Multiple sclerosis：integration of modeling with biology,clinical and imaging measures to provide better monitoring of disease progression and prediction of outcome

Multiple Sclerosis（MS） is a major cause of neurological disability in adults and has an annual cost of approximately $28 billion in the United States. MS is a very complex disorder as demyelination can happen in a variety of locations throughout the brain; therefore, this disease is never the same in two patients making it very hard to predict disease progression. A modeling approach which combines clinical, biological and imaging measures to help treat and fight this disorder is needed. In this paper, I will outline MS as a very heterogeneous disorder, review some potential solutions from the literature, demonstrate the need for a biomarker and will discuss how computational modeling combined with biological, clinical and imaging data can help link disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism.

Fast algorithm for constructing neighbor-joining phylogenetic trees

To improve the performance of Saitou and Nei＇s algorithm （SN） and Studier and Keppler＇s improved algorithm （SK） for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computation, a fast algorithm is proposed. The proposed algorithm includes three techniques. First, a linear array A[N] is introduced to store the sum of every row of the distance matrix （the same as SK）, which can eliminate many repeated computations. Secondly, the value of A [i] is computed only once at the beginning of the algorithm, and is updated by three elements in the iteration. Thirdly, a very compact formula for the sum of all the branch lengths of operational taxonomic units （OTUs） i and j is designed, and the correctness of the formula is proved. The experimental results show that the proposed algorithm is from tens to hundreds times faster than SN and roughly two times faster than SK when N increases, constructing a tree with 2 000 OTUs in 3 min on a current desktop computer. To earn the time with the cost of the space and reduce the computations in the innermost loop are the basic solutions for algorithms with many loops.

Clinical outcomes after autologous haematopoietic stem cell transplantation in patients with progressive multiple sclerosis

Background Multiple sclerosis （MS） is a continuously disabling disease and it is unresponsive to high dose steroid and immunomodulation with disease progression. The autologous haematopoietic stem cell transplantation （ASCT） has been introduced in the treatment of refractory forms of multiple sclerosis. In this study, the clinical outcomes followed by ASCT were evaluated for patients with progressive MS. Methods Twenty-two patients with secondary progressive MS were treated with ASCT. Peripheral blood stem cells were obtained by leukapheresis after mobilization with granulocyte colony stimulating factor. Etoposide, melphalan, carmustin and cytosine arabinoside were administered as conditioning regimen. Outcomes were evaluated by the expanded disability status scale and progression free survival. No maintenance treatment was administered during a median follow-up of 39 months （range, 6 to 59 months）. Results No death occurred following the treatment. The overall confirmed progression free survival rate was 77% up to 59 months after transplantation which was significantly higher compared with pre-transplantation （P=0.000）. Thirteen patients （59%） had remarkable improvement in neurological manifestations, four （18%） stabilized their disability status and five （23%） showed clinical recurrence of active symptoms. Conclusions ASCT as a therapy is safe and available. It can improve or stabilize neurological manifestations in most patients with progressive MS following failure of conventional therapy.

Neuroinflammation in cortical and meningeal pathology in multiple sclerosis:understanding from animal models

Multiple sclerosis(MS)is a neurodegenerative and inflammatory disease usually presenting with acute demyelinating events that can start as,or progress to,chronic damage.The development of animal experimental models,specific for each stage of MS will aid in the design of new drugs specific for the different forms of the disease.Animal models of experimental autoimmune encephalomyelitis successfully reflect the pathophysiological mechanisms of the early phases of MS.However,few models resemble the features of the progressive forms of MS such as cortical demyelination and meningeal inflammation.Recently,a few auspicious animal models recapitulating many of the characteristics of progressive MS,aimed at a better understanding of the pathology of these forms of the disease,have been developed.In this review,we will summarize the latest developments in animal models reflecting the cortical and meningeal pathological features of progressive MS,as well as their response to drugs specifically targeting these forms.