<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02249793</url>
  </required_header>
  <id_info>
    <org_study_id>817759</org_study_id>
    <nct_id>NCT02249793</nct_id>
  </id_info>
  <brief_title>Exploratory Study of Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics</brief_title>
  <official_title>Exploratory Study in Healthy Volunteers to Define Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Pennsylvania</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Ginger.io</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Pennsylvania</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      As citizens of the information age, humans leave digital traces of behavior in their&#xD;
      communication and movement patterns through our cell phone. The Global Positioning System&#xD;
      (GPS) technology tracks the way persons commute to school or work or when visiting family and&#xD;
      friends. Circadian rhythmicity describes the concept that many of the bodily functions follow&#xD;
      a roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best&#xD;
      during daytime while humans rest and sleep during nighttime. The current study wishes to look&#xD;
      for a relationship between patterns in participants' cell phone use (Android only at this&#xD;
      point) and several of their bodily functions.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Cell phones with internet access (so-called smartphones) represent a rich source for user&#xD;
      activity data. Each time one places a call, sends a text message, or uses an app, a data&#xD;
      trace is being produced which overall reflects the user's social activity and behavior. This&#xD;
      data is called 'social sensing data'. Researchers connected this type of data to the health&#xD;
      status of the person operating the cell phone. An example is that an outbreak of seasonal flu&#xD;
      may lead to fewer calls and text messages among cell phone users. Thus, the social sensing&#xD;
      data may show for example how severe an outbreak is and how fast it is spreading.&#xD;
&#xD;
      &quot;Circadian rhythmicity&quot; describes the concept that many of the bodily functions follow a&#xD;
      roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best&#xD;
      during daytime while rest and sleep occurs during nighttime. A disturbance of this pattern,&#xD;
      for example by regular nightshift work, may lead to an increased disease risk, such as for&#xD;
      the cardiovascular system, the heart and blood vessels. Natural factors within a body produce&#xD;
      our 24-hour rhythm. This rhythm is affected by outside cues such as sunlight. Jet lag is a&#xD;
      short-term form of a disturbed 24-hour rhythm. When a person travels fast through several&#xD;
      time zones, by plane for example from the East to the West Coast of the US, s/he arrives with&#xD;
      a time difference of 3 hours. Upon arrival, the body runs still at East Coast time, but is&#xD;
      exposed to the environmental cues following the West Coast time, which may make the person&#xD;
      feel groggy and disoriented at first. Within a couple of days the body time usually adjusts&#xD;
      and the complaints discontinue.&#xD;
&#xD;
      The current study wishes to look for a relationship between patterns in the participant's&#xD;
      cell phone use (Android only at this point) and several of the bodily functions. As bodily&#xD;
      functions the investigators will measure blood pressure and breakdown products (metabolites)&#xD;
      in urine, blood and saliva samples. The investigators will collect stool samples and use&#xD;
      swabs to collect the microbes inhabiting the mouth as well as the rectum. The investigators&#xD;
      will also measure messenger ribonucleic acid (mRNA), messenger products of the participant's&#xD;
      heritable information, in the blood. A cell phone application called &quot;Ginger.io&quot; will collect&#xD;
      the participants' cell phone usage information. This application will also ask the&#xD;
      participant several questions during the installation, during participation as well as at the&#xD;
      end. Furthermore, the investigators will ask the participant about the dietary intake and&#xD;
      habits.&#xD;
&#xD;
      The aim is to learn how the 24-hour rhythm is connected to the social activity and behavior&#xD;
      as well as blood pressure and metabolites as markers for the health status.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>September 2014</start_date>
  <completion_date type="Actual">December 2017</completion_date>
  <primary_completion_date type="Actual">December 2017</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Calls and Text Messages</measure>
    <time_frame>3-4 months</time_frame>
    <description>Aggregate communication as behavioral features has been collected using the cell phone data streams.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes Over Time in Ambulatory Blood Pressure - Systolic Blood Pressure</measure>
    <time_frame>48 hours</time_frame>
    <description>Ambulatory blood pressure monitoring</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Percentage of Total Metabolites</measure>
    <time_frame>48 hours</time_frame>
    <description>Percentage of metabolites displaying different abundances in biosamples collected during the morning hours versus evening hours. Analysis was performed for all participants as a group.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Mobility Radius</measure>
    <time_frame>3-4 months</time_frame>
    <description>The approximate radius of an imaginary circle encompassing the various locations that a user has traveled across on a particular day (in miles)</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Calls</measure>
    <time_frame>3-4 months</time_frame>
    <description>Number of phone calls placed and received</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes Over Time in Ambulatory Blood Pressure - Diastolic Blood Pressure</measure>
    <time_frame>48 hours</time_frame>
    <description>Ambulatory blood pressure monitoring</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Unanswered Calls</measure>
    <time_frame>3-4 months</time_frame>
    <description>The number of calls unanswered.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Unique Contacts</measure>
    <time_frame>3-4 months</time_frame>
    <description>The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Call Duration</measure>
    <time_frame>3-4 months</time_frame>
    <description>The duration of calls (made + received)</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Text Message Length</measure>
    <time_frame>3-4 months</time_frame>
    <description>The total length of all sms messages (sent + received) in characters</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Text Messages</measure>
    <time_frame>3-4 months</time_frame>
    <description>The number of sms messages (sent + received)</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Self-reported Sleep Times [Survey]</measure>
    <time_frame>3-4 months</time_frame>
    <description>Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Time Asleep</measure>
    <time_frame>3-4 months</time_frame>
    <description>Hours asleep per each 24 hour period measured by actigraphy</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Physical Activity</measure>
    <time_frame>3-4 months</time_frame>
    <description>Difference in locomotion between wake and sleep times</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes Over Time in Nutrient Intake - Energy</measure>
    <time_frame>48 hours</time_frame>
    <description>Nutrient intake will be measured using food photography</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH</measure>
    <time_frame>48 hours</time_frame>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome</measure>
    <time_frame>48 hours</time_frame>
    <description>Analysis was performed for all participants as a group.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours</measure>
    <time_frame>48 hours</time_frame>
    <description>Analysis was performed for all participants as a group.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes Over Time in Kidney Function</measure>
    <time_frame>48 hours</time_frame>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">6</enrollment>
  <condition>Healthy</condition>
  <arm_group>
    <arm_group_label>Study group</arm_group_label>
    <description>Healthy volunteers</description>
  </arm_group>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Whole blood, serum, plasma, urine, stool, and mucosal swabs from nose, mouth and rectum&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Healthy volunteers&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Volunteers must be in good health as based on medical history, physical examination,&#xD;
             vital signs, and laboratory tests as deemed by PI;&#xD;
&#xD;
          -  Volunteers are capable of giving informed consent;&#xD;
&#xD;
          -  25-35 years of age;&#xD;
&#xD;
          -  Own a cell phone with internet access (smartphone with Android operating system only&#xD;
             at this point) which installs the social sensing application ginger.io;&#xD;
&#xD;
          -  Non-smoking;&#xD;
&#xD;
          -  Male subjects only if feasible during recruitment; and&#xD;
&#xD;
          -  In case female volunteers are invited to enroll: non-pregnant, female subjects must&#xD;
             consent to a urine pregnancy test.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Recent travel across time zones (within the past month);&#xD;
&#xD;
          -  Planned travel across time zones during the planned study activities;&#xD;
&#xD;
          -  Volunteers with irregular work hours, e.g. night shifts.&#xD;
&#xD;
          -  Use of illicit drugs;&#xD;
&#xD;
          -  Subjects, who have received an experimental drug, used an experimental medical device&#xD;
             within 30 days prior to screening, or who gave a blood donation of ≥ one pint within 8&#xD;
             weeks prior to screening.&#xD;
&#xD;
          -  Subjects with any abnormal laboratory value or physical finding that according to the&#xD;
             investigator may interfere with interpretation of the study results, be indicative of&#xD;
             an underlying disease state, or compromise the safety of a potential subject.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>25 Years</minimum_age>
    <maximum_age>35 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Carsten Skarke, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Pennsylvania</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Garret A FitzGerald, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Pennsylvania</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Aalim Weljie, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Pennsylvania</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania</name>
      <address>
        <city>Philadelphia</city>
        <state>Pennsylvania</state>
        <zip>19104</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>https://zenodo.org/communities/human-chronobiome/?page=1&amp;size=20</url>
    <description>Zenodo data repository</description>
  </link>
  <results_reference>
    <citation>Skarke C, Lahens NF, Rhoades SD, Campbell A, Bittinger K, Bailey A, Hoffmann C, Olson RS, Chen L, Yang G, Price TS, Moore JH, Bushman FD, Greene CS, Grant GR, Weljie AM, FitzGerald GA. A Pilot Characterization of the Human Chronobiome. Sci Rep. 2017 Dec 7;7(1):17141. doi: 10.1038/s41598-017-17362-6.</citation>
    <PMID>29215023</PMID>
  </results_reference>
  <verification_date>January 2020</verification_date>
  <study_first_submitted>March 25, 2014</study_first_submitted>
  <study_first_submitted_qc>September 25, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">September 26, 2014</study_first_posted>
  <results_first_submitted>October 1, 2018</results_first_submitted>
  <results_first_submitted_qc>January 5, 2020</results_first_submitted_qc>
  <results_first_posted type="Actual">January 18, 2020</results_first_posted>
  <last_update_submitted>January 5, 2020</last_update_submitted>
  <last_update_submitted_qc>January 5, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">January 18, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Pennsylvania</investigator_affiliation>
    <investigator_full_name>Carsten Skarke, MD</investigator_full_name>
    <investigator_title>Research Assistant Professor</investigator_title>
  </responsible_party>
  <keyword>circadian</keyword>
  <keyword>oscillation</keyword>
  <keyword>clock</keyword>
  <keyword>human</keyword>
  <keyword>social behavior</keyword>
  <keyword>cell phone with internet access (so-called smartphone)</keyword>
  <keyword>social sensing</keyword>
  <keyword>behavioral feature</keyword>
  <keyword>Ginger.io</keyword>
  <keyword>blood pressure</keyword>
  <keyword>metabolism</keyword>
  <keyword>metabolomics</keyword>
  <keyword>gut bacteria</keyword>
  <keyword>microbiome</keyword>
  <provided_document_section>
    <provided_document>
      <document_type>Informed Consent Form</document_type>
      <document_has_protocol>No</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>July 11, 2014</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/93/NCT02249793/ICF_000.pdf</document_url>
    </provided_document>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>July 11, 2014</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/93/NCT02249793/Prot_SAP_001.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <recruitment_details>Study Started 9/24/14, Ended 3/11/15 located at the Clinical and Translational Research Center, CTRC located at the University of Pennsylvania Hospital</recruitment_details>
      <group_list>
        <group group_id="P1">
          <title>Session 1, 48-hour</title>
          <description>Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 &amp; 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Session 1, 48-hours Healthy Volunteers</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="6"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="6"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
              </participants_list>
            </milestone>
          </milestone_list>
        </period>
        <period>
          <title>Session 2, 48-Hours Healthy Volunteers</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="6"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="6"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
              </participants_list>
            </milestone>
          </milestone_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Male Healthy Volunteers</title>
          <description>Males</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="6"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>&lt;=18 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Between 18 and 65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="6"/>
                  </measurement_list>
                </category>
                <category>
                  <title>&gt;=65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="6"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Ethnicity (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Not Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="6"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Race (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>American Indian or Alaska Native</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Asian</title>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Native Hawaiian or Other Pacific Islander</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Black or African American</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>White</title>
                  <measurement_list>
                    <measurement group_id="B1" value="3"/>
                  </measurement_list>
                </category>
                <category>
                  <title>More than one race</title>
                  <measurement_list>
                    <measurement group_id="B1" value="2"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Calls and Text Messages</title>
        <description>Aggregate communication as behavioral features has been collected using the cell phone data streams.</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Calls and Text Messages</title>
          <description>Aggregate communication as behavioral features has been collected using the cell phone data streams.</description>
          <units>Calls and text messages</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="18.7" lower_limit="0" upper_limit="166"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.9" lower_limit="0" upper_limit="84"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Changes Over Time in Ambulatory Blood Pressure - Systolic Blood Pressure</title>
        <description>Ambulatory blood pressure monitoring</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Changes Over Time in Ambulatory Blood Pressure - Systolic Blood Pressure</title>
          <description>Ambulatory blood pressure monitoring</description>
          <units>mmHg</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Difference Day versus Night</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="20.7" spread="3.9"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="126.1" spread="10.6"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Asleep</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="106.8" spread="11.6"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Percentage of Total Metabolites</title>
        <description>Percentage of metabolites displaying different abundances in biosamples collected during the morning hours versus evening hours. Analysis was performed for all participants as a group.</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Percentage of Total Metabolites</title>
          <description>Percentage of metabolites displaying different abundances in biosamples collected during the morning hours versus evening hours. Analysis was performed for all participants as a group.</description>
          <units>percent</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Plasma metabolome</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="5.4"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Saliva metabolome</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="5.6"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Mobility Radius</title>
        <description>The approximate radius of an imaginary circle encompassing the various locations that a user has traveled across on a particular day (in miles)</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Mobility Radius</title>
          <description>The approximate radius of an imaginary circle encompassing the various locations that a user has traveled across on a particular day (in miles)</description>
          <units>miles</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="6.8" lower_limit="0" upper_limit="193.4"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Calls</title>
        <description>Number of phone calls placed and received</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Calls</title>
          <description>Number of phone calls placed and received</description>
          <units>Calls</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="2.7" lower_limit="0" upper_limit="48"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.1" lower_limit="0" upper_limit="10"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Changes Over Time in Ambulatory Blood Pressure - Diastolic Blood Pressure</title>
        <description>Ambulatory blood pressure monitoring</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Changes Over Time in Ambulatory Blood Pressure - Diastolic Blood Pressure</title>
          <description>Ambulatory blood pressure monitoring</description>
          <units>mmHg</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Difference Day versus Night</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="20.7" spread="3.3"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="78.5" spread="9.1"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Asleep</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="58.8" spread="10.2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Unanswered Calls</title>
        <description>The number of calls unanswered.</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Unanswered Calls</title>
          <description>The number of calls unanswered.</description>
          <units>Unanswered calls</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.6" lower_limit="0" upper_limit="9"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.03" lower_limit="0" upper_limit="2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Unique Contacts</title>
        <description>The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Unique Contacts</title>
          <description>The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity</description>
          <units>Unique contacts</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7.2" lower_limit="0" upper_limit="71"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.5" lower_limit="0" upper_limit="29"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Call Duration</title>
        <description>The duration of calls (made + received)</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Call Duration</title>
          <description>The duration of calls (made + received)</description>
          <units>Seconds</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="820.4" lower_limit="0" upper_limit="16590"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="22.0" lower_limit="0" upper_limit="3162"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Text Message Length</title>
        <description>The total length of all sms messages (sent + received) in characters</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Text Message Length</title>
          <description>The total length of all sms messages (sent + received) in characters</description>
          <units>n (characters)</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="868.0" lower_limit="0" upper_limit="14840"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="47.0" lower_limit="0" upper_limit="3089"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Text Messages</title>
        <description>The number of sms messages (sent + received)</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Text Messages</title>
          <description>The number of sms messages (sent + received)</description>
          <units>messages</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="16.0" lower_limit="0" upper_limit="166"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.8" lower_limit="0" upper_limit="75"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Self-reported Sleep Times [Survey]</title>
        <description>Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Session 1, 48-hour</title>
            <description>Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 &amp; 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.</description>
          </group>
        </group_list>
        <measure>
          <title>Self-reported Sleep Times [Survey]</title>
          <description>Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.</description>
          <units>hour</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7.6" spread="2.9"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Time Asleep</title>
        <description>Hours asleep per each 24 hour period measured by actigraphy</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Time Asleep</title>
          <description>Hours asleep per each 24 hour period measured by actigraphy</description>
          <units>hours</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7.931449224" spread="0.7044404472"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Physical Activity</title>
        <description>Difference in locomotion between wake and sleep times</description>
        <time_frame>3-4 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Physical Activity</title>
          <description>Difference in locomotion between wake and sleep times</description>
          <units>Counts/min</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Awake</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1904.0" lower_limit="0" upper_limit="55757.7"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Sleeping</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="307.2" lower_limit="0" upper_limit="29642.7"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Changes Over Time in Nutrient Intake - Energy</title>
        <description>Nutrient intake will be measured using food photography</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Changes Over Time in Nutrient Intake - Energy</title>
          <description>Nutrient intake will be measured using food photography</description>
          <units>Kcals</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Session 1</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1967" spread="488"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Session 2</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1609" spread="601"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH</title>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH</title>
          <units>relative expression</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Morning</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="23.3" spread="13.5"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Evening</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="17.9" spread="9.4"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome</title>
        <description>Analysis was performed for all participants as a group.</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome</title>
          <description>Analysis was performed for all participants as a group.</description>
          <units>genera</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours</title>
        <description>Analysis was performed for all participants as a group.</description>
        <time_frame>48 hours</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Study Group</title>
            <description>Healthy volunteers</description>
          </group>
        </group_list>
        <measure>
          <title>Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours</title>
          <description>Analysis was performed for all participants as a group.</description>
          <units>Proteins</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Changes Over Time in Kidney Function</title>
        <time_frame>48 hours</time_frame>
        <population>Kidney function was done to evaluate healthy volunteers during Session 1 and 2. Delta was calculated between Session 1 and 2 and averaged across subjects. Note that values for session1 was missing for two subjects, meaning that below reported mean and standard deviation reflect changes for four subjects.</population>
        <group_list>
          <group group_id="O1">
            <title>Session 1, 48-hour</title>
            <description>Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 &amp; 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.</description>
          </group>
        </group_list>
        <measure>
          <title>Changes Over Time in Kidney Function</title>
          <population>Kidney function was done to evaluate healthy volunteers during Session 1 and 2. Delta was calculated between Session 1 and 2 and averaged across subjects. Note that values for session1 was missing for two subjects, meaning that below reported mean and standard deviation reflect changes for four subjects.</population>
          <units>mg/dL</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="6"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="12.925" spread="115.468246"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>1 year</time_frame>
      <desc>All non serious AE were resolved, Serious AE: None</desc>
      <group_list>
        <group group_id="E1">
          <title>Healthy Volunteers</title>
          <description>Males</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="6"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="6"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <default_vocab>0</default_vocab>
        <default_assessment>Non-systematic Assessment</default_assessment>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="1" subjects_at_risk="6"/>
              </event>
            </event_list>
          </category>
          <category>
            <title>General disorders</title>
            <event_list>
              <event>
                <sub_title>headache</sub_title>
                <description>0</description>
                <counts group_id="E1" events="2" subjects_affected="1" subjects_at_risk="6"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>Dr. Carsten Skarke</name_or_title>
      <organization>Upenn</organization>
      <phone>215-573-0673</phone>
      <email>cskarke@pennmedicine.upenn.edu</email>
    </point_of_contact>
  </clinical_results>
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02249793
org study id: 817759
nct id: NCT02249793
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
As citizens of the information age, humans leave digital traces of behavior in their
      communication and movement patterns through our cell phone. The Global Positioning System
      (GPS) technology tracks the way persons commute to school or work or when visiting family and
      friends. Circadian rhythmicity describes the concept that many of the bodily functions follow
      a roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best
      during daytime while humans rest and sleep during nighttime. The current study wishes to look
      for a relationship between patterns in participants' cell phone use (Android only at this
      point) and several of their bodily functions.
Cell phones with internet access (so-called smartphones) represent a rich source for user
      activity data. Each time one places a call, sends a text message, or uses an app, a data
      trace is being produced which overall reflects the user's social activity and behavior. This
      data is called 'social sensing data'. Researchers connected this type of data to the health
      status of the person operating the cell phone. An example is that an outbreak of seasonal flu
      may lead to fewer calls and text messages among cell phone users. Thus, the social sensing
      data may show for example how severe an outbreak is and how fast it is spreading.

      "Circadian rhythmicity" describes the concept that many of the bodily functions follow a
      roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best
      during daytime while rest and sleep occurs during nighttime. A disturbance of this pattern,
      for example by regular nightshift work, may lead to an increased disease risk, such as for
      the cardiovascular system, the heart and blood vessels. Natural factors within a body produce
      our 24-hour rhythm. This rhythm is affected by outside cues such as sunlight. Jet lag is a
      short-term form of a disturbed 24-hour rhythm. When a person travels fast through several
      time zones, by plane for example from the East to the West Coast of the US, s/he arrives with
      a time difference of 3 hours. Upon arrival, the body runs still at East Coast time, but is
      exposed to the environmental cues following the West Coast time, which may make the person
      feel groggy and disoriented at first. Within a couple of days the body time usually adjusts
      and the complaints discontinue.

      The current study wishes to look for a relationship between patterns in the participant's
      cell phone use (Android only at this point) and several of the bodily functions. As bodily
      functions the investigators will measure blood pressure and breakdown products (metabolites)
      in urine, blood and saliva samples. The investigators will collect stool samples and use
      swabs to collect the microbes inhabiting the mouth as well as the rectum. The investigators
      will also measure messenger ribonucleic acid (mRNA), messenger products of the participant's
      heritable information, in the blood. A cell phone application called "Ginger.io" will collect
      the participants' cell phone usage information. This application will also ask the
      participant several questions during the installation, during participation as well as at the
      end. Furthermore, the investigators will ask the participant about the dietary intake and
      habits.

      The aim is to learn how the 24-hour rhythm is connected to the social activity and behavior
      as well as blood pressure and metabolites as markers for the health status.
observational model: Cohort
time perspective: Prospective
measure: Calls and Text Messages
time frame: 3-4 months
description: Aggregate communication as behavioral features has been collected using the cell phone data streams.
measure: Changes Over Time in Ambulatory Blood Pressure - Systolic Blood Pressure
time frame: 48 hours
description: Ambulatory blood pressure monitoring
measure: Percentage of Total Metabolites
time frame: 48 hours
description: Percentage of metabolites displaying different abundances in biosamples collected during the morning hours versus evening hours. Analysis was performed for all participants as a group.
measure: Mobility Radius
time frame: 3-4 months
description: The approximate radius of an imaginary circle encompassing the various locations that a user has traveled across on a particular day (in miles)
measure: Calls
time frame: 3-4 months
description: Number of phone calls placed and received
measure: Changes Over Time in Ambulatory Blood Pressure - Diastolic Blood Pressure
time frame: 48 hours
description: Ambulatory blood pressure monitoring
measure: Unanswered Calls
time frame: 3-4 months
description: The number of calls unanswered.
measure: Unique Contacts
time frame: 3-4 months
description: The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity
measure: Call Duration
time frame: 3-4 months
description: The duration of calls (made + received)
measure: Text Message Length
time frame: 3-4 months
description: The total length of all sms messages (sent + received) in characters
measure: Text Messages
time frame: 3-4 months
description: The number of sms messages (sent + received)
measure: Self-reported Sleep Times [Survey]
time frame: 3-4 months
description: Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.
measure: Time Asleep
time frame: 3-4 months
description: Hours asleep per each 24 hour period measured by actigraphy
measure: Physical Activity
time frame: 3-4 months
description: Difference in locomotion between wake and sleep times
measure: Changes Over Time in Nutrient Intake - Energy
time frame: 48 hours
description: Nutrient intake will be measured using food photography
measure: Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH
time frame: 48 hours
measure: Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome
time frame: 48 hours
description: Analysis was performed for all participants as a group.
measure: Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours
time frame: 48 hours
description: Analysis was performed for all participants as a group.
measure: Changes Over Time in Kidney Function
time frame: 48 hours
arm group label: Study group
description: Healthy volunteers
Whole blood, serum, plasma, urine, stool, and mucosal swabs from nose, mouth and rectum
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 25 Years
maximum age: 35 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Carsten Skarke, MD
role: Principal Investigator
affiliation: University of Pennsylvania
last name: Garret A FitzGerald, MD
role: Principal Investigator
affiliation: University of Pennsylvania
last name: Aalim Weljie, PhD
role: Principal Investigator
affiliation: University of Pennsylvania
facility: 
country: United States
url: https://zenodo.org/communities/human-chronobiome/?page=1&size=20
description: Zenodo data repository
citation: Skarke C, Lahens NF, Rhoades SD, Campbell A, Bittinger K, Bailey A, Hoffmann C, Olson RS, Chen L, Yang G, Price TS, Moore JH, Bushman FD, Greene CS, Grant GR, Weljie AM, FitzGerald GA. A Pilot Characterization of the Human Chronobiome. Sci Rep. 2017 Dec 7;7(1):17141. doi: 10.1038/s41598-017-17362-6.
PMID: 29215023
responsible party type: Principal Investigator
investigator affiliation: University of Pennsylvania
investigator full name: Carsten Skarke, MD
investigator title: Research Assistant Professor
provided document: 
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 