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1.1  Introduction  

It  has  long  been  known  that  cells  express  all  their  functions  in  response   to   stimuli   deriving   from   the   surrounding   microenvironment;   these   stimuli   can   be  electrical  (galvanotaxis),  chemical  (chemotaxis)  and  mechanical  (durotaxis).  

In  biology  such  stimuli  are  often  characterized  by  gradients,  which  represent  the   variation   of   a   certain   physical   constant   in   space   and   time,   such   as   electrical   charge,  chemical  species  or  in  the  case  of  the  mechanical  properties  variation  in   stiffness.    

1.1.1  Durotaxis  

Durotaxis   describes   cells   movement   as   consequence   of   substrate  

stiffness,  for  example  moving  from  the  soft  to  the  stiff  side  of  a  material.  A  very  

interesting  study  done  by  Lo  et  al.  [1],  showed  that  cell  movement  is  guided  by  

the  rigidity  of  the  underlying  substrate.  By  plating  NIH/3T3  fibroblasts  on  PA  gel  

substrates,  which  had  a  transition  in  the  rigidity,  they  showed  that  cells  from  the  

soft   side   could   easily   migrate   to   the   stiff   side   of   the   gel   while   simultaneously  

increasing  their  area  on  the  stiff  side.  However,  the  reverse  of  this  phenomenon  

was  not  true.  Cells,  which  were  present  on  the  stiff  side  of  the  gel,  turned  around  

or  retracted  as  they  reached  the  boundary  and  never  crossed  the  boundary  to  go  

to  the  soft  side  of  the  gel.  As  cell  migration  or  movement  plays  a  critical  role  in  

many  physiological  processes  like  wound  healing,  immune  response,  and  tissue  

morphogenesis   this   study   highlighted   the   importance   of   substrate   rigidity   in  

controlling  cell  locomotion.  


1.1.2  Chemotaxis  

Chemotaxis  describes  the  cellular  movement  of  cells  when  they  move  up   or  down  a  chemical  gradient  [2].  This  movement  allows  the  cells  to  explore  their   extracellular   environment.   Cells   move   randomly,   away   from   repellents   and   towards   attractants.   Questions   have   arisen   on   how   cells   can   detect   small   changes   in   their   extracellular   environment.   Usually   the   cells   will   undergo   a   random   walk,   consisting   of   smooth   swimming   and   brief   direction   changes   (tumbles).  By  increasing  the  attractant,  the  tumbling  is  suppressed,  which  leads   to   a   biased   random   walk.   Chemotaxis   movement   are   widely   study   in   many   biological   aspects   such   as   movements   of   melanocyte   cells   toward   a   particular   hormone  [3]  or  to  study  the  cell  movements  occurring  in  morphogenesis  [2].  

1.1.1  Galvanotaxis  

The   movement   of   cells   due   to   an   electric   field   is   called   galvanotaxis.  

Normal  physiological  range  of  electric  fields  is  between  2  and  600  V/m  [3].  It  has   been   shown   that   cells   in   vitro   can   react   to   an   electric   field   up   to   1000   V/m.  

Electric  fields  in  the  body  are  considered  to  be  caused  by  ions,  such  as  sodium,   potassium   and   chloride   [4-­‐5].   Their   concentrations   vary   over   space   and   time.  

These  different  concentrations  can  be  presented  between  hours  and  days.  This  is   considered  to  give  rise  to  galvanotaxic  behaviour.  There  are  several  examples  of   where   galvanotaxis   could   be   a   reason   of   cell   movement   in   the   body.   Some   examples  are  embryo  development,  directing  nerve  cell  growth,  wound  healing,   angiogenesis,   directing   metastatic   cancer   cells   [4-­‐6].   It   has   been   seen   that   different   cell   types   respond   differently   to   an   applied   electric   field,   which   then   could  be  used  to  separate  cells  [6].  A  large  interest  has  been  shown  to  see  the   effects   of   galvanotaxis   in   the   area   of   cancer   and   its   metastatic   behaviour.  

Metastasis   is   where   cancer   cells   move   from   the   original   tumour   to   form  

daughter  tumours.  The  connection  between  galvanotaxis  and  metastasis  is  that  


it  has  been  shown  that  highly  metastatic  cancer  cells  give  a  stronger  response  to   an  electric  field  than  healthy  or  weakly  metastatic  cancer  cells  [5].  

1.2  Stiffness  has  a  biological  role  

Cells   sense   and   respond   to   differences   in   substrate   rigidity,   which   has   been   shown   to   influence   behaviours   such   as   growth   [7-­‐9]   and   differentiation   [10-­‐12].   However   details   of   the   mechano-­‐chemical   mechanisms   have   not   been   fully  elucidated.  

In  any  case,  it  is  accepted  that  a  major  role  in  cells  regulation  is  played  by   the   stiffness   of   the   tissue   in   which   cells   reside.   The   stiffness   of   an   object   is   characterized  by  its  ability  to  resist  deformation,  and  is  generally  defined  by  its   Young’s  modulus  or  elastic  modulus  [13].  A  rigid  substrate  resists  deformation   more  readily  than  a  soft  substrate  and  thus  possesses  a  larger  elastic  modulus.  

The  elastic  modulus  (E)  of  a  substrate  can  be  determined  by  applying  force  to  it   (stress),  and  then  measuring  the  resulting  change  in  length  (strain).  The  stiffness   of   tissues   within   the   body   varies   greatly,   with   brain   tissue   being   among   the   softest   (several   hundred   Pa)   and   mineralized   bone   among   the   most   rigid   (several  million  kPa)  (Figure  1)  [14].  




Figure  1:  Range  of  stiffness  of  biological  tissues.  Soft  tissues  within  the  human  body  range   from  0.1  kPa  up  to  100  kPa.  Brain  tissue  is  one  of  the  softest  tissues,  and  bone  is  the  



In  multicellular  organisms,  and  specifically  in  tissues,  cells  function  may  


happens:   during   development   [15],   with   the   progression   of   diseases   including   cancer   [16],   fibrosis   [17],   and   atherosclerosis   [18],   and   during   aging   [19-­‐20].  

Diseases  often  result  in  the  stiffening  of  the  tissue:  tumour  formation  and  tissue   fibrosis  markedly  increasing  tissue  stiffness  mostly  due  to  collagen  production.  

For  example,  healthy  adipose  tissue  ranges  from  0.2-­‐2  kPa,  but  as  a  breast  tumor   develops,   the   surrounding   tissues   increase   in   stiffness   to   4-­‐12   kPa   [16,20-­‐21].  

An   increase   in   tissue   stiffness   can   also   correlate   with   the   degree   of   disease   progression.  For  example,  Yin  et  al.  reported  a  correlation  between  the  stiffness   of  liver  tissue  and  the  progression  of  fibrosis,  starting  with  measurements  of  2   kPa  for  normal  liver  up  to  12  kPa  for  the  most  advanced  stages  of  fibrosis  [22].  

Tissue   rigidity   plays   an   important   role   in   cancer   development,   progression   and   metastasis,   with   increased   rigidity   promoting   an   oncogenic   phenotype   [14,16].   Tumours   often   result   in   an   increase   in   tissue   stiffness,   and   this  characteristic  is  commonly  used  to  detect  their  presence  [24-­‐25].  Increased   tumour  rigidity  has  been  found  to  correlate  with  an  increase  in  metastasis  [26-­‐

27]  and  a  decrease  in  successful  treatment  [28].    

Importantly  the  value  of  the  stiffness  is  not  homogeneous  in  space,  and  as   exemple   there   are   some   tissues   [29-­‐30]   that   possess   a   spatial   distribution   of   stiffness.   In   pathological   conditions   changes   in   the   extra   cellular   matrix   (ECM)   composition  were  observed:  the  normal  distribution  of  protein,  such  as  collagen   or   fibronectin,   was   modified   resulting   in   an   increased   deposition   of   ECM   proteins,   thus   and   increase   in   stiffness.   For   example   stiffening   of   tumorogenic   tissue  is  largely  due  to  an  increase  in  the  deposition  and  crosslinking  of  collagen   [14,31-­‐32];  however,  the  amount  of  other  ECM  proteins  such  as  fibronectin  have   also   been   found   to   dramatically   increase   in   breast   tumours   [33-­‐34],   and   fibronectin   has   been   implicated   in   the   progression   of   other   cancers,   including   prostate  cancer,  melanoma,  and  lung  carcinoma  [35-­‐36].    

As   already   stated,   there   are   examples   of   stiffness   variation   in   tissues  

during  aging  processes.  Cosgrove  at  al.  and  Keung  et  al.  report  an  increment  in  


mechanical   properties   associated   with   aged   skeletal   muscles   and   in   brain   [19-­‐


Stiffness  gradients  within  tissues  can  result  from  pathological  conditions,   but   also   occur   through   normal   variations.   For   example   the   tissues   stiffness   varies   naturally   at   interfaces,   e.g.   hard,   calcified   bones   are   connected   to   soft   cartilage  or  as  MSCs  egress  from  bone  marrow  and  hone  to  these  interfaces  or   migrate  through  tissue  [37],  they  may  encounter  such  stiffness  gradient(s),  and   it  is  not  clear  whether  the  MSC  response  to  these  stimuli  is  to  remain  in  place   and  differentiate,  as  with  static  materials  [11],  [38]  or  migrate  in  response  to  the   stiffness  gradient  as  with  fibroblasts  [1-­‐39].  

1.3  Aim  of  this  Work  

All   the   cellular   behaviour   presented   above   are   influenced   by   tissues   stiffness,  and  for  this  reason  the  generation  of  systems  able  to  reproduce  such   stiffness   variation   allow   a   more   representative   reconstruction   of   the   pathophysiological  state.  An  ideal  approach  would  also  include  an  achievement   of  stiffness  variation  using  the  same  mechanism  as  it  happens  in  a  specific  area   of   interest   of   the   target   tissue.   In   any   case,   obtaining   a   surface   with   a   known   variation  of  mechanical  properties  in  space  represents  an  ideal  platform  for  the   study  of  several  cellular  responses,  such  as  migration  and  or  differentiation.    

In   order   to   fabricate   engineered   microsystems   resembling   the   pathophysiological   state   of   a   target   tissue,   the   aim   of   this   thesis   is   the   development   of   a   milli-­‐sized   substrate   with   controlled   stiffness   at   the   micro-­‐

scale.   Hydrogels   will   be   used   for   its   capacities   to   reproduce   the   mechanical  

properties  of  soft  tissue  and  for  their  easiness  in  tune  the  resultant  stiffness.  By  

increasing   the   number   of   cross-­‐linking   using   a   cross-­‐linker   molecule   it   is  

hypothesised  to  control  the  overall  stiffness.  Moreover  to  replicate  the  stiffness  

gradients  of  soft  tissues  (elastic  modulus  ranging  between  1–12  kPa)  in  a  micro-­‐


scaled  manner  (with  a  stiffness  rate  of  about  2.5  kPa/mm),  an  inkjet  system  is   used  in  this  work  to  modify  such  hydrogels.    

Starting   from   the   theoretical   aspects   necessary   to   improve   the  

mechanical   properties   of   the   hydrogel   (i.e.   use   of   cross-­‐linker   molecule),   a  

prediction   of   the   physical   variables   of   the   system   will   be   characterized   by   the  

implementation   of   computational   models,   describing   and   controlling   the  

reaction   and   diffusion   of   a   crosslinking   molecule   within   a   hydrogel   domain  

(monitoring   the   concentration   as   function   of   time   and   space).   Afterwards  

experimental  tests  will  be  performed  to  validate  the  solutions  obtained  by  these  

models.   Particular   attention   will   be   then   dedicated   to   the   generation   of  

concentration  profile  in  space  (among  a  single  axis)  on  the  surface  of  a  hydrogel  

substrate.   The   concentration   profile   will   lead   to   obtain   hydrogel   with   a  

crosslinking   density   able   to   promote   a   material   stiffening   in   the   range   of   soft  

tissues   mechanical   properties   (1–12   kPa).   Again,   once   a   computational   model  

will  return  the  most  suitable  initial  conditions  to  be  used  to  generate  the  desired  

gradient,   this   will   be   experimentally   validated   using   the   same   procedure   used  

before   (assessing   a   fine   control   over   the   crosslinking   density   and   its   spatial  

distribution,   pixel   size   <   1   μm).   Finally,   mechanical   tests   will   be   performed   on  

several  hydrogels  to  measure  the  elastic  modulus  as  function  of  the  crosslinking  

degree.  In  this  way  it  will  be  possible  to  design  functionalized  substrates  having  

a  known  cross-­‐linker  concentration,  thus  a  spatially  distributed  elastic  modulus  

in  a  specific  mechanical  range.  



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