34 research outputs found

    The Use of Bovine Pericardial Buttress on Linear Stapler Fails to Reduce Pancreatic Fistula Incidence in a Porcine Pancreatic Transection Model

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    We investigate the effectiveness of buttressing the surgical stapler to reduce postoperative pancreatic fistulae in a porcine model. As a pilot study, pigs (n = 6) underwent laparoscopic distal pancreatectomy using a standard stapler. Daily drain output and lipase were measured postoperative day 5 and 14. In a second study, pancreatic transection was performed to occlude the proximal and distal duct at the pancreatic neck using a standard stapler (n = 6), or stapler with bovine pericardial strip buttress (n = 6). Results. In pilot study, 3/6 animals had drain lipase greater than 3x serum on day 14. In the second series, drain volumes were not significantly different between buttressed and control groups on day 5 (55.3 ± 31.6 and 29.3 ± 14.2 cc, resp.), nor on day 14 (9.5 ± 4.2 cc and 2.5 ± 0.8 cc, resp., P = 0.13). Drain lipase was not statistically significant on day 5 (3,166 ± 1,433 and 6,063 ± 1,872 U/L, resp., P = 0.25) or day 14 (924 ± 541 and 360 ± 250 U/L). By definition, 3/6 developed pancreatic fistula; only one (control) demonstrating a contained collection arising from the staple line. Conclusion. Buttressed stapler failed to protect against pancreatic fistula in this rigorous surgical model

    Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes

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    A honeynet is a promising active cyber defense mechanism. It reveals the fundamental Indicators of Compromise (IoCs) by luring attackers to conduct adversarial behaviors in a controlled and monitored environment. The active interaction at the honeynet brings a high reward but also introduces high implementation costs and risks of adversarial honeynet exploitation. In this work, we apply infinite-horizon Semi-Markov Decision Process (SMDP) to characterize a stochastic transition and sojourn time of attackers in the honeynet and quantify the reward-risk trade-off. In particular, we design adaptive long-term engagement policies shown to be risk-averse, cost-effective, and time-efficient. Numerical results have demonstrated that our adaptive engagement policies can quickly attract attackers to the target honeypot and engage them for a sufficiently long period to obtain worthy threat information. Meanwhile, the penetration probability is kept at a low level. The results show that the expected utility is robust against attackers of a large range of persistence and intelligence. Finally, we apply reinforcement learning to the SMDP to solve the curse of modeling. Under a prudent choice of the learning rate and exploration policy, we achieve a quick and robust convergence of the optimal policy and value.Comment: The presentation can be found at https://youtu.be/GPKT3uJtXqk. arXiv admin note: text overlap with arXiv:1907.0139

    Strategic Learning for Active, Adaptive, and Autonomous Cyber Defense

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    The increasing instances of advanced attacks call for a new defense paradigm that is active, autonomous, and adaptive, named as the \texttt{`3A'} defense paradigm. This chapter introduces three defense schemes that actively interact with attackers to increase the attack cost and gather threat information, i.e., defensive deception for detection and counter-deception, feedback-driven Moving Target Defense (MTD), and adaptive honeypot engagement. Due to the cyber deception, external noise, and the absent knowledge of the other players' behaviors and goals, these schemes possess three progressive levels of information restrictions, i.e., from the parameter uncertainty, the payoff uncertainty, to the environmental uncertainty. To estimate the unknown and reduce uncertainty, we adopt three different strategic learning schemes that fit the associated information restrictions. All three learning schemes share the same feedback structure of sensation, estimation, and actions so that the most rewarding policies get reinforced and converge to the optimal ones in autonomous and adaptive fashions. This work aims to shed lights on proactive defense strategies, lay a solid foundation for strategic learning under incomplete information, and quantify the tradeoff between the security and costs.Comment: arXiv admin note: text overlap with arXiv:1906.1218

    Ferroptosis-inducing agents compromise in vitro human islet viability and function

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    Human islet transplantation has been hampered by donor cell death associated with the islet preparation procedure before transplantation. Regulated necrosis pathways are biochemically and morphologically distinct from apoptosis. Recently, ferroptosis was identified as a non-apoptotic form of iron-dependent regulated necrosis implicated in various pathological conditions. Mediators of islet oxidative stress, including glutathione peroxidase-4 (GPX4), have been identified as inhibitors of ferroptosis, and mechanisms that affect GPX4 function can impact islet function and viability. Ferroptosis has not been investigated directly in human islets, and its relevance in islet transplantation remains unknown. Herein, we sought to determine whether in vitro human islet viability and function is compromised in the presence of two distinct ferroptosis-inducing agents (FIA), erastin or RSL3, and whether these effects could be rescued with ferroptosis inhibitors, ferrostatin-1 (Fer-1), or desferrioxamine (DFO). Viability, as assessed by lactate dehydrogenase (LDH) release, revealed significant death in erastin- and RSL3-treated islets, 20.3% ± 3.8 and 24.4% ± 2.5, 24 h post culture, respectively. These effects were ameliorated in islets pre-treated with Fer-1 or the iron chelator, desferrioxamine (DFO). Stimulation index, a marker of islet function revealed a significant reduction in function in erastin-treated islets (control 1.97 ± 0.13 vs. 50 μM erastin 1.32 ± 0.1) (p < 0.05). Fer-1 and DFO pre-treatment alone did not augment islet viability or function. Pre-treatment of islets with erastin or Fer-1 did not impact in vivo engraftment in an immunodeficient mouse transplant model. Our data reveal that islets are indeed susceptible to ferroptosis in vitro, and induction of this novel cell death modality leads to compromised islet function, which can be recoverable in the presence of the ferroptosis inhibitors. The in vivo impact of this pathway in islet transplantation remains elusive given the constraints of our study, but warrants continued investigation

    Transplantation of Human Pancreatic Endoderm Cells Reverses Diabetes Post Transplantation in a Prevascularized Subcutaneous Site

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    Beta-cell replacement therapy is an effective means to restore glucose homeostasis in select humans with autoimmune diabetes. The scarcity of “healthy” human donor pancreata restricts the broader application of this effective curative therapy. “β-Like” cells derived from human embryonic stem cells (hESC), with the capacity to secrete insulin in a glucose-regulated manner, have been developed in vitro, with limitless capacity for expansion. Here we report long-term diabetes correction in mice transplanted with hESC-derived pancreatic endoderm cells (PECs) in a prevascularized subcutaneous site. This advancement mitigates chronic foreign-body response, utilizes a device- and growth factor-free approach, facilitates in vivo differentiation of PECs into glucose-responsive insulin-producing cells, and reliably restores glycemic control. Basal and stimulated human C-peptide secretion was detected throughout the study, which was abolished upon graft removal. Recipient mice demonstrated physiological clearance of glucose in response to metabolic challenge and safely retrieved grafts contained viable glucose regulatory cells
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