Human Fat-Derived Mesenchymal Stem Cells Xenogenically Implanted in a Rat Model Show Enhanced New Bone Formation in Maxillary Alveolar Tooth Defects

Background. Due to restorative concerns, bone regenerative therapies have garnered much attention in the field of human oral/maxillofacial surgery. Current treatments using autologous and allogenic bone grafts suffer from inherent challenges, hence the ideal bone replacement therapy is yet to be found. Establishing a model by which MSCs can be placed in a clinically acceptable bone defect to promote bone healing will prove valuable to oral/maxillofacial surgeons. Methods. Human adipose tissue-derived MSCs were seeded onto Gelfoam® and their viability, proliferation, and osteogenic differentiation was evaluated in vitro. Subsequently, the construct was implanted in a rat maxillary alveolar bone defect to assess in vivo bone healing and regeneration. Results. Human MSCs were adhered, proliferated, and uniformly distributed, and underwent osteogenic differentiation on Gelfoam®, comparable with the tissue culture surface. Data confirmed that Gelfoam® could be used as a scaffold for cell attachment and a delivery vehicle to implant MSCs in vivo. Histomorphometric analyses of bones harvested from rats treated with hMSCs showed statistically significant increase in collagen/early bone formation, with cells positive for osteogenic and angiogenic markers in the defect site. This pattern was visible as early as 4 weeks post treatment. Conclusions. Xenogenically implanted human MSCs have the potential to heal an alveolar tooth defect in rats. Gelfoam®, a commonly used clinical biomaterial, can serve as a scaffold to deliver and maintain MSCs to the defect site. Translating this strategy to preclinical animal models provides hope for bone tissue engineering

Ammonia fiber expansion (AFEX) pretreatment of lignocellulosic biomass

Lignocellulosic materials are plant-derived feedstocks, such as crop residues (e.g., corn stover, rice straw, and sugar cane bagasse) and purpose-grown energy crops (e.g., miscanthus, and switchgrass) that are available in large quantities to produce biofuels, biochemicals, and animal feed. Plant polysaccharides (i.e., cellulose, hemicellulose, and pectin) embedded within cell walls are highly recalcitrant towards conversion into useful products. Ammonia fiber expansion (AFEX) is a thermochemical pretreatment that increases accessibility of polysaccharides to enzymes for hydrolysis into fermentable sugars. These released sugars can be converted into fuels and chemicals in a biorefinery. Here, we describe a laboratory-scale batch AFEX process to produce pretreated biomass on the gram-scale without any ammonia recycling. The laboratory-scale process can be used to identify optimal pretreatment conditions (e.g., ammonia loading, water loading, biomass loading, temperature, pressure, residence time, etc.) and generates sufficient quantities of pretreated samples for detailed physicochemical characterization and enzymatic/microbial analysis. The yield of fermentable sugars from enzymatic hydrolysis of corn stover pretreated using the laboratory-scale AFEX process is comparable to pilot-scale AFEX process under similar pretreatment conditions. This paper is intended to provide a detailed standard operating procedure for the safe and consistent operation of laboratory-scale reactors for performing AFEX pretreatment of lignocellulosic biomass

Feasibility randomized-controlled trial of online acceptance and commitment therapy for painful peripheral neuropathy in people living with HIV: The OPEN study

Background Neuropathic pain negatively affects quality of life among people living with HIV (PLWH). This study examined the feasibility of conducting a full‐scale randomized‐controlled trial of online acceptance and commitment therapy (“ACT OPEN”) for neuropathic pain in PLWH. Methods Using a parallel‐groups design, thirty‐eight participants were randomized to ACT OPEN or a waitlist control (2:1). Participants completed standard self‐report outcome measures at baseline, and two‐ and five‐months post‐randomization. Participants were aware of their allocation, but assessment was blinded. Results Twenty‐five participants were randomized to ACT OPEN and 13 to the control (of 133 referrals). ACT OPEN completion was 69% and two‐month trial retention was 82%. Treatment credibility and satisfaction scores for ACT OPEN were comparable to scores reported in previous trials of cognitive‐behavioural treatments for pain. Four adverse events were reported during the study, including one serious adverse event; all of these were unrelated to the research procedures. Small to moderate effects and 95% confidence intervals suggest that the true effect may favour ACT OPEN for improvements in pain intensity/interference and depression. Conclusions A full‐scale RCT of online ACT for pain management in PLWH may be feasible with refinements to trial design to facilitate recruitment. Significance Research on pain management in people living with HIV has primarily focused on pharmacological treatments with limited success. This is the first study to show the potential feasibility of a psychological treatment based on acceptance and commitment therapy delivered online and tailored for pain management in people with HIV (“ACT OPEN”). ACT OPEN may be a promising treatment in this population and further evaluation in a full‐scale randomized‐controlled trial appears warranted. Trial Registration: The trial was registered (clinicaltrials.gov; NCT03584412)

Legacy genetics of Arachis cardenasii in the peanut crop shows the profound benefits of international seed exchange

A great challenge for humanity is feeding its growing population while minimizing ecosystem damage and climate change. Here, we uncover the global benefits arising from the introduction of one wild species accession to peanut-breeding programs decades ago. This work emphasizes the importance of biodiversity to crop improvement: peanut cultivars with genetics from this wild accession provided improved food security and reduced use of fungicide sprays. However, this study also highlights the perilous consequences of changes in legal frameworks and attitudes concerning biodiversity. These changes have greatly reduced the botanical collections, seed exchanges, and international collaborations which are essential for the continued diversification of crop genetics and, consequently, the long-term resilience of crops against evolving pests and pathogens and changing climate.The narrow genetics of most crops is a fundamental vulnerability to food security. This makes wild crop relatives a strategic resource of genetic diversity that can be used for crop improvement and adaptation to new agricultural challenges. Here, we uncover the contribution of one wild species accession, Arachis cardenasii GKP 10017, to the peanut crop (Arachis hypogaea) that was initiated by complex hybridizations in the 1960s and propagated by international seed exchange. However, until this study, the global scale of the dispersal of genetic contributions from this wild accession had been obscured by the multiple germplasm transfers, breeding cycles, and unrecorded genetic mixing between lineages that had occurred over the years. By genetic analysis and pedigree research, we identified A. cardenasii–enhanced, disease-resistant cultivars in Africa, Asia, Oceania, and the Americas. These cultivars provide widespread improved food security and environmental and economic benefits. This study emphasizes the importance of wild species and collaborative networks of international expertise for crop improvement. However, it also highlights the consequences of the implementation of a patchwork of restrictive national laws and sea changes in attitudes regarding germplasm that followed in the wake of the Convention on Biological Diversity. Today, the botanical collections and multiple seed exchanges which enable benefits such as those revealed by this study are drastically reduced. The research reported here underscores the vital importance of ready access to germplasm in ensuring long-term world food security.Genome sequence, genotyping, pedigree information, and yield trial data have been deposited in National Center for Biotechnology Information (NCBI), PeanutBase, and USDA Data Repository (NCBI: JADQCP000000000) (14). Datasets S1–S6 are available at USDA Ag Data Commons: https://data.nal.usda.gov/dataset/data-legacy-genetics-arachis-cardenasii-peanut-crop-v2 (17). All other study data are included in the article and/or supporting information

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Concert recording 2016-11-15

[Track 1]. Subjugation. Connection [Track 2]. Captivation / Durgan Maxey -- [Track 3]. Fight / Bryce Owens -- [Track 4]. Overture to Stay / Joshua Bland -- [Track 5]. A cellist\u27s legacy. Part I [Track 6]. Part II / Eric Dreggors -- [Track 7]. Evening prayer / Robbie Baker -- [Track 8]. Elegy / Brandon Wade -- [Track 9]. The grotesques trio. Gargoyles [Track 10]. Chimera [Track 11]. Grotesques / Marissa Johnson -- [Track 12]. Crosshair / Joshua Bland -- [Track 13]. Nightwind sings / L. Coley Pitchford -- [Track 14]. Six reflections through poetry. Memories (Walt Whitman) [Track 15]. The musician\u27s wife (Weldon Kees) [Track 16]. The road not taken (Robert Frost) [Track 17]. Lessons (Whitman) [Track 18]. Stronger lessons (Whitman) [Track 19]. O me! O life! (Whitman) / Nick Vecchio -- [Tracks 20-21]. String quartet #1 / Jeremiah Flannery -- [Track 22]. Tides. Morning tide [Track 23]. Bore tide / Elizabeth Greener -- [Track 24]. Shepherd\u27s contemplation / Robbie Baker -- Green grass / arranged by Eva Martin -- [Track 25]. Urbe fracta est II. A prayer for Jerusalem / Joshua Bland

Teaching and Generative AI

With the rapid development of generative AI, teachers are experiencing a new pedagogical challenge, one that promises to forever change the way we approach teaching and learning. As a response to this unprecedented teaching context, this collection—Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions—provides interdisciplinary teachers, librarians, and instructional designers with practical and thoughtful pedagogical resources for navigating the possibilities and challenges of teaching in an AI era. Because our goal with this edited collection is to present nuanced discussions of AI technologies across disciplines, the chapters collectively acknowledge or explore both possibilities and tensions—including the strengths, limitations, ethical considerations, and disciplinary potential and challenges—of teaching in an AI era. As such, the authors in this collection do not simply praise or criticize AI, but thoughtfully acknowledge and explore its complexities within educational settings

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447