Table of Contents  
EDUCATIONAL FORUM
Year : 2013  |  Volume : 4  |  Issue : 4  |  Page : 303-306  

How to calculate sample size in animal studies?


Department of Pharmacology, GMERS Medical College, Patan, Government Medical College, Surat, Gujarat, India

Date of Web Publication10-Oct-2013

Correspondence Address:
Jaykaran Charan
Department of Pharmacology, Government Medical College, Surat, Gujarat
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0976-500X.119726

Rights and Permissions
   Abstract 

Calculation of sample size is one of the important component of design of any research including animal studies. If a researcher select less number of animals it may lead to missing of any significant difference even if it exist in population and if more number of animals selected then it may lead to unnecessary wastage of resources and may lead to ethical issues. In this article, on the basis of review of literature done by us we suggested few methods of sample size calculations for animal studies.

Keywords: Alpha error, animal studies, power, sample size


How to cite this article:
Charan J, Kantharia N D. How to calculate sample size in animal studies?. J Pharmacol Pharmacother 2013;4:303-6

How to cite this URL:
Charan J, Kantharia N D. How to calculate sample size in animal studies?. J Pharmacol Pharmacother [serial online] 2013 [cited 2017 Apr 28];4:303-6. Available from: http://www.jpharmacol.com/text.asp?2013/4/4/303/119726

How many animals I should use for my study? This is one of the most confusing questions faced by a researcher. Too small sample size can miss the real effect in experiment and too large sample size will lead to unnecessary wasting of the resources and animals. [1] Issue of sample size has been highlighted adequately for the clinical trials and clinical studies, but not explored much in the case of animal studies in published literature. It is very important to teach young researchers and post-graduate students regarding importance and methods of sample size calculation. To clarify this issue of sample size in animal studies, we decided to search various articles available regarding the sample size in animal studies. We did PubMed search by using various MeSH terms such as "sample size," "sample size calculations," "animal studies" etc., and their combinations. We have also searched various articles through Google and Google Scholar. We have also searched various websites related to animal research (http://www. 3rs-reduction.co.uk/html/6__power_and_sample_size.html, http://www.acuc.berkeley.edu/, http://www.bu.edu/orccommittees/iacuc/policies- and-guidelines/sample-size-calculations/, http://www.ucd.ie/researchethics/etc.). First author read all available literature and an understanding about the concept is made in consultation with the second author. Here, we are explaining briefly about the method of sample size calculations in animal studies based on review of the literature carried out by us.

Basically, there are two methods of sample size calculation in animal studies. The most favored and most scientific method is calculation of sample size by power analysis. [2] Every effort should be carried out to calculate sample size by this method. This method is similar to the method used for calculation of sample size for clinical trials and clinical studies. Simple calculation can be carried out manually with the help of some formula [Appendix 1], but for complex calculations statistical software can be used or help from a statistician can be sought. To calculate the sample size by power analysis a researcher must have knowledge and information about these concepts:

  • Effect size: This is the difference between the mean of two groups (quantitative data) or proportions of events in two groups (qualitative data). A researcher should decide before the start of the study that how much minimum difference between two groups can be considered as clinically significant. The idea about clinically significant difference between the groups should be taken preferably from previously published studies [2],[3],[4],[5]
  • Standard deviation: Standard deviation measures variability within the sample. Information about standard deviation is needed only in the case of quantitative variables. Information about the standard deviation of a particular variable can be taken from previously published studies. If no such study is available then author should conduct a pilot study first and standard deviation can be calculated from the pilot study [2],[3],[4],[5]
  • Type 1 error: This is measured by significance level, which is usually fixed at the level of 5% (P = 0.05). This is an arbitrary value and can be decreased or increased according to the research question [2],[3],[4],[5]
  • Power: Power of a study is probability of finding an effect, which the study is aimed to find. This may be kept between 80% to even 99% depending on research question, but usually, it is kept at 80% [2],[3],[4],[5]
  • Direction of effect (one tailed or two tailed): When a researcher wants to explore the effect of some intervention, the actual effect observed in sample may be in same direction as researcher thought or it may be just opposite to that. If researcher feels that effect may be in both directions then he should use two tailed test and if he has strong reason to believe for the effect to lie in one direction then he can use one tailed test. In animal research, two tailed tests are usually used [2]
  • Statistical tests: For sample size calculation, it is important to have an idea about statistical test, which is to be applied on data. For simple statistical tests such as Students t-test or Chi-square test, manual calculation based on formula can be carried out [Appendix], but for complex tests like ANOVA or non-parametric tests help of statistician or use of software is needed [2],[4]
  • Expected attrition or death of animals: Final sample size should be adjusted for expected attrition. Suppose a researcher is expecting 10% attrition then the sample size calculated by formula or software should be divided by 0.9 to get actual sample size. Suppose sample size calculated by software is 10 animals per group and researcher is expecting 10% attrition then his final sample size will be 11 animals per group (10/0.9 = 11.11). Similarly, for 20% attrition sample size should be divided by 0.8. [5] This can be explained in the form of structured formula i.e.,
Corrected sample size = Sample size/ (1− [% attrition/100])

We suggest use of freely downloadable software G Power (Faul, Erdfelder, Lang and Buchner, 2007) for sample size calculation. This software is equally good for sample size calculation for clinical trials also. This software can be used for simple as well as complex sample size calculations. [6] G Power can calculate sample size based on pre-designed effect size at small, medium, and large difference between the groups based on Cohen's principles. [7] Information about other freely available software and calculators for sample size calculation is given in Appendix 2. More complex sample size will need more sophisticated software such as "nQuery advisor" or "MINITAB."

Second method of calculation is a crude method based on law of diminishing return. This method is called "resource equation" method. [2],[8],[9] This method is used when it is not possible to assume about effect size, to get an idea about standard deviation as no previous findings are available or when multiple endpoints are measured or complex statistical procedure is used for analysis. This method can also be used in some exploratory studies where testing of hypothesis is not the primary aim, but researcher is interested only in finding any level of difference between groups.

According to this method a value "E" is measured, which is nothing but the degree of freedom of analysis of variance (ANOVA). The value of E should lie between 10 and 20. If E is less than 10 then adding more animals will increase the chance of getting more significant result, but if it is more than 20 then adding more animals will not increase the chance of getting significant results. Though, this method is based on ANOVA, it is applicable to all animal experiments. Any sample size, which keeps E between 10 and 20 should be considered as an adequate. E can be measured by following formula:

E = Total number of animals − Total number of groups

Suppose a researcher wants to see the effect of a drug and he made five groups (one group as control and four groups of different doses of that drug) with 10 rats each. In this case E will be

E = (10 × 5) − 5

E = 50 − 5 = 45, which is more than 20 hence sample size in this experiment is more than necessary. However, if sample size is five per group then E will be 20, which is the acceptable limit and hence can be considered as adequate sample size.

This method is easy, but it cannot be considered as robust as power analysis method.

We want to suggest researchers to include a statement about method of calculation of sample size and justification of sample size in the manuscript they want to publish. Animals in research: Reporting in vivo experiments guideline recommends inclusion of a statement mentioning justification of the sample size used in research and detail of method of calculation of sample size. [10] All components of sample size calculation such as effect size, type 1 and type 2 error, one tailed/two tailed test, standard deviation etc., should be reported in manuscript sent for publication the way it is suggested for the clinical research. [11] Shortage of resources (budget, manpower), time constrain etc., cannot be considered as valid justification regarding decision of sample size. Many researchers consider six animals per group as adequate sample size, but after reviewing available literature on this issue we came to a conclusion that this notion of six animals per group has little scientific and statistical basis. This is a brief description and readers are requested to read more resources available for better understanding of various concepts related to the sample size calculation in animal studies.


   Acknowledgment Top


We want to acknowledge unknown reviewer for constructive comments and guidance for improvisation of this manuscript.





 
   References Top

1.Fitts DA. Ethics and animal numbers: Informal analyses, uncertain sample sizes, inefficient replications, and type I errors. J Am Assoc Lab Anim Sci 2011;50:445-53.  Back to cited text no. 1
    
2.Festing MF, Altman DG. Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR J 2002;43:244-58.  Back to cited text no. 2
    
3.Lenth RV. Some practical guidelines for effective sample size determination. Am Stat 2001;55:187-93.  Back to cited text no. 3
    
4.Jones SR, Carley S, Harrison M. An introduction to power and sample size estimation. Emerg Med J 2003;20:453-8.  Back to cited text no. 4
    
5.Naduvilath TJ, John RK, Dandona L. Sample size for ophthalmology studies. Indian J Ophthalmol 2000;48:245-50.  Back to cited text no. 5
[PUBMED]  Medknow Journal  
6.Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175-91.  Back to cited text no. 6
    
7.Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2 nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1988.  Back to cited text no. 7
    
8.National centre for replacement, refinement, and reduction animals in research. Experimental design/statistics. [about 2 screen] Available from: http://www.nc3rs.org.uk/category.asp?catID=7 [Last cited on 2012 Nov 02].  Back to cited text no. 8
    
9.Festing MF. Design and statistical methods in studies using animal models of development. ILAR J 2006;47:5-14.  Back to cited text no. 9
    
10.Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. Improving bioscience research reporting: The ARRIVE guidelines for reporting animal research. J Pharmacol Pharmacother 2010;1:94-9.  Back to cited text no. 10
[PUBMED]  Medknow Journal  
11.Jaykaran P, Yadav N, Chavda, Kantharia ND. Some issues related to the reporting of statistics in clinical trials published in Indian Medical Journals: A survey. Int J Pharmacol 2010;6:354-9.  Back to cited text no. 11
    



This article has been cited by
1 Intermittent hypoxia causes mandibular growth retardation and macroglossia in growing rats
Jun Hosomichi,Yo-ichiro Kuma,Shuji Oishi,Hisashi Nagai,Hideyuki Maeda,Risa Usumi-Fujita,Yasuhiro Shimizu,Sawa Kaneko,Chisa Shitano,Jun-ichi Suzuki,Ken-ichi Yoshida,Takashi Ono
American Journal of Orthodontics and Dentofacial Orthopedics. 2017; 151(2): 363
[Pubmed] | [DOI]
2 Effect of amitriptyline treatment on neurofilament-H protein in an experimental model of depression
Maria Domenica Sanna,Carla Ghelardini,Nicoletta Galeotti
Brain Research Bulletin. 2017; 128: 1
[Pubmed] | [DOI]
3 Differential effects of total and partial sleep deprivation on salivary factors in Wistar rats
Dr. T.J. Lasisi,S.T. Shittu,C.C. Meludu,A.A. Salami
Archives of Oral Biology. 2017; 73: 100
[Pubmed] | [DOI]
4 Behavioural phenotype of histamine H4 receptor knockout mice: Focus on central neuronal functions
Maria Domenica Sanna,Carla Ghelardini,Robin L. Thurmond,Emanuela Masini,Nicoletta Galeotti
Neuropharmacology. 2017; 114: 48
[Pubmed] | [DOI]
5 Biphasic calcium phosphates bioceramics (HA/TCP): Concept, physicochemical properties and the impact of standardization of study protocols in biomaterials research
Mehdi Ebrahimi,Michael G. Botelho,Sergey V. Dorozhkin
Materials Science and Engineering: C. 2017; 71: 1293
[Pubmed] | [DOI]
6 Naringin improves zidovudine- and stavudine-induced skeletal muscle complications in rats
OO Adebiyi,OA Adebiyi,PMO Owira
Human & Experimental Toxicology. 2017; 36(1): 93
[Pubmed] | [DOI]
7 Detecting intratumoral heterogeneity of EGFR activity by liposome-based in vivo transfection of a fluorescent biosensor
G Weitsman,N J Mitchell,R Evans,A Cheung,T L Kalber,R Bofinger,G O Fruhwirth,M Keppler,Z V F Wright,P R Barber,P Gordon,T de Koning,W Wulaningsih,K Sander,B Vojnovic,S Ameer-Beg,M Lythgoe,J N Arnold,E Årstad,F Festy,H C Hailes,A B Tabor,T Ng
Oncogene. 2017;
[Pubmed] | [DOI]
8 Low-intensity (400 mW/cm2, 500 kHz) pulsed transcranial ultrasound preconditioning may mitigate focal cerebral ischemia in rats
Hangdao Li,Junfeng Sun,Daqu Zhang,Daryl Omire-Mayor,Peter A. Lewin,Shanbao Tong
Brain Stimulation. 2017;
[Pubmed] | [DOI]
9 Bisperoxovandium (pyridin-2-squaramide) targets both PTEN and ERK1/2 to confer neuroprotection
Zhi-Feng Zhang,Juan Chen,Xin Han,Ya Zhang,Hua-Bao Liao,Rui-Xue Lei,Yang Zhuang,Ze-Fen Wang,Zhiqiang Li,Jin-Cao Chen,Wei-Jing Liao,Hai-Bing Zhou,Fang Liu,Qi Wan
British Journal of Pharmacology. 2017;
[Pubmed] | [DOI]
10 A Lipid Emulsion Reverses Toxic-Dose Bupivacaine-Induced Vasodilation during Tyrosine Phosphorylation-Evoked Contraction in Isolated Rat Aortae
Seong-Ho Ok,Soo Lee,Seong-Chun Kwon,Mun Choi,Il-Woo Shin,Sebin Kang,Miyeong Park,Jeong-Min Hong,Ju-Tae Sohn
International Journal of Molecular Sciences. 2017; 18(2): 394
[Pubmed] | [DOI]
11 Protective effect of quinacrine against glycerol-induced acute kidney injury in rats
Abdulrahman K. Al Asmari,Khalid Tariq Al Sadoon,Ali Ahmed Obaid,Deivakadatcham Yesunayagam,Mohammad Tariq
BMC Nephrology. 2017; 18(1)
[Pubmed] | [DOI]
12 Effects of platelet-rich plasma against experimental ischemia/reperfusion injury in rat testis
C.A. Sekerci,Y. Tanidir,T.E. Sener,G. Sener,O. Cevik,A. Yarat,B. Alev-Tuzuner,S. Cetinel,E. Kervancioglu,A. Sahan,C. Akbal
Journal of Pediatric Urology. 2017;
[Pubmed] | [DOI]
13 Effects of paclitaxel on the development of neuropathy and affective behaviors in the mouse
Wisam Toma,S. Lauren Kyte,Deniz Bagdas,Yasmin Alkhlaif,Shakir D. Alsharari,Aron H. Lichtman,Zhi-Jian Chen,Egidio Del Fabbro,John W. Bigbee,David A. Gewirtz,M. Imad Damaj
Neuropharmacology. 2017; 117: 305
[Pubmed] | [DOI]
14 Central inhibitory effects on feeding induced by the adipo-myokine irisin
Claudio Ferrante,Giustino Orlando,Lucia Recinella,Sheila Leone,Annalisa Chiavaroli,Chiara Di Nisio,Rugia Shohreh,Fabio Manippa,Adriana Ricciuti,Michele Vacca,Luigi Brunetti
European Journal of Pharmacology. 2016;
[Pubmed] | [DOI]
15 Stress does not increase blood–brain barrier permeability in mice
Martin Roszkowski,Johannes Bohacek
Journal of Cerebral Blood Flow & Metabolism. 2016; 36(7): 1304
[Pubmed] | [DOI]
16 Reinventing Biostatistics Education for Basic Scientists
Tracey L. Weissgerber,Vesna D. Garovic,Jelena S. Milin-Lazovic,Stacey J. Winham,Zoran Obradovic,Jerome P. Trzeciakowski,Natasa M. Milic
PLOS Biology. 2016; 14(4): e1002430
[Pubmed] | [DOI]
17 Considerations for the design and execution of protocols for animal research and treatment to improve reproducibility and standardization: “DEPART well-prepared and ARRIVE safely”
M.M. Smith,E.C. Clarke,C.B. Little
Osteoarthritis and Cartilage. 2016;
[Pubmed] | [DOI]
18 The Effects of Cigarette Smoke Condensate and Nicotine on Periodontal Tissue in a Periodontitis Model Mouse
Mikiko Kubota,Manabu Yanagita,Kenta Mori,Shiori Hasegawa,Motozo Yamashita,Satoru Yamada,Masahiro Kitamura,Shinya Murakami,Luc Malaval
PLOS ONE. 2016; 11(5): e0155594
[Pubmed] | [DOI]
19 Protection against Schistosoma mansoni infection using a Fasciola hepatica-derived fatty acid binding protein from different delivery systems
Belén Vicente,Julio López-Abán,Jose Rojas-Caraballo,Esther del Olmo,Pedro Fernández-Soto,Antonio Muro
Parasites & Vectors. 2016; 9(1)
[Pubmed] | [DOI]
20 Pharmacological enhancement of mGlu5 receptors rescues behavioral deficits in SHANK3 knock-out mice
C Vicidomini,L Ponzoni,D Lim,M J Schmeisser,D Reim,N Morello,D Orellana,A Tozzi,V Durante,P Scalmani,M Mantegazza,A A Genazzani,M Giustetto,M Sala,P Calabresi,T M Boeckers,C Sala,C Verpelli
Molecular Psychiatry. 2016;
[Pubmed] | [DOI]
21 CD101: a novel long-acting echinocandin
Yanan Zhao,Winder B. Perez,Cristina Jiménez-Ortigosa,Grayson Hough,Jeffrey B. Locke,Voon Ong,Ken Bartizal,David S. Perlin
Cellular Microbiology. 2016;
[Pubmed] | [DOI]
22 In vitro and in vivo evaluation of 2-aminoalkanol and 1,2-alkanediamine derivatives against Strongyloides venezuelensis
Ana L. Legarda-Ceballos,Julio López-Abán,Esther del Olmo,Ricardo Escarcena,Luis A. Bustos,Jose Rojas-Caraballo,Belén Vicente,Pedro Fernández-Soto,Arturo San Feliciano,Antonio Muro
Parasites & Vectors. 2016; 9(1)
[Pubmed] | [DOI]
23 The alkylphospholipid edelfosine shows activity against Strongyloides venezuelensis and induces apoptosis-like cell death
Ana L. Legarda-Ceballos,Jose Rojas-Caraballo,Julio López-Abán,Ana Lucía Ruano,Edward Yepes,Consuelo Gajate,Faustino Mollinedo,Antonio Muro
Acta Tropica. 2016; 162: 180
[Pubmed] | [DOI]
24 Experimental design considerations in microbiota/inflammation studies
Robert J Moore,Dragana Stanley
Clinical & Translational Immunology. 2016; 5(7): e92
[Pubmed] | [DOI]
25 Endovanilloid control of pain modulation by the rostroventromedial medulla in an animal model of diabetic neuropathy
M. Silva,D. Martins,A. Charrua,F. Piscitelli,I. Tavares,C. Morgado,V. Di Marzo
Neuropharmacology. 2016; 107: 49
[Pubmed] | [DOI]
26 Long-lived antigen-induced IgM plasma cells demonstrate somatic mutations and contribute to long-term protection
Caitlin Bohannon,Ryan Powers,Lakshmipriyadarshini Satyabhama,Ang Cui,Christopher Tipton,Miri Michaeli,Ioanna Skountzou,Robert S. Mittler,Steven H. Kleinstein,Ramit Mehr,Francis Eun-Yun Lee,Ignacio Sanz,Joshy Jacob
Nature Communications. 2016; 7: 11826
[Pubmed] | [DOI]
27 The use of GRADE approach in systematic reviews of animal studies
Dang Wei,Kun Tang,Qi Wang,Janne Estill,Liang Yao,Xiaoqin Wang,Yaolong Chen,Kehu Yang
Journal of Evidence-Based Medicine. 2016; 9(2): 98
[Pubmed] | [DOI]
28 An integrated in silico approach for functional and structural impact of non- synonymous SNPs in the MYH1 gene in Jeju Native Pigs
Mrinmoy Ghosh,Simrinder Singh Sodhi,Neelesh Sharma,Raj Kumar Mongre,Nameun Kim,Amit Kumar Singh,Sung Jin Lee,Dae Cheol Kim,Sung Woo Kim,Hak Kyo Lee,Ki-Duk Song,Dong Kee Jeong
BMC Genetics. 2016; 17(1)
[Pubmed] | [DOI]
29 Anti-trypanosome effects of nutritional supplements and vitamin D3: in vitro and in vivo efficacy against Trypanosoma brucei brucei
Ripa Jamal,Rieko Shimogawara,Ki-ichi Yamamoto,Nobuo Ohta
Tropical Medicine and Health. 2016; 44(1)
[Pubmed] | [DOI]
30 Experimental Design and Surgical Approach to Create a Spinal Fusion Model in a New Zealand White Rabbit (Oryctolagus cuniculus)
Sohrab S. Virk,Dondrae Coble,Alicia L. Bertone,Hayam Hamaz Hussein,Safdar N. Khan
Journal of Investigative Surgery. 2016; : 1
[Pubmed] | [DOI]
31 Effect of tomato juice consumption on the plasmatic lipid profile, hepatic HMGCR activity, and fecal short chain fatty acid content of rats
María Jesús Periago,Gala Martín-Pozuelo,Rocío González-Barrio,Marina Santaella,Victoria Gómez,Nuria Vázquez,Inmaculada Navarro-González,Javier García-Alonso
Food Funct.. 2016; 7(10): 4460
[Pubmed] | [DOI]
32 Biocompatibility of nanosilver-coated orthodontic brackets: an in vivo study
Gamze Metin-Gürsoy,Lale Taner,Emre Baris
Progress in Orthodontics. 2016; 17(1)
[Pubmed] | [DOI]
33 Tomato Juice Consumption Modifies the Urinary Peptide Profile in Sprague-Dawley Rats with Induced Hepatic Steatosis
Gala Martín-Pozuelo,Rocío González-Barrio,Gonzalo Barberá,Amaya Albalat,Javier García-Alonso,William Mullen,Harald Mischak,María Periago
International Journal of Molecular Sciences. 2016; 17(12): 1789
[Pubmed] | [DOI]
34 Conditional Deletion of Fgfr1 in the Proximal and Distal Tubule Identifies Distinct Roles in Phosphate and Calcium Transport
Xiaobin Han,Jiancheng Yang,Linqiang Li,Jinsong Huang,Gwendalyn King,L. Darryl Quarles,Robert A Fenton
PLOS ONE. 2016; 11(2): e0147845
[Pubmed] | [DOI]
35 Control of mitochondrial function and cell growth by the atypical cadherin Fat1
Longyue L. Cao,Dario F. Riascos-Bernal,Prameladevi Chinnasamy,Charlene M. Dunaway,Rong Hou,Mario A. Pujato,Brian P. O’Rourke,Veronika Miskolci,Liang Guo,Louis Hodgson,Andras Fiser,Nicholas E. S. Sibinga
Nature. 2016; 539(7630): 575
[Pubmed] | [DOI]
36 Changes in bone macro- and microstructure in diabetic obese mice revealed by high resolution microfocus X-ray computed tomography
G. Kerckhofs,M. Durand,R. Vangoitsenhoven,C. Marin,B. Van der Schueren,G. Carmeliet,F. P. Luyten,L. Geris,K. Vandamme
Scientific Reports. 2016; 6: 35517
[Pubmed] | [DOI]
37 VEGF regulates local inhibitory complement proteins in the eye and kidney
Lindsay S. Keir,Rachel Firth,Lyndsey Aponik,Daniel Feitelberg,Susumu Sakimoto,Edith Aguilar,Gavin I. Welsh,Anna Richards,Yoshihiko Usui,Simon C. Satchell,Valeryia Kuzmuk,Richard J. Coward,Jonathan Goult,Katherine R. Bull,Ruchi Sharma,Kapil Bharti,Peter D. Westenskow,Iacovos P. Michael,Moin A. Saleem,Martin Friedlander
Journal of Clinical Investigation. 2016; 127(1): 199
[Pubmed] | [DOI]
38 Targeted Magnetic Nanoparticles for Mechanical Lysis of Tumor Cells by Low-Amplitude Alternating Magnetic Field
Adi Vegerhof,Eran Barnoy,Menachem Motiei,Dror Malka,Yossef Danan,Zeev Zalevsky,Rachela Popovtzer
Materials. 2016; 9(11): 943
[Pubmed] | [DOI]
39 Critical evaluation of challenges and future use of animals in experimentation for biomedical research
Vijay Pal Singh,Kunal Pratap,Juhi Sinha,Koundinya Desiraju,Devika Bahal,Ritushree Kukreti
International Journal of Immunopathology and Pharmacology. 2016; 29(4): 551
[Pubmed] | [DOI]
40 Fabp1 gene ablation inhibits high-fat diet-induced increase in brain endocannabinoids
Gregory G. Martin,Danilo Landrock,Sarah Chung,Lawrence J. Dangott,Drew R. Seeger,Eric J. Murphy,Mikhail Y. Golovko,Ann B. Kier,Friedhelm Schroeder
Journal of Neurochemistry. 2016;
[Pubmed] | [DOI]
41 Iontophoresis Improved Growth Reduction of Invasive Squamous Cell Carcinoma in Topical Photodynamic Therapy
Camila Nunes Lemos,Joel Gonçalves de Souza,Patrícia Sper Simão,Renata Fonseca Vianna Lopez,Michael Hamblin
PLOS ONE. 2016; 11(1): e0145922
[Pubmed] | [DOI]
42 Effect of appendicectomy on colonic inflammation and neoplasia in experimental ulcerative colitis
Y. Harnoy,Y. Bouhnik,N. Gault,L. Maggiori,L. Sulpice,D. Cazals-Hatem,K. Boudjema,Y. Panis,E. Ogier-Denis,X. Treton
British Journal of Surgery. 2016;
[Pubmed] | [DOI]
43 The effect of surgical menopause on the intima-media thickness of the carotid and coronary arteries
S. Ozdemirci,T. Kasapoglu,B. Dilbaz,F. Salgur,B. Duran,O. Koc,H. Unverdi,S. Hucumenoglu
Climacteric. 2016; : 1
[Pubmed] | [DOI]
44 Characterization of age-associated exhausted CD8+T cells defined by increased expression of Tim-3 and PD-1
Kyoo-A Lee,Kwang-Soo Shin,Ga-Young Kim,You Chan Song,Eun-Ah Bae,Il-Kyu Kim,Choong-Hyun Koh,Chang-Yuil Kang
Aging Cell. 2015; : n/a
[Pubmed] | [DOI]
45 Hypothalamic CaMKKß mediates glucagon anorectic effect and its diet-induced resistance
Mar Quiñones,Omar Al-Massadi,Rosalía Gallego,Johan Fernø,Carlos Diéguez,Miguel López,Ruben Nogueiras
Molecular Metabolism. 2015; 4(12): 961
[Pubmed] | [DOI]
46 Coenzyme Q10 remarkably improves the bio-energetic function of rat liver mitochondria treated with statins
Afshin Mohammadi-Bardbori,Asma Najibi,Najmeh Amirzadegan,Raziyeh Gharibi,Ayat Dashti,Mahmoud Omidi,Arastoo Saeedi,Ali Ghafarian-Bahreman,Hossein Niknahad
European Journal of Pharmacology. 2015; 762: 270
[Pubmed] | [DOI]
47 Registered report: Inhibition of BET recruitment to chromatin as an effective treatment for MLL-fusion leukemia
Juan José Fung,Alan Kosaka,Xiaochuan Shan,Gwenn Danet-Desnoyers,Michael Gormally,Kate Owen
eLife. 2015; 4
[Pubmed] | [DOI]
48 Ameliorative Effect of Gallic Acid on Cyclophosphamide-Induced Oxidative Injury and Hepatic Dysfunction in Rats
Ebenezer Olayinka,Ayokanmi Ore,Olaniyi Ola,Oluwatobi Adeyemo
Medical Sciences. 2015; 3(3): 78
[Pubmed] | [DOI]
49 The bone morphogenetic protein-2/7 heterodimer is a stronger inducer of bone regeneration than the individual homodimers in a rat spinal fusion model
Tokimitsu Morimoto,Takashi Kaito,Yohei Matsuo,Tsuyoshi Sugiura,Masafumi Kashii,Takahiro Makino,Motoki Iwasaki,Hideki Yoshikawa
The Spine Journal. 2015; 15(6): 1379
[Pubmed] | [DOI]
50 Effects of crude kerosene on testosterone levels, aggression and toxicity in rat
Rachel W. Njoroge,Benson N. Macharia,Dinah J. Sawe,Geoffrey K. Maiyoh
Toxicology Reports. 2015; 2: 175
[Pubmed] | [DOI]
51 Fibrin gels loaded with cisplatin and cisplatin-hyaluronate complexes tested in a subcutaneous human melanoma model
Maurizio Viale,Marta Rossi,Eleonora Russo,Michele Cilli,Anna Aprile,Aldo Profumo,Pierluigi Santi,Carla Fenoglio,Sergio Cafaggi,Mattia Rocco
Investigational New Drugs. 2015; 33(6): 1151
[Pubmed] | [DOI]
52 Application of 3-D Echocardiography and Gated Micro-Computed Tomography to Assess Cardiomyopathy in a Mouse Model of Duchenne Muscular Dystrophy
Andrew B. Bondoc,Sarah Detombe,Joy Dunmore-Buyze,Kelly M. Gutpell,Linshan Liu,Amanda Kaszuba,Seongryoung Han,Rebecca McGirr,Jennifer Hadway,Maria Drangova,Lisa M. Hoffman
Ultrasound in Medicine & Biology. 2014;
[Pubmed] | [DOI]



 

Top
  
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
    Abstract
   Acknowledgment
    References

 Article Access Statistics
    Viewed5987    
    Printed79    
    Emailed0    
    PDF Downloaded2881    
    Comments [Add]    
    Cited by others 52    

Recommend this journal