一体化手术室消毒供应中心灭菌监测管理

Objective: Explore the Sterilization Monitoring management of the integration of the operating room with CSSD. Methods: Compare sterilization process monitoring with biological monitoring and chemical monitoring. Results: The management in Biological monitoring, chemical monitoring and sterilization process monitoring is crucial. Conclusion: Sterilization monitoring is to ensure the safe use of sterile goods so as to protect the safety of surgical patients.目的  探讨一体化手术室消毒供应中心的灭菌监测管理。方法  比较灭菌监测管理的过程监测、生物监测、化学监测。结果  灭菌过程的生物监测、化学监测和过程监测对于灭菌管理是至关重要的。结论  灭菌监测工作能保证物品使用的安全性，最大限度地保障手术病人的安全

The Differential Spectrum of the Power Mapping xpn−3

Let n be a positive integer and p a prime. The power mapping xpn−3 over Fpn has desirable differential properties, and its differential spectra for p=2,3 have been determined. In this paper, for any odd prime p , by investigating certain quadratic character sums and some equations over Fpn , we determine the differential spectrum of xpn−3 with a unified approach. The obtained result shows that for any given odd prime p , the differential spectrum can be expressed explicitly in terms of n . Compared with previous results, a special elliptic curve over Fp plays an important role in our computation for the general case p≥5.acceptedVersio

User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations

Modern recommender systems utilize users' historical behaviors to generate personalized recommendations. However, these systems often lack user controllability, leading to diminished user satisfaction and trust in the systems. Acknowledging the recent advancements in explainable recommender systems that enhance users' understanding of recommendation mechanisms, we propose leveraging these advancements to improve user controllability. In this paper, we present a user-controllable recommender system that seamlessly integrates explainability and controllability within a unified framework. By providing both retrospective and prospective explanations through counterfactual reasoning, users can customize their control over the system by interacting with these explanations. Furthermore, we introduce and assess two attributes of controllability in recommendation systems: the complexity of controllability and the accuracy of controllability. Experimental evaluations on MovieLens and Yelp datasets substantiate the effectiveness of our proposed framework. Additionally, our experiments demonstrate that offering users control options can potentially enhance recommendation accuracy in the future. Source code and data are available at \url{https://github.com/chrisjtan/ucr}.Comment: Accepted for presentation at 26th European Conference on Artificial Intelligence (ECAI2023

Ferroptosis Contributes to Isoflurane Neurotoxicity

The underlying mechanisms of isoflurane neurotoxicity in the developing brain remain unclear. Ferroptosis is a recently characterized form of programmed cell death distinct from apoptosis or autophagy, characterized by iron-dependent reactive oxygen species (ROS) generation secondary to failure of glutathione-dependent antioxidant defenses. The results of the present study are the first to demonstrate in vitro that ferroptosis is a central mechanism contributing to isoflurane neurotoxicity. We observed in embryonic mouse primary cortical neuronal cultures (day-in-vitro 7) that 6 h of 2% isoflurane exposure was associated with decreased transcription and protein expression of the lipid repair enzyme glutathione peroxidase 4. In parallel, isoflurane exposure resulted in increased ROS generation, disruption in mitochondrial membrane potential, and cell death. These effects were significantly attenuated by pre-treatment with the selective ferroptosis inhibitor ferrostatin-1 (Fer-1). Collectively, these observations provide a novel mechanism for isoflurane-induced injury in the developing brain and suggest that pre-treatment with Fer-1 may be a potential clinical intervention for neuroprotection

BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining

Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e., BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the biomedical domain, such as BioBERT and PubMedBERT. While they have achieved great success on a variety of discriminative downstream biomedical tasks, the lack of generation ability constrains their application scope. In this paper, we propose BioGPT, a domain-specific generative Transformer language model pre-trained on large scale biomedical literature. We evaluate BioGPT on six biomedical NLP tasks and demonstrate that our model outperforms previous models on most tasks. Especially, we get 44.98%, 38.42% and 40.76% F1 score on BC5CDR, KD-DTI and DDI end-to-end relation extraction tasks respectively, and 78.2% accuracy on PubMedQA, creating a new record. Our case study on text generation further demonstrates the advantage of BioGPT on biomedical literature to generate fluent descriptions for biomedical terms. Code is available at https://github.com/microsoft/BioGPT.Comment: Published at Briefings in Bioinformatics. Code is available at https://github.com/microsoft/BioGP

The HI gas fraction scaling relation of the Green Pea galaxies

Green Pea galaxies are compact galaxies with high star formation rates. However, limited samples of Green Pea galaxies have HI 21 cm measurements. Whether the HI gas fraction f_{HI} = M_{HI}/M_{*} of Green Pea galaxies follows the existing scaling relations between the f_{HI} and NUV-r color or linear combinations of color and other physical quantities needs checking. Using archival data of HI 21cm observations, we investigate the scaling relation of the NUV-r color with the M_{HI}/M_{*} of 38 Green Pea galaxies, including 17 detections and 21 non-detections. The HI to stellar mass ratios (f_{HI}) of Green Pea galaxies deviate from the polynomial form, where a higher HI gas fraction is predicted given the current NUV-r color, even with the emission lines removed. The blue sources (NUV-r<1) from the comparison sample (ALFALFA-SDSS) follow a similar trend. The HI gas fraction scaling relations with linear combination forms of -0.34(NUV-r) - 0.64 log(mu_{*,z}) + 5.94 and -0.77 log mu_{*,i} + 0.26 log SFR/M_{*}+8.53, better predict the HI gas fraction of the Green Pea galaxies. In order to obtain accurate linear combined forms, higher-resolution photometry from space-based telescopes is needed.Comment: 15 pages, 7 figures, to be published in RA

Hypoxia-inducible transcription factor-1α promotes hypoxia-induced A549 apoptosis via a mechanism that involves the glycolysis pathway

BACKGROUND: Hypoxia-inducible transcription factor-1α (HIF-1α), which plays an important role in controlling the hypoxia-induced glycolysis pathway, is a "master" gene in the tissue hypoxia response during tumor development. However, its role in the apoptosis of non-small cell lung cancer remains unknown. Here, we have studied the effects of HIF-1α on apoptosis by modulating HIF-1α gene expression in A549 cells through both siRNA knock-down and over-expression. METHODS: A549 cells were transfected with a HIF-1α siRNA plasmid or a HIF-1α expression vector. Transfected cells were exposed to a normoxic or hypoxic environment in the presence or absence of 25 mM HEPES and 2-deoxyglucose (2-DG) (5 mM). The expression of three key genes of the glycolysis pathway, glucose transporter type 1(GLUT1), phosphoglycerate kinase 1(PGK1), and hexokinase 1(HK1), were measured using real-time RT-PCR. Glycolysis was monitored by measuring changes of pH and lactate concentration in the culture medium. Apoptosis was detected by TUNEL assay and flow cytometry. RESULTS: Knocking down expression of HIF-1α inhibited the glycolysis pathway, increased the pH of the culture medium, and protected the cells from hypoxia-induced apoptosis. In contrast, over-expression of HIF-1α accelerated glycolysis in A549 cells, decreased the pH of the culture medium, and enhanced hypoxia-induced apoptosis. These effects of HIF-1α on glycolysis, pH of the medium, and apoptosis were reversed by treatment with the glycolytic inhibitor, 2-DG. Apoptosis induced by HIF-1α over-expression was partially inhibited by increasing the buffering capacity of the culture medium by adding HEPES. CONCLUSION: During hypoxia in A549 cells, HIF-1α promotes activity of the glycolysis pathway and decreases the pH of the culture medium, resulting in increased cellular apoptosis