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.

Tumors are the second leading cause of death worldwide. Exosomes are a type of extracellular vesicle secreted from multivesicular bodies, with particle sizes ranging from 40 to 160 nm. They regulate the tumor microenvironment, proliferation, and progression by transporting proteins, nucleic acids, and other biomolecules. Compared with other drug delivery systems, exosomes derived from different cells possess unique cellular tropism, enabling them to selectively target specific tissues and organs. This homing ability allows them to cross biological barriers that are otherwise difficult for conventional drug delivery systems to penetrate. Due to their biocompatibility and unique biological properties, exosomes can serve as drug delivery systems capable of loading various anti-tumor drugs. They can traverse biological barriers, evade immune responses, and specifically target tumor tissues, making them ideal carriers for anti-tumor therapeutics. This article systematically summarizes the methods for exosome isolation, including ultracentrifugation, ultrafiltration, size-exclusion chromatography (SEC), immunoaffinity capture, and microfluidics. However, these methods have certain limitations. A combination of multiple isolation techniques can improve isolation efficiency. For instance, combining ultrafiltration with SEC can achieve both high purity and high yield while reducing processing time. Exosome drug loading methods can be classified into post-loading and pre-loading approaches. Pre-loading is further categorized into active and passive loading. Active loading methods, including electroporation, sonication, extrusion, and freeze-thaw cycles, involve physical or chemical disruption of the exosome membrane to facilitate drug encapsulation. Passive loading relies on drug concentration gradients or hydrophobic interactions between drugs and exosomes for encapsulation. Pre-loading strategies also include genetic engineering and co-incubation methods. Additionally, we review approaches to enhance the targeting, retention, and permeability of exosomes. Genetic engineering and chemical modifications can improve their tumor-targeting capabilities. Magnetic fields can also be employed to promote the accumulation of exosomes at tumor sites. Retention time can be prolonged by inhibiting monocyte-mediated clearance or by combining exosomes with hydrogels. Engineered exosomes can also reshape the tumor microenvironment to enhance permeability. This review further discusses the current applications of exosomes in delivering various anti-tumor drugs. Specifically, exosomes can encapsulate chemotherapeutic agents such as paclitaxel to reduce side effects and increase drug concentration within tumor tissues. For instance, exosomes loaded with doxorubicin can mitigate cardiotoxicity and minimize adverse effects on healthy tissues. Furthermore, exosomes can encapsulate proteins to enhance protein stability and bioavailability or carry immunogenic cell death inducers for tumor vaccines. In addition to these applications, exosomes can deliver nucleic acids such as siRNA and miRNA to regulate gene expression, inhibit tumor proliferation, and suppress invasion. Beyond their therapeutic applications, exosomes also serve as tumor biomarkers for early cancer diagnosis. The detection of exosomal miRNA can improve the sensitivity and specificity of diagnosing prostate and pancreatic cancers. Despite their promising potential as drug delivery systems, challenges remain in the standardization and large-scale production of exosomes. This article explores the future development of engineered exosomes for targeted tumor therapy. Plant-derived exosomes hold potential due to their superior biocompatibility, lower toxicity, and abundant availability. Furthermore, the integration of exosomes with artificial intelligence may offer novel applications in diagnostics, therapeutics, and personalized medicine.

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.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.