Over the past decade, research has increasingly identified unique dysregulations in lipid metabolism within the tumor microenvironment (TME). Lipids, diverse biomolecules, not only constitute biological membranes but also function as signaling molecules and energy sources. Enhanced synthesis or uptake of lipids in the TME significantly promotes tumorigenesis and proliferation. Moreover, lipids secreted into the TME influence tumor-resident immune cells (TRICs), thereby aiding tumor survival against chemotherapy and immunotherapy. This review aims to highlight recent advancements in understanding lipid metabolism in both tumor cells and TRICs, with a particular emphasis on exogenous lipid uptake and endogenous lipid de novo synthesis. Targeting lipid metabolism for intervention in anticancer therapies offers a promising therapeutic avenue for cancer treatment. Nano-drug delivery systems (NDDSs) have emerged as a means to maximize anti-tumor effects by rewiring tumor metabolism. This review provides a comprehensive overview of recent literature on the development of NDDSs targeting tumor lipid metabolism, particularly in the context of tumor immunotherapy. It covers four key aspects: reprogramming lipid uptake, reprogramming lipolysis, reshaping fatty acid oxidation (FAO), and reshuffling lipid composition on the cell membrane. The review concludes with a discussion of future prospects and challenges in this burgeoning field of research.

Local anaesthetics (LAs) may lead to neurological complications, but the underlying mechanism is still unclear. Many neurotoxicity research studies have examined different LAs, but none have comprehensively explored the distinct mechanisms of neurotoxicity caused by amide- (bupivacaine) and ester- (procaine) type LAs. Here, based on a CCK8 assay, LDH assay, Rhod-2-AM and JC-1 staining, 2′,7′-dichlorohy-drofluorescein diacetate and dihydroethidium probes, an alkaline comet assay, and apoptosis assay, we show that both bupivacaine and procaine significantly induce mitochondrial calcium overload and a decline in the mitochondrial membrane potential as well as overproduction of ROS, DNA damage and apoptosis (P < 0.05). There were no significant differences in mitochondrial injury and apoptosis between the bupivacaine and procaine subgroups (P > 0.05). However, to our surprise, the superoxide anionic level after treatment with bupivacaine, which leads to more severe DNA damage, was higher than the level after treatment with procaine, while procaine produced more peroxidation than bupivacaine. Some of these results were also affirmed in dorsal root ganglia neurons of C57 mice. The differences in the superoxidation and peroxidation induced by these agents suggest that different types of LAs may cause neurotoxicity via different pathways. We can target more accurate treatment based on their different mechanisms of neurotoxicity.

The needling sensation of Deqi during acupuncture is a key factor of influencing acupuncture outcome. Recent studies have mainly focused on the brain function effects of Deqi in a physiological state. Functional magnetic resonance imaging (fMRI) on the effects of acupuncture at Waiguan (SJ5) in pathological and physiological states is controversial. In this study, 12 patients with ischemic stroke received acupuncture at Waiguan (SJ5) and simultaneously underwent fMRI scanning of the brain, with imaging data of the activated areas obtained. Based on the patient's sensation, imaging data were allocated to either the Deqi group or non-Deqi group. In the Deqi group, the activated/deactivated areas were the left superior temporal gyrus (BA39)/right anterior lobe of the cerebellum and left thalamus. In the non-Deqi group, the activated areas included the medial frontal gyrus of the right frontal lobe (BA11), right limbic lobe (BA30, 35), and left frontal lobe (BA47), while the only deactivated area was the right parietal lobe (BA40). Compared with the non-Deqi group, the Deqi group exhibited marked activation of the right anterior lobe of the cerebellum and right limbic lobe (BA30). These findings confirm that the clinical effect of Deqi during acupuncture is based on brain functional changes. Cerebellar activation may be one of the central mechanisms of acupuncture in the treatment of ischemic stroke.

Perioperative anesthetic management entails a multitude of decision-making processes within complex medical scenarios. These demand the continuous and dynamic execution of precise decisions which poses significant challenges. In the age of big data, the exponential growth in data volume from diverse sources has revolutionized many fields, including healthcare, finance, and marketing. Machine learning has emerged as a powerful tool for analyzing big data, enabling the handling of large datasets and uncovering intricate patterns and relationships. The application of big data and artificial intelligence algorithms is gradually being integrated, enabling effective task completion in various stages of perioperative management, including risk prediction, decision support, and auxiliary examination. Through in-depth analysis of big data, healthcare professionals can gain insights into patient prognoses. This review provides a comprehensive overview of the distinctive features of perioperative big data and its applications in anesthesia management during the perioperative period.

Tendon injuries are widespread and chronic disorders of the musculoskeletal system, frequently caused by overload of the tendons. Currently, the most common treatment for tendon injuries is "cell-free therapy", of which exosomes, which can treat a host of diseases, including immune disorders, musculoskeletal injuries and cardiovascular diseases, are one kind. Among the many sources of exosomes, adipose-derived stem cell exosomes (ASC-Exos) have better efficacy. This is attributed not only to the ease of isolation of adipose tissue, but also to the high differentiation capacity of ASCs, their greater paracrine function, and immunomodulatory capacity compared to other exosomes. ASC-Exos promote tendon repair by four mechanisms: promoting angiogenesis under hypoxic conditions, reducing the inflammatory response, promoting tendon cell migration and proliferation, and accelerating collagen synthesis, thus accelerating tendon healing. This review focuses on describing studies of preclinical experiments with various exosomes, the characteristics of ASC-Exos and their mechanisms of action in tendon healing, as well as elaborating the limitations of ASC-Exos in clinical applications.

Background: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), makes it possible to deal with complex clinical time series data in ICU. We aimed to develop and validate it to predict mortality risk using time series data from MIMIC III dataset.Methods: A total of 21,139 records of ICU stays were analysed and 17 physiological variables from the MIMIC III dataset were used to predict mortality risk. Then we compared the model performance of the attention-based TCN with that of traditional artificial intelligence (AI) methods.Results: The area under receiver operating characteristic (AUCROC) and area under precision-recall curve (AUC-PR) of attention-based TCN for predicting the mortality risk 48 h after ICU admission were 0.837 (0.824 -0.850) and 0.454, respectively. The sensitivity and specificity of attention-based TCN were 67.1% and 82.6%, respectively, compared to the traditional AI method, which had a low sensitivity (< 50%).Conclusions: The attention-based TCN model achieved better performance in the prediction of mortality risk with time series data than traditional AI methods and conventional score-based models. The attention-based TCN mortality risk model has the potential for helping decision-making for critical patients.Trial registration: Data used for the prediction of mortality risk were extracted from the freely accessible MIMIC III dataset. The project was approved by the Institutional Review Boards of Beth Israel Deaconess Medical Center (Boston, MA) and the Massachusetts Institute of Technology (Cambridge, MA). Requirement for individual patient consent was waived because the project did not impact clinical care and all protected health information was deidentified. The data were accessed via a data use agreement between PhysioNet, a National Institutes of Health–supported data repository (https://www.physionet.org/), and one of us (Yu-wen Chen, Certification Number: 28341490). All methods were carried out in accordance with the institutional guidelines and regulations.