing methods included steaming. In the Song dynasty， drying and light stir-frying were predominant， while wine washing emerged in the Ming dynasty. Modern practices primarily involve using raw， stir-frying or honey processing. Regarding the medicinal properties of CARR， both ancient and modern texts agree it has a bitter and salty taste and is non-toxic. Records prior to the Qing dynasty predominantly describe its nature as extremely cold， while mainstream herbal texts after the Qing dynasty generally characterize it as cold. Before the Ming dynasty， there were no records of its meridian tropism. It was not until the Qing dynasty that it was recorded in the lung meridian. Modern records mainly refer to the stomach， liver， and kidney meridians. Throughout history， its main functions have been to clear heat， diuresis， nourish Yin， and replenish essence， primarily treating Yin deficiency and fever syndrome. Based on the research results， it is suggested that when developing famous classical formulas containing CARR， the dried roots and rhizomes of C. atratum can be selected as its medicinal source. If there are no specific processing requirements， raw products can be selected as medicine. If the processing requirements are specified， corresponding processed products can be selected as medicine according to the original formula requirements.

ObjectiveTo identify potential influencing factors of urate crystal deposition at ankle/foot in patients with hyperuricemia （HUA）， and to analyze the predictive value of inflammatory indicators for urate crystal deposition in patients with different traditional Chinese medicine （TCM） syndromes， so as to provide potential reference for clinical risk assessment and individualized TCM intervention. MethodsA retrospective study was carried out with the enrollment of 231 HUA patients from The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine between January 2021 and December 2024. The enrolled patients were further divided into a crystal deposition-positive group （143 cases） and a crystal deposition-negative group （88 cases） according to the results of dual-energy computed tomography （CT）. Sociodemographic data， living habits， serum uric acid levels， and inflammatory indicators of the enrolled patients were collcted， and TCM syndrome differentiation was performed. Furthermore， univariate analysis was used to compare inter-group differences in clinical characteristics. MMultivariate Logistic regression was applied to identify the influencing factors of urate crystal deposition. In addition， the receiver operating characteristic （ROC） curves were plotted to evaluate the predictive efficacy of inflammatory indicators for crystal deposition across different TCM syndromes. ResultsThere were statistically significant inter-group differences in the proportion of males， age， body mass index， proportion of mental labor， rate of low water intake， and rate of high-sugar beverage consumption （P<0.05），whereas no significant difference in low exercise intensity was found between the two groups. Furthermore， compared with the negative group， the positive group had higher serum uric acid level， neutrophil-to-lymphocyte ratio （NLR）， and platelet-to-lymphocyte ratio （PLR）， but lower systemic immune-inflammation index （SIRI） （P<0.05）. Regarding the distribution of TCM syndromes， the positive group was dominated by the dampness-heat accumulation syndrome （55/143，38.46%）， while the negative group was mainly characterized by the phlegm-turbidity obstruction syndrome （44/88，50.00%）. Multivariate Logistic regression analysis revealed that high-sugar beverage consumption， elevated NLR， and elevated PLR were risk factors for urate crystal deposition ［odd ratio （OR） = 8.002， 5.377， 1.034， respectively； 95% CI 1.572-40.732， 2.179-13.270， 1.013-1.054，all P<0.05］， while SIRI was a protective factor （OR = 0.869， 95% CI 0.778-0.971， P<0.05）. In the positive group， patients with the dampness-heat accumulation syndrome exhibited the highest NLR， while the lowest PLR and SIRI， showing statistically significant differences with those of other syndromes （all P<0.05）. In addition， ROC curve analysis indicated that for the dampness-heat accumulation syndrome， the combined "NLR + PLR" model had an area under the curve （AUC） of 0.901 （95% CI 0.850-0.951， P<0.01）， with a sensitivity of 89.1% and a specificity of 79.5%； for the blood stasis-heat obstruction syndrome， the combined "NLR + PLR" model had an AUC of 0.880 （95% CI 0.825-0.934， P<0.01）， with a sensitivity of 100.0% and a specificity of 67.3%； for the liver-kidney Yin-deficiency syndrome， the single PLR model had an AUC of 0.842 （95% CI 0.731-0.952， P<0.01）， with a sensitivity of 83.3% and a specificity of 84.0%. ConclusionUrate crystal deposition in HUA patients exhibits intimate associations with high-sugar beverage consumption as well as elevated NLR and PLR levels. Meanwhile， TCM syndrome differentiation has potential correlation with inflammatory characteristics. The inflammatory indicator-based prediction model constructed based on TCM syndromes exhibits good predictive value.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

Although global brain science research has progressed rapidly in recent decades, several fundamental questions in neuroscience remain unresolved. In particular, the physical mechanism underlying neural signal transmission remains controversial, and the carriers responsible for neural information storage and retrieval have not yet been fully clarified. These unresolved issues motivate us to re-examine the processes of neural information generation, transmission, integration, storage, and retrieval from multiple perspectives. A key observation is that neural electromagnetic activities are closely associated with time. Their duration, temporal structure, and dynamic evolution play crucial roles in neural information processing. In this work, we analyze neural electromagnetic activities from the perspective of temporal scales (referred to here as the “time course”). By reviewing and integrating findings from previous studies, we examine the characteristic time requirements and dynamic features of neural processes occurring at different stages of information processing. These stages include neural signal generation, signal transmission along axons, synaptic integration, synaptic plasticity, and memory formation and retrieval. Based on this temporal analysis, we outline a framework describing neural electromagnetic activities across a wide range of time scales, spanning from microseconds to minutes, hours, or even longer periods associated with long-term memory, which suggests that neural information processing involves multiple physical processes operating at different time levels. Rapid electromagnetic events may occur on microsecond scales, whereas electrophysiological phenomena such as action potentials typically last on the order of milliseconds. Longer time scales are associated with synaptic plasticity and memory-related processes. From this perspective, we propose that the physical carrier of neural information may be transient electromagnetic pulses with durations on the microsecond scale. In this framework, action potentials can be interpreted as the macroscopic electrophysiological manifestation of underlying electromagnetic processes triggered by ionic currents across neuronal membranes. Rather than being the fundamental neural signal itself, the action potential may represent a measurable membrane-level response associated with the successful activation of these electromagnetic events. Moreover, we discuss a possible mechanism for long-term memory storage. Considering the apparent temporal contradiction between the millisecond-scale excitation of neurons and the long-term persistence of memories, we believe that long-term memory information may be stored within neural network topologies formed by electrical synapse coupling. Such structures, referred to as electrically coupled memory networks (ECMNs), may enable neurons within the same network to respond rapidly and synchronously to stimuli, thereby facilitating efficient memory retrieval. Overall, this study emphasizes the importance of considering the temporal organization of neural electromagnetic activities when interpreting neural signaling mechanisms. It may provide new insights into the physical nature of neural information carriers and the mechanisms of memory storage and retrieval. Furthermore, highlighting the potential role of electromagnetic interactions in neural activity may contribute to the development of new theoretical frameworks and experimental approaches in neuroscience. Such perspectives may also offer valuable references for future research on neural coding, brain function mechanisms, and neuromodulation technologies.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.