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1

Andreula, C. F., A. M. N. Recchia-Luciani, A. Tarantino, V. Pavone, A. P. Garribba, R. De Blasi, and A. Carella. "I linfomi secondari del sistema nervoso centrale." Rivista di Neuroradiologia 7, no. 6 (December 1994): 883–93. http://dx.doi.org/10.1177/197140099400700605.

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Esponiamo i risultati della nostra esperienza nello studio dei linfomi secondari del SNC con la risonanza magnetica, in confronto con i dati disponibili in letteratura. In particolare, abbiamo analizzato i dati epidemiologici e l'eventuale ricaduta delle risultanze della RM sul protocollo diagnostico-terapeutico dei linfomi secondari. Inoltre, abbiamo tentato di identificare delle ipotesi di correlazione tra quadro anatomo-patologico e segnale RM. Nei 10 pazienti sono state individuate 20 lesioni, in 7 casi singole, in 3 multiple, queste ultime da un minimo di 2 a un massimo di 6. Complessivamente le lesioni sono risultate così distribuite: — 15 lesioni intrassiali, 5 delle quali singole, 3 multiple; 1 lesione intra-assiale aveva localizzazione midollare; — 5 lesioni extrassiali, di cui 3 meningo-durali e 2 leptomeningee, tutte singole. Nelle lesioni intrassiali in T1 la zona 1 è apparsa sostanzialmente isointensa (80%) e raramente ipero iso-iperintensa (20%). In T2 si è evidenziata una prevalente iperintensità (70%), raramente una isointensità (20%) o una ipointensità (10%). La zona 2 è risultata evidente nel 30% dei casi. L '80% delle lesioni ha mostrato un potenziamento dopo contrasto, in tutti i casi da moderato a marcato e di aspetto omogeneo. In nessun caso è stata evidenziata una diffusione subependimale. Nelle immagini tardive solo nel 10% dei casi si è osservato un aumento del grado di impregnazione e senza estensione alla zona 2. Le lesioni meningodurali, così come le leptomeningee, si presentano isointense in T1, male apprezzabili in T2, ma vengono rivelate dopo mdc dalla netta impregnazione. All'esame istologico, tali forme secondarie si sono rivelate eterogenee: 5 casi a grandi cellule, 1 a piccole cellule, 1 linfoblastico, 1 tipo Burkitt, 2 linfomi di Hodgkin. In un caso a presentazione contemporanea nel SNC ed in sede periferica, il riscontro istologico cerebrale (a grandi cellule), si è mostrato differente da quello bioptico linfonodale (a piccole cellule). È stata valutata infine la risposta al trattamento, in massima parte chemioterapico; in 2 pazienti questo è stato associato a radioterapia. Si è osservata una regressione o una riduzione volumetrica lesionale nel 50% dei casi, una progressione nel 30%, ed un reperto sostanzialmente invariato nel 20%. La durata minima di tali regressioni è stata di circa 2 mesi. Solo un paziente è attualmente in remissione completa dopo circa 12 mesi dalla regressione delle lesioni. L'esame RM ha confermato di possedere una elevatissima sensibilità alle ripetizioni secondarie dei linfomi a livello del SNC: il rilievo di una elevata frequenza di tali localizzazioni, comunque in misura inferiore a quanto segnalato nei lavori anatomopatologici, è da mettere in rapporto alla selezione delle forme linfomatose a più elevata malignità, forme nelle quali il contributo dell'esame di risonanza ci appare irrinunciabile, al punto di caldeggiarne l'introduzione nei protocolli diagnostici standard.
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2

Andreula, F. C., A. M. N. Recchia-Luciani, and L. Garofalo. "Linfomi del sistema nervoso centrale e Aids." Rivista di Neuroradiologia 10, no. 2_suppl (October 1997): 206. http://dx.doi.org/10.1177/19714009970100s292.

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I linfomi del sistema nervoso centrale, a lungo eteroplasie intracraniche rare (1–2%) sono in continuo aumento percentuale in relazione con l'immunodepressione virale dell' AIDS (6% dei pazienti, 3% in età pediatrica), così come con quella iatrogena. Tipiche dei linfomi AIDS l'associazione con l'EB virus, l'elevata malignità, la scarsa risposta alla terapia, la localizzazione (SNC, midollo, intestino, cute, anoretto). Oggi tali tumori sono riscontrati in tutte le età (60 anni è la decade di presentazione tipica negli immunocompetenti). Le forme intracraniche, soprattutto B (80%), sono l'1% dei Non-Hodgkin, e dovrebbero essere considerate in realtà secondarie, dal punto di vista fisiopatologico, anche nei casi in cui l'esordio riguardi il SNC. Dal 20 al 40% dei casi sono forme multiple. Il ruolo giocato dall'Imaging deve essere considerato importante, poiché, nonostante le frequenti recidive a breve termine (la sopravvivenza media dalla diagnosi supera di poco l'anno, ed è minore nell'AIDS), queste forme rispondono, quando correttamente inquadrate, assai bene alle alte dosi di cortisonici (nel 40% dei soggetti trattati, già in 24 ore, per linfolisi e ripristino della b.e.e.) così come alla radioterapia. Nella patogenesi sono invocati differenti meccanismi di interconnessione tra neoplasie e agenti virali. La sede preferenziale è sopratentoriale in regione dei nuclei della base o comunque in strutture in cui la componente prevalente è la sostanza bianca. L'estensione dell'edema è incongrua rispetto all'entità della lesione, in ragione della esigua neoangiogenesi indotta. Queste masse hanno margini relativamente ben definiti solo macroscopicamente, con ben maggiore infiltrazione all'istologia; foci di rammollimento necrotico o emorragico sono rari nei pazienti AIDS. All'istologia la zona centrale di cellularità elevata, più rarefatta in periferia, mostra un caratteristico aspetto a “bulbo di cipolla” della trama reticolare. Queste neoplasie si localizzano a livello degli “involucri” cerebrali: sedi caratteristiche sono infatti le leptomeningi e le aree lungo lo spazio subependimal (40–50%), aree di coinvolgimento rese manifeste dalla impregnazione del m.d.c. L'impregnazione lungo le pareti ventricolari suggerisce la diagnosi specie se le immagini RM rivelano l'ulteriore diffusione delle localizzazione leptomeningee lungo gli spazi perivascolari di Virchow Robin. Questi tumori metastatizzano per via ematica, determinando la comparsa di lesioni parenchimali, leptomeningee e meningo-durali. In sede meningo-durale un notevole infiltrato linfomatoso può assumere aspetto a lente biconvessa. Non esistono significative differenze di imaging tra forme linfomatose primitive e secondarie del S.N.C. La TC dimostra lesioni solide singole o multiple, rotondeggianti, isodense al parenchima, (nel 20% dei casi iperdense) con quasi costante accentuazione dopo m.d.c., raramente solo periferica. La RM dimostra isoiperintensità in T1, modesto incremento in DP e ipointensità rispetto alla grigia in T2, da scarso citoplasma delle cellule componenti. L'impregnazione è unicamente da alterazione della barriera emato-encefalica (scarsa la componente neovascolare).
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3

OASA, Sho. "Report; Single Protein Dynamics in Cellulo 2014." Seibutsu Butsuri 54, no. 5 (2014): 280–82. http://dx.doi.org/10.2142/biophys.54.280.

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4

O. H. Abdelwahed, O. H. Abdelwahed, and M. El-Sayed Wahed. "Optimizing Single Layer Cellular Neural Network Simulator using Simulated Annealing Technique with Neural Networks." Indian Journal of Applied Research 3, no. 6 (October 1, 2011): 91–94. http://dx.doi.org/10.15373/2249555x/june2013/31.

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5

Miller, W., N. Abrosimov, I. Rasin, and D. Borissova. "Cellular growth of single crystals." Journal of Crystal Growth 310, no. 7-9 (April 2008): 1405–9. http://dx.doi.org/10.1016/j.jcrysgro.2007.11.046.

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6

Aonuma, Yuki, Taiji Adachi, Mototsugu Tanaka, Masaki Hojo, Teruko Takano-Yamamoto, and Hiroshi Kamioka. "MECHANOSENSITIVITY OF A SINGLE OSTEOCYTE : DIFFERENCE IN CELL PROCESS AND CELL BODY(3A1 Cellular & Tissue Engineering & Biomaterials I)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S165. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s165.

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7

O. H. Abdelwahed, O. H. Abdelwahed, and M. El-Sayed Wahed. "Optimizing Single-Layer Raster Cellular Neural Network Simulator Using Simulated Annealing Technique and RK4(2), RK4(3) and RK 6(4)." International Journal of Scientific Research 2, no. 6 (June 1, 2012): 108–12. http://dx.doi.org/10.15373/22778179/june2013/35.

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8

Ge, Xiaohu, Meidong Huang, Jiaqi Chen, Hui Xu, Jing Xu, Wuxiong Zhang, and Yang Yang. "Wireless Single Cellular Coverage Boundary Models." IEEE Access 4 (2016): 3569–77. http://dx.doi.org/10.1109/access.2016.2582960.

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9

Lee, J., J. Y. Sul, and J. H. Eberwine. "Single Cell/Cellular Subregion-Targeted Phototransfection." Cold Spring Harbor Protocols 2014, no. 9 (September 1, 2014): pdb.prot072421. http://dx.doi.org/10.1101/pdb.prot072421.

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10

Leake, M. C. "Analytical tools for single-molecule fluorescence imaging in cellulo." Phys. Chem. Chem. Phys. 16, no. 25 (2014): 12635–47. http://dx.doi.org/10.1039/c4cp00219a.

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11

Teratani, Toshiaki, Suguru Kawato, and Yoshihiro Ohta. "1P395 An attempt at imaging of single functioning synaptosomes(15. Cellular signal transduction,Poster Session,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S245. http://dx.doi.org/10.2142/biophys.46.s245_3.

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12

Morikawa, Daisuke, and Yoshihiro Ohta. "1P398 Single Mitochondrion Imaging of Internal Membrane Structure Changes(15. Cellular signal transduction,Poster Session,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S246. http://dx.doi.org/10.2142/biophys.46.s246_2.

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13

Kaur, Haleena. "Cellular uptake of aptamer by Quantum Dots (QDs)." Biomarkers and Drug Discovery 1, no. 1 (November 5, 2018): 01. http://dx.doi.org/10.31579/2642-9799/004.

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Aptamers are short single stranded oligonucleotide sequences that exhibit high binding affinity and high specificity against their target molecule. Binding affinity and specificity are crucial features for aptamers in order to exploit their therapeutic and diagnostic potential and to make them an appealing candidate for the commercial market1,2. Aptamers contain functional moieties that can fold into different conformation such as hairpin stem and loops, G-quadruplexes, and pseudoknots. A study led by Dr Harleen Kaur involving unique stem-loop truncation strategy was employed to find the binding domain in a 66-mer long DNA aptamer sequence against the heparin binding domain of vascular endothelial growth factor (VEGF165) protein1. The results from the work demonstrated identification of a 26-mer long aptamer sequence referred as SL2-B in the paper with improvement in the binding affinity by more than 200-folds (Kd = 0.5nM) against VEGF protein. To improve the biostability of the aptamer in the biological fluids, the phosphorothioate linkages (PS-linkages) in the phosphate backbone of the DNA were introduced at the 5’-and 3’-termini of the obtained SL2-B aptamer sequence. The PS-modified SL2-B aptamer sequence demonstrated significant improvement in the stability without comprising
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14

Raddi, Gianmarco, Ana Beatriz F. Barletta, Mirjana Efremova, Jose Luis Ramirez, Rafael Cantera, Sarah A. Teichmann, Carolina Barillas-Mury, and Oliver Billker. "Mosquito cellular immunity at single-cell resolution." Science 369, no. 6507 (August 27, 2020): 1128–32. http://dx.doi.org/10.1126/science.abc0322.

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Hemocytes limit the capacity of mosquitoes to transmit human pathogens. Here we profile the transcriptomes of 8506 hemocytes of Anopheles gambiae and Aedes aegypti mosquito vectors. Our data reveal the functional diversity of hemocytes, with different subtypes of granulocytes expressing distinct and evolutionarily conserved subsets of effector genes. A previously unidentified cell type in An. gambiae, which we term “megacyte,” is defined by a specific transmembrane protein marker (TM7318) and high expression of lipopolysaccharide-induced tumor necrosis factor–α transcription factor 3 (LL3). Knockdown experiments indicate that LL3 mediates hemocyte differentiation during immune priming. We identify and validate two main hemocyte lineages and find evidence of proliferating granulocyte populations. This atlas of medically relevant invertebrate immune cells at single-cell resolution identifies cellular events that underpin mosquito immunity to malaria infection.
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15

Coskun, Ahmet F., Umut Eser, and Saiful Islam. "Cellular identity at the single-cell level." Molecular BioSystems 12, no. 10 (2016): 2965–79. http://dx.doi.org/10.1039/c6mb00388e.

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16

Sasvári, Márton, and János Kertész. "Cellular automata models of single-lane traffic." Physical Review E 56, no. 4 (October 1, 1997): 4104–10. http://dx.doi.org/10.1103/physreve.56.4104.

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17

Yamamura, Shohei, Hiroyuki Kishi, Yoshiharu Tokimitsu, Sachiko Kondo, Ritsu Honda, Sathuluri Ramachandra Rao, Masahiro Omori, Eiichi Tamiya, and Atsushi Muraguchi. "Single-Cell Microarray for Analyzing Cellular Response." Analytical Chemistry 77, no. 24 (December 2005): 8050–56. http://dx.doi.org/10.1021/ac0515632.

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18

Afrin, Rehana, Masakazu Saito, Takahiro Watanabe-Nakayama, and Atsushi Ikai. "Membrane wound healing at single cellular level." Nanomedicine: Nanotechnology, Biology and Medicine 13, no. 7 (October 2017): 2351–57. http://dx.doi.org/10.1016/j.nano.2017.07.011.

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19

Pereyra, Victor, Andrey Milchev, and Victor Fleurov. "Diffusion of single particles in cellular media." Physical Review E 50, no. 6 (December 1, 1994): 4636–45. http://dx.doi.org/10.1103/physreve.50.4636.

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20

Szynka, Jerzy, and Zbigniew Poznański. "Cellular system based on single-chip-microcomputers." Microprocessing and Microprogramming 16, no. 4-5 (November 1985): 301–4. http://dx.doi.org/10.1016/0165-6074(85)90019-5.

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21

Li, Min, and Robbyn K. Anand. "Cellular dielectrophoresis coupled with single-cell analysis." Analytical and Bioanalytical Chemistry 410, no. 10 (February 23, 2018): 2499–515. http://dx.doi.org/10.1007/s00216-018-0896-y.

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22

Chakraborty, Bidesh, Mamata Dalui, and Biplab K. Sikdar. "Synthesis of Scalable Single Length Cycle, Single Attractor Cellular Automata in Linear Time." Complex Systems 30, no. 3 (September 15, 2021): 415–39. http://dx.doi.org/10.25088/complexsystems.30.3.415.

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This paper proposes the synthesis of single length cycle, single attractor cellular automata (SACAs) for arbitrary length. The n-cell single length cycle, single attractor cellular automaton (SACA), synthesized in linear time O(n), generates a pattern and finally settles to a point state called the single length cycle attractor state. An analytical framework is developed around the graph-based tool referred to as the next state transition diagram to explore the properties of SACA rules for three-neighborhood, one-dimensional cellular automata. This enables synthesis of an (n+1)-cell SACA from the available configuration of an n-cell SACA in constant time and an (n+m)-cell SACA from the available configuration of n-cell and m-cell SACAs also in constant time.
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23

Hurd, Lyman P., Jarkko Kari, and Karel Culik. "The topological entropy of cellular automata is uncomputable." Ergodic Theory and Dynamical Systems 12, no. 2 (June 1992): 255–65. http://dx.doi.org/10.1017/s0143385700006738.

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AbstractThere is no algorithm which will take a description of a celluar automaton and determine whether it has zero topological entropy, or for any fixed ε > 0 compute its topological entropy to a tolerance e. Furthermore a set of aperiodic Wang tiles arising from Penrose's kite and dart tiles is used to demonstrate specific examples of cellular automata with a single periodic point but non-trivial non-wandering sets, which furthermore can be constructed to have arbitrarily high topological entropy.
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24

Cheow, Lih Feng, Elise T. Courtois, Yuliana Tan, Ramya Viswanathan, Qiaorui Xing, Rui Zhen Tan, Daniel S. W. Tan, et al. "Single-cell multimodal profiling reveals cellular epigenetic heterogeneity." Nature Methods 13, no. 10 (August 15, 2016): 833–36. http://dx.doi.org/10.1038/nmeth.3961.

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25

Peters, Reiner. "Single-Molecule Fluorescence Analysis of Cellular Nanomachinery Components." Annual Review of Biophysics and Biomolecular Structure 36, no. 1 (June 2007): 371–94. http://dx.doi.org/10.1146/annurev.biophys.36.040306.132715.

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26

Willaert, Ronnie G., Pieterjan Vanden Boer, Anton Malovichko, Mitchel Alioscha-Perez, Ksenija Radotić, Dragana Bartolić, Aleksandar Kalauzi, et al. "Single yeast cell nanomotions correlate with cellular activity." Science Advances 6, no. 26 (June 2020): eaba3139. http://dx.doi.org/10.1126/sciadv.aba3139.

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Living single yeast cells show a specific cellular motion at the nanometer scale with a magnitude that is proportional to the cellular activity of the cell. We characterized this cellular nanomotion pattern of nonattached single yeast cells using classical optical microscopy. The distribution of the cellular displacements over a short time period is distinct from random motion. The range and shape of such nanomotion displacement distributions change substantially according to the metabolic state of the cell. The analysis of the nanomotion frequency pattern demonstrated that single living yeast cells oscillate at relatively low frequencies of around 2 hertz. The simplicity of the technique should open the way to numerous applications among which antifungal susceptibility tests seem the most straightforward.
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27

Larson, Joshua D., Margaret L. Rodgers, and Aaron A. Hoskins. "Visualizing cellular machines with colocalization single molecule microscopy." Chem. Soc. Rev. 43, no. 4 (2014): 1189–200. http://dx.doi.org/10.1039/c3cs60208g.

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28

Mohanty, Samarendra K., Khyati S. Mohanty, and Michael W. Berns. "Single-Fiber Optical Tweezers for Cellular Micro-Manipulation." Optics and Photonics News 19, no. 12 (December 1, 2008): 42. http://dx.doi.org/10.1364/opn.19.12.000042.

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29

Pick, Horst, Evelyne L. Schmid, Ana-Paula Tairi, Erwin Ilegems, Ruud Hovius, and Horst Vogel. "Investigating Cellular Signaling Reactions in Single Attoliter Vesicles." Journal of the American Chemical Society 127, no. 9 (March 2005): 2908–12. http://dx.doi.org/10.1021/ja044605x.

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30

NELSON, A. J., and S. T. HESS. "Localization microscopy: mapping cellular dynamics with single molecules." Journal of Microscopy 254, no. 1 (February 25, 2014): 1–8. http://dx.doi.org/10.1111/jmi.12115.

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31

Hovestadt, Volker, Kyle S. Smith, Laure Bihannic, Mariella G. Filbin, McKenzie L. Shaw, Alicia Baumgartner, John C. DeWitt, et al. "Resolving medulloblastoma cellular architecture by single-cell genomics." Nature 572, no. 7767 (July 24, 2019): 74–79. http://dx.doi.org/10.1038/s41586-019-1434-6.

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32

Shapiro, E. M., S. Skrtic, K. Sharer, J. M. Hill, C. E. Dunbar, and A. P. Koretsky. "MRI detection of single particles for cellular imaging." Proceedings of the National Academy of Sciences 101, no. 30 (July 15, 2004): 10901–6. http://dx.doi.org/10.1073/pnas.0403918101.

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33

Kröger, A. Pia P., Muhabbat I. Komil, Naomi M. Hamelmann, Alberto Juan, Martina H. Stenzel, and Jos M. J. Paulusse. "Glucose Single-Chain Polymer Nanoparticles for Cellular Targeting." ACS Macro Letters 8, no. 1 (December 18, 2018): 95–101. http://dx.doi.org/10.1021/acsmacrolett.8b00812.

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34

Wu, Nan-Jian, Noboru Asahi, and Yoshihito Amemiya. "Cellular-Automaton Circuits Using Single-Electron-Tunneling Junctions." Japanese Journal of Applied Physics 36, Part 1, No. 5A (May 15, 1997): 2621–27. http://dx.doi.org/10.1143/jjap.36.2621.

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35

Zhi Ding and Ge Li. "Single-channel blind equalization for GSM cellular systems." IEEE Journal on Selected Areas in Communications 16, no. 8 (1998): 1493–505. http://dx.doi.org/10.1109/49.730456.

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36

Busch, Sebastian, and Hiromu Tanimoto. "Cellular configuration of single octopamine neurons in Drosophila." Journal of Comparative Neurology 518, no. 12 (January 20, 2010): 2355–64. http://dx.doi.org/10.1002/cne.22337.

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37

Bendall, Sean C., El-ad D. Amir, Michelle Tadmor, Kara L. Davis, Erin F. Simonds, Daniel Shenfeld, Jacob Levine, Garry P. Nolan, and Dana Pe'er. "Dimensionality Reduction Reveals Distinct Shapes of Normal and Malignant Hematopoietic Cell Populations." Blood 120, no. 21 (November 16, 2012): 1451. http://dx.doi.org/10.1182/blood.v120.21.1451.1451.

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Abstract Abstract 1451 Simultaneously examining multiple epitopes in single cells has become increasingly useful as improvements are made to multi-parametric flow techniques. Increased parameterization has enabled subdivision of functionally distinct cell populations based on an increasing variety of physiological attributes. It has not only helped better define the landscape of “normal” hematopoiesis, but also has been clinically applied in detection of minimal residual disease (MRD) in hematopoietic malignancies. Detection of rare “abnormal” cells is the crux of MRD-based risk stratification where sporadic residual cancer cells are identified through multi-parameter flow cytometry. Current methods for the detection and characterization of cellular populations are generally reliant on manual examination and targeted gating techniques. This approach relies almost entirely on prior knowledge and leaves little room for discovery of novel populations. As the number of parameter per cell increases there is a rising need for dimensionality reduction (DR) methods to resolve high dimensional data “down” into a human-interpretable space. Classical DR, such as principle component analysis (PCA), fail to address the non-linear relationships in cellular phenotypes while newer approaches, such as spanning-tree progression of density normalized events (SPADE), have an inherent level of stochasticity that might adversely affect the robust separation of cellular phenotypes (i.e. discriminating healthy vs. diseased cells). Here, we present a novel algorithm that identifies and characterizes distinct cell populations, preserving the high dimensional information, but providing an interpretable visualization of their phenotypic relationships. This approach was applied to a cohort of normal human bone marrow (BM) specimens to discern a landscape of normal hematopoietic phenotypes. We then contrasted this to overlays of human leukemic bone marrow aspirates (AML and ALL) to understand the extent to which cancer corrupts the shape and form of the landscape. We illustrate the application for automated MRD detection in human leukemia (Figure 1). Method: Our approach, CellSNE, is an adaptation of t-Distributed Stochastic Neighbor Embedding (t-SNE), a non-linear dimensionality reduction algorithm. CellSNE finds a low dimensional mapping of cells that preserves their pairwise distances in a high dimensional space. A distance between each cell to every other cell in the dataset is calculated, based on a vector defined by the combined values of cellular parameters measure. An optimization algorithm then searches for a projection of the points into 2D, in such a way that maximizes the similarity in pairwise distances between the high-dimensional and two dimensional spaces. The resulting 2D projection organizes the sample into subpopulations that conserve the shape and relative distances between each cell. Results/Conclusion: Application of CellSNE to healthy BM clearly separated cells based on their known immune subtype and was confirmed by manual analysis (Figure 1A). The results are robust across data collected from different individuals on different days as well as in analyses conducted using low numbers of single cell parameters, suggesting that healthy BM generally maintains the same cellular population characteristics (or “shape”) across samples. When applied to leukemic BM from patients with AML and ALL CellSNE demonstrates a unique cancer landscape (“shape”) for each patient that is dramatically different from normal (Figure 1B). It is critical to note that despite the overwhelming infiltration by cancer cells, rare “normal” cell populations can still be discerned in the ALL BM. CellSNE succeeded in automatically identifying rare (<1%) abnormal ALL cells (tracked using a CellSNE independent parameter) in an otherwise normal BM (Figure 1C). As such, CellSNE achieves in identifying and characterizing rare cellular populations that can be applied in both normal and malignant hematopoiesis. Thus, it provides opportunities for the automated analysis of both large cytometry datasets and clinical MRD detection. Disclosures: No relevant conflicts of interest to declare.
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38

Das, Alvin S., and Wen-Quan Zou. "Prions: Beyond a Single Protein." Clinical Microbiology Reviews 29, no. 3 (May 25, 2016): 633–58. http://dx.doi.org/10.1128/cmr.00046-15.

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SUMMARYSince the term protein was first coined in 1838 and protein was discovered to be the essential component of fibrin and albumin, all cellular proteins were presumed to play beneficial roles in plants and mammals. However, in 1967, Griffith proposed that proteins could be infectious pathogens and postulated their involvement in scrapie, a universally fatal transmissible spongiform encephalopathy in goats and sheep. Nevertheless, this novel hypothesis had not been evidenced until 1982, when Prusiner and coworkers purified infectious particles from scrapie-infected hamster brains and demonstrated that they consisted of a specific protein that he called a “prion.” Unprecedentedly, the infectious prion pathogen is actually derived from its endogenous cellular form in the central nervous system. Unlike other infectious agents, such as bacteria, viruses, and fungi, prions do not contain genetic materials such as DNA or RNA. The unique traits and genetic information of prions are believed to be encoded within the conformational structure and posttranslational modifications of the proteins. Remarkably, prion-like behavior has been recently observed in other cellular proteins—not only in pathogenic roles but also serving physiological functions. The significance of these fascinating developments in prion biology is far beyond the scope of a single cellular protein and its related disease.
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39

Durmus, Naside Gozde, H. Cumhur Tekin, Sinan Guven, Kaushik Sridhar, Ahu Arslan Yildiz, Gizem Calibasi, Ionita Ghiran, Ronald W. Davis, Lars M. Steinmetz, and Utkan Demirci. "Magnetic levitation of single cells." Proceedings of the National Academy of Sciences 112, no. 28 (June 29, 2015): E3661—E3668. http://dx.doi.org/10.1073/pnas.1509250112.

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Several cellular events cause permanent or transient changes in inherent magnetic and density properties of cells. Characterizing these changes in cell populations is crucial to understand cellular heterogeneity in cancer, immune response, infectious diseases, drug resistance, and evolution. Although magnetic levitation has previously been used for macroscale objects, its use in life sciences has been hindered by the inability to levitate microscale objects and by the toxicity of metal salts previously applied for levitation. Here, we use magnetic levitation principles for biological characterization and monitoring of cells and cellular events. We demonstrate that each cell type (i.e., cancer, blood, bacteria, and yeast) has a characteristic levitation profile, which we distinguish at an unprecedented resolution of 1 × 10−4g⋅mL−1. We have identified unique differences in levitation and density blueprints between breast, esophageal, colorectal, and nonsmall cell lung cancer cell lines, as well as heterogeneity within these seemingly homogenous cell populations. Furthermore, we demonstrate that changes in cellular density and levitation profiles can be monitored in real time at single-cell resolution, allowing quantification of heterogeneous temporal responses of each cell to environmental stressors. These data establish density as a powerful biomarker for investigating living systems and their responses. Thereby, our method enables rapid, density-based imaging and profiling of single cells with intriguing applications, such as label-free identification and monitoring of heterogeneous biological changes under various physiological conditions, including antibiotic or cancer treatment in personalized medicine.
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40

Mayer, Simone, Shokoufeh Khakipoor, Maxim A. Drömer, and Daniel A. Cozetto. "Single-cell RNA-Sequencing in Neuroscience." Neuroforum 25, no. 4 (November 26, 2019): 251–58. http://dx.doi.org/10.1515/nf-2019-0021.

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Summary Technical innovations in the last decade have allowed to sequence transcriptomes of single cells. Single-cell RNA-sequencing (scRNA-seq) has since then opened the window to a deeper understanding of cellular identity and is becoming a widely used method in molecular biology. In neuroscience, scRNA-seq has broad applications, for example in determining cellular diversity in different brain regions and in revealing transcriptomic variations across brain disorders. The method consists of several steps: isolation and lysis of single cells, reverse transcription of RNAs, amplification of cDNAs, and next-generation sequencing. The large datasets can subsequently be analysed using different bioinformatic tools to deduce biological meaning. Current developments aim to integrate scRNA-seq into cellular network analysis through multimodal analysis, spatial localisation and perturbation experiments, in order to understand brain physiology and pathology.
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41

Sun, Yujie. "Single molecule study of cytoskeleton and membrane dynamics." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C108. http://dx.doi.org/10.1107/s205327331409891x.

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Molecular motors are proteins that convert chemical energy directly into mechanical work in the cell, driving many cellular processes. Given their intrinsic unsynchronous nature, single molecule fluorescence and manipulation techniques are nearly the ultimate tools to understand the mechanisms of molecular motors. I will talk about single molecule fluorescence studies of cytoskeleton associated motors, and their roles in cellular trafficking and membrane shaping of intra-cellular structures.
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42

Redmond, Robert W., and Irene E. Kochevar. "Spatially Resolved Cellular Responses to Singlet Oxygen." Photochemistry and Photobiology 82, no. 5 (2006): 1178. http://dx.doi.org/10.1562/2006-04-14-ir-874.

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43

Ravanat, Jean-Luc, Paolo Di Mascio, Glaucia R. Martinez, Marisa H. G. Medeiros, and Jean Cadet. "Singlet Oxygen Induces Oxidation of Cellular DNA." Journal of Biological Chemistry 275, no. 51 (September 27, 2000): 40601–4. http://dx.doi.org/10.1074/jbc.m006681200.

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44

Ravanat, Jean-Luc, Paolo Di Mascio, Glaucia R. Martinez, MarisaH G. Medeiros, and Jean Cadet. "Singlet oxygen induces oxidation of cellular DNA." Journal of Biological Chemistry 276, no. 8 (February 2001): 6056. http://dx.doi.org/10.1016/s0021-9258(19)46360-6.

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45

Nie, L., A. C. Nusantara, V. G. Damle, R. Sharmin, E. P. P. Evans, S. R. Hemelaar, K. J. van der Laan, et al. "Quantum monitoring of cellular metabolic activities in single mitochondria." Science Advances 7, no. 21 (May 2021): eabf0573. http://dx.doi.org/10.1126/sciadv.abf0573.

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Free radicals play a vital role in all kinds of biological processes including immune responses. However, free radicals have short lifetimes and are highly reactive, making them difficult to measure using current methods. Here, we demonstrate that relaxometry measurement, or T1, inherited from the field of diamond magnetometry can be used to detect free radicals in living cells with subcellular resolution. This quantum sensing technique is based on defects in diamond, which convert a magnetic signal into an optical signal, allowing nanoscale magnetic resonance measurements. We functionalized fluorescent nanodiamonds (FNDs) to target single mitochondria within macrophage cells to detect the metabolic activity. In addition, we performed measurements on single isolated mitochondria. We were able to detect free radicals generated by individual mitochondria in either living cells or isolated mitochondria after stimulation or inhibition.
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46

Senavirathna, Lakmini, Cheng Ma, Ru Chen, and Sheng Pan. "Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity." Cells 11, no. 15 (August 7, 2022): 2450. http://dx.doi.org/10.3390/cells11152450.

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Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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47

Shojaee, Abbas, Michelle Saavedra, and Shao-shan Carol Huang. "Potentials of single-cell genomics in deciphering cellular phenotypes." Current Opinion in Plant Biology 63 (October 2021): 102059. http://dx.doi.org/10.1016/j.pbi.2021.102059.

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48

Nyyssölä, Antti, Anniina Suhonen, Anneli Ritala, and Kirsi-Marja Oksman-Caldentey. "The role of single cell protein in cellular agriculture." Current Opinion in Biotechnology 75 (June 2022): 102686. http://dx.doi.org/10.1016/j.copbio.2022.102686.

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49

Yanagida, Toshio. "Single molecule imaging of dynamic molecular and cellular systems." Seibutsu Butsuri 43, supplement (2003): S16. http://dx.doi.org/10.2142/biophys.43.s16_2.

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50

Antonelli, A., S. Serafini, M. Menotta, C. Sfara, F. Pierigé, L. Giorgi, G. Ambrosi, L. Rossi, and M. Magnani. "Improved cellular uptake of functionalized single-walled carbon nanotubes." Nanotechnology 21, no. 42 (September 22, 2010): 425101. http://dx.doi.org/10.1088/0957-4484/21/42/425101.

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