Dexmedetomidine post-treatment attenuates cardiac ischaemia/reperfusion injury by inhibiting apoptosis through HIF-1α signalling.

Hypoxia-inducible factor 1α (HIF-1α) plays a critical role in the apoptotic process during cardiac ischaemia/reperfusion (I/R) injury. This study aimed to investigate whether post-treatment with dexmedetomidine (DEX) could protect against I/R-induced cardiac apoptosis in vivo and in vitro via regulating HIF-1α signalling pathway. Rat myocardial I/R was induced by occluding the left anterior descending artery for 30 minutes followed by 6-hours reperfusion, and cardiomyocyte hypoxia/reoxygenation (H/R) was induced by oxygen-glucose deprivation for 6 hours followed by 3-hours reoxygenation. Dexmedetomidine administration at the beginning of reperfusion or reoxygenation attenuated I/R-induced myocardial injury or H/R-induced cell death, alleviated mitochondrial dysfunction, reduced the number of apoptotic cardiomyocytes, inhibited the activation of HIF-1α and modulated the expressions of apoptosis-related proteins including BCL-2, BAX, BNIP3, cleaved caspase-3 and cleaved PARP. Conversely, the HIF-1α prolyl hydroxylase-2 inhibitor IOX2 partly blocked DEX-mediated cardioprotection both in vivo and in vitro. Mechanistically, DEX down-regulated HIF-1α expression at the post-transcriptional level and inhibited the transcriptional activation of the target gene BNIP3. Post-treatment with DEX protects against cardiac I/R injury in vivo and H/R injury in vitro. These effects are, at least in part, mediated via the inhibition of cell apoptosis by targeting HIF-1α signalling

Determining the local dark matter density with LAMOST data

Measurement of the local dark matter density plays an important role in both Galactic dynamics and dark matter direct detection experiments. However, the estimated values from previous works are far from agreeing with each other. In this work, we provide a well-defined observed sample with 1427 G \& K type main-sequence stars from the LAMOST spectroscopic survey, taking into account selection effects, volume completeness, and the stellar populations. We apply a vertical Jeans equation method containing a single exponential stellar disk, a razor thin gas disk, and a constant dark matter density distribution to the sample, and obtain a total surface mass density of $\rm {78.7 ^{+3.9}_{-4.7}\ M_{\odot}\ pc^{-2}}$up to 1 kpc and a local dark matter density of$0.0159^{+0.0047}_{-0.0057}\,\rm M_{\odot}\,\rm pc^{-3}$. We find that the sampling density (i.e. number of stars per unit volume) of the spectroscopic data contributes to about two-thirds of the uncertainty in the estimated values. We discuss the effect of the tilt term in the Jeans equation and find it has little impact on our measurement. Other issues, such as a non-equilibrium component due to perturbations and contamination by the thick disk population, are also discussed.Comment: 11 pages, 10 figure

SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation

The Segment Anything Model (SAM) is a powerful foundation model that has revolutionised image segmentation. To apply SAM to surgical instrument segmentation, a common approach is to locate precise points or boxes of instruments and then use them as prompts for SAM in a zero-shot manner. However, we observe two problems with this naive pipeline: (1) the domain gap between natural objects and surgical instruments leads to poor generalisation of SAM; and (2) SAM relies on precise point or box locations for accurate segmentation, requiring either extensive manual guidance or a well-performing specialist detector for prompt preparation, which leads to a complex multi-stage pipeline. To address these problems, we introduce SurgicalSAM, a novel end-to-end efficient-tuning approach for SAM to effectively integrate surgical-specific information with SAM's pre-trained knowledge for improved generalisation. Specifically, we propose a lightweight prototype-based class prompt encoder for tuning, which directly generates prompt embeddings from class prototypes and eliminates the use of explicit prompts for improved robustness and a simpler pipeline. In addition, to address the low inter-class variance among surgical instrument categories, we propose contrastive prototype learning, further enhancing the discrimination of the class prototypes for more accurate class prompting. The results of extensive experiments on both EndoVis2018 and EndoVis2017 datasets demonstrate that SurgicalSAM achieves state-of-the-art performance while only requiring a small number of tunable parameters. The source code will be released at https://github.com/wenxi-yue/SurgicalSAM.Comment: Technical Report. The source code will be released at https://github.com/wenxi-yue/SurgicalSA

Trust in Software Supply Chains: Blockchain-Enabled SBOM and the AIBOM Future

Software Bill of Materials (SBOM) serves as a critical pillar in ensuring software supply chain security by providing a detailed inventory of the components and dependencies integral to software development. However, challenges abound in the sharing of SBOMs, including potential data tampering, hesitation among software vendors to disclose comprehensive information, and bespoke requirements from software procurers or users. These obstacles have stifled widespread adoption and utilization of SBOMs, underscoring the need for a more secure and flexible mechanism for SBOM sharing. This study proposes a novel solution to these challenges by introducing a blockchain-empowered approach for SBOM sharing, leveraging verifiable credentials to allow for selective disclosure. This strategy not only heightens security but also offers flexibility. Furthermore, this paper broadens the remit of SBOM to encompass AI systems, thereby coining the term AI Bill of Materials (AIBOM). This extension is motivated by the rapid progression in AI technology and the escalating necessity to track the lineage and composition of AI software and systems. Particularly in the era of foundational models like large language models (LLMs), understanding their composition and dependencies becomes crucial. These models often serve as a base for further development, creating complex dependencies and paving the way for innovative AI applications. The evaluation of our solution indicates the feasibility and flexibility of the proposed SBOM sharing mechanism, positing a new solution for securing (AI) software supply chains

Rhein: A Review of Pharmacological Activities

Rhein (4, 5-dihydroxyanthraquinone-2-carboxylic acid) is a lipophilic anthraquinone extensively found in medicinal herbs, such as Rheum palmatum L., Cassia tora L., Polygonum multiflorum Thunb., and Aloe barbadensis Miller, which have been used medicinally inChina formore than 1,000 years. Its biological activities related to human health are being explored actively. Emerging evidence suggests that rhein has many pharmacological effects, including hepatoprotective, nephroprotective, anti-inflammatory, antioxidant, anticancer, and antimicrobial activities. The present review provides a comprehensive summary and analysis of the pharmacological properties of rhein, supporting the potential uses of rhein as a medicinal agent

Effect of rosiglitazone on rabbit model of myocardial ischemia-reperfusion injury

AbstractObjectiveTo explore mechanism and protective effect of rosiglitazone on myocardial ischemia reperfusion (I/R) injury.MethodsA total of 48 male Japanese white big-ear rabbits were randomly divided into control group (A), I/R group (B), low dose of rosiglitazone group (C), high dose of rosiglitazone group (D). Plasma concentration of and also reduced the concentration of plasma serum creatine kinase (CK), CK-MB, high-sensitivity C-reactive protein (hsCRP), ultra-superoxide dismutase (SOD), malondialdehyde (MDA), lactic acid glutathione skin peroxidase (GSH-PX), nitric oxide (NO) and endothelin (ET) were measured 1 h later after I/R. Twenty-four hours after I/R the hearts were harvested for pathological and ultrastructural analysis. Area of myocardial infarction were tested.ResultsPlasma concentration of CK, CK-MB, hsCRP, NO, MDA and ET were decreased in C, D group compared with group B. Plasma concentration of T-SOD and GSH-Px were increased significantly in C, D group compared with group B. Compared with group B, pathological and ultrastructural changes in C and D group were slightly. There was significant difference in myocardial infarction area between group C, D and group B (P<0.05). Myocardial infarction area and arrhythmia rate were lower in group C, D compare with group B.ConclusionsRosiglitazone may protect myocardium from I/R injury by enhancing T-SOD and GSH-Px concentration, inhibit inflammatory reaction, and improve endothelial function