Background and aimThis study aims to evaluate the safety and efficacy of laparoscopic enucleation for liver hemangioma in special hepatic segments.MethodsWe retrospectively reviewed 58 patients who underwent laparoscopic surgery for hepatic hemangioma at a single center from January 2016 to January 2022. Segments I, IVa, VII, and VIII are defined as special hepatic segments, attributing to the bad visualization and adjacent to important vessels such as hepatic veins and inferior vena cava that lead to a high risk in laparoscopic surgery. Patients were categorized into a special location group (SLG) and a normal location group (NLG) according to the location of hemangioma. General data, intraoperative and postoperative outcomes, and postoperative complications of the two groups were compared and analyzed.ResultsThere were no significant differences in age (p = 0.288), gender (p = 0.331), body mass index (p = 0.168), the maximum diameter of hemangioma (p = 0.330), ASA risk grading (p = 0.615), and comorbidities (p > 0.05) between the two groups. The operation time (p < 0.001), intraoperative blood loss (p < 0.001), and intraoperative blood transfusion rate (p = 0.047) were significantly higher in the SLG. The rate of conversion to laparotomy was higher in the SLG, but there was no significant difference (p = 0.089). In addition, the exhaust time (p = 0.03) and postoperative hospital stay (p < 0.01) were significantly shorter in the NLG. The postoperative complications were comparable between the two groups, and there were no perioperative deaths.ConclusionLaparoscopic enucleation of hemangioma in special hepatic segments is difficult and has a critical risk of massive bleeding during surgery. Meanwhile, it is also safe, feasible, and effective.

Circadian dysregulation can be involved in the development of malignant tumors, though its relationship with the progression of hepatocellular carcinoma is not yet fully understood. We identified genes related to circadian rhythms from the Cancer Genome Atlas (TCGA), measured gene expression, and conducted genomic difference analysis to construct a circadian rhythm-related signature. The resulting prognosis model proved to be an effective biomarker, as demonstrated by Kaplan-Meier survival analysis for both the training (n = 370, P = 2.687e-10) and external validation cohorts (n = 230, P = 1.45e-02). Further, we found that patients considered ‘high risk’, with an associated poor prognosis, displayed elevated levels of immune checkpoint genes and immune filtration. We also conducted functional enrichment, which indicated that the risk model showed a significant positive correlation with certain malignant phenotypes, including G2M checkpoint, MYC targets, and the MTORC1 signaling pathway. In summary, we identified a novel circadian rhythm-related signature allowing assessment of prognosis for hepatocellular carcinoma patients, and further can be used to predict immune infiltration sensitivity.

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The effective use of multimodal data to obtain accurate land cover information has become an interesting and challenging research topic in the field of remote sensing. In this paper, we propose a new method, multi-scale learning and attention enhancement network (MSLAENet), to implement Hyperspectral image (HSI) and light detection and ranging (LiDAR) data fusion classification in an end-to-end manner. Specifically, our model consists of three main modules. First, we design the composite attention (CA) module, which adopts self-attention to enhance the feature representations of HSI and LiDAR data, respectively, and cross-attention to achieve crossmodal information enhancement. Second, the proposed multiscale learning (MSL) module combines self-calibrated convolutions and hierarchical residual structure to extract different scales of information to further improve the representation capability of the model. Finally, the attention-based feature fusion (FF) module fully considers the complementary information properties between different modalities and adaptively fuses heterogeneous features from different modalities. To test the performance of MSLAENet, we conduct experiments on three multimodal remote sensing datasets and compare them with the state-ofthe-art fusion model, which demonstrates the effectiveness and superiority of the model.

Background: Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) was introduced in 2007. The current study explored the mechanisms of rapid liver hypertrophy after ALPPS in cirrhotic rats.Methods: A cirrhotic rat model was constructed and portal vein ligation (PVL) or ALPPS treatments were administered. The liver hyperplasia rate of the rats was calculated, and hepatic function was evaluated using biochemical factors and the indocyanine green excretion test. Subsequently, enzyme-linked immunosorbent assay (ELISA), immunohistochemistry, and hematoxylin and eosin (HE) staining were performed to determine the degree of liver regeneration. Differentially expressed genes during the rapid liver hypertrophy were detected by bioinformatics analysis, followed verification using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry. Results:The body weight of rats that underwent PVL and ALPPS changed during the first 1-4 days postoperatively, and the alterations were more pronounced in rats receiving ALPPS. The recovery of body weight in cirrhotic rats was slower than that in normal rats. The levels of biochemical factors and the indocyanine green retention rate increased 1 day after PVL and ALPPS, and then decreased gradually. PVL and ALPPS elevated the levels of cytokines, inflammatory factors, and proliferating cell nuclear antigen (PCNA) in rats at 1 day postoperatively. HE observation of rat liver condition showed that rats recovered faster within the first 4 days postoperatively. ALPPS surgery resulted in a significant downregulation of matrix metalloproteinase (MMP)2/9 expression in cirrhotic rats at postoperative day 4.Conclusions: Liver function was partially recovered in cirrhotic rats after ALPPS, and the underlying mechanisms may involve PCNA and MMP2/9.