OBJECTIVE To investigate the effects of borneol on pharmacodynamic and pharmacokinetic effects of Corydalis saxicola total alkaloids in depression model rats. METHODS Thirty male SD rats were divided into blank control group， negative control group， positive control group （fluoxetine 10 mg/kg， i.g.）， single drug group （C. saxicola total alkaloids 210 mg/kg， i.g.） and combined drug group （C. saxicola total alkaloids 210 mg/kg+borneol 50 mg/kg， i.g.） according to the random number table method， with 6 rats in each group. By lipopolysaccharide （LPS） induction modeling， except blank control group （no model and no administration） received intraperitoneal injection of the same amount of normal saline， the rats in the other groups were intraperitoneally injected with LPS once a day to establish a rat model of depression. After 1 week of modeling， each administration group was given relevant drug intragastrically according to the corresponding dose， and blank control group and negative control group （without drug treatment） were administered intragastrically with an equal volume of solvent to dissolve the drug； continued modeling while administering the drug. After two weeks of continuous administration， the effects of C. saxicola total alkaloids versus the combination of C. saxicola total alkaloids and borneol on the behavior of depressed rats were tested by behavioral experiments； the levels of tumor necrosis factor-α， interleukin-1β and interleukin-6 in rats were determined； the histopathological changes of the hippocampus of rats were observed. Blood sample was collected from the orbit at different time points after administration on the 15th day， and the upper plasma was obtained. Ultra-performance liquid chromatography-triple quadrupole tandem mass spectrometry was established for the simultaneous determination of dehydrocarvedine， tetrahydropalmatine， coptisine， palmatine， jatrorrhizine， berberine， berberrubine and epiberberine in rat plasma. The average plasma concentration-time curve was depicted， the area under the curve （AUC） was calculated， and the pharmacokinetic parameters were analyzed by DAS 3.2.2 software. RESULTS Compared with blank control group， the negative control group had a decrease in body mass and sugar water preference rate， a decrease in the total distance of open field， a prolonged swimming immobility time， and a increased in the expression of inflammatory factors in serum （P＜0.05）； compared with negative control group, the single drug group and the combined drug group increased the preference rate of sugar water， increased the total distance of open field， shortened the time of swimming immobility， and decreased the expression of inflammatory factors in serum （P＜0.05）. There was no significant difference in the above indicators between the single drug group and the combined drug group in rats （P＞0.05）. Pharmacokinetic results showed that compared with single drug group， AUC0-t of coptisine， AUC0-t， AUC0-∞， tmax and cmax of jatrorrhizine， AUC0-t， AUC0-∞， t1/2 and cmax of berberrubine， and AUC0-t of epiberberine， cmax of dehydrocarvedine， cmax of palmatine were significantly increased in combined drug group， but there was no significant difference， indicating that borneol didn’t have a significant effect on the efficacy of Corydalis saxicola nigra at this dose. CONCLUSIONS Both C. saxicola total alkaloids alone and in combination with borneol can improve depression-like behavior in depression model rats， reduce serum inflammatory cytokine levels， and protect hippocampal neurons. Compared with the use of Corydalis saxicola base alone， the combination with borneol do not show significant pharmacodynamic differences， bu can improve the absorption of coptisine， jatrorrhizine in model rats.

[Objective] To compare the diagnostic accuracy of three imaging modalities, inlducing CT urography (CTU), contrast-enhanced MRI (CE-MRI), and contrast-enhanced ultrasound (CEUS) in the qualitative diagnosis of renal space-occupying lesions. [Methods] A retrospective analysis was performed on 542 patients with renal lesions confirmed by surgical pathology in our hospital during Jan.2019 and May 2024.The diagnostic results of CTU, CE-MRI and CEUS were compared and analyzed based on the patients' clinical and pathological data. [Results] The diagnostic accuracy rate of CTU, CE-MRI and CEUS were 84.50%, 83.14% and 86.14%, respectively.For the 161 patients who underwent all three examinations, CEUS was significantly more accurate than CTU (84.16% vs. 77.02%, P=0.018), while there was no significant difference between CTU or CEUS and CE-MRI (79.81%) (P>0.05). Further analysis found that for lesions ≤4 cm, the accuracy of the three examinations was as follows: CEUS=CTU 79.55%, CE-MRI 76.14%, with no significant difference (P>0.05). However, for lesions >4 cm, CEUS ranked the first, followed by CE-MRI and CTU (89.73% vs. 84.25% vs. 73.97%), and CEUS and CE-MRI were better than CTU (P<0.05). Additionally, for the diagnosis of clear cell renal carcinoma and benign renal space-occupying lesions, there was no statistically significant difference among the three imaging modalities (P>0.05), while for the qualitative diagnosis of non-clear cell renal carcinoma, CEUS ranked the first, followed by CE-MRI and CTU (83.87% vs. 74.19% vs. 56.45%), and CE-MRI and CEUS were better than CTU (P<0.05). [Conclusion] All of them have important diagnostic value, and the appropriate selection should be based on patients' specifc conditions.CEUS and CE-MRI are more accurate in the qualitative diagnosis of renal space-occupying lesions than CTU, especially for large lesions and non-clear cell carcinoma.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Oral cancer is one of the most common malignancies in the head and neck regions. few patients benefit from current clinical therapy. Zinc finger proteins (ZNFs) are one of the largest transcription factor family proteins in the human genome. ZNFs bind to DNA, RNA, and proteins through their unique three-dimensional structure created by zinc ions to regulate gene transcription, RNA packaging, and protein folding. In recent years, the number of studies focused on the functional mechanism of ZNFs in regulating the progression of oral cancer has been increasing, with focuses on: ① ZNF677, ZNF460, ZNF154, ZNF132, ZNF281, Kaiso, and ZNF582, which regulate the invasion and metastasis of tumor cells; ② ZNF750 and PEST-containing nuclear protein (PCNP), which regulate the cell cycle; ③ ZNFs, which are involved in forming the tumor immune microenvironment, such as ZNF71 and myeloid zinc finger 1 (MZF1). For example, methylation modification modulates the reduction of ZNF677 in oral cancer and reduces the proliferation, migration, and invasion of oral cancer cells by inhibiting the protein kinase B/forkhead box O3a (AKT/FOXO3a) pathway; and ZNF460 promotes the proliferation, migration, and invasion of oral cancer cells by regulating microRNA-320a/alpha thalassemia/mental retardation, X-linked (ATRX) axis. In addition, ZNF750 inhibits the growth and metastasis of oral cancer by suppressing cell cycle transcription factor activity. Further, ZNF71 promotes the progression of oral cancer by reducing the infiltration of tumor immune cells. In this review, we will summarize the molecular mechanism, regulatory meshwork, and pro-tumor and anti-tumor roles of ZNFs in the pathogenesis of oral cancer. Our study may provide a new strategy for the diagnosis and treatment of oral cancer.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.