Occupant Dynamics in Rollover Crashes: Influence of Roof Deformation and Seat Belt Performance on Probable Spinal Column Injury

Motor vehicle crashes are the leading cause of death in the United States for people ages 3–33, and rollover crashes have a higher fatality rate than any other crash mode. At the request and under the sponsorship of Ford Motor Company, Autoliv conducted a series of dynamic rollover tests on Ford Explorer sport utility vehicles (SUV) during 1998 and 1999. Data from those tests were made available to the public and were analyzed in this study to investigate the magnitude of and the temporal relationship between roof deformation, lap–shoulder seat belt loads, and restrained anthropometric test dummy (ATD) neck loads.
Introduction
Motor vehicle crashes are the leading cause of death in the United States for persons of every age from 3 through 33.18 Rollover crashes, in particular, have a higher fatality rate than any other crash mode. Of the 6,159,287 police reported crashes in 2005 in the United States, only 4.1% involved a rollover. Yet, rollovers accounted for 34.4% (10,816) of all passenger vehicle fatalities. The fatality rate (defined as deaths per 100,000 registered vehicles) in rollover crashes is more than two and one-half times higher in sport utility vehicles (SUVs) than in passenger cars (8.28 vs. 3.22, respectively). Another 149,406 individuals sustained serious injuries in rollover crashes in 2005, approximately 30% of whom were occupants of SUVs.18
Measurement tools are required to evaluate appropriate intervention strategies to reduce the mortality and morbidity associated with rollover crashes. The Abbreviated Injury Scale (AIS) and Harm value (HARM) are two such measures, which are used to compare injuries of different types and severities.9 The AIS reflects “threat to life” (or risk of death) and stratifies injuries into six categories (AIS 1–6) with AIS 6 defined as an “untreatable” injury. The maximum AIS (MAIS) score refers to the most severe injury sustained in a specific individual. The highest rate of seriously injured (MAIS 3+) children 4–12 years old occurs in rollovers, more than double any other crash mode.22 One study reported that despite the increased weight of SUVs, the risk of injury for children in SUVs was similar to that for passenger cars, which may be due to the increased tendency of SUVs to roll over.6 HARM is a mathematical measure that applies a weighting factor to each injured, yet surviving occupant, which includes both monetary costs of the injury (i.e., direct costs associated with the loss of wages) and comprehensive costs (i.e., monetary costs plus non-monetary costs).9,14 Importantly, the non-monetary costs include such measures as loss of functional capacity and quality of life. In rollover crashes, the highest HARM is reflected in the population of occupants who survive the crash, yet sustain catastrophic injury, including permanent brain and/or spinal cord injury.9
A major source of HARM in rollover crashes results from occupant contact with the vehicle roof, support pillars and side headers.9 According to Digges et al. “Countermeasures to reduce rollover casualties include increased belt use, and technological interventions to prevent ejection and reduce the severity of body contacts with the vehicle interior.”9 Hugh DeHaven outlined principles for designing vehicles for human transport in 1952, and stated that “the package (the passenger compartment) should not collapse under expected conditions of force, thereby exposing objects (and people) inside it to damage.”7 Closely related to this principle, DeHaven stated that “the packaging structures which shield the inner container must not be made of brittle or frail materials; they should resist force by yielding and absorbing energy applied to the outer container so as to cushion and distribute impact forces and thereby protect the inner container.”
Franchini11 reported the importance of maintaining the integrity of the occupant compartment (referred to as “survival space”) for belted occupants during a crash event. Few studies, however, have experimentally evaluated the influence of dynamic roof deformation with concomitant loss of occupant survival space as a potentially preventable cause of head and cervical spine injuries in rollover crashes. Bahling et al.1 conducted rollover and drop tests of late 1980s model Chevrolet Malibu passenger cars using lap–shoulder belted anthropomorphic test dummies (ATDs) to evaluate the influence of roof strength on injury mechanics. In several studies, Moffatt and other investigators reported on a customized, dynamic test procedure with controlled roof impacts of passenger vans and sedans.3,5,15 Both groups concluded that “potentially injurious impacts” (defined by these authors as 2000 N recorded by the ATD upper neck sensor) occurred prior to significant roof crush and that enhanced roof strength made no difference in the likelihood of serious neck injury to restrained occupants. These conclusions have been contradicted in other literature, albeit without the benefit of scientific data from comparable full-scale, dynamic rollover crash tests.12,13
Recently, the raw data from a series of full-scale, dynamic rollover tests of 1998–1999 model year Ford Explorer SUVs, using fully instrumented ATDs, were made publicly available to the scientific community.2 These tests were conducted using a standardized test methodology specified by Federal Motor Vehicle Safety Standard (FMVSS) 208 of the U.S. Department of Transportation (FMVSS 208 49 CFR Ch. V (10-01-04 Edition)). These data provide the first opportunity to analyze the dynamics of belted occupants within a contemporary SUV in a standardized rollover test environment.
The authors used the described data in the present study. The study’s objective was to investigate both the magnitude of and the temporal relationship between dynamic roof deformation, lap–shoulder seat belt loads, and restrained ATD neck loads in these FMVSS 208 dolly rollover tests of Ford Explorer SUVs.
Materials and Methods
Three full-scale dolly rollover tests of 1998–1999 Explorer SUVs were sponsored by Ford Motor Company and conducted at the North American Autoliv test facility1 according to the standardized FMVSS 208 test protocol. This standard, issued by the National Highway Transportation Safety Administration (NHTSA) in 1971, outlines vehicle crash performance requirements designed for improving occupant protection. Described within FMVSS 208 is a voluntary, dolly rollover test used to evaluate occupant protection during a lateral rollover. This standardized test procedure was used for all three SUV rollover tests.
The FMVSS 208 test procedure involves accelerating a rollover dolly carrying a test vehicle to a set velocity and then rapidly decelerating the dolly, causing the vehicle to release, trip, and enter a lateral roll. The SUVs were first placed on a dolly fixed with a rigid, angled platform positioned 9 in. from the ground and 23° from the horizontal. To assure that the roll was driver-side leading (i.e., that the driver’s side contacted the ground first), each vehicle was situated on the platform so that its driver’s side tires rested along a 4 in. lip at the forward edge of the test platform, as shown in Figs. 1a and 1b.
Figure 1(a) FMVSS 208 dynamic rollover pre-test setup of SUV test B190043 on a dolly rollover cart; (b) critical dimensions of FMVSS 208 dolly
The vehicle and dolly were then accelerated along a straight path perpendicular to the longitudinal axis of the vehicle. The dolly was then decelerated rapidly (minimum deceleration rate of 20 g for 0.04 s), resulting in vehicle trip and subsequent rollover. The target speed for all Explorer tests was 30 mph. The vehicle identification number (VIN) and actual dolly launch velocity for each of the three tests are summarized in Table 1.
Table 1Test conditionsAutoliv test numberTest descriptionData sampling rateSampling durationTest dateAccelerometerCoordinates (mm)XYZB190042FMVSS 208 Rollover (VIN1FMCU24E5VUC19292) (23°; 30.5 mph)20,000 Hz∼13,000 ms8/10/99Center of gravity2073.10−24.50975.00Driver’s rail at A-pillar2038.20−596.101770.0Driver’s rail at B-pillar2776.40−571.301863.30Driver’s rail at C-pillar3209.70−580.601871.40Passenger’s rail at A-pillar2011.80592.101758.60Passenger’s rail at B-pillar2786.60532.601857.10Passenger’s rail at C-pillar3234.40523.301868.20B190043FMVSS 208 Rollover (VIN1FMDU34E6VUB99290) (23°; 30.4 mph)20,000 Hz∼13,000 ms8/11/99Center of gravity2231.0−4.1761.3Driver’s rail at A-pillar2077.2−543.71626.8Driver’s rail at B-pillar2637.2−535.01644.0Driver’s rail at C-pillar3436.0572.41598.0Passenger’s rail at A-pillar2077.9573.51564.7Passenger’s rail at B-pillar2636.5569.71625.5Passenger’s rail at C-pillar3436.3−543.01617.6B180220FMVSS 208 Rollover (VIN1FMDU35P5VUC14510) (23°; 30.9 mph)12,500 Hz∼8000 ms12/10/98Center of gravity2231.0−4.1761.3Driver’s rail at A-pillar2077.2−543.71626.8Driver’s rail at B-pillar2637.2−535.01644.0Driver’s rail at C-pillar3436.0572.41598.0Passenger’s rail at A-pillar2077.9573.51564.7Passenger’s rail at B-pillar2636.5569.71625.5Passenger’s rail at C-pillar3436.3−543.01617.6
Vehicle and ATD Instrumentation
Triaxial and biaxial accelerometers were installed in each SUV to measure vehicle structural dynamics during the rollover tests. Accelerations were recorded at each of the following vehicle structure locations in coordinate systems consistent with SAE J211 guidelines (SAE J211-1 REV DEC03), as shown in Figs. 2a and 2b, and Table 1.Center of Gravity (CG) (x, y, z)Left (driver) roof rail at
A-pillar (y, z)B-pillar (y, z)C-pillar (y, z)Right (passenger) roof rail at
A-pillar (y, z)B-pillar (y, z)C-pillar (y, z)
Figure 2
(a) Exterior view of test vehicle indicating A, B, and C-pillars; (b) interior view of test vehicle—accelerometers were mounted at the roof rail-to-pillar junction at the A, B, and C-pillars for both driver and passenger sides of the Ford Explorer SUVs
In each test, two Hybrid III 50th percentile male, instrumented ATDs were placed in the front seats of Ford Explorer SUVs and restrained with lap–shoulder belts that were affixed with load cells. Time synchronized with all other sensors and cameras in the experimental setup, these load cells continuously recorded tensile forces in the webbing of the lap and shoulder belts. Both ATDs were positioned in their respective seats according to reference FMVSS 208 Dummy Positioning Procedure with the seats located in the mid-track position. Given that the vehicle was positioned to roll driver-side leading, the driver ATD represented the “near-side” occupant and the passenger ATD, the “far-side” occupant in this test series. The following sensor outputs were recorded continuously throughout each rollover test for both driver and passenger ATDs:Head CG acceleration (x, y, z)Upper Neck
Force (x, y, z)Moment (x, y, z)Lower Neck
Force (x, y, z)Moment (x, y, z)Chest
Acceleration (x, y, z)DeflectionPelvis Acceleration (x, y, z)Femur Force (Fz, right and left)
Dynamic motion of the SUVs was visually recorded by up to 10 high speed external cameras, which were time synchronized with the cart release trigger and imaged at 500 frames/s. (Fig. 3) Clocks that were positioned along the test track were visible in the external camera views throughout the roll sequence. Targets were affixed to the rear aspect of the driver and passenger ATD heads and were visible by the same camera monitoring the onboard time clock. Up to three onboard, high speed cameras recorded ATD kinematics as a function of time using the onboard clock, which was also time synchronized with the cart release trigger, external cameras, and electronic sensors affixed to both ATDs, the seat belts, and the SUV structure.
Figure 3External camera setup
With the cart positioned according to FMVSS 208 specifications, the data acquisition system was set up and armed for trigger. Time zero for all data acquisition was provided by a contact switch at both shock absorbers to indicate the start of cart deceleration. The data-sampling rates for each test are provided in Table 1.
Data Analysis
The raw ASCII sensor data retrieved from the ATD and vehicle-mounted transducers were filtered according to the SAE J211 channel filtering class (CFC) requirements to remove the effects of crash related noise on the sensor readings. Each CFC specifies that the channel frequency response lies within limits detailed in SAE J211. Neck forces, neck moments, and vehicle data were filtered at CFC 1000, CFC 600, and CFC 60 accordingly. Subsequently, the filtered vehicle acceleration data were transformed into a vehicle-fixed, center-of-gravity, coordinate system using MATLAB® (registered trademark of The Mathworks, Inc.). Roof rail accelerations were transformed by subtracting the center of gravity accelerations from each measurement as a function of time. The result of the transformations was the acceleration of the roof rail relative to the vehicle’s center of gravity. The transformed roof rail acceleration values provided insight into when and in what direction the rail was moving. Transformed data was then compared to the ATD neck and seat belt loads as a function of time. The accelerations recorded by the rail sensors were influenced by both vehicle rotation (angular velocity) and localized pillar deformation. The contribution due to vehicle rotation was made at a low frequency given that the peak roll rate of the vehicle at any time during the test interval (0–1000 ms) was approximately 350–400°/s (i.e., less than 2 Hz). Thus, all higher frequency accelerations were necessarily due to localized structural deformation.
The sensor outputs from the driver and passenger roof rail accelerometers positioned at the B-pillar were used as a quantitative definition of roof intrusion (i.e., “objective roof crush”) into the occupant survival space. The mathematically transformed driver and passenger roof rail acceleration tracings in the present study provided objective evidence of the time interval(s) when roof/pillar deformation occurred, and the time of deformation was corroborated through careful scrutiny of the high speed video images (“observable” roof crush). Objective roof crush in our study was defined under the following necessary, contemporaneous conditions:Vertical and/or lateral rail acceleration peak(s) “downward” and/or inboard toward the restrained ATDExternal camera video images consistent with SUV roof-to-ground contactOnboard camera video images consistent with a compromise in occupant survival space (i.e., reduced headroom)
Roof rail accelerations, seat belt loads and peak ATD axial neck force (Fz, axial compression/tension) and moments (My, chin-to-chest flexion, and Mx, ear-to-shoulder lateral bending) were compared to the high-speed video data to validate the correlation in time between the presence of objective roof crush and the development of peak ATD neck and seat belt loads.
Results
Results are presented and discussed for the first full second of the roll sequence for each of the three SUV tests, which includes the initial driver-side-to-ground contact and full roof contact, followed by the first passenger-side-to-ground contact.
In all three tests, the external high-speed cameras recorded continuous roof-to-ground contact from the first contact of the driver’s roof rail with the ground until the end of the 1000 ms period, which corresponded to approximately 5/8 roll. Onboard high speed video cameras recorded the front passenger compartment of each SUV, capturing the kinematics of the ATDs as well as the deformation of the roof header and side roof rails during the rollover event. These cameras recorded inboard displacement of roof rails (“observable” roof crush) of both driver and passenger-side roof rails during the respective roof rail-to-ground contact for all three tests. The onboard clock, which was recorded by the interior cameras, allowed for a time-synchronized comparison of this data to the sensor output of the ATD neck transducers and roof rail accelerometers.
In all three tests, the head of each lap–shoulder belt restrained ATD (driver and passenger) contacted the roof two or more times during the first 1000 ms roll interval as indicated by increased neck compression loads (negative Fz values) recorded by the ATDs’ upper neck sensor (Fig. 4). The time of occurrence of each peak neck load for the driver and passenger ATD head-to-roof contacts (the “Local Maximum” as well as the “Absolute Maximum” or “Peak” neck loads) was consistent with the onboard high speed video data. For each of the three tests, the time recorded by the onboard camera during observable ATD head-to-roof contact was within 3 ms of the time recorded by the neck sensors for peak neck loads. Peak axial neck force data (Fz) were measured by the ATDs’ upper neck sensors and the moment loads (My and Mx) were measured by the ATDs’ lower neck sensors (Table 2).
Figure 4Passenger upper neck Fz vs. time (Test B190042)Table 2Magnitudes of Local and Absolute maximum (Peak) neck loads (during time interval of continuous roof-to-ground contact)Test parameterDriverPassengerB190042B190043B180220B190042B190043B180220Max peak Fz (N)a−958−1962−1920−5933−3245NonebLocal peak (s), Fz−200−295−223−361−50200–260Max peak My (N m)5811094304178261Local peak (s), My2112–5412–2220–2410Max peak Mx (N m)−106−124−167689841Local peak (s), Mx−11 to −18n/a−20 to −4691219–21aFz was measured at the dummy upper neck load cell; My and Mx measured at the lower load cellbIn Test 180220, no absolute maximum Fz was identified as all peak neck compression loads were within the range of 200–260 N
The near-side (i.e., the driver) ATD recorded Peak axial neck compression (Fz) loads of −2000 N or less for all three tests. Peak neck flexion (My) loads for the driver ATD resulted in chin-toward-chest head motion and were within a range of 58–110 N m for all three tests. In contrast, the far-side (i.e., the passenger) ATD recorded Peak neck Fz values in the range of −3244 to −5933 N for two out of three tests. In Test B180220, no Absolute Maximum Fz value was identified as all Local Maxima compression loads were within the range of −200 to −260 N. The Peak neck flexion (My) loads, recorded by the passenger ATDs, resulted in chin-toward-chest head motion and ranged from 178 to 304 N m for all three tests. The Peak lateral neck bending ear-to-shoulder (Mx) loads ranged from 41 to 98 N m for the passenger ATD, and the driver experienced Mx load magnitudes in the range of −106 to −167 N m, for all three tests.
The time of occurrence of objective vertical and lateral roof crush was identified by the roof rail acceleration peak, for both the passenger and driver side roof rails in all three tests (Table 3). Objective roof crush occurred prior to the Absolute Maximum dummy neck loads (Fz, My, Mx) in each of the three tests for both driver and passenger ATDs (Table 3, Fig. 5). The far-side, passenger ATD recorded Peak neck loads within 10 ms following the time of occurrence of objective roof crush for all three tests. Peak neck loads for the near-side, driver ATD occurred up to 65 ms following the time of occurrence of objective roof crush for all three tests.
Table 3Time of occurrence (ms) of roof/pillar deformation and absolute maximum neck loadsTest parameterDriverPassengerB190042B190043B180220B190042B190043B180220Objective roof/pillar deformation (vertical acceleration peaks)497513510730∼600–800a742Objective roof/pillar deformation (lateral acceleration peaks)497513494496512495Peak Fzc533540516730764n/abPeak My533541517729764751Peak Mx537548540783774760aNo isolated spike in acceleration was noted; however, a sustained level of roof deformation is reflected in the roof rail tracings and the video footage for this testbNo isolated absolute maximum Fz value was noted, which differed significantly from the other “local” maximums. This was consistent with the very high peak My in this test, however, which was noted at 751 ms (see Table 2)cFz was measured at the upper neck load cell, whereas My and Mx were measured at the lower neck load cellsFigure 5Driver upper neck Fz vs. vertical acceleration of the driver rail at B-pillar (Test B190043)
Lap and shoulder belt loads were recorded for both driver and passenger ATDs in all three tests, with the exception of the driver’s shoulder belt for test B190043 and passenger shoulder belt for test B180220, both of which experienced sensor failures (Table 4). The Peak lap belt loads for the near-side, driver ATD occurred within 1 ms of the time of Peak Fz and My neck loads for two out of three tests (Figs. 6, 7). In the remaining test (B190042), the Peak lap belt load occurred 22 ms prior to the time that peak neck Fz and My neck loads occurred in the driver ATD. In contrast, the far-side, passenger ATDs’ Peak lap belt loads occurred 65–131 ms prior to the time of Peak neck compression (Fz) for two out of three tests and 65–145 ms prior to the time of Peak neck flexion (My) for all three tests (Fig. 8). In Test B180220, the passenger’s Peak lap belt load occurred 6 ms after the time of Peak neck compression, yet 145 ms before the Peak neck flexion load (My).
Table 4Peak belt loads compared to belt loads at time of absolute maximum (peak) neck loadsTest parameterDriverPassengerB190042B190043B180220B190042B190043B180220Peak lap belt (N)548 (511 ms)795 (540 ms)940 (515 ms)797 (599 ms)705 (699 ms)779 (606 ms)Peak shoulder belt (N)395 (379 ms)N/Aa410 (373 ms)899 (587 ms)953 (689 ms)N/AaPeak FzLap belt (N)398 (533 ms)789 (540 ms)937 (516 ms) 359 (730 ms)115 (764 ms)771 (600 ms)Shoulder belt (N) 231 (533 ms)N/Aa236 (516 ms)337 (730 ms)426 (764 ms)N/AaPeak My(N m)Lap belt (N)393 (533 ms) 785 (541 ms)937 (517 ms)361 (729 ms)115 (765 ms) 218 (751 ms) Shoulder belt (N) 227 (533 ms)N/Aa236 (517 ms)341 (729 ms)417 (764 ms)N/AaaData not available due to transducer failureFigure 6Driver lap belt and neck load vs. time (Test B190043)Figure 7Inverted 50th percentile Hybrid III Driver ATD “diving” into roof with lap and shoulder belt providing restraining forces, which reduces neck loadFigure 8(a) Roof crush—passenger lap belt and neck load vs. time (Test B190043); (b) Roof crush—passenger shoulder belt and neck load vs. time (Test B190043)
The driver ATDs’ Peak lap belt loads ranged from 548 to 940 N for the three tests, and the shoulder belt loads were 395–410 N for two tests (the driver’s shoulder belt sensor failed on Test B190043) (Table 4). The passenger ATDs’ Peak lap belt loads were similar to those of the driver ATDs’, ranging from 705 to 797 N for all three tests; the shoulder belt loads were 899–953 N for two of three tests (the passenger’s shoulder belt sensor failed on test B180220).
The near-side, driver ATD lap belt loads at the time of occurrence of the Peak Fz and My neck loads were 72–99% of the ATDs’ respective Peak lap belt load for all three tests (Table 4). In contrast, the far-side, passenger ATD lap belt loads at the time of occurrence of the Peak neck compression (Fz) were less than 45% of the passenger ATDs’ respective Peak lap belt load recorded for two of the three tests. At the time of Peak neck flexion (My), the lap belt loads were less than 45% of the Peak lap belt load for all three tests. Shoulder belt loads for both driver and passenger ATDs at the time of occurrence of the Peak neck Fz and My were 37–58% of the ATDs’ respective Peak shoulder belt loads for two of three tests (load cells malfunctioned in the driver’s shoulder belt in test B190043 and passenger’s shoulder belt in test B180220).
Discussion
The three rollover tests of 1998–1999 Ford Explorer SUVs analyzed in the present study represent a unique dataset evaluating occupant dynamics in rollover crashes as represented by Hybrid III ATDs. To the authors’ knowledge, this study represents the first published test series of full-scale rollover crashes of a contemporary SUV with time synchronized sensor output from ATD neck transducers, roof rail accelerometers, an onboard high speed clock, and high speed external and internal video cameras.
ATD Biofidelity
The biofidelity of the Hybrid III ATD in rollover crash conditions is a significant limitation of this study as well as other published rollover studies1,15; however, ATD sensor data may be carefully evaluated within such limitations to yield objective insights. The ATDs used in this study were originally designed as a measurement tool in frontal crash tests, not rollovers. Thus, the Hybrid III ATD neck was designed and tested primarily to simulate dynamic head motion in the sagittal plane (neck flexion and extension).8,10 The Hybrid III ATD neck was not specifically designed to produce a biofidelic response under axial compression loading, typical of the neck loads resulting from the head-to-roof contacts observed in this study. Researchers have shown that with an axially directed impact to the crown of the ATD head, the ATD lower neck sensor records essentially the same magnitude axial force as the upper neck load cell, whereas the human cadaver neck lower load cell records a much reduced load magnitude compared to the upper load cell.24,29 Also, the Hybrid III ATD necks are neither frangible nor viscoelastic; therefore, they cannot accurately simulate individual vertebral displacement and/or fracture.
Notwithstanding the biomechanical differences between the necks of human cadavers and ATD mechanical necks, the Fz measurements of the upper load cell of a restrained Hybrid III dummy may provide a reasonable estimate of the initial input load to a restrained occupant’s head when it contacts the roof in a rollover crash under similar dynamic conditions (e.g., impact velocity, impact duration). Given that the mass of a Hybrid III dummy head reasonably mimics that of the comparable human (50th percentile male in the present study), the inertial effect of the dummy head should not confound Fz readings from its upper neck load cell.
In all three tests within the present study, Fz values for ATD axial neck load were evaluated solely from the upper neck load cells, thereby taking into consideration, as much as possible, the significant differences in axial stiffness between the ATD and cadaver human neck (the lower neck Fz sensor was not evaluated). These upper neck Fz sensor readings were interpreted relative to the head impact loads in cadaver tests under similar dynamic conditions (described below). Given that the Hybrid III ATD neck was specifically designed to be biofidelic in dynamic, sagittal plane bending (flexion and extension) loads, neck flexion loads (My) were evaluated in this study from the lower neck load cell of driver and passenger ATDs. Lateral bending loads (Mx) were recorded and reported, but not interpreted in this study due to the lack of available biomechanical tolerance data for the human spine when subjected to lateral bending. Additional research in this important area, for both rollover and side impact crashes, is needed.
Injury Tolerance of the Human Cervical Spine
Semantic confusion exists in the published literature regarding cervical spine tolerance or “failure load.” Some investigators have reported cervical spine “failure loads” resulting from impacts to cadaver heads as the output force measured at the lower cervical spine, thereby neglecting the kinetic energy dissipation associated with vertebral fracture and/or subluxation above the position of the sensor as well as the viscoelastic response of the intervertebral discs.19,20 Other studies have reported both the input and output loads in cadaver tests of the cervical spine.23–26 These data provide a quantitative comparison of the significant differences between the input loads measured at the cadaver head versus what might be more appropriately referred to as the residual force magnitude that is recorded at the base of the cervical spine segment. No experimental cadaver work has measured and/or estimated the input loads at the superior aspect of the human neck, which is the site of the upper neck load cell in the Hybrid III dummy, when the head is subjected to an axial impact on the crown of the head. Additional research in this area is needed.
The confusion of terms regarding cervical spine failure loads in the published literature has a significant bearing on the proper interpretation of Hybrid III ATD axial neck load sensor output in controlled rollover tests such as the present study. Bahling et al. utilized 2000 N as a neck sensor Fz threshold for “potentially injurious impacts (PII)” in rollovers, which is in the range of the published residual force magnitude recorded at the lower cervical spine following an injurious impact to the cadaver head.1,19 In contrast, other investigators reported the actuator (input) force at the head that was required for cervical spine injury in axial compression.24 In interpreting the ATD neck sensor data in this study, an Fz value of 7000 N was utilized as a threshold of “probable (spinal) column injury,” which is in the range of the published head impact loads in cadaver studies. A value of 150 N m was used as the threshold for probable column injury for interpretation of My readings from the lower neck sensor. In reality, the true axial compressive failure load of the human cervical spine is likely slightly lower than that measured by the head input loads in cadaver tests (due to inertial effects of the cadaver head), yet substantially greater than the lower cervical spine force data reported in the same cadaver tests. Thus, the real world relevance of threshold values used for both PII and “probable column injury” as a predictor of human injury risk must be tempered, consistent with the known biofidelity limitations of the ATD neck (described previously) and the wide variation in injury tolerance of the human spine, as described below.
The biomechanical literature suggests that the tolerance of the human cervical spine to serious injury is influenced by several mechanical factors, including individual tolerance variations due to age and gender, load magnitude and loading rate, pre-alignment (initial head-to-neck position), and end conditions of the cervical spine. Pintar et al.24 reported that serious (AIS 3+) cervical spine injury under axial compression loading conditions occurred at 5856 N with a loading rate of 3 m/s (for a 67-year-old female cadaver) and 11,242 N with a loading rate of 8 m/s (for a 50-year-old male cadaver). In the present study, none of the near-side, driver ATD sensors recorded upper neck Fz values exceeding even 2000 N neck compression, and only one far-side passenger dummy (Test B190042) exceeded a neck sensor reading of 5856 N compression. Controlling for loading rate, age, and gender in a sample of 25 human cadaver head-neck compression tests, Pintar and Yoganandan27 reported that compressive tolerance varied from 7 kN in the young (third decade) to 2 kN in the very old (ninth decade). “Failure loads” (recorded at the lower cervical spine) ranged from 2 kN at quasi-static loading rates to 5 kN at dynamic loading rates (8 m/s). Failure tolerance for the male population was 25% higher than the female population (without regard to age and rate of loading). The present study recorded roof rail-to-dummy head contacts in the range of 5 m/s (11.2 mph) in the first ground strike of the SUV rollovers.4 Thus, the roof rail-to-head impact speeds in the present study were within the range of loading rates to cadaver and Hybrid III ATD heads in the studies by Pintar et al.24,27
Pre-alignment of the head and neck complex when struck by (or when it strikes) the roof is a key variable in determining whether catastrophic injury will occur, and if so, the specific type of injury that will be sustained. Published biomechanical studies suggest that cervical spine pre-flexion yields a greater incidence of lower cervical compression and burst fractures than neutrally positioned spines.24,25 Restrained occupants in rollover collisions are typically pre-flexed, due to the initial locking of their belt restraint system, and thus are at higher risk of cervical spine injury in the presence of an intruding roof structure when compared to unrestrained occupants. This higher risk of roof impact for restrained vs. unrestrained occupants in rollovers was confirmed with U.S. field accident data.9 The degree of pre-flexion of the ATD necks prior to head-to-roof contact in the present study was not determined because the onboard cameras were positioned behind the ATDs during the rollover tests. The seat belt load cells (i.e., excluding the two sensors described previously that malfunctioned) recorded continuous tensile loads in both lap and shoulder belts throughout the test interval for both driver and passenger ATDs in all three tests. This belt load data indicated that the lap–shoulder belts locked and remained locked during the first 1000 ms test interval for all ATDs in all three tests.
Nightingale et al.20 reported on the influence of boundary or end conditions of the cervical spine relative to specific injury types. When the head was unconstrained and free to translate and/or rotate away from the applied load, no cervical injury was sustained, despite high input loads to the head. In “full constraint” conditions, with the head pre-flexed along its stiffest axis (i.e., the removal of the normal cervical lordosis), buckling and burst fractures were noted. With rotational constraint (e.g., when the neck flexes forward to the point where the chin is against the sternum), bilateral locked facets typically occurred. Using cadaver spine specimens, Pintar et al.26 determined that the average peak My magnitude resulting in “major” neck injury was 97 N m at the specific site of injury in the cervical spine (i.e., not positioned as inferior as the lower neck load cell of the Hybrid III ATDs in the present study). The peak axial head impact force ranged from 3000 to 9700 N, with the peak flexion bending moment at the injured level ranging from 19 to 169 N m. Thus, the degree of constraint imposed by the contacting surface, such as an intruding roof, can be a major determinant for cervical spine injury. In all three tests of the present study, the far-side, passenger ATDs recorded lower neck flexion (My) loads that exceeded 175 N m. None of the near-side, driver ATD lower neck sensors recorded peak My loads exceeding 110 N m. No dynamic test data for cervical spine tolerance in lateral bending was identified; therefore, no interpretation of the peak Mx sensor outputs for any of the ATDs was made.
The biomechanical impact environment to which the restrained ATDs were subjected in the present study was shown to be comparable to that of published cadaver studies on the basis of the following: head impact load magnitude and direction, loading rate, pre-alignment of the ATD head and neck, and degree of rotational head constraint. Thus, a comparison of the ATD sensor outputs for upper load cell Fz and lower load cell My values to probable column injury values of 7000 N and 150 N m, respectively appears scientifically reasonable, subject to the limitations described above.
Roof Crush as a Correlate or Cause of Injury
Two opposing views exist in the published literature regarding whether roof crush causes serious injury or whether it is simply associated or correlated with serious injury. One group of investigators has concluded that restrained occupants receive catastrophic head and neck injury from diving into the roof and making head-to-roof contact while the top of the vehicle/roof is striking/hitting the ground during a rollover.1,3,5,15,16 Other investigators have concluded that serious neck injuries to restrained occupants are directly caused by the dynamic intrusion of the roof structure into the occupant’s survival space during a rollover crash.12,13,28 The present study reports quantitative evidence of the temporal relationship between dynamic roof deformation, lap–shoulder seat belt loads, and restrained ATD neck loads, which provides further clarification in this scientific debate.
Objective roof/pillar deformation occurred prior to the occurrence of Peak neck loads (Fz, My, Mx) for both driver and passenger ATDs in all three rollover tests. Prior to the occurrence of Peak neck loads, the driver and passenger ATD heads contacted the roof one or more times in all three tests; the magnitude of neck sensor responses ranged from 3 to 57% of the respective dummies’ Peak neck loads. Thus, the restrained driver and passenger ATDs did, indeed, “dive” into the roof while the roof was in contact with the ground, resulting in Local Maximum neck load values, which in no instance exceeded 57% of the Absolute Maximum (Peak) neck load. In particular, the “diving” neck loads (Local Maxima) for the far-side, passenger ATDs were only 2–13% of the Peak neck loads (Fz and My) for all three tests (Table 2, Fig. 4).
In each test, the Peak neck loads of the far-side, passenger ATD occurred within 10 ms following the time of maximum objective roof crush for all three tests, which is consistent with published inertial effects of the ATD head in transmitting an axial force to the lower neck sensors.24 In contrast, Peak neck loads for the near-side, driver ATD occurred up to 65 ms following the time of occurrence of objective roof crush for all three tests. The onboard cameras also revealed observable roof crush into the far-side versus the near-side occupant compartment during the time of the peak neck loads, which was completely consistent with the timing and higher neck load magnitudes of the passenger, compared to driver, ATD for all three tests.
The lap and shoulder belt load profiles for both driver and passenger ATDs provide further insights in the scientific debate regarding roof crush as a correlate versus a cause of serious injury. During the time interval of the Peak neck loads in the passenger ATDs for all three tests, the shoulder belt load, which should increase in magnitude as it resists torso augmentation, instead consistently decreased by 65–85% to only 44 N in some cases. The lap belt showed the same reduction in load during the time period that Peak neck load was recorded; it was reduced by 58% to approximately 156 N (Table 4, Figs. 8a and 8b). The belt load reductions occurred at the same time that on-board cameras clearly recorded the passenger ATD hanging upside down in the lap–shoulder belt and the roof crushing into the occupant space. This time of “observable” roof crush also occurred contemporaneously with the “objective” roof crush predicted by the accelerometers mounted on the SUV roof rails. The belt load that was recorded during each Peak neck load event for the far-side, passenger ATD was less than 50% of the Peak belt load in all three tests (Table 4). The shoulder and lap belt load cells indicated that the belts were off-loaded (i.e., loading decreased) as the roof crushed down on the ATD head and pushed the ATD back toward the seat cushion, away from the shoulder and lap belts, at the time of Peak neck loads (Fig. 9). Additionally, the deformation of the passenger (far-side) B-pillar lowered the upper attachment point (i.e., D-ring) for the belt, causing slack in the shoulder belt with a concomitant reduction in shoulder belt load.
Figure 9The shoulder and lap belts are off loaded (i.e., load decreases) as the roof crushes down on the passenger head and pushes the dummy back toward the seat cushion, away from the shoulder and lap belts, at the time of injurious neck loads
Repeatability and Reliability
The FMVSS 208 dolly rollover test methodology has been criticized for its alleged lack of reliability and/or repeatability.15 The results of this study, however, demonstrated that the 208 rollover tests are very reliable when viewed from a vehicle-based, occupant protection frame of reference. Test-to-test comparisons of the FMVSS 208 rollover results revealed remarkable similarity in predicting the time of occurrence of Peak neck loads for both driver and passenger ATDs. The Peak neck Fz occurred in all three tests at 530 ± 15 ms for the driver ATD (Fig. 10 and Table 3) and 730 ± 15 ms for the passenger ATD (Table 3). The Peak neck My occurred in all three tests at 530 ± 18 ms for the driver ATD (Fig. 11 and Table 3) and 750 ± 21 ms for the passenger ATD (Table 3). The Peak value for Mx occurred in all three tests at 530 ± 18 ms for the driver ATD and 770 ± 13 ms for the passenger ATD. These small variations in time of occurrence of roof/pillar deformation and Peak neck loads are particularly remarkable given that (1) the data came from six different dummies and three different vehicles tested on three different days, (2) the differences in the time of occurrence of the Peak neck loads was ≤20 ms in an overall time interval of 1000 ms, and (3) each 1000 ms time interval included either a sampling rate of 20,000 data points (B190043 and B190042) or 12,500 (B180220).
Figure 10The absolute maximum value for upper neck Fz occurred in all three tests at 530 ± 15 ms for the driver dummyFigure 11The absolute maximum value for lower neck My occurred in all three tests at 530 ± 18 ms for the driver dummy
Quantitative analyses were undertaken to determine the significance probability of each pairwise comparison. Restated, the probability that the similarity of the maximum and minimum values of any two tests were related to something other than chance was analyzed (e.g., B190042-Fz vs. B190043-Fz, B190042-Fz vs. B190220-Fz, and B190043-Fz vs. B190220-Fz). Appendix 1 examines this issue and computes the probability for each pair of test metrics. This analysis revealed that there is a 93.1–98.6% probability that the differences in time occurrence of Peak neck loads between these results are NOT due to random chance alone. Stated more simply, there is a less than 7% probability that these differences are coincidental.
Validity
The constellation of driver vs. passenger neck loads measured in this test series of SUV rollovers was consistent with certain incidence trends of catastrophic head and neck injuries observed in real-world rollovers with restrained front seat occupants.9,21,28 None of the peak neck loads recorded in the near-side, driver ATD neck sensors exceeded the threshold values for probable column injury, which were used in this study. In contrast, the far-side, passenger ATDs recorded Peak neck loads that consistently exceeded the threshold for probable column injury due to neck flexion, My. These findings are consistent with 1992–1998 data obtained from NHTSAs National Accident Sampling System (NASS) database, which showed serious spinal injuries were more frequent for the far-side occupants (compared to the near-side), where the source was most often coded as roof, windshield, and interior.21
A probability of two common catastrophic spinal column injuries was predicted by the passenger ATD neck sensors in all three rollover tests. A combination load of compression and of flexion is associated with burst fractures and wedge compression fractures. This load profile was recorded by the upper and lower neck sensors in the far-side passenger ATD in B190042. Bilateral facet dislocation injuries have been associated with sagittal plane flexion.17 The flexion moments recorded by the passenger ATD lower neck sensors in tests B180220 and B190043 exceeded the threshold values for probable spinal column injury by 40–240%. Thus, the results of this rollover test series suggest that the FMVSS 208 dolly rollover test may be a valid predictor of serious spinal injuries to restrained occupants in real-world rollovers.
The results of this study provide a unique data set that furthers understanding of probable spinal column injury mechanisms within a rollover crash environment. Such information may assist the scientific community and automotive engineers in recommending and designing appropriate intervention strategies to mitigate morbidity and mortality in rollover crashes. Moreover, these data may inform government agencies in formulating appropriate public safety policy to improve rollover crash protection for restrained occupants.
Conclusions
During each of the three FMVSS 208 dolly rollover tests of Ford Explorer SUVs, the far-side, passenger ATDs exhibited Peak neck compression and flexion loads, which indicated a probable spinal column injury in all three tests. In those same tests, the near-side, driver ATD neck loads never predicted a serious injury. In all three tests, objective roof/pillar deformation occurred prior to the occurrence of Peak neck loads (Fz, My) for far-side, passenger ATDs, and Peak neck loads were predictive of probable spinal column injury. The production lap and shoulder seat belts in the SUVs, which restrained both driver and passenger ATDs, consistently allowed ATD head contact with the roof while the roof was contacting the ground during this 1000 ms test series. Local peak neck forces and moments were noted each time the far-side, passenger ATD head contacted (“dived into”) the roof while the roof was in contact with the ground; however, the magnitude of these local maxima was only 2–13% of Peak neck loads in all three tests. “Diving-type” neck loads were not predictive of spinal column injury for either driver or passenger ATD in any of the three tests. When viewed from a vehicle-based, occupant protection frame of reference, the existing FMVSS 208 dynamic rollover test is a repeatable, reliable, and valid test method to evaluate the risk of probable spinal column injury in rollover crash environments.

suv
roof crush
crash test
restraint system
spinal injury


Transforming growth factor beta-regulated gene expression in a mouse mammary gland epithelial cell line

Background Transforming growth factor beta (TGF-β) plays an essential role in a wide array of cellular processes. The most well studied TGF-β response in normal epithelial cells is growth inhibition. In some cell types, TGF-β induces an epithelial to mesenchymal transition (EMT). NMuMG is a nontransformed mouse mammary gland epithelial cell line that exhibits both a growth inhibitory response and an EMT response to TGF-β, rendering NMuMG cells a good model system for studying these TGF-β effects.
Introduction
Transforming growth factor beta (TGF-β) is the prototype of a large family of signaling molecules with more than 40 members. TGF-β signals through the type I receptor (TβRI) and the type II receptor (TβRII), and the Smad transcriptional regulators, as well as many other signaling pathways [1]. TGF-β plays an essential role in a wide array of cellular processes, including early embryonic development, cell growth, differentiation, motility, and apoptosis. In nontransformed epithelial cells, the most studied TGF-β response is growth inhibition. In some cell types, TGF-β induces an epithelial to mesenchymal transition (EMT). TGF-β plays an important, albeit complex, role in tumorigenesis. In many tumors of epithelial origin, cells become resistant to TGF-β-mediated growth inhibition. In parallel, TGF-β induces EMT in tumor cells, and increases tumor invasion and metastasis [2]. NMuMG is a nontransformed mouse mammary epithelial cell line that exhibits both a growth inhibitory and EMT response to TGF-β [3]. These properties render NMuMG cells a suitable model system for studying these TGF-β actions.
Previous gene expression profiling studies of TGF-β action on cell lines utilized cDNA microarrays to characterize extracellular matrix-related genes in human dermal fibroblasts. The upregulation of these genes by TGF-β was Smad mediated [4]. Another study examining the genetic programs of epithelial cell plasticity directed by TGF-β utilized the human keratinocyte HaCaT cell line [5]. In this study, HaCaT cells were treated for up to 4 hours, and microarray gene expression profiling was performed using an array of 16,580 human cDNAs. The expression of 728 known genes (10% of those analyzed) was regulated by TGF-β within 4 hours of treatment.
In the present study, we examined TGF-β regulation of gene expression in the NMuMG epithelial cell line. NMuMG cells were chosen as a model system because the results are more relevant to our studies employing transgenic mouse mammary tumor models, and because NMuMG cells are a well-established model system for studying both growth inhibition and EMT induced by TGF-β [3]. EMT represents a complex physiological process that includes dissolution of adherens junctions, a change to spindle-like cell morphology, cytoskeletal reorganization, increased cell motility, loss of epithelial markers, and induction of mesenchymal markers. EMT thus includes several cellular responses that may occur through different mechanisms and at different time points after TGF-β treatment. We consequently examined changes in gene expression at 1, 6, and 24 hours after TGF-β treatment.
In agreement with previous studies with HaCaT cells [5], approximately 10% of the genes examined were regulated by TGF-β in our microarray studies that queried more than 15,000 mouse cDNAs. Our study demonstrates that by 1 hour, TGF-β suppresses the expression of multiple genes that play key roles in regulating cell cycle progression. At 6 and 24 hours, TGF-β enhances the expression of multiple genes involved in regulating cell shape and cell adhesion, and therefore may mediate TGF-β-induced EMT. Additionally, several novel TGF-β-regulated genes were identified that may play important roles in TGF-β responses.
Materials and methods
Cell culture and treatment
NMuMG cells were cultured in Dulbecco's modified Eagle's medium containing 10% serum and 10 μg/ml insulin, until reaching 70–80% confluency. The cells were treated with 4 ng/ml TGF-β1 for 1, 6 or 24 hours. Untreated cells were used as reference samples at each time point, and were referred to as controls in the analyses. Four independent replicates of each experiment were performed. Cell morphology was examined under phase contrast using an Olympus CK40 microscope (Melville, NY, USA).
Growth inhibition assay
3H-thymidine incorporation assays were performed using cells that had been treated for 24 hours with TGF-β. The cells were pulsed with 3H-thymidine for the final 2 hours of the treatment period. 3H-thymidine incorporation was quantitated using a LS 6500 Multi-Purpose Scintillation Counter (Beckman). Four replicates of each experiment were performed, and each 3H-thymidine incorporation experiment was performed in triplicate.
RNA sample preparation
NMuMG cells were lysed and homogenized in Trizol reagent (Invitrogen, Carlsbad, CA, USA), and total RNA was prepared according to the manufacturer's instructions. Two rounds of extraction were performed to isolate pure, high-quality total RNA. Thirty micrograms of total RNA from each sample were used for reverse transcription and cyanine (Cy)-dye incorporation.
cDNA microarray hybridization
The National Institutes of Aging (NIA) 15,000 cDNA microarray was printed on three contiguous slides by the Vanderbilt Microarray Shared Resource. The mouse 15,000 NIA microarray contains 15,247 genes of known and unknown function, developed at the NIA. Detailed descriptions of the gene array list, microarray hardware and procedures are available online .
The reference RNA samples from nontreated NMuMG cells were labeled with Cy5, and the test RNA samples from NMuMG cells treated with 4 ng/ml TGF-β for 1, 6, and 24 hours were labeled with Cy3. The Cy3-labeled and Cy5-labeled samples were hybridized simultaneously to the same array. Four independent replicates of TGF-β treatment, RNA isolation and labeling, and microarray hybridization were performed. To estimate 'system noise' that may be due to differences in Cy-dye labeling between samples, we performed a 'self-to-self' hybridization, where the same control sample was labeled separately with Cy3 and Cy5, and then hybridized.
Oligo dT for reverse transcription was synthesized by Invitrogen. SuperScript II reverse transcriptase (Invitrogen) was used. A Qiagen PCR purification kit was used for purification of probes (Qiagen, Valencia, CA, USA). Slides were prehybridized to eliminate nonspecific interactions in prehybridization solution: 1% BSA, 5 × sodium chloride/sodium citrate buffer (SSC), 0.1% SDS at 65°C for 45 min. Hybridizations were performed at 65°C for 14–16 hours in a humidified hybridization chamber (Corning, Acton, MA, USA). After hybridization, the slides were washed once each in solutions 1–3 (wash solution 1, 2 × SSC, 0.1% SDS; wash solution 2, 1 × SSC; wash solution 3, 0.1 × SSC) for 5 min at 55°C with gentle stirring/agitation. Washed slides were centrifuged in a conical tube for 5 min at 1600 rpm to dry them. Microarray slides were scanned using a Genepix 4000 B scanner (Axon Instruments, Union City, CA, USA) at a resolution of 10 μm, and the original data files were generated by GenePixPro software (version 4.0; Axon Instruments).
Data analysis
A merged 15,000 data file was constructed by combining the three original 5000 data files generated from the three contiguous slides on which the total 15,000 gene clones were printed. The GenBank accession number and the full annotation gene name for each gene were incorporated. Data analyses were performed using the GeneSpring 4.1.5 software package (Silicon Genetics, Redwood City, CA, USA).
The normalization for the two-color cDNA microarray data was designed as follows. The net signal intensity in each channel (Cy3 or Cy5) was determined by subtracting the local background from signal intensity values. Each gene's measured intensity was divided by its control channel value (the reference RNA sample channel of Cy5). A Cy3/Cy5 ratio represents the relative abundance of a target transcript in TGF-β-treated and nontreated samples respectively. When the control channel value was below 1000.0, the data point was considered too weak and was discarded. Each sample was normalized to the 50th percentile of all measurements. The bottom 10th percentile was considered background, and was subtracted from all the other values.
Each experimental result was interpreted as the average of the four replicates of each time point. Time-course gene expression profiles were required to be present in two of the four datasets, and to be present in at least two of the three time points. A signal to control channel ratio > 2.5 and a probability t test P < 0.05 was defined as upregulation by TGF-β. A signal to control channel ratio < 0.4 and a probability t test P < 0.05 was defined as downregulation. The annotated gene lists were constructed from all genes represented in the normalized dataset. The differentially expressed genes were classified into functional subgroups using Simplified Ontology in GeneSpring. For each pathway, pathway images were saved as GIF files and loaded into GeneSpring. Each pathway element was identified in the normalized data.
Northern hybridization
All cDNAs of the NIA mouse 15,000 microarray were cloned into the NotI/SalI sites of the ampicillin-resistant pSPORT1 vector (Invitrogen). The insert sizes ranged from 0.5 to 3 kb, with an average insert size of 1.5 kb. The Escherichia coli host strain used was DH10B. Plasmid DNA was isolated using the High Pure Plasmid Isolation Kit (Roche, Indianapolis, IN, USA). The inserts were verified for their correct annotation by DNA sequencing. The reverse pSPORT1 primer was used as the sequencing primer. To prepare cDNA probes, cDNA inserts were amplified using pSPORT1 primers: forward, GTTTTCCCAGTCACGACGTTG; reverse, TGA-GCGGATAACAATTTCACACAG.
Plasmid DNA was used as the template for PCR amplification under the following conditions: initial denaturation at 95°C for 1 min; then 40 cycles of denaturation at 94°C for 30 s, annealing at 54°C for 30 s, and extension at 72°C for 3.5 min. A final extension was performed at 72°C for 7 min. To examine the quality and quantity of PCR products, they were separated on 1.2% agarose gels. Specific cDNA bands were recovered from the gels using QIAEX II Gel Extraction Kits (Qiagen). Seventy-five nanograms of cDNA was labeled with 32P using a Random Primed DNA Labeling Kit (Roche).
For northern blot analysis, 10 μg total RNA was separated by electrophoresis on a 1% agarose, 0.66 M formaldehyde gel and transferred to Hybrid Nylon transfer membranes (Amersham Biosciences, Piscataway, NJ, USA). After transfer, the membrane was UV cross-linked (Stratalinker; Stratagene, La Jolla, CA, USA). All cDNA probes were hybridized overnight at 42°C in ULTRAhyb solution (Ambion, Austin, TX, USA). Each filter was washed twice for 5 min in 2 × SSC and 0.1% SDS at 42°C, followed by two 15 min washes each in 0.5 × SSC and 0.1% SDS at 42°C, followed by two 15 min washes in 0.1 × SSC, 0.1% SDS at 42°C. Equal loading of gel lanes was confirmed by hybridization with the house keeping gene 1B15. Results were visualized and quantitated using a FUJIFILM-FLA-5000 Phosphoimager (Fuji Photo Film Co. Ltd, Stamford, CT, USA).
Results
Biological and gene expression responses of NMuMG cells to TGF-β
NMuMG cells react to TGF-β treatment with both an EMT response and a growth inhibitory response (Fig. 1). These characteristics render NMuMG cells an appropriate model system to study the signaling pathways mediating these TGF-β effects. To examine TGF-β regulation of genes involved in EMT and cell cycle control, we treated NMuMG cells with TGF-β for 1, 6, or 24 hours, isolated the total RNA, and performed gene expression profiling by cDNA microarray. The relative transcript abundance was expressed as Cy3/Cy5 ratios of signal intensities after background subtraction in each channel. Data analysis and quality control procedures are described in detail in Materials and methods. TGF-β treatment resulted in the upregulation or downregulation of 939 genes out of the 15,247 genes examined. Subtracting redundancy or signals too weak to score, this represents approximately 10% of the genes analyzed.
The time course of TGF-β1-dependent changes in gene expression demonstrates a progressively greater alteration of gene expression over time (Fig. 2). In general, TGF-β1 regulation of cell cycle-related genes occurred with an onset of less than 1 hour, while TGF-β1 regulation of EMT-related genes occurred with a later onset, with changes first becoming apparent at 6 or 24 hours (see later).
Figure 3 and Table 1 present the distribution of downregulated genes and of upregulated genes, and the sum of upregulated and downregulated genes at each time point. The total number of differentially expressed genes at each time point does not differ significantly. The 6 and 24 hour time points shared more TGF-β1-regulated genes than were shared between the 1 and 6 hour time points, or the 1 and 24 hour time points. Full lists of TGF-β-regulated genes at each time point can be accessed on our website .
Functional class distribution of the novel and known TGF-β1-regulated genes
Of the 939 genes regulated by TGF-β1, approximately one-third (350 genes) can be classified into functional groups. The classified genes were further separated into two tables of genes previously reported or not previously reported to be regulated by TGF-β. This was determined by performing a Medline search using the gene name and TGF-β as keywords. Tables of the complete dataset with each gene in its functional category are presented on our website . Tables 1 and 2 present some selected examples of known or unknown TGF-β-regulated genes, respectively. The genes involved in cell cycle regulation and cell adhesion (see later) are included.
Northern analysis verification of microarray data
To validate the microarray results, we subjected nine of the novel TGF-β-regulated genes to northern analysis. Of the nine genes examined, seven exhibited TGF-β1-induced changes in gene expression that matched those observed in the microarray experiments. The seven novel TGF-β1-regulated genes verified by northern analysis include Akt, mCalpain, RhoB, PR53, actinin 3, Ikki (Fig. 4) and the IQ motif-containing GTPase-activating protein 1 (IQGAP1). IQGAP1 showed upregulation in NMuMG cells after 1, 6 and 24 hours of treatment with TGF-β, supporting the microarray data. As reported by other investigators [6], we detected multiple IQGAP1 transcripts. The IQGAP1 northern blot is thus not shown in Fig. 4. Akt and RhoB were reported previously to be regulated by TGF-β at the translational level [7,8], but not at the transcriptional level as we show here. Some of the TGF-β1-induced changes in gene expression were also verified by real-time RT-PCR (data not shown). In further support of the reliability of the microarray experiments, genes that were represented multiple times in the array as different clones exhibited identical expression profiles (examples can be found in the supplementary tables at our website: . In addition, our expression profiling results are consistent with previously reported expression patterns of TGF-β1-responsive genes [1,5].
Examination of cell cycle control and cell adhesion-related genes by microarray
There are multiple ways to explore the biological significance of results obtained in microarray experiments. One may organize the genes into functional groups or signaling pathways to examine the regulation of clusters of genes. We were interested in identifying TGF-β-regulated genes involved in the induction of EMT and cell cycle arrest. In our study in NMuMG cells, the expression of many cell cycle regulators was altered by TGF-β. One hour after TGF-β treatment, cyclin D2, cdk4, E2F5, cyclin A, and c-myc were downregulated. Six hours after TGF-β treatment, cyclin D2, p107, E2F5, c-myc, and Id2 were downregulated. Twenty-four hours after TGF-β treatment, cyclin D2, p107, E2F5, cyclin A, cyclin B, cyclin H, and Id2 were downregulated (Fig. 5). These data are consistent with these genes serving as mediators of TGF-β-induced growth arrest.
The microarray results also revealed upregulation of a number of genes that play a role in cell–cell and cell–matrix adhesion and EMT. At 1 hour, c-Jun, β-integrin, and IQGAP were upregulated. At 6 hours, actin, calpain, β-integrin, fibronectin, collagen, myosin light chain, α-actinin, β-catenin and IQGAP were upregulated. At 24 hours, c-Jun, actin, calpain, α-integrin, β-integrin, fibronectin, collagen, α-actinin, β-catenin and IQGAP were upregulated. The only gene in this category observed to be downregulated was E-cadherin at 6 hours (Fig. 6). The results are consistent with these genes playing a role in TGF-β1-mediated changes in cell–cell and cell–substratum adhesion.
Our results are consistent with previous studies, but we identified several novel TGF-β-regulated genes that could play important roles in both EMT and cell cycle regulation, including RhoB, mCalpain, actinin 3, IQGAP1, Ikki and protein phosphatase 2A (PP2A)-PR53.
Discussion
The mechanisms by which TGF-β signals are not fully understood. In this regard, gene expression profiling has been used successfully by a variety of investigators to explore genetic events involved in TGF-β signaling. Zavadil and colleagues detected genetic programs of epithelial cell plasticity directed by TGF-β [5]. Verrecchia and colleagues identified novel TGF-β/Smad gene targets in dermal fibroblasts [4]. Chen and colleagues found defective repression of c-myc in breast cancer cells, suggesting that this event is at the core of the TGF-β growth arrest program [9]. Shen and colleagues discovered that the activity of the guanine exchange factor NET1 is essential for TGF-β-mediated stress fiber formation [10].
In the present study, we have selected the NMuMG nontransformed mouse mammary gland epithelial cell line as a model system to identify TGF-β-regulated target genes involved in the control of growth inhibition and EMT. To identify TGF-β-regulated genes, we employed a cDNA microarray that represents 15,247 genes of known and unknown function. We found that the expression of 939 of the genes was altered by TGF-β regulation. This represents about 10% of the genes examined. Many of the genes identified were previously determined to mediate key biological responses to TGF-β. In addition, several novel TGF-β-regulated genes were identified. The present report provides a comprehensive view of the coordinated regulation of genetic programs induced by TGF-β during the processes of cell cycle arrest and EMT. A remarkably large number of genes undergo rapid changes in expression after TGF-β treatment. This report adds to the database of hundreds of genes that are regulated by TGF-β [5]. In addition, we have identified several novel TGF-β-regulated genes, and have verified these results in northern blotting experiments.
Table 1 presents previously identified TGF-β-regulated genes, many of which are known to play important roles in TGF-β induction of EMT and cell cycle arrest. Briefly, in the cellular communication category, platelet-derived growth factor was upregulated by TGF-β. Multiple genes involved in cell adhesion were upregulated by TGF-β, including integrins (integrin α3A, integrin β, integrin β5), integrin-linked kinase, and the integrin ligand fibronectin. These results are consistent with TGF-β activating integrin-dependent cell adhesion. TGF-β upregulation of α-actinin, β-tropomyosin 2, and p120 catenin may play a role in the induction of EMT. RhoB was upregulated at 6 and 24 hours. RhoB is an endosomal small GTPase, and it functions as a negative regulator of integrin and growth factor signals [11]. Our previous results [8] and those of other workers [12] suggest a novel mechanism of tumor suppressive regulation by TGF-β, and implicate RhoB as a negative regulator of TGF-β signal transduction.
TGF-β downregulation of the helix–loop–helix DNA binding protein Id2 and of the inhibitor of DNA binding Idb3 were previously identified as important events in TGF-β-regulated signaling. These proteins belong to a family of helix–loop–helix proteins that, in general, function as positive regulators of cell growth and as negative regulators of cell differentiation in many cell types [13].
TGF-β also regulates many genes involved in the progression of cancer. The proto-oncogene Akt is upregulated at 1 hour at the mRNA level. The Gro1 proto-oncogene is downregulated by TGF-β at all the time points examined. The roles that these gene products play downstream of TGF-β during tumorigenesis have not been extensively studied [14,15]. Well-established TGF-β responses such as downregulation of c-myc and upregulation of the Jun oncogene were also observed.
TGF-β is a potent growth inhibitor of epithelial cells. TGF-β-mediated growth inhibition has been associated with effects on G1 phase cyclins, cyclin-dependent kinases (Cdks), Cdk-activating kinase, Cdc25A, and Cdk inhibitors. TGF-β potently inhibits the activities of both the cyclin D–Cdk4/Cdk6 and cyclin E–Cdk2 complexes, resulting in the hypophosphorylation of pRbs and in the decreased transcriptional activity of E2Fs. TGF-β does not affect the expression levels of Cdk4, Cdk6, or Cdk2 in exponentially proliferating cells. TGF-β decreases the expression levels of cyclin A, which is probably the result of cell cycle arrest in the late G1 phase. TGF-β has been associated with upregulation of Cdk inhibitors p15Ink4B, p21Cip1, and p27Kip1. The c-myc proto-oncogene has been implicated in TGF-β-mediated growth inhibition. TGF-β rapidly inhibits c-myc expression in a wide variety of cell types [1]. c-Myc downregulation is a key event in the TGF-β program of growth inhibition [9]. Additional mechanisms mediating TGF-β-induced cell cycle arrest continue to be uncovered. In our study, examination of cell cycle genes demonstrated TGF-β1-induced downregulation of cyclin D2, c-myc, Id2, p107, E2F5, cyclin A, cyclin B, and cyclin H. These data are consistent with these genes serving as mediators of TGF-β-induced growth arrest.
Of the genes that could be placed into functional categories, the expression of the majority of the genes was not previously reported to be regulated by TGF-β. Table 2 presents some examples of genes that we have identified in this study to be regulated by TGF-β that are involved in cell signaling. Gadd45g was upregulated. Gadd45g specifically interacts with the Cdk1-cyclin complex, B1 resulting in inhibition of kinase activity [16]. The IQGAP1 gene is a target molecule of Cdc42 and Rac1. IQGAP negatively regulates the E-cadherin–catenin complex-based cell–cell adhesion by dissociating α-catenin and/or β-catenin, a key molecule that links the E-cadherin-catenin complex to the actin cytoskeleton. These data suggest that TGF-β upregulation of IQGAP may be one of the mechanisms by which TGF-β regulates cell–cell adhesion [17]. Calpains are a family of Ca2+-dependent intracellular cysteine proteases, including the ubiquitously expressed micro-calpains and m-calpains. Calpain activity may be regulated by targeting to specific adhesion-related substrates [18].
Our results also demonstrate that TGF-β regulates multiple genes involved in regulation of the actin cytoskeleton. Some of these components include actinin α3, the Arp2–Arp3 complex, and myosin light chain 2. Four different isoforms of tropomyosin were upregulated. Actinin α3 is a calcium-dependent cytoskeletal protein with an actin-binding domain. Actinin α3 is associated with adherens junctions and desmosomes, together with E-cadherin, α-catenin, β-catenin and γ-catenin, vinculin, α-actinin, and polymerized actin. The genes α-actinin, myosin light chain 1/myosin light chain 2, and tropomyosin are components of myofilaments involved in cell contractility and motility.
During our studies we identified several genes not previously reported to be regulated by TGF-β that are regulated by TGF-β in NMuMG cells. These novel TGF-β-regulated genes include IQGAP1, mCalpain and actinin α3, which were discussed earlier, and also Ikki and PP2A-PR53. For the first time, we show in the present study that Ikki is downregulated by TGF-β within 1 hour of treatment, and that downregulation persisted for at least 24 hours. NF-κB activation depends on the phosphorylation and degradation of its inhibitor protein, IkB. The phosphorylation of IkBα is initiated by an IkB kinase complex that includes a catalytic heterodimer composed of IkB kinase 1 (IKK-1) and IkB kinase 2 (IKK-2) [19]. A novel inducible IkB kinase (IKKi) has recently been described. IKKi is functionally and structurally distinct from the constitutively expressed IKK-1 and IKK-2. In contrast to TGF-β, tumor necrosis factor alpha stimulated IKKi expression, an effect that persisted for at least 24 hours [20]. The biological significance of TGF-β downregulation of IKKi is currently under investigation. PP2A is a multifunctional serine/threonine phosphatase that is critical to many cellular processes, including cell cycle regulation and signal transduction. PR53 belongs to one of the families of PP2A regulatory subunits. The significance of TGF-β regulation of PR53 expression is unknown [21].
Altogether, our results are consistent with the important role of TGF-β in regulating focal adhesions, integrin-based adhesion, actin cytoskeletal architecture, and cell motility. TGF-β plays a profound role in the dedifferentiation of epithelial cells, causing depolarization, disruption of epithelial interactions, altered expression of extracellular matrix proteins, rearrangement of the cytoskeleton, and formation of actin stress fibers. These TGF-β responses provide cells with increased metastatic potential and with increased motility.
Over the past few years, tremendous progress has been made in identifying signal transduction pathways activated by TGF-β family members. In the present study, we have combined microarray analysis with the examination of specific signaling pathways. Because of the important role that TGF-β plays in controlling cell proliferation and cell adhesion, we used the signaling elements involved in these processes as a template for the analysis of our microarray results. Many of the genes that we identified as being regulated by TGF-β were previously reported to be downstream targets of TGF-β. We also discovered several novel TGF-β target genes known to play roles in regulating cell adhesion, and thus EMT, and also cell cycle regulation. Examining the biological functions of these novel TGF-β target genes will increase our knowledge of the mechanisms by which TGF-β mediates its cellular effects. Furthermore, our results indicate several possible points of convergence between TGF-β signaling and other major intracellular and intercellular signaling systems.
Conclusion
A 15,247 cDNA microarray was used to examine TGF-β-regulated gene expression in mouse mammary NMuMG cells. Expression of 10% of the genes examined (939) was altered by TGF-β treatment. We have reported a comprehensive analysis of the coordinated regulation of genetic programs induced by TGF-β in mammary epithelial cells during the processes of cell cycle arrest and EMT. In addition, several genes previously not known to be regulated by TGF-β at the transcriptional level were identified, including Akt, RhoB, IQGAP1, mCalpain, actinin α3, Ikki and PP2A-PR53.
Competing interests
None declared.
Abbreviations
BSA = bovine serum albumin; Cdk = cyclin-dependent kinase; Cy = cyanine; EMT = epithelial to mesenchymal transition; IKKi = inducible IkB kinase; IQGAP1 = IQ motif-containing the GTPase-activating protein 1; NF = nuclear factor; NIA = National Institutes of Aging; PCR = polymerase chain reaction; PP2A = protein phosphatase 2A; RT = reverse transcriptase; SSC = sodium chloride/sodium citrate (buffer); TGF-β = transforming growth factor beta.

mammary gland
epithelial
cdna microarray
adhesion
cell cycle control