e-ISSN: 2319-9873 p-ISSN: 2347-2324

Research & Reviews: Journal of Pharmacology and Toxicological Studies

A Short Study on Phylogenetics

Indu Sama*

Department of plant Pathology and forest genetics, Bharat University, India

Review Article

ABSTRACT Received: 06/09/2016 Accepted : 09/09/2016 Published: 12/09/2016 In science, phylogenetics is the investigation of transformative *For Correspondence connections among gatherings of life forms (e.g. species,populations), which are found through atomic sequencing information and morphological information grids. The term phylogeneticsderives from the Greek Department of plant Pathology expressions phylé (φυλή) and phylon (φῦλον), meaning "tribe", "faction", and forest genetics, Bharat "race" and the descriptive structure, genetikós(γενετικός), of the word University, India genesis (γένεσις) "source", "source", "conception". Indeed, phylogenesis is the procedure, phylogeny is science on this procedure, and phylogenetics is E-mail: [email protected] phylogeny in view of examination of successions of organic macromolecules (DNA, RNA and proteins, in the first). The consequence of phylogenetic Keywords: Phylogenetics, studies is a speculation about the developmental history of taxonomic Devolopment, Computation gatherings: their phylogeny.

INTRODUCTION

Development is a procedure whereby populaces are modified over the long run and may part into particular branches, hybridize together, or end by elimination [1 -15]. The transformative expanding procedure may be portrayed as a phylogenetic tree, and the spot of each of the different living beings on the tree is in view of a speculation about the arrangement in which developmental spreading occasions happened. Inhistorical phonetics, comparative ideas are utilized regarding connections in the middle of dialects; and in literary feedback withstemmatics [15-25].

Phylogenetic examinations have ended up crucial to research on the developmental tree of life. Case in point, the RedToL goes for recreating the Red Algal Tree of Life. The National Science Foundation supports an undertaking called the Assembling the Tree of Life (AToL) action [26,27]. The objective of this task is to focus developmental connections crosswise over expansive gatherings of creatures all through the historical backdrop of life. The exploration on this venture regularly includes vast groups working crosswise over establishments and orders, and normally gives backing to specialists dealing with computational phylogenetics and phyloinformatics assignments, including information securing, examination, and calculation advancement and dispersal [28-32].

Scientific categorization the arrangement, recognizable proof and naming of creatures is typically luxuriously educated by phylogenetics, yet remains a methodologically and coherently unmistakable discipline [4]. The extent to which scientific classifications rely on upon phylogenies varies relying upon the school of scientific categorization: phenetics disregards phylogeny through and through, attempting to speak to the closeness between organic entities rather; cladistics (phylogenetic systematics) tries to recreate phylogeny in its order without loss of data; developmental scientific categorization tries to discover a bargain between them so as to speak to phases of advancement [33-36].

Development of a phylogenetic tree

The logical systems for phylogenetics are regularly gathered under the term cladistics. The most well-known ones are niggardliness, greatest probability (ML), and MCMC-basedBayesian derivation [37]. All systems rely on a

RRJPTS | Volume 4 | Issue 3 | August, 2016 39 e-ISSN: 2319-9873 p-ISSN: 2347-2324

verifiable or unequivocal scientific model portraying the development of characters saw in the species incorporated; all can be, and are, utilized for atomic information, wherein the characters are adjusted nucleotide or amino corrosive successions, and everything except most extreme probability (see beneath) can be, and are, utilized for phenotypic (morphological, concoction, and physiological) information (likewise called established or customary information) [38-40].

Phenetics, prevalent in the mid-20th century however now generally out of date, uses separation grid based systems to build trees in light of general closeness in morphology or other recognizable qualities (i.e. in the phenotype, not the DNA), which was regularly accepted to surmised phylogenetic connections [41].

An exhaustive orderly convention on developing phylogenetic tree, including DNA/Amino Acid coterminous grouping get together, various succession arrangement, model-test (testing best-fitting substitution models) and phylogeny remaking utilizing Maximum Likelihood and Bayesian Inference, is accessible at Nature Protocol [42].

Before 1990, phylogenetic surmisings were by and large displayed as story situations. Such techniques are honest to goodness, however regularly questionable and difficult to test [43-46].

Homoplasy

Certain characters are more inclined to develop concurrently than others; intelligently, such characters ought to be given less weight in the reproduction of a tree. Weights as a model of advancement can be deduced from sets of atomic information, so that greatest probability or Bayesian systems can be utilized to investigate them. For sub- atomic groupings, this issue is exacerbated when the taxa under study have separated generously. As time subsequent to the uniqueness of two taxa build, so does the likelihood of numerous substitutions on the same site, or back changes, all of which result in homoplasies. For morphological information, lamentably, the main target approach to focus merging is by the development of a tree – a to a degree roundabout system [47-50]. Indeed, even along these lines, weighting homoplasious characters improves upheld trees. Further refinement can be gotten by weighting alters one course higher than changes in another; for case, the vicinity of thoracic wings very nearly ensures arrangement among the pterygote creepy crawlies on the grounds that, in spite of the fact that wings are frequently lost optionally, there is no proof that they have been increased more than once [51].

Level quality exchange

As a rule, organic entities can acquire qualities in two ways: vertical quality exchange and even quality exchange. Vertical quality exchange is the entry of qualities from guardian to posterity, and level (likewise called sidelong) quality exchange happens when qualities bounce between disconnected living beings, a typical sensation particularly in prokaryotes; a great sample of this is the obtained anti-toxin resistance as an aftereffect of quality trade between different microbes prompting multi-drug-safe bacterial species [52-56]. There have additionally been all around reported instances of flat quality exchange between eukaryotes.

Even quality exchange has confused the determination of phylogenies of creatures, and irregularities in phylogeny have been accounted for among particular gatherings of life forms relying upon the qualities used to develop transformative trees [57]. The best way to figure out which qualities have been procured vertically and which evenly is toparsimoniously expect that the biggest arrangement of qualities that have been acquired together have been acquired vertically; this obliges breaking down an extensive number of qualities [58-62].

Mixtures, speciation and introgressions

The essential suspicion fundamental the numerical model of cladistics is a circumstance where animal types part flawlessly in bifurcating manner. While such a presumption may hang on a bigger scale (bar even quality exchange, see above), speciation is regularly significantly less deliberate [63 -70]. Research following the cladistic system was presented has demonstrated that half and half speciation, once thought uncommon, is truth be told very basic, especially in plants. Additionally paraphyletic speciation is regular, making the suspicion of a bifurcating example inadmissible, prompting phylogenetic systems as opposed to trees. Introgression can likewise move qualities between generally unmistakable species and at times even genera, confounding phylogenetic examination in light of qualities. This wonder can add to "inadequate line sorting" and is thought to be a typical sensation over various gatherings. In species level examination this can be managed by bigger inspecting or better entire genome [71-80] investigation. Frequently the issue is maintained a strategic distance from by confining the investigation to less, not nearly related example.

RRJPTS | Volume 4 | Issue 3 | August, 2016 40 e-ISSN: 2319-9873 p-ISSN: 2347-2324

Taxon inspecting

Attributable to the advancement of cutting edge sequencing systems in atomic science, it has ended up attainable to accumulate a lot of information (DNA or amino corrosive successions) to derive phylogenetic speculations [81-84]. Case in point, it is not uncommon to discover studies with character networks in light of entire mitochondrial genomes (~16,000 nucleotides, in numerous creatures). Nonetheless, recreations have demonstrated that it is more critical to expand the quantity of taxa in the grid than to build the quantity of characters, on the grounds that the more taxa there are, the more precise and more vigorous is the subsequent phylogenetic tree. This may be halfway because of the separating of long branches [85-90].

Phylogenetic sign

Another essential element that influences the precision of tree remaking is whether the information investigated really contain a valuable phylogenetic sign, a term that is utilized for the most part to indicate whether a character advances gradually enough to have the same state in nearly related taxa instead of fluctuating arbitrarily. Tests for phylogenetic sign exist [91-93].

Preparing Phylogenetic data

• Using molecular data is easier than the morphology data.

• However, we must be aware of a major assumption in handling the data: we assumed that evolution is always divergent. That is, if two sequences are similar we rule out the possibility that this similarity may result from convergent evolution. • More precisely, convergent evolution at a molecular level is extremely rare

• The quality of the data is critical (“garbage in, garbage out”), that is, the quality of the multiple sequence alignment must be high. • If you have DNA sequences, you can use them, but only if the sequence identity is high • Otherwise, convert DNA into protein sequences (only coding parts) and align proteins • Then, convert back to DNA if you want to observe synonymous mutations etc. • Work on orthologs to study differences among species

• Work on paralogs to study (often)-related proteins within the same species (for example, you can attempt to reconstruct the gene duplication events)

• Genes that result from horizontal transfer between two organisms. Xenologs may introduce noise as one of the species contains a gene that does not have the same history as the genome in which it is inserted.

• The genes that are homologous and are coming from two different species are not necessarily orthologous!

• Finally, don’t use sequence fragments, fusion proteins, large complex families. Use an outgroup whenever you can. • Use a reliable program for multiple sequence alignment

Phylogenetic comparative methods

Phylogenetic comparative methods (PCMs) use data on the transformative connections of life forms (phylogenetic trees) to analyze species. The most widely recognized applications are to test for associated transformative changes in two or more qualities, or to figure out if a quality contains a phylogenetic sign (the propensity for related species to look like one another. Nevertheless, a few methods are accessible to relate specific phenotypic attributes to variety in rates of speciation and/or termination, including endeavors to distinguish developmental key developments. Albeit most studies that utilize PCMs concentrate on surviving creatures, the methods can likewise be connected to terminate taxa and can consolidate data from the fossil record [94-98].

Attributable to their computational necessities, they are typically executed by PC projects (see list beneath). PCMs can be seen as a component of transformative science, systematics, phylogenetics, bioinformatics or even measurements, as most methods include factual systems and standards for estimation of different parameters and drawing surmisings about developmental procedures.

RRJPTS | Volume 4 | Issue 3 | August, 2016 41 e-ISSN: 2319-9873 p-ISSN: 2347-2324

What recognizes PCMs from most customary methodologies in systematics and phylogenetics is that they normally do not endeavor to gather the phylogenetic connections of the species under study. Maybe, they utilize a free gauge of the phylogenetic tree (topology in addition to branch lengths) that is gotten from a different phylogenetic investigation, for example, comparative DNA arrangements that have been broke down by greatest niggardliness, most extreme probability or Bayesian methods. The primary goal of PCMs is to study the advancement of subjective and quantitative attributes and recognizing examples of beginning and termination in phylogenies. Most comparative models expect the phylogenetic tree is known without mistake keeping in mind the end goal to gauge parameters of hobby. In this manner, PCMs use phylogenies which are now accessible and do not deliver them. Appropriately, the rundown of phylogenetics programming shows little cover with the projects for PCMs, with the exemption to a huge arrangement of R bundles, for example, "chimp" and "geiger" and standalone phylogenetic programming, for example, "Mesquite".

Correlation of species to explain parts of science has a long history. Charles Darwin depended on such correlations as a real wellspring of proof when composing The Origin of Species. Numerous different fields of science utilization interspecific examination also, including behavioral nature, ethology, ecophysiology, comparative physiology, transformative physiology, utilitarian morphology, comparative biomechanics, and the investigation of sexual choice [98-100].

REFERENCES

1. Srinivasan B. Synthesis of Silver Nano Particles Using Herbal Extract and its Anti-Microbial Activity. J Phylogen Evolution Biol. 2015;3:146.

2. Thomas EA. Homo Sapiens: Epidermal Growth Factor Receptor (DNA Data Mining). J Phylogen Evolution Biol. 2015;3:145.

3. Bast F, et al. European Species of Subaerial Green AlgaTrentepohlia annulata (Trentepohliales, Ulvophyceae) Caused Blood Rain in Kerala, India. J Phylogen Evolution Biol. 2015;3:144.

4. Yoon J, et al. Phylogenetic and Taxonomic Analyses of Rhodopirellula caenicola Sp. Nov., a New MarinePlanctomycetes Species Isolated from Iron Sand. J Phylogen Evolution Biol. 2015;3:143.

5. Shashi S, et al. Laboratory Investigation and Molecular Epidemiology of H1N1pdm Virus 2012-2013 from India. J Phylogen Evolution Biol. 2015;3:139. 6. Evans AT. Phylogeny and Diversity of Rhizobial Bacteria. J Phylogen Evolution Biol. 2015;3:e111. 7. Evans AT. DNA Testing. J Phylogen Evolution Biol 3:e110. doi: 10.4172/2329-9002.1000e110.

8. Brocchieri L. Phylogenetic Diversity and the Evolution of Molecular Sequences. J Phylogen Evolution Biol. 2015;3:e109.

9. Nakai R, et al. The Newest Class of the Phylum Proteobacteria, Consisting of only One Cultured Species and Uncultured Bacterial Phylotypes from Diverse Habitats. J Phylogen Evolution Biol. 2015;3:141.

10. Pérez-Losada M, et al. An Updated Multilocus Phylogeny of the Lumbricidae (Annelida: Clitellata: Oligochaeta) Earthworms. J Phylogen Evolution Biol. 2015;3:140. 11. Rajarapu G. Horizontal Gene Transfer. J Phylogen Evolution Biol. 2014;2:136. 12. Ponnuru NK. Carboxydothermus hydrogenoformans. J Phylogen Evolution Biol. 2014;2:135.

13. Spudeit WA. Behavioral Sequence of Satiety: A Comparative Approach between Birds and Mammals. J Phylogen Evolution Biol. 2014;2:132.

14. Patwardhan A, et al. Molecular Markers in Phylogenetic Studies – A Review. J Phylogen Evolution Biol. 2014;2:131.

15. Hukowska SB, et al. Phylogenetic Analysis of Selected RHDV Strains on the Basis of a Fragment of the Gene Encoding C-Terminal End of VP60 Capsid Structural Protein. J Phylogen Evolution Biol. 2014;2:130. 16. Kupriyanova NS and Ryskov AP. The New Mode of Thought of Vertebrates’ Evolution. J Phylogen Evolution Biol. 2014;2:129.

17. Cocchi M, et al. Human and Animal Brain Phospholipids Fatty Acids, Evolution and Mood Disorders. J Phylogen Evolution Biol. 2014;2:128.

18. Sherkhane AS, et al. Study of Conserved Domain across Divergent Phylogenetic Lineages of Long Neurotoxin from Genus Naja (Elapidae Family). J Phylogen Evolution Biol. 2014;2: 127. 19. Rajarapu G. Genes and Genome of HIV-1. J Phylogen Evolution Biol. 2014;2: 126.

20. Takiue S and Akiyoshi H. Histological and Scanning Electron Microscopic Examination of the Digestive Tract in Whitespotted Conger, Conger Myriaster (Anguilliformes). J Phylogen Evolution Biol. 2014;2:125.

RRJPTS | Volume 4 | Issue 3 | August, 2016 42 e-ISSN: 2319-9873 p-ISSN: 2347-2324

21. Brocchieri L. The GC Content of Bacterial Genomes. J Phylogen Evolution Biol. 2014;2:e108.

22. Chen LJ, et al. Development and Maintenance of a Cross-mixed Mating System in the Orchid Bulbophyllum orientale. J Phylogen Evolution Biol. 2014;2:124.

23. Abdul RF, et al. The Distribution of Polyhedral Bacterial Microcompartments Suggests Frequent Horizontal Transfer and Operon Reassembly. J Phylogen Evolution Biol. 2014;1:118.

24. Kartavtsev YP. Some Current Concerns of Neo-Darwinism:Gene Introgression Throughout a Species Border. J Phylogen Evolution Biol. 2013;1:e107.

25. Robalo JI, et al. Monitoring Climate Change Impact on the Genetic Population Structure: The Case of the Fivebeard Rockling (Ciliata Mustela, Linnaeus, 1758) In Its Southern Limit of Distribution. J Phylogen Evolution Biol. 2013; 2:123.

26. Sathyanarayana Reddy G. Phylogenetic Analyses of the Genus Hymenobacter and Description of Siccationidurans gen. nov., and Parahymenobacter gen. Nov. J Phylogen Evolution Biol. 2013;1: 122.

27. Brocchieri L. Phenotypic and Evolutionary Distances in Phylogenetic Tree Reconstruction. J Phylogen Evolution Biol. 2013;1:e106.

28. Kartavtsev YP. Sequence Diversity at Cyt-b and Co-1 mtDNA Genes in Animal Taxa Proved Neo-Darwinism. J Phylogen Evolution Biol. 2013;1:120.

29. Cocchi M, et al. Molecular Contiguity between Human and Animal Consciousness through Evolution: Some Considerations. J Phylogen Evolution Biol. 2013;1:119.

30. Viviano J, et al. Evolutionary Interrelationships and Insights into Molecular Mechanisms of Functional Divergence: An Analysis of Neuronal Calcium Sensor Proteins. J Phylogen Evolution Biol. 2013;1:117.

31. Som A. Genome-Scale Approach and the Performance of Phylogenetic Methods. J Phylogen Evolution Biol. 2013;1:116.

32. Pepper JW, et al. Are Internal, Death-Promoting Mechanisms Ever Adaptive? J Phylogen Evolution Biol. 2013;1:113.

33. Holmes RS. Evolution of Mammalian KELL Blood Group Glycoproteins and Genes (KEL): Evidence for a Marsupial Origin from an Ancestral M13 Type II Endopeptidase Gene. J Phylogen Evolution Biol. 2013;1:112.

34. Stehle F, et al. Snap-shot of Serine Carboxypeptidase-like Acyltransferase Evolution: The Loss of Conserved Disulphide Bridge is Responsible for the Completion of Neo-functionalization. J Phylogen Evolution Biol. 2013;1:115.

35. McVay JD and Carstens BC. Phylogenetic Model Choice: Justifying a Species Tree or Concatenation Analysis. J Phylogen Evolution Biol. 2013;1:114.

36. Giuliani A, et al. Amino-Acid Correlated Mutations inside a Single Protein System: A New Method for the Identification of Main Coherent Directions of Evolutive Changes. J Phylogen Evolution Biol. 2013;1:111.

37. Satpathy R, et al. Computational Phylogenetic Study and Data Mining Approach to Laccase Enzyme Sequences. J Phylogen Evolution Biol. 2013;1:108. 38. Sperber GH. The Divination of Dentitions in Evolution. J Phylogen Evolution Biol. 2013;1:109. 39. Paliy O. The Golden Age of Molecular Ecology. J Phylogen Evolution Biol. 2013;1:e105. 40. Xiong M. New Era for Health Care and Genomics. J Phylogen Evolution Biol. 2013;1:e104.

41. Yang D and Liu Z. An Evolutionary Perspective on Cardiovascular Disease. J Phylogen Evolution Biol. 2013;1:e103.

42. Patel S, et al. Error in Phylogenetic Estimation for Bushes in the Tree of Life. J Phylogen Evolution Biol. 2013;1:110.

43. Mukherjee K and Brocchieri L. Ancient Origin of Chaperonin Gene Paralogs Involved in Ciliopathies. J Phylogen Evolution Biol. 2013;1:107. 44. John L, et al. Population Structure of Denison’s barb, Puntius denisonii (Pisces: Cyprinidae): A Species

Complex Endemic to the Western Ghats of India. J Phylogen Evolution Biol 1:106. doi: 10.4172/2329- 9002.1000106.

45. Lents NH (2013) Teaching the Biology of Gender, Sex, and Sexuality Leads to a Marked Increase in Acceptance of the Theory of Evolution by Natural Selection. J Phylogen Evolution Biol. 2013;1:105.

46. Brusini J, et al. To Fuse or Not to Fuse? An Evolutionary View of Self-Recognition Systems. J Phylogen Evolution Biol. 2013;1:103.

47. Ramya Ranjan M, et al. Elucidation of Genetic Relationships in the Genus Cajanus Using Random Amplified Polymorphic DNA Marker Analysis. J Phylogen Evolution Biol. 2013;1:102.

RRJPTS | Volume 4 | Issue 3 | August, 2016 43 e-ISSN: 2319-9873 p-ISSN: 2347-2324

48. Jitesh Kumar M and Amiya Kumar P. Physico-Chemical Characterization and Mine Soil Genesis in Age Series Coal Mine Overburden Spoil in Chronosequence in a Dry Tropical Environment. J Phylogen Evolution Biol. 2013;1:101. 49. Lee HW and Brocchieri L. The Evolution of Fuzzy Proteins. J Phylogen Evolution Biol. 2013;1:e102. 50. Lents NH. Teaching All Things Evolution. J Phylogen Evolution Biol. 2013;1:e101.

51. Ahmad S and Siddiqui Z. Protein Glycation: A Firm Link to Cause Metabolic Disease and their Complications. J Glycomics Lipidomics. 2013;4:127.

52. Nikkhah A. Nutrient Assimilation Circadian Physiology: A Novel SciTech in Integrative Crop Production. Adv Crop Sci Tech. 2013;3:e121.

53. Udaya Lakshmi P and Divya A, Priyanka R. A Review on Medicative Plants Touching Memory Loss on Hyoscine Evoked Model. J Plant Biochem Physiol. 2013;R1:001.

54. Vaidya S, et al. Variability in Drought Stress Induced Responses of Groundnut (Arachis hypogaea L.) Genotypes. Biochem Physiol. 2013;4:149.

55. Dhir B and Rajam MV. Soil Amendment with Municipal Sludge Does not Alter the Physiological Status of Solanum melongena. J Plant Biochem Physiol. 2013;3:141.

56. Minaeva E and Ermilova E. Sequencing and Expression Analysis of the Gene Encoding PII Signal Protein in Chlorella VariabilisNC64A. J Plant Biochem Physiol. 2013;3:142.

57. Nikkhah A. Optimizing Gestation and Early Life Physiology through Timing of Energy Turnover: Bioprocessing of Human Life. J Bioprocess Biotech. 2013;5:e125.

58. Teshome Z, et al. Effect of Nitrogen and Phosphorus on Yield Components, Yield and Sugarcane Juice Quality parameters of Soybean-Sugarcane Intercropping at Tendaho Sugar Factory. Biochem Physiol. 2013;4:151.

59. Mohamad RH, et al. New Aspects of Therapy of Hepatocellular Carcinoma Egyptian Patients. Biochem Physiol. 2013;4:150.

60. Sinha PK. The Magnificent World of Sulfatase and Sulfatase Maturating Enzymes. Biochem Physiol. 2013;4:e134. 61. Hu D, et al. The Bright Future of Liposome Mediated Drug Delivery. Biochem Physiol. 2013;4:e133. 62. Kuddus M. Cold-active Microbial Enzymes. Biochem Physiol. 2013;4:e132.

63. Jain M, et al. When Seed and Soil Theory Meets Chicken or Egg Theory in Cancer Metastasis. Biochem Physiol. 2013;4:e131.

64. Kulakovskaya T. Phosphorus storage in Microorganisms: Diversity and Evolutionary Insight. Biochem Physiol. 2013;4:e130. 65. Balbaa M. Inhibition of Glycosidases. Biochem Physiol. 2013;4:e129.

66. Tyagi AK and Prasad S. Drug Discovery Inspired by Mother Nature for Cancer Therapy. Biochem Physiol. 2013;4:e128.

67. Bello A, et al. Histomorphometric Study of the Prenatal Development of the Circumvallate Papillae of One-Humped Camel (Camelus Dromedarius). Anat Physiol. 2013;5:168. 68. May J, et al. Penile Replantation in an Acutely Psychotic Patient. Anat Physiol. 2013;5:170.

69. Hashish HA. Alteration of Glial Fibrillary Acidic Protein Immunoreactivity in Astrocytes of the Cerebellum of Diabetic Rats and Potential Effect of Insulin and Ginger. Anat Physiol; 2013;5:167. 70. Gnanavel A, et al. Cystic Hygroma- A Case Report and its Embryological Basis. Anat Physiol. 2016;5:169. 71. Ferreira LG. Efficiency of Stretching to Prevent Injury in Military Police Runners. Anat Physiol. 2013;5:166.

72. Kumar A, et al. Morphological Variations in Lumbricals of Upper Limb: A Cadaveric Study. Anat Physiol. 2013;5:165.

73. Dobrzynski H, et al. Molecular Investigation into the Human Atrioventricular Node in Heart Failure . Anat Physiol. 2013;5:164.

74. Ogeng’o J, et al. Intima-Media Thickness of Left Anterior Descending Coronary Artery in a Black Kenyan Population: Correlation with Morphological Features. Anat Physiol; 2013;5:163.

75. Balnyte R, et al. Associations of HLA DRB1 Alleles with Igg Oligoclonal Bands and Their Influence on Multiple Sclerosis Course and Disability Status. J Neurol Neurophysiol. 2013;6:268.

76. Ossig C, et al. Sinking Skin Flap Syndrome after Hemicraniectomy and Ventriculo-Peritoneal Shunt Overdrainage. J Neurol Neurophysiol. 2013;6:272.

RRJPTS | Volume 4 | Issue 3 | August, 2016 44 e-ISSN: 2319-9873 p-ISSN: 2347-2324

77. Chayasirisobhon S, et al. Efficacy of Neuromodulation Therapy with Vagus Nerve Stimulator in Patients with Drug-Resistant Epilepsy on Unchanged Antiepileptic Medication Regimen for 24 Months Following the Implant. J Neurol Neurophysiol. 2013;6:268. 78. Luo J. A Practical Approach to Neurophysiologic Intraoperative Monitoring. J Neurol Neurophysiol. 2013;6:266.

79. Veiga A, et al. Conus Terminallis Neurocysticercosis: A Rare Cause of Lumbar Radiculopathy. J Neurol Neurophysiol. 2013;6:265.

80. Daskalakis G and Papapanagiotou A. Serum Markers for the Prediction of Preeclampsia. J Neurol Neurophysiol. 2013;6:264.

81. Torrado M, et al. Alexithymia, Physiological Reactivity and Cognitive Appraisals of Emotional Stimuli in Opiate Dependents: A Pilot Study. J Neurol Neurophysiol. 2013;6:263.

82. Rocha FT, et al. EEG Brain Mapping of Normal and Learning Disabled Children Using Factor and Linear Discriminant Analyses. J Neurol Neurophysiol. 2016;6:262.

83. Ikemoto K, et al. Prenatal Maternal Stress Due to Repeated Exposure to A Cold Environment Affects Development of Catecholamine Neurons in Rat Offspring: An Imunohistochemical Study. J Neurol Neurophysiol. 2013;6:271.

84. Yoshinaga T, et al. A Case Report of WEBINO Syndrome with Convergence Impairment. J Neurol Neurophysiol. 2013;6:270.

85. Matsuo K, et al. Effects of Food Consistencies and Mastication on Bolus Transport and Swallow Initiation in Individuals with Hemispheric Stroke. J Neurol Neurophysiol. 2013;6:269.

86. Yamamoto T, et al. Assessment of A New Magnetic Device to Monitor Swallowing in Parkinson’s Disease. J Neurol Neurophysiol. 2013;6:267.

87. Nikkhah A. Intake Circadian Physiology: An Overlooked Public Health Concern. Endocrinol Metab Synd. 2014;4:153.

88. Micheal Eskin. Boron: An Overlooked Micronutrient that Plays an Important Role In Human Physiology. Vitam Miner. 2013;4:e135.

89. Liu Y, et al. Dynamic Element Concentrations and Similar Proteome of the Rhizome and Root of Miscanthus X Gigantheus. J Plant Biochem Physiol. 2013;2:139.

90. Zhou L, et al. Pathophysiology and Treatment of Discogenic and Radicular Lower Back Pain. Int J Phys Med Rehabil. 2016;2:e107.

91. Rosival V. Interesting Development in the Pathophysiology of Diabetic Ketoacidotic Coma. J Diabetes Metab. 2014;5:455.

92. Ouedraogo N and Roux E. Physiology of Airway Smooth Muscle Contraction: An Overview. J Pulm Respir Med. 2014;4:221.

93. Malcolm MP, et al. Methods for an International Randomized Clinical Trial to Investigate the Effect of Gsk249320 on Motor Cortex Neurophysiology using Transcranial Magnetic Stimulation in Survivors of Stroke. J Clin Trials. 2014;4:199.

94. Olalekan A. The Effect of Palm Kernel Oil (PKO) Biodiesel-Contaminated Soil on Morphological and Biochemical Properties of Zea mays. J Plant Biochem Physiol. 2014;2:138.

95. Li D, et al. Transcriptome Analysis of Tessellated and Green Leaves in Paphiopedilum Orchids Using Illumina Paired- End Sequencing and Discovery Simple Sequence Repeat Markers. J Plant Biochem Physiol. 2016;2:136.

96. Guo N, et al. Sciatic Nerve Neuropathy in Cynomolgus Monkey Macaca Fascicularis: Altered Leg Usage and Peripheral Nerve Firing. 2014;5:247.

97. Shimizu Y, et al. LoudNoise Exposure during Activity and Neurogenesis in the Living Rat Brain: Preliminary Study. J Neurol Neurophysiol. 2014;5:253.

98. Lee A and Rajaratnam R. Tailoring the Novel Anticoagulants to the Stroke Patient – One Size Does Not Fit All Novel Anticoagulants in Stroke. J Neurol Neurophysiol. 2014;5:248.

99. Pavlova MK, et al. Unexpected EEG Abnormalities in Adults with Parasomnia – A Case Series. J Neurol Neurophysiol. 2014;5:246.

100. Martìnez HR, et al. Increase of Pyramidal Tract Fractional Anisotropy on MRI after Stem Cell Transplantation in ALS Patients. J Neurol Neurophysiol. 2014;5:244.

RRJPTS | Volume 4 | Issue 3 | August, 2016 45