A Non-parametric Approach to Measuring the \kpi{} Amplitudes in \dpkkpi{} Decay

Using a large sample of \dpkkpi{} decays collected by the FOCUS photoproduction experiment at Fermilab, we present the first non-parametric analysis of the \kpi{} amplitudes in \dpkkpi{} decay. The technique is similar to the technique used for our non-parametric measurements of the \krzmndk{} form factors. Although these results are in rough agreement with those of E687, we observe a wider S-wave contribution for the \ksw{} contribution than the standard, PDG \cite{pdg} Breit-Wigner parameterization. We have some weaker evidence for the existence of a new, D-wave component at low values of the $K^- \pi^+$ mass.Comment: 13 pages 3 figure

Study of Cabibbo Suppressed Decays of the Ds Charmed-Strange Meson involving a KS

We study the decay of Ds meson into final states involving a Ks and report the discovery of Cabibbo suppressed decay modes Ds -> Kspi-pi+pi+ (179 +/- 36 events) and Ds -> Kspi+ (113 +/-26 events). The branching ratios for the new modes are Gamma(Ds -> Kspi-pi+pi+)/Gamma(Ds -> KsK-pi+pi+) = 0.18 +/- 0.04 +/- 0.05 and Gamma(Ds -> Kspi+)/Gamma(Ds -> KsK+) = 0.104 +/- 0.024 +/- 0.013.Comment: 11 pages, 6 figure

Measurements of branching fraction ratios and CP-asymmetries in suppressed B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^- decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- -> D(-> K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- -> D(-> K^+ pi^-)pi^- decay are also reported.Comment: 8 pages, 1 figure, accepted by Phys.Rev.D Rapid Communications for Publicatio

Identification by Automated Screening of a Small Molecule that Selectively Eliminates Neural Stem Cells Derived from hESCs but Not Dopamine Neurons

BACKGROUND:We have previously described fundamental differences in the biology of stem cells as compared to other dividing cell populations. We reasoned therefore that a differential screen using US Food and Drug Administration (FDA)-approved compounds may identify either selective survival factors or specific toxins and may be useful for the therapeutically-driven manufacturing of cells in vitro and possibly in vivo. METHODOLOGY/PRINCIPAL FINDINGS:In this study we report on optimized methods for feeder-free culture of hESCs and hESC-derived neural stem cells (NSCs) to facilitate automated screening. We show that we are able to measure ATP as an indicator of metabolic activity in an automated screening assay. With this optimized platform we screened a collection of FDA-approved drugs to identify compounds that have differential toxicity to hESCs and their neural derivatives. Nine compounds were identified to be specifically toxic for NSCs to a greater extent than for hESCs. Six of these initial hits were retested and verified by large-scale cell culture to determine dose-responsive NSC toxicity. One of the compounds retested, amiodarone HCL, was further tested for possible effects on postmitotic neurons, a likely target for transplant therapy. Amiodarone HCL was found to be selectively toxic to NSCs but not to differentiated neurons or glial cells. Treated and untreated NSCs and neurons were then interrogated with global gene expression analysis to explore the mechanisms of action of amiodarone HCl. The gene expression analysis suggests that activation of cell-type specific cationic channels may underlie the toxicity of the drug. CONCLUSIONS/SIGNIFICANCE:In conclusion, we have developed a screening strategy that allows us to rapidly identify clinically approved drugs for use in a Chemistry, Manufacture and Control protocol that can be safely used to deplete unwanted contaminating precursor cells from a differentiated cell product. Our results also suggest that such a strategy is rich in the potential of identifying lineage specific reagents and provides additional evidence for the utility of stem cells in screening and discovery paradigms

Enzymatic Glucose Based Bio batteries: Bioenergy to Fuel Next Generation Devices

[EN] This article consists of a review of the main concepts and paradigms established in the field of biological fuel cells or biofuel cells. The aim is to provide an overview of the current panorama, basic concepts, and methodologies used in the field of enzymatic biofuel cells, as well as the applications of these bio-systems in flexible electronics and implantable or portable devices. Finally, the challenges needing to be addressed in the development of biofuel cells capable of supplying power to small size devices with applications in areas related to health and well-being or next-generation portable devices are analyzed. The aim of this study is to contribute to biofuel cell technology development; this is a multidisciplinary topic about which review articles related to different scientific areas, from Materials Science to technology applications, can be found. With this article, the authors intend to reach a wide readership in order to spread biofuel cell technology for different scientific profiles and boost new contributions and developments to overcome future challenges.Financial support from the Spanish Ministry of Science, Innovation and University, through the State Program for Talent and Employability Promotion 2013-2016 by means of Torres Quevedo research contract in the framework of Bio2 project (PTQ-14-07145) and from the Instituto Valenciano de Competitividad Empresarial-IVACE-GVA (BioSensCell project)Buaki-Sogo, M.; García-Carmona, L.; Gil Agustí, MT.; Zubizarreta Saenz De Zaitegui, L.; García Pellicer, M.; Quijano-Lopez, A. (2020). Enzymatic Glucose Based Bio batteries: Bioenergy to Fuel Next Generation Devices. Topics in Current Chemistry (Online). 378(6):1-28. https://doi.org/10.1007/s41061-020-00312-8S1283786Schlögl R (2015) The revolution continues: Energiewende 2.0. Angew Chem Int Ed 54:4436–4439Mitcheson PD, Yeatman EM, Rao GK, Holmes AS, Green TC (2008) Energy harvesting from human and machine motion for wireless electronic devices. Proc IEEE 96(9):1457–1486Wang ZL, Wu W (2012) Nanotechnology-enabled energy harvesting for self-powered micro-/nanosystems. Angew Chem Int Ed 51:11700-11721Lamy C, Lima A, LeRhun V, Delime F, Coutanceau C, Léger J-M (2002) Recent advances in the development of direct alcohol fuel cells (DAFC). J Power Sources 105:283Cheng X, Shi Z, Glass N, Zhang L, Zhang J, Song D, Liu Z-S, Wang H, Shen J (2007) A review of PEM hydrogen fuel cell contamination: impacts, mechanisms, and mitigation. J Power Sources 165:739Boudghere Stambouli A, Traversa E (2002) Solid oxide fuel cells (SOFC): a review of an environmentally clean and efficient source of energy. Renew Sustain Energy Rev 6:433–455Qiao Y, Li CM (2011) Nanostructured catalyst in fuel cells. J Mater Chem 21:4027–4036Edwards PP, Kuznetsov VL, David WIF, Brandon NP (2008) Hydrogen and fuel cells: towards sustainable energy future. Energy Policy 36:4356–4362Kirubakaran A, Jain S, Nema RK (2009) A review on fuel cell technologies and power electronic interface. Renew Sustain Energy 13:2430–2440Kerzenmacher S, Ducree J, Zengerle R, von Stetten F (2008) An abiotically catalyzed glucose fuel cell for powering medical implants: reconstructed manufacturing protocol and analysis of performance. J Power Sources 182:66–75Drake RF, Kusserow BK, Messinger S, Matsuda S (1970) A tissue implantable fuel cell power supply. Trans Am Soc Artif Intern Organs 16:199–205Giner J, Holleck G, Malachesky PA (1973) Eine implantierbare Brennstoffzelle zum Betrieb eines mechanischen Herzens. Phys Chem 77:782–783. https://doi.org/10.1002/bbpc.19730771009Cosnier S, LeGoff A, Holzinger M (2014) Towards glucose biofuel cells implanted in human body for powering artificial organs: review. Electrochem Commun 38:19–23Katz E (2015) Implantable biofuel cells operating in vivo—potential power sources for bioelectronic devices. Bioelectron Med 2:1–12Bullen RA, Arnot TC, Lakeman JB, Walsh FC (2006a) Biofuel cells and their development . Biosens Bioelectron 21:2015–2045Cooney MJ, Svoboda V, Lau C, Martin G, Minteer SD (2008) Enzyme catalysed biofuel cells. Energy Environ Sci 1:320–337Cracknell JA, Vincent KA, Armstrong FA (2008) Enzymes as working or inspirational electrocatalysts for fuel cells and electrolysis. Chem Rev 108:2439–2461Sheldon RA (2007) Enzyme immobilization: the quest for optimum performance. Adv Synth Catal 349:1289–1307Bullen RA, Arnot TC, Lakeman JB, Walsh FC (2006b) Biofuel cells and their development. Biosens Bioelectron 21:2015–2045Koch C, Popiel D, Harnisch F (2014) Functional redundancy of microbial anodes fed by domestic wastewater. ChemElectroChem 1:1923–1931Mano N, Mao F, Heller A (2003) Characteristics of a miniature compartment-less glucose−O2 biofuel cell and its operation in a living plant. J Am Chem Soc 125(21):6588–6594Mano N, Mao F, Heller A (2002) A miniature biofuel cell operating in a physiological buffer. J Am Chem Soc 124(44):12962–12963Bruen D, Delaney C, Florea L, Diamond D (2017) Glucose sensing for diabetes monitoring: recent developments. Sensors 17:1866Falk M, Blum Z, Shleev S (2012) Direct electron transfer based enzymatic fuel cells. Electrochim Acta 82:191–202White HB (1976) Coenzymes as fossils of an earlier metabolic state. J Mol Evol 7:101–104Broderick JB (2001) Coenzymes and cofactors. In: eLS. Wiley, Chichester. https://www.els.net. https://doi.org/10.1038/npg.els.0000631Sakurai T, Kataoka K (2007) Basic and applied features of multicopper oxidases, CueO, bilirubin oxidase, and laccase. Chem Rec 7:220–229Bankar SB, Bule MV, Singhal RS, Ananthanarayan L (2009) Glucose oxidase—an overview. Biotech Adv 27:489–501Ferri S, Kojima K, Sode K (2011) Review of glucose oxidases and glucose dehydrogenases: a bird’s eye view of glucose sensing enzymes. J Diabetes Sci Technol 5:1068–1076Katz E, MacVittie K (2013) Implanted biofuel cells operating in vivo—methods, applications and perspectives—feature article. Energy Environ Sci 6:2791–2803Ghindilis AL, Atanasov P, Wilkins E (1997) Enzyme catalysed direct electron transfer: fundamentals and analytical applications. Electroanalysis 9:661–674Von Woedtke Th, Fisher U, Abel P (1994) Glucose oxidase electrodes: effect of H2O2 on enzyme activity? Biosens Bioelectron 9:65–71Kleppe K (1966) The effect of H2O2 on glucose oxidase from Aspergillus niger. Biochemistry 5:139–143Zebda A, Godran C, Le Goff A, Holzinger M, Cinquin P, Cosnier S (2011) Mediatorless high-power glucose biofuel cells based on compressed carbon nanotube-enzyme electrodes. Nat Commun 2:370Borenstein A, Hanna O, Attias R, Luski S, Brousse T, Aurbach D (2017) Carbon-based composite materials for supercapacitor electrodes: a review. J Mater Chem A 5:12653–12672Angione MD, Pilolli R, Cotrone S, Magliulo M, Mallardi A, Palazzo G, Sabbatini L, Fine D, Dodabalapur A, Lioffi N, Torsi L (2011) Carbon based nanomaterials for electronic bio-sensing. Mat Today 14:424–433Cha C, Shin SR, Annabi N, Dokmeci MR, Khademhosseini A (2013) Carbon based nanomaterials: multifunctional materials for biomedical engineering. ACS Nano 7:2891–2897Wang Z, Dai Z (2015) Carbon nanomaterials-based electrochemical biosensors: an overview. Nanoscale 7:6420–6431Jariwala D, Sangwan VK, Lauhon LJ, Marks TJ, Hersam MC (2013) Carbon nanomaterials for electronics, optoelectronics, photovoltaics and sensing. Chem Soc Rev 42:2824–2860Babadi AA, Bagheri S, Abdul Hamid SB (2016) Progress on implantable biofuel cell: nano-carbon functionalization for enzyme immobilization enhancement. Biosens Bioelectron 15:850–860Osadebe I, Leech D (2014) Effect of multi-walled carbon nanotubes on glucose oxidation by glucose oxidase or a flavin-dependent glucose dehydrogenase in redox-polymer-mediated enzymatic fuel cell anodes. ChemElectroChem 1:1988–1993Si P, Huang Y, Wang T, Ma J (2013) Nanomaterials for electrochemical non-enzymatic glucose biosensors. RSC Adv 3:3487–3502Putzbach W, Ronkainen NJ (2013) Immobilization techniques in the fabrication of nanomaterial-based electrochemical biosensors: a review. Sensors 13(4):4811–4840Walcarius A, Minteer SD, Wang J, Lin Y, Merkoçi A (2013) Nanomaterials for bio-functionalized electrodes: recent trends. J Mater Chem B 1:4878–4908Datta S, Christena LR, Rajaram YRS (2013) Enzyme immobilization: an overview on techniques and support materials. 3 Biotech 3(1):1–9Ivanov I, Vidaković-Koch T, Sundmaker K (2010) Recent advances in enzymatic fuel cells; experiments and modelling. Energies 3:803–846Nguyen HH, Kim M (2017) An overview of techniques in enzyme immobilization. Appl Sci Converg Technol 26(6):157–163Fu J, Reinhold J, Woodbury NW (2011) Peptide-modified surfaces for enzyme immobilization. PLoS One 6(4):e18692Lee DH, Park CH, Yeo JM, Kim SW (2006) Lipase immobilization on silica gel using a cross-linking method. J Ind Eng Chem 12(5):777–782Szymańska K, Bryjak J, Jarzębski AB (2009) Immobilization of invertase on mesoporous silicas to obtain hyper active biocatalysts. Top Catal 52:1030–1036Al-Lolage F, Meneghello M, Ma S, Ludwig R, Barlett PN (2017) A flexible method for the stable, covalent immobilization of enzymes at electrode surfaces. ChemElectroChem 4:1528–1534Gutierrez-Sanchez C, Shleev S, De Lacey AL, Pita M (2015) Third-generation oxygen amperometric biosensor based on Trametes hirsuta laccase covalently bound to graphite electrode. Chem Pap 69:237–240Pita M, Gutierrez-Sanchez C, Toscano MD, Shleev S, De Lacey AL (2013) Oxygen biosensor based on bilirubin oxidase immobilized on a nanostructured gold electrode. Bioelectrochemistry 94:69–74Vaz-Dominguez C, Campuzano S, Rüdiger O, Pita M, Gorbacheva M, Shleev S, Fernandez VM, de Lacey LA (2008) Laccase electrode for direct electrocatalytic reduction of O2 to H2O with high-operational stability and resistance to chloride inhibition. Biosens Bioelectron 24(4):531–537Gutiérrez-Sánchez C, Jia W, Beyl Y, Pita M, Schuhmann W, de Lacey LA, Stoica L (2012) Enhanced direct electron transfer between laccase and hierarchical carbon microfibers/carbon nanotubes composite electrodes. Comparison of three enzyme immobilization methods. Electrochim Acta 82:218–223Lv Y, Jin S, Wang Y, Lun Z, Xia C (2016) Recent advances in the application of nanomaterials in enzymatic glucose sensors. J Iran Chem Soc 13(10):1767–1776Zhao C, Gai P, Song R, Chen Y, Zhang J, Zhu J-J (2017) Nanostructured material-based biofuel cells: recent advances and future prospects. Chem Soc Rev 46:1545–1564Yu EH, Scott K (2010) Enzymatic biofuel cells—fabrication of enzyme electrodes. Energies 3:23–42Minteer SD, Atanassov P, Luckarift HR, Johnson GR (2013) New materials for biological fuel cells. Mater Today 15(4):166–173Sarma AK, Vatsyayan P, Goswami P, Minteer SD (2009) Recent advances in material science for developing enzyme electrodes. Biosens Bioelectron 24:2313–2322Jesionowski T, Zdarta J, Krajewska B (2014) Enzyme immobilization by adsorption: a review. Adsorption 20:801–821Sardar M, Gupta MN (2005) Immobilization of tomato pectinase on Con A-Seralose 4B by bioaffinity layering. Enzyme Microbial Technol 37:355–359Sheldon RA (2011) Characteristic features and biotechnological applications of cross-linked enzyme aggregates (CLEAs). Appl Microbiol Biotechnol 92:467–477Velasco-Lozano S, López-Gallego F, Mateos-Díaz JC, Favela-Torres E (2015) Cross-linked enzyme aggregates (CLEA) in enzyme improvement—a review. Biocatalysis 1:166–177Cosnier S (1999) Biomolecule immobilization on electrode surfaces by entrapment or attachment to electrochemically polymerized films. A review. Biosen Bioelectron 14:443–456Heller A (1990) Electrical wiring of redox enzymes. Acc Chem Res 29:128–134Heller A (1992) Electrical connection of enzyme redox centres to electrodes. J Phys Chem 96:3579–3587Martins MVA, Pereira AR, Luz RAS, Iost RM, Crespilho FN (2014) Evidence of short-range electron transfer of a redox enzyme on graphene oxide electrodes. Phys Chem Chem Phys 16:17426–17436Luz RAS, Pereira AR, de Souza JCP, Sales FCPF, Crespilho FN (2014) Enzyme biofuel cells: thermodynamics. Kinetics and challenges in applicability. ChemElectroChem 1(11):1751–1777Neto SA, De Andrade AR (2013) New energy sources: the enzymatic biofuel cell. J Braz Chem Soc 24(12):1891–1912Rapoport BI, Kedzierski JT, Sarpeshkar R (2012) A glucose fuel cell for implantable brain–machine interfaces. PLoS One 7(6):6 e38436Zebda A, Alcaraz J-P, Vadgama P, Shleev S, Minteer SD, Boucher F, Cinquin P, Martin DK (2018) Challenges for successful implantation of biofuel cells. Bioelectrochemistry 124:57–72Ferraris RP, Diamond J (1997) Regulation of intestinal sugar transport. Physiol Rev 77:257–301Sprague JE, Arbeláez AM (2011) Glucose counterregulatory responses to hypoglicemia. Pediatr Endocrinol Rev 9:463–475Slaughter G, Kulkarni T (2019) Detection of human plasma glucose using a self-powered glucose biosensor. Energies 12:825Rathee K, Dhull V, Dhull R, Singh S (2016) Biosensors based on electrochemical lactate detection: a comprehensive review. Biochem Biophys Rep 5:35–54Koushanpour A, Gamella M, Katz E (2017) A biofuel cell based on biocatalytic reactions of lactate on both anode and cathode electrodes—extracting electrical power from human sweat. Electroanalysis 29:1602–1611Yao Y, Li H, Wang D, Liu C, Zhang C (2017) An electrochemiluminescence cloth-based biosensor with smartphone-based imaging for detection of lactate in saliva. Analyst 142:3715–3724Pankratov D, González-Arribas E, Blum Z, Shleev S (2016) Tear based bioelectronics. Electroanalysis 28:1250–1266Krogstad AL, Jansson PA, Gisslen P, Lönnroth P (1996) Microdialysis methodology for the measurement of dermal interstitial fluid in humans. Br J Dermatol 134(6):1005–1012Bandodkar AJ, Wang J (2016) Wearable biofuel cells: a review. Electroanalysis 28:1188–1200Jia W, Valdés-Ramírez G, Bandodkar AJ, Windmiller JR, Wang J (2013) Epidermal biofuel cells: energy harvesting from human perspiration. Angew Chem Int Ed 52:1–5Jeerapan I, Sempionatto JR, Pavinatto A, You J-M, Wang J (2016) Stretchable biofuel cells as wearable textile-based self-powered sensors. J Mater Chem A 4:18342–18353Valdés-Ramírez G, Li Y-G, Kima J, Jia W, Bandodkar AJ, Nuñez-Flores R, Miller PR, Wu S-Y, Narayan R, Windmiller JR, Polsky R, Wang J (2016) Microneedle-based self-powered glucose sensor. Electrochem Commun 47:58–62Gamella M, Koushanpour A, Katz E (2018) Biofuel cells—activation of micro- and macro- electronic devices. Bioelectrochemistry 119:33–42Mano N, Mao F, Shin W, Chen T, Heller A (2003) A miniature biofuel cell operating at 0.78 V. Chem Commun 20:518–519Shi B, Li Z, Fan Y (2018) Implantable energy harvesting devices. Adv Mater 30:1801511MacVittie K, Halámek J, Halámková L, Southcott M, Jemison WD, Lobel R, Katz E (2013) From “cyborg” lobsters to a pacemaker powered by implantable biofuel cells. Energy Environ Sci 6:81–86Szczupak A, Halámek J, Halámková L, Bocharova V, Alfonta L, Katz E (2012) Living battery—biofuel cells operating in vivo in clams. Energy Environ Sci 5:8891–8895Southcott M, MacVittie K, Halámek J, Halámková L, Jemison WD, Lobel R, Katz E (2013) A pacemaker powered by an implantable biofuel cell operating under conditions mimicking the human blood circulatory system—battery not included. Phys Chem Chem Phys 15:6278–6283MacVittie K, Conlon T, Katz E (2015) A wireless transmission system powered by an enzyme biofuel cell implanted in an orange. Bioelectrochemistry 106:28–33Aghahosseini H, Ramazani A, Asiabi PA, Gouranlou F, Hosseini F, Rezaei A, Min B-K, Joo SW (2016) Glucose-based biofuel cells: nanotechnology as a vital science in biofuel cell performance. Nanochem Res 1(2):83–204Zebda A, Cosnier S, Alcaraz J-P, Holzinger M, Le Goff A, Gondran C, Boucher F, Giroud F, Gorgy K, Lamraoui H, Cinquin P (2013) Single glucose biofuel cells implanted in rats power electronic devices. Sci Rep 2013:1516Ichi-Ribault SE, Alcaraz J-P, Boucher F, Boutaud B, Dalmolin R, Boutonnat J, Cinquin P, Zebda A, Martin DK (2018) Remote wireless control of an enzymatic biofuel cell implanted in a rabbit for 2 months. Electrochim Acta 269:360–366Bandodkar A (2017) Review—wearable biofuel cells: past, present and future. J Electrochem Soc 164(3):H3007–H3014Coman V, Ludwig R, Harreither W, Haltrich D, Gorton L, Ruzgas T, Shleev S (2010) A direct electron transfer-based glucose/oxygen biofuel cell operating in human serum. Fuel Cells 10(1):9–16Shoji K, Akiyama Y, Suzuki M, Nakamura N, Ohno H, Morishima K (2016) Biofuel cell backpacked insect and its application to wireless sensing. Biosens Bioelectron 78:390–395Reuillard B, Abreu C, Lalaoui N, Le Goff A, Holzinger M, Ondel O, Buret F, Cosnier S (2015) One-year stability for a glucose/oxygen biofuel cell combined with pH reactivation of the laccase/carbon nanotube biocathode. Bioelectrochemistry 106:73–76Sales FCPF, Iost RM, Martins MVA, Almeida MC, Crespilho FN (2013) An intravenous implantable glucose/dioxygen biofuel cell with modified flexible carbon fiber electrodes. Lab Chip 13:468Falk M, Narvez Villarrubia CW, Babanova S, Atanassov P, Shleev S (2013) Biofuel cells for biomedical applications: colonizing the animal kingdom. ChemPhysChem 14:2045–2058Rasmussen M, Ritzmann RE, Lee I, Pollack AJ, Scherson D (2012) An implantable biofuel cell for a live insect. J Am Chem Soc 134(3):1458–1460Halámková L, Halámek J, Bocharova V, Szczupak A, Alfonta L, Katz E (2012) Implanted biofuel cell operating in a living snail. J Am Chem Soc 134:5040–5043Cinquin P, Gondran C, Giroud F, Mazabrard S, Pellisier A, Boucher F, Alcaraz J-P, Gorgy K, Lenouvel F, Mathé S, Porcu P, Cosnier S (2010) A glucose biofuel cell implanted in rats. Plos One 5(5):e010476Chen C, Xie Q, Yang D, Xiao H, Fu Y, Tan S, Yao S (2013) Recent advances in electrochemical glucose biosensors: a review. RSC Adv 3:4473–4491Andoralov V, Falk M, Suyatin DB, Granmo M, Sotres J, Ludwig R, Popov VO, Schouenborg J, Blum Z, Shleev S (2013) Biofuel cell based on microscale nanostructured electrodes with inductive coupling to rat brain neuronsVerbeek MM, Leen WG, Willemsen MA, Slats D, Claassen JA (2016) Hourly analysis of cerebrospinal fluid glucose shows large diurnal fluctuations. J Cereb Blood F Met 36(5):899–902González-Guerrero MJ, Del Campo FJ, Esquivel JP, Leech D, Sabaté N (2017) Paper-based microfluidic biofuel cell operating under glucose concentrations within physiological range. Biosens Bioelectron 90:475–480Takeuchi ES, Leising RA (2002) Lithium batteries for biomedical applications. MRS Bull 27(8):624–627Bock DC, Marschilok A, Takeuchi KJ, Takeuchi ES (2012) Batteries used to power implantable biomedical devices. Electrochim Acta 84:155–164Greatbatch W, Lee JH, Mathias W, Eldridge M, Moser JR, Schneider AA (1971) The solid-state lithium battery: a new improved chemical power source for implantable cardiac pacemaker. IEEE Trans Biomed Eng 18(5):317–324Liu Y, Dong S (2007) A biofuel cell with enhanced power output by grape juice. Electrochem Commun 9(7):1423–1427Choi S, Lee H, Ghaffari R, Hyeon T, Kim D-H (2016) Recent advances in flexible and stretchable bio-electronic devices integrated with nanomaterials. Adv Mater 28:4203–4218Zhou L, Mao J, Ren Y, Han ST, Roy VAL, Zhou Y (2018) Recent advances of flexible data storage devices based on organic nanoscale materials. Small 14(10):1703126Gwon H, Kim H-S, Lee KU, Seo D-H, Park YC, Lee Y-S, Ahn BT, Kong K (2011) Flexible energy storage devices based on graphene paper. Energy Environ Sci 4:1277–1283Pang C, Lee C, Suh K-Y (2013) Recent advances in flexible sensors for wearable and implantable devices. J Appl Pol Sci 130:1429–1441Bandodkar AJ, Wang J (2014) Non-invasive wearable electrochemical sensors: a review. Trends Biotech 32(7):363–371Bandodkar AJ, Uia W, Wang J (2015) Tatto-based wearable electrochemical devices: a review. Electroanalysis 27(3):562–572Reid RC, Minteer SD, Gale BK (2015) Contact lens biofuel cell tested in a synthetic tear solution. Biosens Bioelectron 68:142Falk M, Andoralov V, Blum Z, Sotres J, Suyatin DM, Ruzgas T, Arnebrant T, Shleev S (2012) Biofuel cells as a power source for electronic contact lenses. Biosens Bioelectron 37(1):38–45Falk M, Andoralov V, Silow M, Toscano MD, Shleev S (2013) Miniature biofuel cell as a potential power source for Glucose-sensing contact lenses. Anal Chem 85(13):6342–6348Reid R, Jones SR, Hickey DP, Minteer SD, Gale BK (2016) Modeling carbon nanotubes connectivity and surface activity in a contact lens biofuel cell. Electrochim Acta 203:30–40Blum Z, Pankratov D, Shleev S (2014) Powering electronic contact lenses: current achievements, challenges and perspective. Expert Rev Ophthalmol 9(4):269–273Xiao X, Siepenkoetter T, Conghaile PÓ, Leech D, Magner E (2018) Nanoporous gold-based biofuel cell on contact lenses. ACS Appl Mater Interfaces 10(8):7107–7116Yang X-Y, Tian G, Jiang N, Su B-L (2012) Immobilization technology: a sustainable solution for biofuel cell design. Ener Environ Sci 5:5540–5563Mano N (2019) Engineering glucose oxidase for bioelectrochemical applications. Bioelectrochemistry 128:218–240Mate DM, Gonzalez-Perez D, Falk M, Kittl R, Pita M, De Lacey LA, Ludwig R, Shleev S, Alcalde M (2013) Blood tolerant caccase by directed evolution. Chem Biol 20:223–231Zhang L, Carucci C, Reculusa S, Goudeau B, Lefrançois P, Gounel S, Mano N, Kuhn A (2019) Rational design of enzyme-modified electrodes for optimized bioelectrocatalytic activity. ChemElectroChem 6(19):4980–4984Arechederra MN, Addo PK, Minteer SD (2011) Poly(neutral red) as a NAD+ reduction catalyst and a NADH oxidation catalyst: towards the development of a rechargeable biobattery. Electrochim Acta 56:1585Yang Y, Wang ZL (2015) Hybrid energy cells for simultaneously harvesting multi-types of energies. NanoEnergy 14:245–256Hansen BJ, Liu Y, Yang R, Wang ZL (2010) Hybrid nanogenerator for concurrently harvesting biomechanical and biochemical energy. ACS Nano 4:3647Song K, Han JH,

Efficacy of Synaptic Inhibition Depends on Multiple, Dynamically Interacting Mechanisms Implicated in Chloride Homeostasis

Chloride homeostasis is a critical determinant of the strength and robustness of inhibition mediated by GABAA receptors (GABAARs). The impact of changes in steady state Cl− gradient is relatively straightforward to understand, but how dynamic interplay between Cl− influx, diffusion, extrusion and interaction with other ion species affects synaptic signaling remains uncertain. Here we used electrodiffusion modeling to investigate the nonlinear interactions between these processes. Results demonstrate that diffusion is crucial for redistributing intracellular Cl− load on a fast time scale, whereas Cl−extrusion controls steady state levels. Interaction between diffusion and extrusion can result in a somato-dendritic Cl− gradient even when KCC2 is distributed uniformly across the cell. Reducing KCC2 activity led to decreased efficacy of GABAAR-mediated inhibition, but increasing GABAAR input failed to fully compensate for this form of disinhibition because of activity-dependent accumulation of Cl−. Furthermore, if spiking persisted despite the presence of GABAAR input, Cl− accumulation became accelerated because of the large Cl− driving force that occurs during spikes. The resulting positive feedback loop caused catastrophic failure of inhibition. Simulations also revealed other feedback loops, such as competition between Cl− and pH regulation. Several model predictions were tested and confirmed by [Cl−]i imaging experiments. Our study has thus uncovered how Cl− regulation depends on a multiplicity of dynamically interacting mechanisms. Furthermore, the model revealed that enhancing KCC2 activity beyond normal levels did not negatively impact firing frequency or cause overt extracellular K− accumulation, demonstrating that enhancing KCC2 activity is a valid strategy for therapeutic intervention

Search for B_s --> mu+mu- and B_d --> mu+mu- Decays with CDF II

A search has been performed for B_s --> mu+mu- and B_d --> mu+mu- decays using 7/fb of integrated luminosity collected by the CDF II detector at the Fermilab Tevatron collider. The observed number of B_d candidates is consistent with background-only expectations and yields an upper limit on the branching fraction of BF(B_d-->mu+mu-) < 6.0E-9 at 95% confidence level. We observe an excess of B_s candidates. The probability that the background processes alone could produce such an excess or larger is 0.27%. The probability that the combination of background and the expected standard model rate of B_s --> mu+mu- could produce such an excess or larger is 1.9%. These data are used to determine BF(B_s-->mu+mu-) = (1.8^{+1.1}_{-0.9})E-8 and provide an upper limit of BF(B_s -->mu+mu-) < 4.0E-8 at 95% confidence level.Comment: 7 pages, 1 figure; version accepted by PR

Measurement of Energy Correlators inside Jets and Determination of the Strong Coupling Formula Presented

Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of $\sqrt{s}$=13 TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3 fb$^{−1}$. The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the Z boson mass: α$_S$ (m$_Z$)=0.1229 $\frac{0.0040}{-0.0050}$ , the most precise α$_S$m$_Z$ value obtained using jet substructure observable