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.

ObjectiveThis paper aims to observe the effect of Huazhuo Sanjie Chubi prescription （HSCD） on the gouty bone erosion model rats and investigate its action mechanism. MethodsThirty-six two-month-old male SD rats were randomly divided into the blank group with nine rats and the modeling group with 27 rats. The rats in the modeling group were administered hypoxanthine solution at 300 mg·kg^-1·d^-1 and potassium oxonate solution at 250 mg·kg^-1·d^-1， combined with intra-articular injection of 200 μL monosodium urate （MSU） crystal suspension at 25 g·L^-1 into the right ankle joint （joint injection once every three days）， so as to induce the gouty bone erosion model. After four weeks of modeling， three rats were selected from these two groups to validate the model. The modeled 24 rats were randomly divided into the model group， HSCD group （10.35 g·kg^-1·d^-1）， allopurinol group （20 mg·kg^-1·d^-1）， and inhibitor group （LY294002， 10 mg·kg^-1·d^-1）， with six rats per group. Except for the blank group， rats in all other groups continued to receive hypoxanthine solution at 300 mg·kg^-1 and potassium oxonate solution at 250 mg·kg^-1 via gavage concurrently with administration to maintain modeling intervention. The rats in the HSCD group and allopurinol group received administration by gavage at the above doses. The rats in the inhibitor group received an intraperitoneal injection at the above dose. The rats in the blank group and model group received saline （10.35 g·kg^-1·d^-1） by gavage for four consecutive weeks. After administration， ankle joint swelling of the rats in all groups was observed， and the diameters were measured. Bone volume fraction （BV/TV） and bone surface area to bone volume （BS/BV） were observed and quantitatively analyzed by Micro-CT. Histopathological changes in the ankle joint were observed by hematoxylin-eosin （HE） staining and safranin O-fast green staining. The uric acid in the rats' serum was determined by enzyme colorimetry. The levels of inflammatory factors， including tumor necrosis factor-α （TNF-α）， interleukin （IL）-1β， and IL-6 were measured by enzyme-linked immunosorbent assay （ELISA）. The protein expressions of receptor activator of nuclear factor-κB ligand （RANKL） and phosphorylated （p）-phosphatidylinositol-3-kinase （PI3K） in ankle joint tissues of rats were detected by immunofluorescence staining. The mRNA levels of the proteins related to the bone erosion， including RANKL， tartrate-resistant acid phosphatase （TRAP）， cathepsin K （CTSK）， and matrix metalloproteinase-9 （MMP-9） in the ankle joint tissues of rats were determined by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The expressions of the proteins related to the bone erosion， including RANKL， CTSK， TRAP， MMP-9， and the proteins related to the PI3K/protein kinase B （Akt） signaling pathway， including PI3K， Akt， mammalian target of rapamycin （mTOR）， p-PI3K， phosphorylated protein kinase B （p-Akt）， and phosphorylated mammalian target of rapamycin （p-mTOR）， were detected by Western blot. ResultsCompared with the blank group， the modeling group showed marked ankle swelling and increased diameter. Micro-CT revealed an uneven articular surface and honeycomb-like bone erosion in the ankle joint. Quantitative analysis showed decreased BV/TV and increased BS/BV （P<0.05）. HE staining revealed a narrowed joint space， rough and discontinuous cartilage surfaces， reduced and unevenly distributed chondrocytes， partial hypertrophy， and blurred tidemarks， confirming successful model establishment. After four weeks of intervention， compared with those in the blank group， the rats in the model group exhibited severe ankle swelling and increased diameters （P<0.05）. Micro‑CT showed that the ankle joint surface was irregular， and bone erosion exhibited a honeycomb‑like morphology. The microstructural parameters of the bone revealed a decreased BV/TV and an increased BS/BV （P<0.05）. Histopathological examination revealed a narrowed joint space and severe articular cartilage destruction. The levels of uric acid in the serum and inflammatory factors （IL-1β， IL-6， and TNF-α） were increased （P<0.05）. The mRNA and protein levels of the proteins related to bone erosion in joint tissue， including RANKL， CTSK， TRAP， and MMP-9， were upregulated （P<0.05）. The ratios of p-PI3K/PI3K， p-Akt/Akt， and p-mTOR/mTOR in the proteins related to the PI3K/Akt signaling pathway were increased （P<0.05）. RANKL and p-PI3K protein fluorescence intensities were elevated （P<0.05）. Compared with those in the model group， the above indicators in all other administration groups showed varying degrees of improvement. The HSCD group and inhibitor groups exhibited more significant effects in reducing ankle swelling， improving bone erosion， bone microstructure （significant decrease in BV/TV and increase in BS/BV）， and the pathology of cartilage erosion， lowering inflammatory factor levels， downregulating the proteins related to the bone erosion， and suppressing activation of the PI3K/Akt/mTOR pathway （P<0.05）. The uric acid levels in rats' serum were reduced in both HSCD and allopurinol groups （P<0.05）. Compared with those in the HSCD group， the rats in the allopurinol group had larger ankle diameters （P<0.05）， more severe bone erosion and bone microstructure damage （P<0.05）， worse improvement of the pathology of cartilage erosion， higher levels of IL-6 and TNF-α （P<0.05）， elevated expressions of the proteins related to the bone erosion， higher expression ratio of proteins related to the PI3K/Akt signaling pathway （P<0.05）， and higher fluorescence intensities of RANKL and p-PI3K proteins （P<0.05）. The inhibitor group achieved comparable results to the HSCD group in improvements of bone microstructure and the reduction of IL-1β and IL-6， stronger suppression of TNF-α and PI3K/Akt/mTOR signaling pathway activation （P<0.05）， but weaker effects on cartilage repair and serum uric acid reduction （P<0.05）. ConclusionHSCD effectively reduces uric acid levels in serum， suppresses inflammatory factor secretion， and downregulates the expressions of proteins related to bone erosion， including RANKL， CTSK， TRAP， and MMP-9 in the joint tissues. Its action mechanism of improving gouty bone erosion may be associated with inhibition of the PI3K/Akt signaling pathway.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Objective To analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

[Objective] To analyze the clinicopathological characteristics of treatment-naive patients with highly suspected prostate cancer (PCa) with prostate-specific antigen (PSA) level ≥20 ng/mL, to provide reference for promoting early screening of PCa. [Methods] A retrospective analysis was conducted on the clinical data of treatment-naive patients with PSA level ≥20 ng/mL, undergoing prostate biopsy for highly suspected PCa at the Department of Urology, Tianjin Medical University Second Hospital during Jan.2013 and Jun.2023. The correlation between patients' age, body mass index (BMI), PSA, prostate volume (PV), prostate cancer-specific antigen density (PSAD), prostate imaging reporting and data system (PI-RADS) score, and International Society of Urological Pathology (ISUP) grade with highly suspected PCa metastasis and PSA stratification were analyzed. [Results] A total of 1778 suspected patients were enrolled. Pathological findings confirmed PCa in 1465 cases (82.4%), with 487(33.2%) diagnosed as metastatic PCa. Over the past decade, the number of patients undergoing prostate biopsy for highly suspected PCa and being confirmed has been increasing annually, with the proportion of metastatic cases remaining at around 30%. Compared with those with PSA level being 20-50 ng/mL, patients with PSA level >50 ng/mL had older age, lower BMI, higher PSAD, higher PI-RADS, higher ISUP, more diverse pathological types, and a higher incidence of metastasis (P<0.05) with lower proportion of urban residents. Additionally, analysis of metastatic PCa cases showed that 46.8%(228/487) had oligometastasis (≤5 metastatic lesions), including 99.0% bone metastasis, 4.1% extraregional lymph node metastasis, and 4.3% other organ metastasis. [Conclusion] Over the past 10 years, there has been a continuous increase in the number of treatment-naive biopsied cases and newly diagnosed cases of highly suspicious PCa with PSA level ≥20 ng/mL, while the proportion of metastatic cases remains high. Therefore, proactive efforts should be made to promote early screening of high-risk suspected cases.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.