The game of chess is the longest-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific ...adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. By contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go by reinforcement learning from self-play. In this paper, we generalize this approach into a single AlphaZero algorithm that can achieve superhuman performance in many challenging games. Starting from random play and given no domain knowledge except the game rules, AlphaZero convincingly defeated a world champion program in the games of chess and shogi (Japanese chess), as well as Go.
A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world ...champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo's own move selections and also the winner of AlphaGo's games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100-0 against the previously published, champion-defeating AlphaGo.
Programming is a powerful and ubiquitous problem-solving tool. Systems that can assist programmers or even generate programs themselves could make programming more productive and accessible. Recent ...transformer-based neural network models show impressive code generation abilities yet still perform poorly on more complex tasks requiring problem-solving skills, such as competitive programming problems. Here, we introduce AlphaCode, a system for code generation that achieved an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform. AlphaCode solves problems by generating millions of diverse programs using specially trained transformer-based networks and then filtering and clustering those programs to a maximum of just 10 submissions. This result marks the first time an artificial intelligence system has performed competitively in programming competitions.
Carbon nanofibers (CNFs) were functionalized with 3-glycidoxypropyltrimethoxysilane and dispersed into epoxy resin. The chemical modification of CNFs was confirmed by FTIR, SEM, EDX and TGA ...measurements. After silanization, FTIR showed the existance of epoxy ring; EDX detected Si element; while TGA indicated 1.1wt.% Si on CNFs. Mechanical properties were analyzed by DMA. Silanized CNFs/epoxy composites demonstrated improved dispersion of CNFs in the matrix, and an enhancement of storage modulus for about 20% compared to the neat matrix, which indicated that the modification of CNFs improved the adhesion between fillers and matrices. DC electrical conductivity of CNFs was reduced about 7-fold compared to the original CNFs due to the silane coating. Accordingly, the composites containing silanized CNFs also had lower electrical conductivity than those containing original CNFs. In spite of decreased electrical conductivity, thermal conductivity of silanized CNFs/epoxy composites was increased due to the surface modification of CNFs.
The long-term outcome of allogenic islet transplantation is unknown. The aim of this study was to evaluate the 10-year outcome of islet transplantation in patients with type 1 diabetes and ...hypoglycemia unawareness and/or a functioning kidney graft.
We enrolled in this prospective parallel-arm cohort study 28 subjects with type 1 diabetes who received islet transplantation either alone (ITA) or after a kidney graft (IAK). Islet transplantation consisted of two or three intraportal infusions of allogenic islets administered within (median interquartile range) 68 days (43-92). Immunosuppression was induced with interleukin-2 receptor antibodies and maintained with sirolimus and tacrolimus. The primary outcome was insulin independence with A1C ≤6.5% (48 mmol/mol). Secondary outcomes were patient and graft survival, severe hypoglycemic events (SHEs), metabolic control, and renal function.
The primary outcome was met by (Kaplan-Meier estimates 95% CI) 39% (22-57) and 28% (13-45) of patients 5 and 10 years after islet transplantation, respectively. Graft function persisted in 82% (62-92) and 78% (57-89) of case subjects after 5 and 10 years, respectively, and was associated with improved glucose control, reduced need for exogenous insulin, and a marked decrease of SHEs. ITA and IAK had similar outcomes. Primary graft function, evaluated 1 month after the last islet infusion, was significantly associated with the duration of graft function and insulin independence.
Islet transplantation with the Edmonton protocol can provide 10-year markedly improved metabolic control without SHEs in three-quarters of patients with type 1 diabetes, kidney transplanted or not.
The mechanisms underlying the ability of axons to regrow after injury remain poorly explored at the molecular genetic level. We used a laser injury model in Caenorhabditis elegans mechanosensory ...neurons to screen 654 conserved genes for regulators of axonal regrowth. We uncover several functional clusters of genes that promote or repress regrowth, including genes classically known to affect axon guidance, membrane excitability, neurotransmission, and synaptic vesicle endocytosis. The conserved Arf Guanine nucleotide Exchange Factor (GEF), EFA-6, acts as an intrinsic inhibitor of regrowth. By combining genetics and in vivo imaging, we show that EFA-6 inhibits regrowth via microtubule dynamics, independent of its Arf GEF activity. Among newly identified regrowth inhibitors, only loss of function in EFA-6 partially bypasses the requirement for DLK-1 kinase. Identification of these pathways significantly expands our understanding of the genetic basis of axonal injury responses and repair.
► Systematic screening identifies new genes that promote and repress axon regrowth ► Slit/Robo signaling and the extracellular matrix repress regrowth ► A conserved signaling protein EFA-6 inhibits regrowth via microtubule dynamics ► Genetic analysis defines a genetic pathway for axon regrowth
Abstract
Islet transplantation is a unique paradigm in organ transplantation, since multiple donors are required to achieve complete insulin-independence. Preformed or de novo Donor Specific ...Antibodies (DSA) may target one or several donor islets, which adds complexity to the analysis of their impact. Adult patients with type 1 diabetes transplanted with pancreatic islets between 2005 and 2018 were included in a single-center observational study. Thirty-two recipients with available sera tested by solid-phase assays for anti-HLA antibodies during their whole follow-up were analyzed. Twenty-five recipients were islet-transplantation-alone recipients, and 7 islet-after-kidney recipients. Seven recipients presented with DSA at any time during follow-up (two with preformed DSA only, one with preformed and de novo DSA, 4 with de novo DSA only). Only islet-transplantation-alone recipients presented with de novo DSA. Three clinical trajectories were identified according to: 1/the presence of preformed DSA, 2/early de novo DSA or 3/late de novo DSA. Only late de novo DSA were associated with unfavorable outcomes, depicted by a decrease of the β-score. Islet transplantation with preformed DSA, even with high MFI values, is associated with favorable outcomes in our experience. On the contrary, de novo DSA, and especially late de novo DSA, may be associated with allograft loss.
Introduction
Nowadays, there are no strong diabetic pig models, yet they are required for various types of diabetes research. Using cutting‐edge techniques, we attempted to develop a type 2 diabetic ...minipig model in this study by combining a partial pancreatectomy (Px) with an energetic overload administered either orally or parenterally.
Methods
Different groups of minipigs, including Göttingen‐like (GL, n = 17) and Ossabaw (O, n = 4), were developed. Prior to and following each intervention, metabolic assessments were conducted. First, the metabolic responses of the Göttingen‐like (n = 3) and Ossabaw (n = 4) strains to a 2‐month High‐Fat, High‐Sucrose diet (HFHSD) were compared. Then, other groups of GL minipigs were established: with a single Px (n = 10), a Px combined with a 2‐month HFHSD (n = 6), and long‐term intraportal glucose and lipid infusions that were either preceded by a Px (n = 4) or not (n = 4).
Results
After the 2‐month HFHSD, there was no discernible change between the GL and O minipigs. The pancreatectomized group in GL minipigs showed a significantly lower Acute Insulin Response (AIR) (18.3 ± 10.0 IU/mL after Px vs. 34.9 ± 13.7 IU/mL before, p < .0005). In both long‐term intraportal infusion groups, an increase in the Insulinogenic (IGI) and Hepatic Insulin Resistance Indexes (HIRI) was found with a decrease in the AIR, especially in the pancreatectomized group (IGI: 4.2 ± 1.9 after vs. 1.5 ± 0.8 before, p < .05; HIRI (×10−5): 12.6 ± 7.9 after vs. 3.8 ± 4.3 before, p < .05; AIR: 24.4 ± 13.7 µIU/mL after vs. 43.9 ± 14.5 µIU/mL before, p < .005). Regardless of the group, there was no fasting hyperglycemia.
Conclusions
In this study, we used pancreatectomy followed by long‐term intraportal glucose and lipid infusions to develop an original minipig model with metabolic syndrome and early signs of glucose intolerance. We reaffirm the pig's usefulness as a preclinical model for the metabolic syndrome but without the fasting hyperglycemia that characterizes diabetes mellitus.
In this work, we tried to elaborate a type 2 diabetic minipig model corresponding to the World Health Organization definition by performing a subtotal pancreatectomy and long‐term intraportal glucose and lipid infusions. If we did not observe fasting hyperglycemia, our innovative minipig model showed early signs of glucose intolerance and metabolic syndrome.
Painless and controlled on-demand drug delivery is the ultimate goal for the management of various chronic diseases, including diabetes. To achieve this purpose, microneedle patches are gaining ...increased attention. While degradable microneedle (MN) arrays are widely employed, the use of non-dissolving MN patches remains a challenge to overcome. In this study, we demonstrate that crosslinking gelatin methacrylate with polyethylene glycol diacrylate (PEGDA) is potent for engineering non-dissolving MN arrays. Incorporation of MoS
2
nanosheets as a photothermal component into MN hydrogels results in MNs featuring on-demand release properties. An optimized MoS
2
-MN array patch formed using a hydrogel solution containing 500 μg mL
−1
of MoS
2
and photochemically crosslinked for 5 min shows required mechanical behavior under a normal compressive load to penetrate the stratum corneum of mice or pig skin and allows the delivery of macromolecular therapeutics such as insulin upon swelling. Using
ex vivo
and
in vivo
models, we show that the MoS
2
-MN patches can be used for loading and releasing insulin for therapeutic purposes. Indeed, transdermal administration of insulin loaded into MoS
2
-MN patches reduces blood glucose levels in C57BL/6 mice and mini-pigs comparably to subcutaneously injected insulin. We believe that this on-demand delivery system might alter the current insulin therapies and might be a potential approach for delivery of other proteins.
Painless and controlled on-demand drug delivery is the ultimate goal for the management of various chronic diseases, including diabetes.
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