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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 $\rm {78.7 ^{+3.9}_{-4.7}\
M_{\odot}\ pc^{-2}}0.0159^{+0.0047}_{-0.0057}\,\rm M_{\odot}\,\rm pc^{-3}$. 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
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