Sintilimab plus bevacizumab combined with radiotherapy as first-line treatment for hepatocellular carcinoma with portal vein tumor thrombus: A multicenter, single-arm, phase 2 study.

BACKGROUND AND AIMS: Systemic treatments are listed as first-line therapies for HCC with portal vein tumor thrombus (PVTT), resulting in modest efficacy. We aimed to evaluate the efficacy and safety of sintilimab plus bevacizumab combined with radiotherapy in HCC with PVTT and to identify prognostic biomarkers. APPROACH AND RESULTS: This open-label, multicenter, single-arm, phase 2 clinical trial was conducted at 3 tertiary hospitals in China. A total of 46 patients with HCC with PVTT were enrolled. All the patients received the first cycle of i.v. sintilimab (200 mg, day 1) plus bevacizumab (15 mg/kg, day 1) within 3 days after enrollment. Radiotherapy (30-50 Gy/10 fractions) was administered after 2 cycles of Sin-Bev. Sin-Bev was disrupted during radiotherapy and resumed 2 weeks after radiotherapy and continued every 3 weeks thereafter until disease progression, unacceptable toxicity, or withdrawal of consent. The primary end point was objective response rate. Patients obtained an objective response rate of 58.7% and a disease control rate of 100%. After a median follow-up time of 26.0 months (95% CI: 24.0-26.0), the median OS was 24.0 months (95% CI: 19.0 to not applicable) and the median progression-free survival was 13.8 months (95% CI: 12.0-21.0), respectively. No unexpected adverse events or treatment-related deaths occurred. Mutations of PCTMD1 were predictive of shorter OS and progression-free survival. CONCLUSIONS: Sintilimab plus bevacizumab combined with radiotherapy provides favorable treatment response and survival outcomes along with an acceptable safety profile in the first-line setting for patients with HCC with PVTT (ClinicalTrials.gov Identifier: NCT05010434).

The oxidized phospholipid PGPC impairs endothelial function by promoting endothelial cell ferroptosis via FABP3.

Ferroptosis is a novel cell death mechanism that is mediated by iron-dependent lipid peroxidation. It may be involved in atherosclerosis development. Products of phospholipid oxidation play a key role in atherosclerosis. 1-palmitoyl-2-glutaroyl-sn-glycero-3-phosphocholine (PGPC) is a phospholipid oxidation product present in atherosclerotic lesions. It remains unclear whether PGPC causes atherosclerosis by inducing endothelial cell ferroptosis. In this study, human umbilical vein endothelial cells (HUVECs) were treated with PGPC. Intracellular levels of ferrous iron, lipid peroxidation, superoxide anions (O2•-), and glutathione were detected, and expression of fatty acid binding protein-3 (FABP3), glutathione peroxidase 4 (GPX4), and CD36 were measured. Additionally, the mitochondrial membrane potential (MMP) was determined. Aortas from C57BL6 mice were isolated for vasodilation testing. Results showed that PGPC increased ferrous iron levels, the production of lipid peroxidation and O2•-, and FABP3 expression. However, PGPC inhibited the expression of GPX4 and glutathione production and destroyed normal MMP. These effects were also blocked by ferrostatin-1, an inhibitor of ferroptosis. FABP3 silencing significantly reversed the effect of PGPC. Furthermore, PGPC stimulated CD36 expression. Conversely, CD36 silencing reversed the effects of PGPC, including PGPC-induced FABP3 expression. Importantly, E06, a direct inhibitor of the oxidized 1-palmitoyl-2-arachidonoyl-phosphatidylcholine IgM natural antibody, inhibited the effects of PGPC. Finally, PGPC impaired endothelium-dependent vasodilation, ferrostatin-1 or FABP3 inhibitors inhibited this impairment. Our data demonstrate that PGPC impairs endothelial function by inducing endothelial cell ferroptosis through the CD36 receptor to increase FABP3 expression. Our findings provide new insights into the mechanisms of atherosclerosis and a therapeutic target for atherosclerosis.

Perimeter monitoring of urban buried pipeline threated by construction activities based on distributed fiber optic sensing and real-time object detection.

Urban construction activities seriously jeopardize the security of buried pipeline. Distributed optical fiber vibration monitoring is one of the most promising ways to prevent third-party threats, of which the biggest challenge is to quickly and accurately detect rare abnormal events from extremely large amounts of time-space raw data. By analogy with image recognition, the task here is similar to object detection if considering the time-space optical signals as the grayscale images and the abnormal events as the objects. Given this, what we believe to be a novel monitoring method is proposed, which consists of two Faster R-CNN models, a max pooling layer and a monitoring strategy. In the field tests, the 86-hour optical vibration signals for 5.25 km distance are recognized within 6.6 minutes with the recognition rate of 98.85% for construction activities, and only two false alarms are issued. The proposed method can reduce the recognition time by 99.59% compared to the CNN-based method.

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and deciding on a course of treatment. With the advent of advanced deep learning frameworks, fully automated and accurate MRI segmentation is advancing. Traditional supervised deep learning techniques have advanced tremendously, reaching clinical-level accuracy in the field of segmentation. However, these algorithms still require a large amount of annotated data, which is oftentimes unavailable or impractical. One way to circumvent this issue is to utilize algorithms that exploit a limited amount of labeled data. This paper aims to review such state-of-the-art algorithms that use a limited number of annotated samples. We explain the fundamental principles of self-supervised learning, generative models, few-shot learning, and semi-supervised learning and summarize their applications in cardiac, abdomen, and brain MRI segmentation. Throughout this review, we highlight algorithms that can be employed based on the quantity of annotated data available. We also present a comprehensive list of notable publicly available MRI segmentation datasets. To conclude, we discuss possible future directions of the field-including emerging algorithms, such as contrastive language-image pretraining, and potential combinations across the methods discussed-that can further increase the efficacy of image segmentation with limited labels.

Foreground Segmentation-Based Density Grading Networks for Crowd Counting.

Estimating object counts within a single image or video frame represents a challenging yet pivotal task in the field of computer vision. Its increasing significance arises from its versatile applications across various domains, including public safety and urban planning. Among the various object counting tasks, crowd counting is particularly notable for its critical role in social security and urban planning. However, intricate backgrounds in images often lead to misidentifications, wherein the complex background is mistaken as the foreground, thereby inflating forecasting errors. Additionally, the uneven distribution of crowd density within the foreground further exacerbates predictive errors of the network. This paper introduces a novel architecture with a three-branch structure aimed at synergistically incorporating hierarchical foreground information and global scale information into density map estimation, thereby achieving more precise counting results. Hierarchical foreground information guides the network to perform distinct operations on regions with varying densities, while global scale information evaluates the overall density level of the image and adjusts the model's global predictions accordingly. We also systematically investigate and compare three potential locations for integrating hierarchical foreground information into the density estimation network, ultimately determining the most effective placement.Through extensive comparative experiments across three datasets, we demonstrate the superior performance of our proposed method.

STING pathway contributes to the prognosis of hepatocellular carcinoma and identification of prognostic gene signatures correlated to tumor microenvironment.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most malignant solid tumors worldwide. Recent evidence shows that the stimulator of interferon genes (STING) pathway is essential for anti-tumor immunity via inducing the production of downstream inflammatory cytokines. However, its impact on the prognosis and tumor microenvironment of HCC was still limited known. METHODS: We obtained gene expression profiles of HCC from GEO, TCGA, and ICGC databases, and immune-related genes (IRGs) from the ImmPort database. Multivariate Cox regression was performed to identify independent prognostic factors. Nomogram was established to predict survival probability for individual patients. Kaplan-Meier curve was used to evaluate the survival difference. Afterward, ESTIMATE, TISCH, and TIMER databases were combined to assess the immune cell infiltration. Furthermore, the qPCR, western blotting, and immunohistochemistry were done to evaluate gene expression, and in vitro cell models were built to determine cell migratory ability. RESULTS: We found that gene markers of NLRC3, STING1, TBK1, TRIM21, and XRCC6 within STING pathway were independent prognostic factors in HCC patients. Underlying the finding, a predictive nomogram was constructed in TCGA-training cohort and further validated in TCGA-all and ICGC datasets, showing credible performance. Experimentally, up-regulated TBK1 promotes the ability of HCC cell migration. Next, the survival-related immune-related co-expressed gene signatures (IRCGS) (VAV1, RHOA, and ZC3HAV1) were determined in HCC cohorts and their expression was verified in human HCC cells and clinical samples. Furthermore, survival-related IRCGS was associated with the infiltration of various immune cell subtypes in HCC, the transcriptional expression of prominent immune checkpoints, and immunotherapeutic response. CONCLUSION: Collectively, we constructed a novel prognostic nomogram model for predicting the survival probability of individual HCC patients. Moreover, an immune-related prognostic gene signature was determined. Both might function as potential therapeutic targets for HCC treatment in the future.

Effect of Peptide Drug Liraglutide Nano-Formulation Combined with Sodium-Glucose Cotransporter-2 Inhibitor on Blood Lipids in Patients with Type 2 Diabetes.

With the aging of our population and the increase in the number of obese people, diabetes has become a common disease. At present, drug treatment is mainly used for diabetes. Dyslipidemia is the main cause of diabetes. The regulation of blood lipids in diabetic patients through drugs is the key to treating diabetes. The purpose of this article is to further explore the specific effect and mechanism of peptide drug liraglutide nano-formulation combined with sodium-glucose co-transporter-2(SGCT-2) inhibitor on blood lipids in patients with type 2 diabetes. This article uses 30 people included in our hospital in 2019 2 patients with type 2 diabetes are divided into the group of peptide drug liraglutide nano preparations, the group of SGCT-2 inhibitors and the peptide drug liraglutide nano preparations combined with SGCT-2. In the inhibitor combination medication group, patients were given drug intervention according to the group name with the consent of the patients. After three days, the serum cholesterol, triglyceride, lipoprotein and lipid metabolism levels of all patients were tested. The results showed that under the intervention of peptide drug liraglutide nanoparticles combined with SGCT-2 inhibitor, the cholesterol level of patients with type 2 diabetes decreased from (368.2 ± 8.3) mmol / L to (1978.4 ± 4.7) mmol/L, triglyceride level decreased from (653.7 ± 12.5) mg/dL to (426.8 ± 9.6) mg/dl, and lipid metabolism level increased by 25.6%. Therefore, it can be seen that the peptide drug liraglutide nano preparation combined with SGCT-2 inhibitor has a certain therapeutic effect on type 2 diabetes.

Correlation between vascular endothelial growth factor pathway and immune microenvironment in head and neck squamous cell carcinoma.

BACKGROUND: Immunotherapy is a crucial therapeutic approach in oncology. However, most patients with head and neck squamous cell carcinoma (HNSCC) do not derive benefit from immunotherapy. Vascular endothelial growth factor (VEGF)/VEGF Receptor 2 (VEGFR2) signaling pathway is one of the most important pathways regulating angiogenesis in tumor. The combination of immunotherapy and anti-angiogenic therapy is considered to improve efficacy of immunotherapy. The correlation between VEGF signaling pathway and tumor immune microenvironment in HNSCC patients is unclear. METHODS: We utilized RNA sequencing and clinical data of HNSCC patients from the TCGA database to study the correlation between VEGF signaling pathway and tumor immune microenvironment, on aspect of immune cell infiltration, immune-related gene expression profiling and immune-related biological pathways. RESULTS: We observed that VEGF signaling pathway is positively correlated with immune cell infiltration, immune-related gene expression profiles, and the prognosis of HNSCC patients. The functional enrichment analysis of differentially expressed genes between different VEGF score subtypes detected multiple immune-related biological processes. CONCLUSION: Our findings suggested that combining anti-VEGF signaling pathway agents with immunotherapy, such as immune checkpoint inhibitors (ICI) therapy, may exhibit encouraging benefits in HNSCC.

Radiomics using CT images for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma.

OBJECTIVES: To investigate and compare radiomics and clinical information for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma (ICC). METHODS: A total of 203 ICC patients from two centers were included and randomly allocated with a ratio of 7:3 into the training cohort and the validation cohort. Clinical characteristics and radiomics features were selected using random forest algorithm and logistic models to construct a clinical model and a radiomics model, respectively. A combined logistic model that incorporated the developed radiomics signature and clinical risk factors was then built. The performance of these models was evaluated and compared by plotting the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). RESULTS: The radiomics model showed a higher AUC than the clinical model in the validation cohort (AUC: 0.804 (95% CI: 0.697, 0.912) vs. 0.590 (95% CI: 0.415, 0.765), p = 0.043) for predicting futile resection in ICC. The radiomics model reached a sensitivity of 0.846 (95% CI: 0.546, 0.981) and a specificity of 0.771 (95% CI: 0.627, 0.880) in the validation cohort. Moreover, the radiomics model had comparable AUCs with the combined model in training and validation cohorts. CONCLUSIONS: We presented an internally validated radiomics model for the prediction of futile resection in ICC patients. Compared with clinical information, radiomics using CT images had greater potential for predicting futile resection accurately before surgery. KEY POINTS: • Radiomics model using CT images could predict futile resection in intrahepatic cholangiocarcinoma preoperatively. • Radiomics model using CT images was superior to clinical information for predicting futile resection accurately before surgery.

[Transurethral decompression and drainage with holmium laser for prostatic abscess: Analysis of clinical therapeutic effect].

OBJECTIVE: To investigate the clinical effect and safety of transurethral decompression and drainage with holmium laser in the treatment of prostatic abscess. METHODS: We retrospectively analyzed the clinical data on 13 cases of prostatic abscess treated in our hospital from January 2015 to May 2019. One of the patients was cured by drug therapy while the other 12 underwent transurethral decompression and drainage with holmium laser after failure in medication. We recorded such postoperative symptoms as fever, frequent urination, urgent urination, painful urination, tenteria, dysuria and abdominal distension, obtained the dynamical indices of blood and urine routine and culture after surgery, and performed MRI during the follow-up for possible recurrence and complications. Those with disappearance of the clinical symptoms, negative results of urine leukocyte and pathogen examinations, and no recurrence revealed by MRI were considered to be cured. RESULTS: After operation, the clinical symptoms were improved significantly and the urinary catheters removed within 5－10 days in all the cases. At 3－5 days after removal of the catheters, all the patients experienced smooth urination, with no urinary retention or urethral stricture. The patients were followed up for 3－16 months, during which no recurrence was observed. CONCLUSIONS: Transurethral decompression and drainage with holmium laser can achieve a definite clinical effect in the treatment of prostatic abscess and therefore deserves to be promoted in clinical practice.

Activation of STAT3-mediated CXCL12 up-regulation in the dorsal root ganglion contributes to oxaliplatin-induced chronic pain.

Oxaliplatin-induced chronic painful neuropathy is the most common dose-limiting adverse event that negatively affects cancer patients' quality of life. However, the underlying molecular mechanisms are still unclear. In the present study, we found that the intraperitoneal administration of oxaliplatin at 4 mg/kg for five consecutive days noticeably upregulated the expression of CXC motif ligand 12 (CXCL12) in the dorsal root ganglion, and the intrathecal injection of an anti-CXCL12 neutralizing antibody or CXCL12 siRNA attenuated the mechanical allodynia and thermal hyperalgesia induced by oxaliplatin. We also found that the signal transducers and transcription activator 3 (STAT3) was activated in the dorsal root ganglion, and inhibition of STAT3 with S3I-201 or the injection of AAV-Cre-GFP into STAT3flox/flox mice prevented the upregulation of CXCL12 expression in the dorsal root ganglion and chronic pain following oxaliplatin administration. Double-label fluorescent immunohistochemistry findings also showed that p-STAT3 was mainly localized in CXCL12-positive cells in the dorsal root ganglion. Furthermore, the results of a chromatin immunoprecipitation assay revealed that p-STAT3 might be essential for oxaliplatin-induced CXCL12 upregulation via binding directly to the specific position of the CXCL12 gene promoter. Finally, we found that cytokine TNF-α and IL-1ß increases mediated the STAT3 activation following oxaliplatin treatment. Taken together, these findings suggested that the upregulation of CXCL12 via TNF-α/IL-1ß-dependent STAT3 activation contributes to oxaliplatin-induced chronic pain.

Enhancing the Thermal Stability of Zein Particle-Stabilized Aeratable Emulsions Through Genipin-Protein Cross-Linking and Its Possible Mechanism of Action.

Protein particle-stabilized emulsions often lack thermal stability, impacting their industrial use. This study investigated the effects of genipin (GP)-zein cross-linked particles with varying GP-to-protein weight ratios (0/0.02/0.1:1) on emulsion thermal stability. Enhanced stability was observed at the GP level of 0.1. Heat treatment increased the covalent cross-linking in raw particles and emulsions. Isolated particles from heated emulsions grew in size (micrometer scale) with higher GP levels, unlike heated raw particles (nanoscale). GP-protein cross-linking reduced the droplet-droplet and particle-emulsifier interactions in the heated emulsion. Spectroscopic analysis and electrophoresis revealed that GP-zein cross-linking increased protein structural stability and inhibited nondisulfide and non-GP cross-linking reactions in heated emulsions. The GP-zein bridges between particles at the oil-water interface create strong connections in the particle layer (shell), referred to as "particle-shell locking", enhancing the thermal stability of emulsion significantly. This insight aids the future design of protein-particle-based emulsions, preserving properties like aeratability during thermal processing.

Research on optimization method of railway construction scheme based on multidimensional combination weighting and improved grey theory.

The optimization of railway construction schemes is a complexity system engineering task with multiple dimensions, diverse conditional constraints, and multifaceted objective assessments. The decision-making and scheme evaluation entail subjectivity, randomness, and fuzziness. To address the comprehensive optimization challenge in construction schemes effectively and efficiently, we investigate an optimization method for railway construction schemes. This method is based on multi-dimensional combination weighting and improved grey theory. After analyzing the primary influencing factors, we established a railway construction plan optimization index system comprising 4 dimensions and 18 factors. The weight combination coefficient is determined using the pros and cons solution distance method, and the optimal weight set for the index is determined through the multi-dimensional combination weighting approach. Utilizing the method of superior and inferior solution distance coupled with grey theory, we ascertain the order of advantages and disadvantages for each construction scheme, subsequently achieving construction scheme optimization. To illustrate this, we employ the optimization process for a high-speed railway section in Guangxi as an exemplar. The verification results indicate that the gray relative closeness values for schemes A, B, and C are 0.7089, 0.4813, and 0.4463, respectively. Scheme A has the highest gray relative closeness value, thus making it the optimal route scheme. The optimal results obtained through this method align with the outcomes of expert validation and existing research, thereby validating the effectiveness and practicality of the model. By employing a multidimensional combination weighting method, the deficiencies of traditional indicator weight calculations are mitigated, resulting in indicator weights that are more reflective of the actual circumstances. At the same time, the application of improvements in the grey theory comprehensive evaluation method enables the integration and computation of indicator data for each construction plan. Through the intuitive representation of grey relative closeness, the advantages and disadvantages of each plan are effectively characterized. This enhances the scientific rigor and applicability of the railway construction plan optimization process. The research findings can serve as a reference for similar railway construction scheme selection problems in the future.

Precision co-composting of multi-source organic solid wastes provide a sustainable waste management strategy with high eco-efficiency: a life cycle assessment.

With the increase of organic solid wastes (OSWs), current waste management practices, such as landfill, incineration, and windrow composting, have shown weaknesses in both resource recycling and environmental protection. Co-composting has been used to achieve nutrient and carbon recycling but is accused of high ammonia emission and low degradation efficiency. Therefore, this study developed a precision co-composting strategy (S3, which adds functional bacteria generated from food processing waste to a co-composting system) and compared it with the current OSW treatment strategy (S1) and traditional co-composting strategy (S2) from a life cycle assessment (LCA) perspective. The results showed that compared with S1, the eco-efficiency increased by 31.3% due to the higher economic profit of S2 but did not directly reduce the environmental cost. The addition of bacterial agents reduced ammonia emissions and shortened composting time, so compared with S1 and S2, the environmental cost of S3 was reduced by 37.9 and 43.6%, while the economic profit increased by 79.8 and 24.4%, respectively. The changes in environmental costs and economic benefits resulted in a huge improvement of S3's eco-efficiency, which was 189.6 and 121.7% higher than S1 and S2. Meanwhile, the adoption of S3 at a national scale in China could reduce the emission of 1,4-dichlorobenzene by 99.9% compared with S1 and increase profits by 6.58 billion USD per year. This study proposes a novel approach that exhibits high eco-efficiency in the treatment of OSWs.

The Role of Artificial Intelligence in the Identification and Evaluation of Bone Fractures.

Artificial intelligence (AI), particularly deep learning, has made enormous strides in medical imaging analysis. In the field of musculoskeletal radiology, deep-learning models are actively being developed for the identification and evaluation of bone fractures. These methods provide numerous benefits to radiologists such as increased diagnostic accuracy and efficiency while also achieving standalone performances comparable or superior to clinician readers. Various algorithms are already commercially available for integration into clinical workflows, with the potential to improve healthcare delivery and shape the future practice of radiology. In this systematic review, we explore the performance of current AI methods in the identification and evaluation of fractures, particularly those in the ankle, wrist, hip, and ribs. We also discuss current commercially available products for fracture detection and provide an overview of the current limitations of this technology and future directions of the field.

Generating a multimodal artificial intelligence model to differentiate benign and malignant follicular neoplasms of the thyroid: A proof-of-concept study.

BACKGROUND: Machine learning has been increasingly used to develop algorithms that can improve medical diagnostics and prognostication and has shown promise in improving the classification of thyroid ultrasound images. This proof-of-concept study aims to develop a multimodal machine-learning model to classify follicular carcinoma from adenoma. METHODS: This is a retrospective study of patients with follicular adenoma or carcinoma at a single institution between 2010 and 2022. Demographics, imaging, and perioperative variables were collected. The region of interest was annotated on ultrasound and used to perform radiomics analysis. Imaging features and clinical variables were then used to create a random forest classifier to predict malignancy. Leave-one-out cross-validation was conducted to evaluate classifier performance using the area under the receiver operating characteristic curve. RESULTS: Patients with follicular adenomas (n = 7) and carcinomas (n = 11) with complete imaging and perioperative data were included. A total of 910 features were extracted from each image. The t-distributed stochastic neighbor embedding method reduced the dimension to 2 primary represented components. The random forest classifier achieved an area under the receiver operating characteristic curve of 0.76 (clinical only), 0.29 (image only), and 0.79 (multimodal data). CONCLUSION: Our multimodal machine learning model demonstrates promising results in classifying follicular carcinoma from adenoma. This approach can potentially be applied in future studies to generate models for preoperative differentiation of follicular thyroid neoplasms.

Adjuvant Transarterial Chemoembolization With Sorafenib for Portal Vein Tumor Thrombus: A Randomized Clinical Trial.

Importance: Certain patients with hepatocellular carcinoma with portal vein tumor thrombus could benefit from surgical resection, and postoperative adjuvant therapy may lower the incidence of tumor recurrence. Objective: To compare the efficacy and safety of sorafenib plus transarterial chemoembolization vs sorafenib alone as postoperative adjuvant therapy for patients with hepatocellular carcinoma with portal vein tumor thrombus. Design, Setting, and Participants: This was a phase 3, multicenter, randomized clinical trial conducted in 5 hospitals in China. A total of 158 patients were enrolled and randomized from October 2019 to March 2022, with a median follow-up of 28.4 months. Portal vein tumor thrombus was graded by the Cheng classification. Eligible patients with hepatocellular carcinoma with Cheng grade I to III portal vein tumor thrombus (ie, involving segmental or sectoral branches, right- or left-side branch, or main trunk of portal vein) were included. Interventions: Patients were randomly assigned 1:1 to receive transarterial chemoembolization with sorafenib or sorafenib alone as postoperative adjuvant therapy. Sorafenib treatment was started within 3 days after randomization, with an initial dose of 400 mg orally twice a day. In the transarterial chemoembolization with sorafenib group, transarterial chemoembolization was performed 1 day after the first administration of sorafenib. Main Outcomes and Measures: The primary end point was recurrence-free survival. Efficacy was assessed in the intention-to-treat population and safety was assessed in patients who received at least 1 dose of study treatment. Results: Of 158 patients included, the median (IQR) age was 54 (43-61) years, and 140 (88.6%) patients were male. The median (IQR) recurrence-free survival was significantly longer in the transarterial chemoembolization with sorafenib group (16.8 [12.0-NA] vs 12.6 [7.8-18.1] months; hazard ratio [HR], 0.57; 95% CI, 0.39-0.83; P = .002). The median (IQR) overall survival was also significantly longer with transarterial chemoembolization with sorafenib than with sorafenib alone (30.4 [20.6-NA] vs 22.5 [15.4-NA] months; HR, 0.57; 95% CI, 0.36-0.91; P = .02). The most common grade 3/4 adverse event was hand-foot syndrome (23 of 79 patients in the transarterial chemoembolization with sorafenib group [29.1%] vs 24 of 79 patients in the sorafenib alone group [30.4%]). There were no treatment-related deaths in either group. The transarterial chemoembolization with sorafenib group did not show additional toxicity compared with the sorafenib monotherapy group. Conclusion and Relevance: In this study, the combination of sorafenib and transarterial chemoembolization as postoperative adjuvant therapy in patients with hepatocellular carcinoma with portal vein tumor thrombus resulted in longer recurrence-free survival and overall survival than sorafenib alone and was well tolerated. Trial Registration: ClinicalTrials.gov Identifier: NCT04143191.

Effects of Geographical Origin and Tree Age on the Stable Isotopes and Multi-Elements of Pu-erh Tea.

Pu-erh tea is a famous tea worldwide, and identification of the geographical origin of Pu-erh tea can not only protect manufacture's interests, but also boost consumers' confidence. However, tree age may also influence the fingerprints of Pu-erh tea. In order to study the effects of the geographical origin and tree age on the interactions of stable isotopes and multi-elements of Pu-erh tea, 53 Pu-erh tea leaves with three different age stages from three different areas in Yunnan were collected in 2023. The δ13C, δ15N values and 25 elements were determined and analyzed. The results showed that δ13C, δ15N, Mg, Mn, Fe, Cu, Zn, Rb, Sr, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu had significant differences among different geographical origins (p < 0.05). Mn content was significantly influenced by region and tree age interaction. Based on multi-way analysis of variance, principal component analysis and step-wised discriminant analysis, 24 parameters were found to be closely related to the geographical origin rather than tree age, and the geographical origin of Pu-erh tea can be 100.0% discriminated in cross-validation with six parameters (δ13C, δ15N, Mn, Mg, La, and Tb). The study could provide references for the establishment of a database for the traceability of Pu-erh tea, and even the identification of tea sample regions with different tree ages.

Endothelial extracellular vesicles induce acute lung injury via follistatin-like protein 1.

Cardiopulmonary bypass has been speculated to elicit systemic inflammation to initiate acute lung injury (ALI), including acute respiratory distress syndrome (ARDS), in patients after cardiac surgery. We previously found that post-operative patients showed an increase in endothelial cell-derived extracellular vesicles (eEVs) with components of coagulation and acute inflammatory responses. However, the mechanism underlying the onset of ALI owing to the release of eEVs after cardiopulmonary bypass, remains unclear. Plasma plasminogen-activated inhibitor-1 (PAI-1) and eEV levels were measured in patients with cardiopulmonary bypass. Endothelial cells and mice (C57BL/6, Toll-like receptor 4 knockout (TLR4-/-) and inducible nitric oxide synthase knockout (iNOS-/-)) were challenged with eEVs isolated from PAI-1-stimulated endothelial cells. Plasma PAI-1 and eEVs were remarkably enhanced after cardiopulmonary bypass. Plasma PAI-1 elevation was positively correlated with the increase in eEVs. The increase in plasma PAI-1 and eEV levels was associated with post-operative ARDS. The eEVs derived from PAI-1-stimulated endothelial cells could recognize TLR4 to stimulate a downstream signaling cascade identified as the Janus kinase 2/3 (JAK2/3)-signal transducer and activator of transcription 3 (STAT3)-interferon regulatory factor 1 (IRF-1) pathway, along with iNOS induction, and cytokine/chemokine production in vascular endothelial cells and C57BL/6 mice, ultimately contributing to ALI. ALI could be attenuated by JAK2/3 or STAT3 inhibitors (AG490 or S3I-201, respectively), and was relieved in TLR4-/- and iNOS-/- mice. eEVs activate the TLR4/JAK3/STAT3/IRF-1 signaling pathway to induce ALI/ARDS by delivering follistatin-like protein 1 (FSTL1), and FSTL1 knockdown in eEVs alleviates eEV-induced ALI/ARDS. Our data thus demonstrate that cardiopulmonary bypass may increase plasma PAI-1 levels to induce FSTL1-enriched eEVs, which target the TLR4-mediated JAK2/3/STAT3/IRF-1 signaling cascade and form a positive feedback loop, leading to ALI/ARDS after cardiac surgery. Our findings provide new insight into the molecular mechanisms and therapeutic targets for ALI/ARDS after cardiac surgery.

Aging aggravates aortic aneurysm and dissection via miR-1204-MYLK signaling axis in mice.

The mechanism by which aging induces aortic aneurysm and dissection (AAD) remains unclear. A total of 430 participants were recruited for the screening of differentially expressed plasma microRNAs (miRNAs). We found that miR-1204 is significantly increased in both the plasma and aorta of elder patients with AAD and is positively correlated with age. Cell senescence induces the expression of miR-1204 through p53 interaction with plasmacytoma variant translocation 1, and miR-1204 induces vascular smooth muscle cell (VSMC) senescence to form a positive feedback loop. Furthermore, miR-1204 aggravates angiotensin II-induced AAD formation, and inhibition of miR-1204 attenuates ß-aminopropionitrile monofumarate-induced AAD development in mice. Mechanistically, miR-1204 directly targets myosin light chain kinase (MYLK), leading to the acquisition of a senescence-associated secretory phenotype (SASP) by VSMCs and loss of their contractile phenotype. MYLK overexpression reverses miR-1204-induced VSMC senescence, SASP and contractile phenotypic changes, and the decrease of transforming growth factor-ß signaling pathway. Our findings suggest that aging aggravates AAD via the miR-1204-MYLK signaling axis.