[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.

In maintaining normal function and activation processes, glycolysis, lipid metabolism, and amino acid metabolism play key roles in the energy demand of platelets. In the resting state, platelets primarily rely on glycolysis and aerobic oxidation to generate energy. Upon activation, platelets preferentially utilize glycolysis, as it can more rapidly provide the required ATP. In addition to glycolysis, platelets can also utilize glycogen and fatty acids as additional energy sources. The ATP provided by fatty acid oxidation is crucial for platelet activation. Additionally, during platelet storage, distinctive changes in energy metabolism occur. In the early stages of storage, platelets primarily rely on glycolysis and the pentose phosphate pathway (PPP) to generate energy. In the mid-storage phase, there is an increase in tricarboxylic acid cycle (TCA) metabolism. In the later stages of storage, cellular metabolism gradually declines. The regulation and flexibility of these metabolic pathways play a critical role in the survival and function of platelets in different states.

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.

Serine protease inhibitor Kazal-type (SPINK) is a skin keratinizing protease inhibitor, which was initially found in animal serum and is widely present in plants, animals, bacteria, and viruses, and they act as key regulators of skin keratinizing proteases and are involved in the regulation of keratinocyte proliferation and inflammation, primarily through the inhibition of deregulated tissue kinin-releasing enzymes (KLKs) in skin response. This process plays a crucial role in alleviating various skin problems caused by hyperkeratinization and inflammation, and can greatly improve the overall condition of the skin. Specifically, the different members of the SPINK family, such as SPINK5, SPINK6, SPINK7, and SPINK9, each have unique biological functions and mechanisms of action. The existence of these members demonstrates the diversity and complexity of skin health and disease. First, SPINK5 mutations are closely associated with the development of various skin diseases, such as Netherton’s syndrome and atopic dermatitis, and SPINK5 is able to inhibit the activation of the STAT3 signaling pathway, thereby effectively preventing the metastasis of melanoma cells, which is important in preventing the invasion and migration of malignant tumors. Secondly, SPINK6 is mainly distributed in the epidermis and contains lysine and glutamate residues, which can act as a substrate for epidermal transglutaminase to maintain the normal structure and function of the skin. In addition, SPINK6 can activate the intracellular ERK1/2 and AKT signaling pathways through the activation of epidermal growth factor receptor and protease receptor-2 (EphA2), which can promote the migration of melanoma cells, and SPINK6 further deepens its role in stimulating the migration of malignant tumor cells by inhibiting the activation of STAT3 signaling pathway. This process further deepens its potential impact in stimulating tumor invasive migration. Furthermore, SPINK7 plays a role in the pathology of some inflammatory skin diseases, and is likely to be an important factor contributing to the exacerbation of skin diseases by promoting aberrant proliferation of keratinocytes and local inflammatory responses. Finally, SPINK9 can induce cell migration and promote skin wound healing by activating purinergic receptor 2 (P2R) to induce phosphorylation of epidermal growth factor and further activating the downstream ERK1/2 signaling pathway. In addition, SPINK9 also plays an antimicrobial role, preventing the interference of some pathogenic microorganisms. Taken as a whole, some members of the SPINK family may be potential targets for the treatment of dermatological disorders by regulating multiple biological processes such as keratinization metabolism and immuno-inflammatory processes in the skin. The development of drugs such as small molecule inhibitors and monoclonal antibodies has great potential for the treatment of dermatologic diseases, and future research on SPINK will help to gain a deeper understanding of the physiopathologic processes of the skin. Through its functions and regulatory mechanisms, the formation and maintenance of the skin barrier and the occurrence and development of inflammatory responses can be better understood, which will provide novel ideas and methods for the prevention and treatment of skin diseases.

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 establish a method for simultaneous determination of 7 anti-tumor drugs （irinotecan， capecitabine， paclitaxel， docetaxel， tamoxifen， letrozole and methotrexate） in human plasma and apply it to the clinic. METHODS After precipitating with a methanol-acetonitrile mixture （1∶ 1， V/V） containing 0.1% formic acid， liquid chromatography-tandem mass spectrometry （LC-MS/MS） was used to determine the plasma concentration， using deuterium isotopes of each analyte as internal standards. The chromatography was performed on the Agilent Eclipse Plus C18 column with a gradient elution of water （containing 0.1% formic acid+0.04% 5 mmol/L ammonium formate） as mobile phase A and acetonitrile （containing 0.1% formic acid） as mobile phase B. The flow rate was 0.6 mL/min， and the column temperature was set at 40 ℃ . The sample size was 10 μL， and the analysis lasted for 5.5 min. Electrospray ionization was used in positive and negative ion mode， and multiple reaction monitoring mode was used. The ion pairs used for quantitative analysis were m/z 587.1→167.1 （irinotecan）， m/z 360.1→244.1 （capecitabine）， m/z 876.4→308.0 （paclitaxel）， m/z 830.3→304.2 （docetaxel）， m/z 372.1→129.1 （tamoxifen）， m/z 284.1→242.1 （letrozole）， and m/z 455.0→ 308.0 （methotrexate）. A total of 97 patients with malignant tumors in our hospital were selected to measure the plasma concentrations of 7 anti-tumor drugs using the above method. RESULTS The linear ranges of irinotecan， capecitabine， paclitaxel， docetaxel， tamoxifen， letrozole and methotrexate were 2-1 000 ng/mL （r＝0.994 3）， 20-10 000 ng/mL （r＝0.997 5）， 2-1 000 ng/mL （r＝0.997 9）， 1-500 ng/mL （r＝0.995 8）， 1-500 ng/mL （r＝0.995 2）， 1-500 ng/mL （r＝0.996 4）， 10-5 000 （r＝0.997 7）， respectively. The quantitative lower limits were 2， 20， 2， 1， 1， 1 and 10 ng/mL； RSDs of intra-assay precision were 0.08%-14.86% （n＝6）. RSDs of inter-batch precision were 1.51%-11.55% （n＝3）， and the accuracies were 89.17%-114.93% （n＝6）. The matrix effects ranged from 89.89%-119.74% （n＝6）. RSDs of the stability tests were 1.98%-14.88% （n＝6）. The results of E-mail：hangpengzhou@163.com clinical application showed， the average plasma concentrations of irinotecan， capecitabine， paclitaxel and docetaxel were 704.09， 909.40， 36.45， 150.43 ng/mL， respectively. The values of the coefficient of variation were 25.24%， 62.65%， 122.69%， and 92.27%. CONCLUSIONS The established LC-MS/MS method is simple and rapid， and can be used for the simultaneous determination of 7 commonly used anti-tumor drugs in the plasma of patients with malignancy.

OBJECTIVE To assess the safety profile of sintilimab in combination with chemotherapy for the treatment of cholangiocarcinoma. METHODS The data of patients with cholangiocarcinoma from January 1st， 2021 to December 31st， 2022 were collected and divided into control group （29 cases） and observation group （18 cases） based on different medication regimens. Patients in the control group were treated with Gemcitabine hydrochloride for injection+Cisplatin for injection or Oxaliplatin for injection， the observation group was treated with Sintilimab injection based on the control group. Patients in each group underwent blood routine， liver and kidney function， biochemical and other examinations before and after each treatment cycle to observe the occurrence of adverse drug reactions. The correlation of adverse drug reactions with drugs was evaluated with Naranjo’s scale. RESULTS The correlation between blood toxicity and drug use was deemed “probable” in both groups； however， the observation group exhibited a significantly higher score， indicating a stronger correlation. In the control group， hepatotoxic reactions were classified as “suspicious” whereas in the observation group， they were categorized as “probable”. The correlation of gastrointestinal symptoms between the two groups was considered “possible”. Systemic symptoms， skin toxicity， musculoskeletal toxicity， endocrine toxicity and renal toxicity were all classified as having a “suspicious” correlation with drug use. The total incidence of blood toxicity in the observation group was significantly higher than control group （P＝0.014）. There was no statistically significant difference in the total incidences of hepatotoxic， gastrointestinal symptoms， systemic symptoms， skin toxicity， musculoskeletal toxicity， endocrine toxicity， renal toxicity， or the incidence of grade 3 or higher blood toxicity， hepatotoxic between the two groups （P＞0.05）. For the patients experiencing adverse drug reactions， the symptoms were alleviated following drug discontinuation or symptomatic supportive treatment. No fatalities occurred during the treatment period. CONCLUSIONS Sintilimab combined with chemotherapy may significantly increase the risk of blood toxicity in patients with cholangiocarcinoma， especially thrombocytopenia， but the adverse reactions are within a controllable range， and the overall safety is good.

ObjectiveTo combine metabolomics， proteomics， and transcriptomics to analyze the biological characteristics of damp-heat toxin accumulation syndrome and damp-heat accumulation syndrome in acute gout. MethodsBlood samples were collected from 15 patients with damp-heat toxin accumulation syndrome and 15 patients with damp-heat accumulation syndrome in acute gout in clinical practice. Metabolomics technology was applied to detect serum metabolites， and an orthogonal partial sample least squares discriminant analysis model was constructed to screen for metabolites with significant intergroup changes， and enrichment pathway analysis and receiver operating characteristic （ROC） curve analysis were performed. Astral data independence acquisition （DIA） was used to detect serum proteins， perform principal component analysis and screen differential proteins， demonstrate differential ploidy by radargram， apply subcellular localisation to analyse protein sources， and finally apply weighted gene co-expression network analysis （WGCNA） to find key proteins. Transcriptome sequencing technology was also applied to detect whole blood mRNA， screen differential genes and perform WGCNA， and construct machine learning models to screen key genes. ResultsMetabolome differential analysis revealed 62 differential metabolites in positive ion mode and 26 in negative ion mode. These differential metabolites were mainly enriched in the mTOR signaling pathway and FoxO signaling pathway， with trans-3,5-dimethoxy-4-hydroxycinnamaldehyde， guanabenz， 4-aminophenyl-1-thio-beta-d-galactopyranoside showing the highest diagnostic efficacy. The proteome differential analysis found that 55 proteins up-regulated and 20 proteins down-regulated in the samples of damp-heat toxin accumulation syndrome. Notably， myelin basic protein （MBP）， transferrin （TF）， DKFZp686N02209， and apolipoprotein B （APOB） showed the most significant differences in expression. Differential proteins were mainly enriched in pathways related to fat digestion and absorption， lipid and atherosclerosis， and cholesterol metabolism. WGCNA showed the highest correlation between damp-heat toxin accumulation syndrome and the brown module， with proteins in this module primarily enriched in the hypoxia-inducible factor 1 （HIF-1） signaling pathway and lipid and atherosclerosis. Transcriptomic differential analysis identified 252 differentially expressed genes， with WGCNA indicating the highest correlation between damp-heat toxin accumulation syndrome and the midnight blue module. The random forest （RF） model was identified as the optimal machine learning model， predicting apolipoprotein B receptor （APOBR）， far upstream element-binding protein 2 （KHSRP）， POU domain class 2 transcription factor 2 （POU2F2）， EH domain-containing protein 1 （EHD1）， and family with sequence similarity 110A （FAM110A） as key genes. Integrated multi-omics analysis suggested that damp-heat toxin accumulation syndrome in the acute phase of gout is closely associated with lipid metabolism， particularly APOB. ConclusionCompared to damp-heat accumulation syndrome in the acute phase of gout， damp-heat toxin accumulation syndrome is more closely associated with lipid metabolism， particularly APOB， and lipid metabolism disorders contribute to the development of damp-heat toxin accumulation syndrome in patients with acute gout.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

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.