ObjectiveThis paper aims to investigate the potential molecular biological mechanism of Buyang Huanwu Tongfeng decoction in treating hyperuricemia and gouty arthritis by network pharmacology and molecular docking technology and preliminarily verify the mechanism through animal experiments. MethodsThe active ingredients and targets in the Buyang Huanwu Tongfeng decoction were obtained by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and ETCM databases. The DisGeNET and GeneCards databases were utilized to acquire disease targets associated with hyperuricemia and gouty arthritis. These disease targets were then intersected with drug targets to identify key targets. The R language ClusterProfiler package and Python were employed for conducting gene ontology（GO） enrichment analysis and Kyoto encyclopedia of genes and genomes（KEGG） enrichment analysis. The regulatory network diagram of the drug-key target-function-pathway was visualized using Cytoscape 3.9.1 software， and the protein-protein interaction （PPI） network for key targets was depicted. Finally， the hub gene was determined through topological analysis. Auto Dock， PyMOL， and other software were used for molecular docking to explore the possible therapeutic mechanism of Buyang Huanwu Tongfeng decoction for hyperuricemia and gouty arthritis. In animal experiments， a composite rat model of hyperuricemia induced by intraperitoneal injection of oteracil potassium combined with gouty arthritis induced by the modified Coderre method was established. Through hematoxylin-eosin（HE） staining， uric acid test， enzyme linked immunosorbent assay（ELISA）， Western blot， and real-time polymerase chain reaction（Real-time PCR）， the molecular mechanism and key targets of Buyang Huanwu Tongfeng decoction for treating hyperuricemia and gouty arthritis were observed. ResultsAfter screening and removing duplicate values， 76 active ingredients and 15 key targets were finally obtained. GO enrichment analysis yielded that the treatment of hyperuricemia and gouty arthritis with Buyang Huanwu Tongfeng decoction was significantly associated with acute inflammatory response， astrocyte activation， regulation of interleukin （IL）-8 production， nuclear receptor activity， and binding of growth factor receptor. KEGG pathway enrichment analysis obtained that the key target genes were significantly associated with the IL-17 signaling pathway， advanced glycosylation end/receptor of advanced glycation endproducts（AGE/RAGE） signaling pathway， anti-inflammatory， and other pathways. PPI network indicated that albumin（ALB）， peroxisome proliferator-activated receptor-γ （PPAR-γ）， IL-6， IL-1β， and C-reactive protein（CRP） were the key protein targets. The molecular docking results showed that ALB had the strongest binding force with beta-carotene （β-carotene）. Biochemical results showed that blood uric acid decreased in the Buyang Huanwu Tongfeng decoction groups. HE staining results showed that the low-dose （7.76 g·kg^-1·d^-1）， medium-dose （15.53 g·kg^-1·d^-1）， and high-dose （31.05 g·kg^-1·d^-1） groups of Buyang Huanwu Tongfeng decoction had different degrees of remission， and the remission of the high-dose group was the most obvious. Fibroblastic tissue hyperplasia in synovial joints accompanied with inflammatory cell infiltration， as well as inflammatory cell infiltration in renal tissue of the high-dose group was significantly reduced， followed by the medium-dose and low-dose groups， and the expression of ALB， PPAR-γ， IL-6， IL-1β， and CRP was down-regulated to different degrees. ConclusionBy regulating the targets such as ALB， PPAR-γ， IL-6， IL-1β， and CRP， inhibiting the PPAR-γ/nuclear transcription factor （NF）-κB pathway， and reducing AGEs/RAGE-mediated inflammation， Buyang Huanwu Tongfeng decoction exerts anti-inflammatory and analgesic effects and activates blood circulation and diuresis in the treatment of hyperuricemia and gouty arthritis.

Objective To explore the technical process and clinical application of laparoscopic combined upper midline incision minimally invasive liver transplantation. Methods A retrospective analysis was conducted on 30 cases of laparoscopic combined upper midline incision minimally invasive liver transplantation. The cases were divided into cirrhosis group (15 cases) and liver failure group (15 cases) based on the primary disease. The surgical and postoperative conditions of the two groups were compared. Results All patients successfully underwent laparoscopic "clockwise" liver resection, with no cases of passive conversion to open surgery or intolerance to pneumoperitoneum. In 6 cases, the right lobe was relatively large, and the right hepatic ligaments could not be completely mobilized. One case required an additional reverse "L" incision during open surgery. All patients successfully completed the liver transplantation, with no major intraoperative bleeding, cardiovascular events, or other occurrences in the 30 patients. The model for end-stage liver disease (MELD) score in the cirrhosis group was lower than that in the liver failure group (P<0.001). There were no statistically significant differences between the two groups in terms of age, surgical time, blood loss, anhepatic phase, or cold ischemia time (all P>0.05). During the perioperative period, there was 1 case of hepatic artery embolism, 1 case of portal vein anastomotic stenosis, no complications of hepatic vein and inferior vena cava, and 3 cases of biliary anastomotic stenosis, all of which occurred in the liver failure group. Conclusions In strictly selected cases, the minimally invasive liver transplantation technique combining laparoscopic hepatectomy with upper midline incision for graft implantation has the advantages of smaller incisions, less bleeding, relatively easier operation, and faster postoperative recovery, which is worthy of clinical promotion and application.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

Objective To explore the feasibility and clinical experience of the middle hepatic vein splitting-reconstruction technique in split liver transplantation from low-age donor livers. Methods A retrospective analysis was conducted on the cases of two low-age donor livers that underwent middle hepatic vein splitting-reconstruction, which were transplanted into four child recipients at the Liver Transplantation Center of the Third Affiliated Hospital of Sun Yat-sen University from January 2017 to July 2023. The surgical and postoperative conditions were summarized and analyzed. Results Donor 1 was a 6-year-old and 4-month-old girl with a body weight of 21 kg, and the obtained donor liver weighed 496 g. After splitting, the left and right liver weights were 201 g and 280 g, and transplanted into a 9-month-old boy weighing 6.5 kg and a 9-month-old boy weighing 7.5 kg, respectively. The graft to recipient weight ratio (GRWR) was 3.09% and 3.73%, respectively. Donor 2 was a 5-year-old and 8-month-old boy with a body weight of 19 kg, and the donor liver weighed 673 g. After splitting, the left and right liver weights were 230 g and 400 g, and transplanted into a 13-month-old girl weighing 9.5 kg and a 15-month-old boy weighing 12 kg. The GRWR was 2.42% and 3.33%, respectively. Both donor livers were split ex vivo, with the middle hepatic vein being completely split in the middle and reconstructed using allogeneic iliac vein and iliac artery vascular patches. According to GRWR, none of the 4 transplant livers were reduced in volume. Among the 4 recipients, one died due to postoperative portal vein thrombosis and non-function of the transplant liver, while the other three cases recovered smoothly without early or late complications. Regular follow-up was conducted until July 31, 2023, and liver function recovered well. Conclusions Under the premise of detailed assessment of the donor liver and meticulous intraoperative operation, as well as matching with suitable child recipients, low-age donor livers may be selected for splitting. The complete splitting and reconstruction of the middle hepatic vein in the middle may effectively ensure the adequate venous return of the left and right liver and provide sufficient functional liver volume.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is challenging to treat and lacks targeted therapeutic drugs in the clinic. Natural active ingredients provide promising opportunities for discovering and developing targeted therapies for TNBC. This study investigated the effects of daurisoline on TNBC and elucidated its potential mechanisms. Using network pharmacology, a correlation was identified between daurisoline, derived from Menispermum dauricum, and breast cancer, particularly involving the Notch signaling pathway. The effects of daurisoline on the proliferation, migration, and apoptosis of MDA-MB-231 and MDA-MB-468 cells were evaluated in vitro. Additionally, the impact of daurisoline on the growth of MDA-MB-231 xenograft tumors in nude mice was assessed through in vivo experiments. Expression levels of Notch signaling pathway-related proteins, including Notch-1, NICD, PSEN-1, Bax, and Bcl-2, were examined using molecular docking and Western blotting to explore the underlying mechanisms of daurisoline’s anti-breast cancer effects. It was revealed that daurisoline could effectively inhibit the proliferation and migration of MDA-MB-231 and MDA-MB-468 cells and promote apoptosis. Furthermore, it significantly reduced the growth of subcutaneous tumors in nude mice. Notably, daurisoline could reduce the hydrolytic activity of γ-secretase by binding to the catalytic core PSEN-1, thereby inhibiting activation of the γ-secretase/Notch axis and contributing to its anti-TNBC effects.This study supported the development of naturally targeted drugs for TNBC and provided insights into the research on dibenzylisoquinoline alkaloids, such as daurisoline.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is challenging to treat and lacks targeted therapeutic drugs in the clinic. Natural active ingredients provide promising opportunities for discovering and developing targeted therapies for TNBC. This study investigated the effects of daurisoline on TNBC and elucidated its potential mechanisms. Using network pharmacology, a correlation was identified between daurisoline, derived from Menispermum dauricum, and breast cancer, particularly involving the Notch signaling pathway. The effects of daurisoline on the proliferation, migration, and apoptosis of MDA-MB-231 and MDA-MB-468 cells were evaluated in vitro. Additionally, the impact of daurisoline on the growth of MDA-MB-231 xenograft tumors in nude mice was assessed through in vivo experiments. Expression levels of Notch signaling pathway-related proteins, including Notch-1, NICD, PSEN-1, Bax, and Bcl-2, were examined using molecular docking and Western blotting to explore the underlying mechanisms of daurisoline’s anti-breast cancer effects. It was revealed that daurisoline could effectively inhibit the proliferation and migration of MDA-MB-231 and MDA-MB-468 cells and promote apoptosis. Furthermore, it significantly reduced the growth of subcutaneous tumors in nude mice. Notably, daurisoline could reduce the hydrolytic activity of γ-secretase by binding to the catalytic core PSEN-1, thereby inhibiting activation of the γ-secretase/Notch axis and contributing to its anti-TNBC effects.This study supported the development of naturally targeted drugs for TNBC and provided insights into the research on dibenzylisoquinoline alkaloids, such as daurisoline.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is challenging to treat and lacks targeted therapeutic drugs in the clinic. Natural active ingredients provide promising opportunities for discovering and developing targeted therapies for TNBC. This study investigated the effects of daurisoline on TNBC and elucidated its potential mechanisms. Using network pharmacology, a correlation was identified between daurisoline, derived from Menispermum dauricum, and breast cancer, particularly involving the Notch signaling pathway. The effects of daurisoline on the proliferation, migration, and apoptosis of MDA-MB-231 and MDA-MB-468 cells were evaluated in vitro. Additionally, the impact of daurisoline on the growth of MDA-MB-231 xenograft tumors in nude mice was assessed through in vivo experiments. Expression levels of Notch signaling pathway-related proteins, including Notch-1, NICD, PSEN-1, Bax, and Bcl-2, were examined using molecular docking and Western blotting to explore the underlying mechanisms of daurisoline’s anti-breast cancer effects. It was revealed that daurisoline could effectively inhibit the proliferation and migration of MDA-MB-231 and MDA-MB-468 cells and promote apoptosis. Furthermore, it significantly reduced the growth of subcutaneous tumors in nude mice. Notably, daurisoline could reduce the hydrolytic activity of γ-secretase by binding to the catalytic core PSEN-1, thereby inhibiting activation of the γ-secretase/Notch axis and contributing to its anti-TNBC effects.This study supported the development of naturally targeted drugs for TNBC and provided insights into the research on dibenzylisoquinoline alkaloids, such as daurisoline.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

ObjectiveFat infiltration has been shown to be closely related to muscle mass loss and a variety of muscle diseases. This study proposes a method based on phase-angle electrical impedance tomography (ΦEIT) to visualize the electrical characteristic response caused by muscle fat infiltration, aiming to provide a new technical means for early non-invasive detection of muscle mass deterioration. MethodsThis study was divided into two parts. First, a laboratory pork model was constructed to simulate different degrees of fat infiltration by injecting1 ml or 2 ml of emulsified fat solution into different muscle compartments, and the phase angle images were reconstructed using ΦEIT. Second, a human experiment was conducted to recruit healthy subjects (n=8) from two age groups (20-25 years old and 26-30 years old). The fat content percentage η_fat of the left and right legs was measured by bioelectrical impedance analysis (BIA), and the phase angle images of the left and right calves were reconstructed using ΦEIT. The relationship between the global average phase angle Φ_M and the spatial average phase angle Φ_Mi of each muscle compartment and fat infiltration was further analyzed. ResultsIn the laboratory pork model, the grayscale value of the image increased with the increase of η_fat and Φ_M showed a downward trend. The results of human experiments showed that at the same fat content percentage, the Φ_M of the 26-30-year-old group was about 20%-35% lower than that of the 20-25-year-old group. The fat content percentage was significantly negatively correlated with Φ_M. In addition, the M₂ (soleus) compartment was most sensitive to fat infiltration, and the spatial average phase angles of the M₂ (soleus), M₃ (tibialis posterior and flexor digitorum longus), and M₄ (tibialis anterior, extensor digitorum longus, and peroneus longus) compartments all showed significant inter-group differences. ConclusionΦEIT imaging can effectively distinguish different degrees of fat infiltration, especially in deep, small or specially located muscles, showing high sensitivity, demonstrating the potential application of this method in local muscle mass monitoring and early non-invasive diagnosis.