• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Cereb Blood Flow Metab. Author manuscript; available in PMC Sep 3, 2009.
Published in final edited form as:
PMCID: PMC2737347
NIHMSID: NIHMS116426

Multiplexed Cytokine Protein Expression Profiles From Spreading Depression in Hippocampal Organotypic Cultures

Summary

Cytokines are involved in ischemic tolerance, including that triggered by spreading depression (SD), yet their roles in neuroprotection remain incompletely defined. The latter may stem from the pleiotropic nature of these signaling molecules whose complexities for interaction might be better deciphered through simultaneous measurement of multiple targeted proteins. Accordingly, the authors used microsphere-based flow cytometric immunoassays and hippocampal organotypic cultures (HOTCs) to characterize the magnitude, time course, and diversity of cytokine (interleukin [IL] 1α, IL-1β, IL-2, IL-4, IL-6, IL-10, granulocyte-macrophage colony-stimulating factor [GM-CSF], interferon-γ [IFN-γ], and tumor necrosis factor-α [TNF-α]) response to SD. GM-CSF was not detected in HOTCs or media. However, SD triggered a significant, generalized increase in seven cytokines evident in HOTCs 6 hours later, with the remaining cytokine, IL-1β, becoming significantly different at 1 and 3 days. Additionally, these changes extended to include surrounding media for IL-6 and TNF-α by 1 and 3 days. This increase was localized to microglia via immunostaining for IL-1α, IL-1β, and interferon-γ. IL-10, although significantly more abundant in HOTCs 6 hours after SD, was significantly less abundant in surrounding media at that time and at 1 day. Finally, the generalized early increase in tissue cytokines later settled to a pattern at 3 days of recovery centering on changes in IL-1α, IL-1β, and TNF-α, cytokines capable of modulating ischemic injury.

Keywords: Spreading depression, Cytokine, Ischemic tolerance, Hippocampal organotypic culture, Multiplexed MFCA, Bio-Plex

Cytokines are powerful signaling molecules capable of modulating the severity of ischemic brain injury (Arvin et al., 1996), including so-called ischemic tolerance (IT) (Dirnagl et al., 2003; Ginis et al., 2002; Jander et al., 2001; Ohtuski et al., 1996; Stoll et al, 2000; Wang et al., 2000a,b), though mechanisms for such endogenous neuroprotection are incompletely defined. This void in part likely stems from the complexities of cytokine interactions. Cytokines are individually pleiotropic and variably pleiotropic in combination with other cytokines (e.g., Oppenheim and Feldmann, 2001). Furthermore, their effects can be species (Schroeter et al., 2003) and situation dependent. For example, interleukin-1β (IL-1β) worsens excitotoxic injury when administered with N-methyl-D-aspartate (NMDA) receptor agonists to rat neuronal–microglial cocultures (Ma et al., 2002–2003), but this prototypic cytokine is neuroprotective when similarly given to mouse neuronal–astrocytic cultures (Carlson et al., 1999). In addition, neuroprotection induced by IT evident 3 days after a reduction in blood flow depends on IL-1 (Ohtsuki et al., 1996), suggesting that a temporal disparity between NMDA receptor activation and the level of IL-1 exposure may have pathophysiologic significance (Viviani et al., 2003). Tumor necrosis factor-α (TNF-α) can also be neurotoxic or neuroprotective (Saha and Pahan, 2003). TNF-α pretreatment increases focal infarct volume in rats (Arvin et al., 1996; Barone et al., 1997) but has an opposite effect on infarct size in mice (Nawashiro et al., 1997). Finally, these exemplary cytokines, like other members of this signaling molecule family (Oppenheim and Feldmann, 2001), not only affect their own production, but also affect one another’s production and subsequent impact on cellular, tissue, and organismal function.

The improved insight needed to further clarify complex mechanisms by which cytokines affect IT can stem from simultaneous measurement of multiple, related targets (del Zoppo et al., 2000; Hulse et al., 2004). The use of RNAse protection assays that include simultaneous measurement of multiple candidate RNA species is one increasingly used experimental strategy (e.g., Dinkel et al., 2003). Indeed, the effects of cytokines often are inferred from the behavior of related mRNA species because cytokines are typically produced upon need (Oppenheim and Feldmann, 2001). However, newly synthesized cytokine mRNA is not always transcribed to protein, making measurement of related protein changes more critical for deciphering function (Wang et al., 2000a,b). Although previously exceedingly difficult to accomplish by use of individual enzyme-linked immunosorbent assays, sensitive, accurate and reliable simultaneous measurements of multiple protein targets in serum, culture media (for review see Hulse et al., 2004) and brain tissue (Hulse et al., 2004) are now possible using multiplexed microsphere-based flow cytometric immunoassay (MFCA) technology.

To further elucidate the potential contribution of cytokine proteins to IT, we used multiplexed MFCAs to study the temporal expression of cytokine proteins (i.e., IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon-γ [IFN-γ], and TNF-α after spreading depression (SD) in hippocampal organotypic cultures (HOTCs). Furthermore, we confirmed selected cytokine changes using immunohistologic techniques. Use of HOTCs allowed us to define spatiotemporal cytokine protein expression changes intrinsic to nervous tissue without potential confounding systemic inflammatory changes or those derived from injury, because SD occurs without irreversible injury (Nedergaard and Hansen, 1988). We show that the expression of selected cytokine proteins is rapidly induced by recurrent SD and evident within HOTC tissue and surrounding media after 6 hours. Furthermore, the cytokine changes stem from microglia. These cytokine profile changes may be important in deciphering how SD can either worsen (e.g., when it occurs immediately before; Takano et al., 1996) or lessen (e.g., when it occurs after 3 days; Kawahara et al., 1995; Kobayashi et al., 1995; Matsushima et al., 1996) the degree of ischemic injury. Aspects of this work have appeared in preliminary form (Kunkler et al., 2003).

MATERIALS AND METHODS

Hippocampal organotypic culture preparation

Hippocampal organotypic cultures are widely accepted experimental models (for review, see Bahr, 1995; Gähwiler et al., 1997) and were prepared and maintained as described previously (Kunkler and Kraig, 1997, 1998a, 2004). Slices were maintained in vitro for 21 to 30 days before use, a period during which the cultures remain stable. Synaptic functional activity and susceptibility to SD are stable for at least 21 to 42 days in vitro (Kunkler and Kraig, 1998a; Schmitt et al., 2002). Furthermore, pyramidal cell viability (assessed by NeuN expression) and astrocytic reactivity (assessed by glial fibrillary acidic protein expression, a marker commonly of tissue injury) remain unchanged over this period in HOTCs (Schmitt et al., 2002). Dendritic spine density of pyramidal cell apical dendrites in HOTCs (McKinney et al., 1999) resembles that seen in 15-day-old counterparts in vivo (Harris et al., 1992), perhaps due to reduced synaptic input. Nonetheless, alpha-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA)- and NMDA-type glutamate receptors and other synaptic proteins in HOTCs remain stable for at least 4 weeks in vitro (Bahr et al., 1995), and HOTCs show intrinsic patterns of inhibitory neurotransmission similar to that seen in vivo (Streit et al., 1989).

Like acute brain slices, HOTCs are deafferented. However, the considerably longer survival of HOTCs allows sufficient time for some synaptic reorganization. For example, some CA3 and CA1 pyramidal cells synapse back onto CA3 pyramidal neurons (Debanne et al., 1995) in HOTCs. Furthermore, CA1–CA1 synapses and synapses from CA3 to dentate granule cells are seen in HOTCs (Gutierrez and Heinemann, 1999). Nonetheless, these aberrant connections are not a dominant confounding factor for the use of HOTCs. This conclusion follows from the fact that the basic trisynaptic loop (i.e., dentate gyrus–CA3–CA1) is structurally (Zimmer and Gähwiler, 1984) and functionally (Gutierrez and Heinemann, 1999) preserved in HOTCs.

Electrophysiologic recording

For electrophysiologic recordings, HOTCs on a Millipore insert were placed in a 35-mm culture dish, mounted in a movable open perfusion microincubator (PDMI-2; Medical Systems, Greenvale, NY, U.S.A.) on an inverted microscope (DM IRBE; Leica Mikroskopie und Systeme GmbH; Wetzlar, Germany) sitting on a specially designed Gibraltar frame (Burleigh Instruments, Inc., Fishers, NY, U.S.A.) as previously described (Kunkler and Kraig, 1998a, 2004) and illustrated in Fig. 1. HOTCs were perfused with a normal Ringer’s solution containing (in mmol/L): NaCl 124, KCl 2, NaHCO3 26, CaCl2 2.5, MgCl2 1, KH2PO4 1.2, glucose 25 (300 to 310 mOsm), adjusted to pH 7.3 to 7.4 with 5% CO2/50% O2/balanced N2 and maintained at 36°C. The Ringer’s solution was directed outside (i.e., around and beneath) the insert at a rate of 1 to 2 mL/minute. To prevent the sections from drying, Ringer’s was dripped within the insert during the experimental manipulations (50 μL/min).

FIG. 1
Schematic of electrophysiologic recording paradigm and representative interstitial DC potentials recorded during recurrent spreading depression in hippocampal organotypic cultures. Bipolar stimulating electrode (stim) in the dentate gyrus was used to ...

To record evoked responses, an interstitial microelectrode (tip diameter, 4 to 6 μm) filled with 150-mmol/L NaCl was driven into the CA3 pyramidal cell layer. A bipolar (90% platinum, 10% iridium) twisted, Teflon insulated wire (125 μm diameter, #7780; A-M Systems, Everett, WA, U.S.A.) stimulating electrode was placed gently on top of the dentate gyrus. A 1-mol/L KCl agar bridge ground electrode was placed outside of the insert and within the 35-mm culture dish beneath the level of the perfusate. Stimulating pulses were 100 microseconds in duration and 20 to 50 V in intensity at a constant current setting using a stimulator (World Precision Instruments 1800 series; New Haven, CT, U.S.A.) and an associated stimulus isolator. Interstitial DC signals were monitored using an A-1 Axoprobe amplifier system (Axon Instruments, Foster City, CA, U.S.A.), digitized with a 1200 series Digidata system (Axon Instruments) and analyzed using Axoscope software (version 9.0; Axon Instruments). Separate Pentium AST computers (AST Research, Irvine, CA, U.S.A.) were used to acquire fast and slow signals. Fast-evoked signals were digitized and sampled every 100 microseconds; slow potential recordings were digitized and sampled every 0.1 to 5 milliseconds.

To initiate SD, the perfusate was switched to a modified Ringer’s solution in which NaCl was replaced with a millimolar equivalent of sodium acetate (NaAc) (7.6 pH) (Kunkler and Kraig, 1998a, 2004). This modified Ringer’s was pulsed on for 2 minutes during which time the Ringer’s dripped over the preparation was turned off. An SD episode was initiated with a single pulse from the bipolar stimulating electrode and induced every 10 minutes over a 1-hour period (seven total). Sham HOTCs received similar recurrent exposure to NaAc Ringer’s but no concomitant bipolar stimulus pulse. After manipulations, the insert was rinsed, placed back into normal growth media and returned to the incubator.

Culture media samples (200 μL) were collected at 6 hours and at 1 and 3 days from the 3-day survival cultures and an equivalent volume of fresh media returned to the cultures. Samples were stored at −80°C until ready for assay.

Tissue sample homogenization

At 6 hours or at 1 or 3 days after SD or sham treatment, the inserts were rinsed with chilled (4°C) phosphate-buffered saline (PBS; 7.4 pH), the cultures removed using a fine brush, and frozen on dry ice and stored at −80°C. HOTCs were agitated five times with a pipette (100 μL size, tip removed to 2-mm opening) in 100 μL of Cell Lysis Buffer (Bio-Rad, Hercules CA, U.S.A.), which contained a cocktail of protease inhibitors selected by the manufacturer plus the addition of phenylmethylsulfonyl fluoride (Sigma, St. Louis, MO, U.S.A.) in dimethyl sulphoxide (Sigma) for a working concentration of 1.5 mmol/L. After agitation, the tissue was placed on a shaker platform for 20 minutes at 4°C at 300 revolutions per minute (RPM) and then centrifuged for 15 minutes at 4,500 RPM. Supernatant was collected and diluted in equal volume with Phosphoprotein Assay Buffer (Bio-Rad). Samples were stored at −80°C until ready for assay.

Tissue sample total protein determination

Total protein of HOTC samples was determined by use of a Bio-Dot SF (Bio-Rad) and Colloidal Gold Total Protein Stain (Bio-Rad). Briefly, filter and nitrocellulose papers were pre-soaked in PBS (7.4 pH) and placed in the Bio-Dot SF. Samples and tissue standards were applied and incubated for 10 minutes at room temperature before removal by even, constant vacuum pressure. The nitrocellulose was rinsed three times for 30 minutes each at room temperature in 20-mmol/L Tris, 500-mmol/L NaCl, and 0.3% Tween-20 (7.5 pH) followed by three 1-minute rinses in distilled water. Nitrocellulose was incubated for 1 hour in 50 mL of Colloidal Gold Total Protein Stain, briefly rinsed in distilled water and placed between filter papers to dry.

Dried dot blots were scanned using an HPScanJet 6100c (Hewlett Packard, Palo Alto, CA, U.S.A.) and resultant images stored electronically for subsequent densitometric analyses that were performed as follows using Image ProPlus 4.1 software (Media Cybernetics, Silver Springs, MD, U.S.A.). First, a calibration curve was established via linear regression of densitometric values from known protein concentration standards using SigmaStat 2.0 (SPSS Inc., Chicago, IL, U.S.A.). Second, total protein of experimental samples was determined by comparing respective densitometric values to the established standard curve (when ρ2 > 0.99). Determined total protein concentration of HOTC samples was used to normalize (via dilution as needed) protein content of samples for subsequent uniform evaluation of cytokine content. All subsequent immunoassay measurements were based on sample total protein contents that varied less than 15%.

Cytokine measurements

Cytokines were measured using a Bio-Plex Rat 9-Plex A Panel (Bio-Rad), a multiplexed MFCA immunoassay kit, in conjunction with a Cytokine Reagent Kit (Bio-Rad), and a Bio-Plex Protein Array System (Bio-Rad) according to protocols recently established in our laboratories (Hulse et al., 2004) and summarized below. The 9-Plex A Panel consisted of the following analytes: IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, GM-CSF, IFN-γ, and TNF-α.

The cytokine assays were performed for culture media and tissue homogenates as follows. Standards and positive controls were created using lyophilized recombinant cytokines (9-Plex A Panel) in Cell Lysis Buffer at concentrations that bracketed and were within the expected concentrations for measured cytokines, respectively. A 96-well multiscreen plate (Cytokine Reagent Kit) was prewashed with Assay Buffer (Cytokine Reagent Kit) using a multichannel pipette (#EDP3-Plus; Rainin, Oakland, CA, U.S.A.). Microspheres (9-Plex A Panel) were sonicated for 1 minute, diluted to 1x in Assay Buffer, and 50 μL pipetted in each well. The plate was washed twice with Wash Buffer (Cytokine Reagent Kit), fluid removed by a calibrated vacuum using a MultiScreen Resist Vacuum Manifold (Millipore, Billerica, MA, U.S.A.) and the bottom of plate blotted with a paper towel.

Samples, standards, and positive controls (50 μL each) were then pipetted into individual wells on the plate. Samples and positive controls were run in triplicate, standards and blanks in duplicate. The plate was then sealed and covered with foil and allowed to incubate for 90 minutes at room temperature on an orbital shaker (model MTS-4 shaker; IKA-Works, Inc., Wilmington, NC, U.S.A.). Fluid was then removed by vacuum, the plate washed three times with Wash Buffer (100 μL each wash), and blotted between each fluid removal. Detection Antibody (9-Plex A Panel) was diluted 1x in Antibody Diluent (Cytokine Reagent Kit) and 25 μL added to each well. The plate was sealed and covered with foil again and allowed to incubate for 30 minutes. The fluid was then removed by vacuum, the plate washed three times with Wash Buffer (100 μL each wash), and blotted between each fluid removal. Streptavidin-PE (Cytokine Reagent Kit) was diluted 1x in Assay Buffer and 50 μL added to each well. The plate was sealed and covered with foil and allowed to incubate for 10 minutes. The fluid was then removed by vacuum, the plate washed three times with Wash Buffer (100 μL each wash), and blotted between each fluid removal. Last, 125 μL of Assay Buffer was added to resuspend the beads, and the plate was sealed and shaken at 1,100 RPM for 1 minute. At all incubation steps, the first 30 seconds of incubation on the orbital shaker was at 1,100 RPM, with the remaining time at 300 RPM. The plate was then placed in the Bio-Plex Protein Array System and processed for cytokine detection.

Data analysis for results was performed using Bio-Plex Manager 3.0 software (Bio-Rad). Standards and positive controls were assessed for goodness of fit (defined as observed/expected value × 100) and samples were assessed using a coefficient of variation. Standards exhibiting 70% to 130% of expected value were used to create five parameter logistic regression curves using a weighting model. Positive controls were accepted as accurate if they exhibited 70% to 130% of expected values. Samples with greater than 10% coefficient of variation were excluded from analysis. Finally, results were exported to Excel (Microsoft, Redmond, WA, U.S.A.).

Immunohistochemistry

Hippocampal organotypic cultures were prepared for immunostaining as described previously (Kunkler and Kraig, 1997). Briefly, cultures were fixed overnight in an ice-cold solution of 10-mmol/L sodium periodate, 75-mmol/L lysine-HCL, and 2% paraformaldehyde fixative in 37-mmol/L phosphate buffer (pH 6.2). The cultures were then gently removed from the insert with a fine brush and placed in 10-mmol/L PBS (7.4 pH) for an additional 24 hours. The latter solution also contained 1% Triton X-100 and 0.01% NaN3 (Sigma). Next, the cultures were quenched with 0.3% H2O2 in PBS for 15 minutes, washed three times in PBS for 10 minutes each, and placed for 1 hour in blocking solution consisting of 3% goat serum, 0.25% Triton X-100, and 0.01% NaN3 in PBS to block nonspecific binding. The cultures were then incubated overnight at 4°C in blocking solution containing either OX-42 (1:1,000 dilution; Serotec, Raleigh, NC, U.S.A.), IL-1α (1:500; Serotec), IL-1β (1:200; Serotec), or IFN-γ (1:200; Biosource International, Camarillo, CA, U.S.A.). After three washes in PBS, the cultures were incubated in peroxidase-labeled secondary antibodies (1:100) for 1 hour. The immunoreactive product was visualized with the diaminobenzidine reaction. To examine the specificity of the immunoreactivity, the primary antibody was omitted to provide a nonspecific control.

Histology

Hippocampal organotypic cultures were processed for histological analysis 3 days after experimental procedures to determine if sham or SD manipulations irreversibly injured neurons. HOTCs were fixed and processed for routine plastic embedding, serially sectioned (1 μm) using a ultramicrotome, stained with 1% toluidine blue, and examined using light microscopy.

Statistics

All values are given as mean ± SD. Descriptive statistics, Student’s t test, and analysis of variance were performed using SigmaStat 2.0 for Windows. Results were plotted as horizontal bar charts using SigmaPlot 8.0 (SPSS Inc.). CorelDraw 11.0 (Corel, Ontario, Canada) and Photoshop 6.0 (Adobe, San Jose, CA, U.S.A.) were used to create final figures.

RESULTS

Spreading depression initiation in HOTCs

Spreading depression could be reliably induced by single bipolar electrical stimulation when the Ringer’s was transiently switched to NaAc-containing Ringer’s (Kunkler and Kraig, 1998a, 2004). Recurrent SD, induced over a 1-hour period, resulted in 6.7 ± 0.5, 6.5 ± 0.8, and 6.6 ± 0.7 SD episodes in the 6-hour, 1-day, and 3-day recovery groups, respectively (n = 11 for each group; range 5 to 7). Figure 1 shows the electrophysiologic recording paradigm and typical interstitial DC changes of SD in HOTCs. The DC change consisted of a very rapid deflection followed by a characteristic “inverted saddle” waveform similar to that observed in the in vivo hippocampus (Herreras and Somjen, 1993). Peak negative interstitial DC potentials often reached 30 to 40 mV followed by a DC shift toward baseline that variably included spontaneous epileptiform activity. In the sham-treated groups, no SDs were recorded in the 6-hour or 1-day sham groups (n = 10 each), but in a few instances SDs were induced in the 3-day-recovery group (0.5 ± 0.5, range 0 to 1; n = 10).

Histology

There were no marked differences in neuronal morphology evident in toluidine blue-stained sections from normal HOTCs (n = 3) and those recovered for 3 days after sham control (n =3) or SD (n =3) treatment (Fig. 2). This is consistent with observations made in vivo showing that neocortical SD does not trigger irreversible neuronal injury (Nedergaard and Hansen, 1988). Pyramidal neurons from CA1 in normal HOTCs and both treatment groups displayed large cell bodies containing an oval nucleus with a prominent nucleolus and large clusters of Nissl bodies throughout the cytoplasm, without histologic evidence of neuronal injury (Duchen, 1992). However, recurrent SD in HOTCs induced astrocytic morphology changes consistent with reactive astrogliosis. Astrocytic nuclei were somewhat enlarged and more eccentrically located compared with their sham counterparts (Duchen, 1992). These are analogous to astrocytic changes that occur in vivo after neocortical SD (Kraig et al., 1991).

FIG. 2
Representative photomicrographs showing normal CA1 area neural cell histology in hippocampal organotypic culture. One-micron-thick toluidine blue-stained sections show age-matched CA1 pyramidal neurons (arrowheads) and astrocytes (arrows) in normal (left), ...

Immunoassays

Several indices were measured to determine the accuracy and range of the multiplexed MFCAs (Table 1). First, “goodness of fit” (i.e., a measure of accuracy defined as observed/expected concentrations × 100) was determined for standards and positive controls. For example, “goodness of fit” determinations showed that 7.2 ± 0.7 (n = 288; e.g., 4 plates with 9 analytes per plate and 8 standards per analyte) of 8 values of each standard were within 70% to 130% of their expected ranges. Similarly, all values for the positive control measurements (n = 3/analyte and 9 analytes per assay plate using 4 assay plates) fell within 70% to 130% of the expected percent recovery levels—thus further confirming the accuracy and reproducibility of the assays. Second, the range of assay response for each analyte was determined based on the recovered standard values. All analytes displayed a wide range that extended three to four orders of magnitude from 2 to 4 pg/mL to 16,000 to 32,000 pg/mL with only IL-10 (e.g., 50 to 32,000 pg/mL) showing a more narrowed range. Finally, the mean intraassay coefficient of variation (for tissue and culture media) was 7% (n = 4) and the interassay coefficient of variation was 12% (n = 4), a reproducibility that compares with the best of single enzyme-linked immunosorbent assay measurements (Davies, 2001).

TABLE 1
Bio-Plex 9-cytokine measurement characteristics

These results support the potential impact that MFCA use can have on studies designed to determine how cytokines and their related cascades modulate brain function in health and disease (Hulse et al., 2004). Indeed, MFCAs are well suited as tools to help dissect complex interactions among cytokine (and other) protein signaling molecules because they are accurate, reproducible, and sensitive measurement strategies that are responsive within the physiologic range (i.e., 1 to 1,000 pg/mL; Oppenheim and Feldmann, 2001) yet also can extend to pathophysiologic range.

Simultaneous measurements of nine cytokines from SD and sham-treated tissue samples are shown in Fig. 3. In age-matched normal cultures, only four of the nine cytokines were measurable (IL-1α, 14.8 ± 12.3; IL-1β, 123.2 ± 44.7; IL-6, 9.2 ± 3.8; IFN-γ, 8.6 ± 6.2 pg/mg). After 6 hours of recovery from recurrent SD or sham treatment, detectable levels of eight of nine cytokines were present. Sham-treated cultures had tissue levels of IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, IFN-γ, and TNF-α of 1,081 ± 411, 27,036 ± 10,538, 27 ± 112, 20 ± 8, 115 ± 32, 220 ± 212, 71 ± 47, and 171 ± 75 pg/mg, respectively. SD cultures had levels of 2,488 ± 1,003, 34,467 ± 4,328, 48 ± 14, 42 ± 9, 209 ± 96, 531 ± 409, 199 ± 56, and 340 ± 42 pg/mg, respectively. All cytokine levels were significantly increased (P < 0.05; n = 5 to 9 for all samples, Student’s t test) after SD compared with the sham-treated cultures, except for IL-1β levels, which showed no difference between groups at 6 hours. GM-CSF was below the detection limit of 2 pg/mL at all recovery time points in both the tissue and culture media assays and therefore is not shown in Figs. 3 or or44.

FIG. 3
Tissue cytokine changes in hippocampal organotypic cultures after SD. Tissue cytokine measurements from sham-treated (light-gray bars) and SD-treated (dark-gray bars) cultures were made after recovery of 6 hours, 1 day, and 3 days (left, middle, and right ...
FIG. 4
Cytokine changes in culture media from hippocampal organotypic cultures after SD. Cytokine measurements from culture media obtained from sham-treated (light-gray bars) and SD-treated (dark-gray bars) cultures were made after recovery of 6 hour, 1 day, ...

By 1 day of recovery, all tissue cytokines levels measured in the SD cultures were below those measured at 6 hours of recovery (Fig. 3). In contrast, four of eight tissue cytokine levels in the sham-treated cultures were higher at 1 day of recovery. Sham-treated cultures had tissue levels of IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, and IFN-γ of 1,046 ± 390, 25,918 ± 8,990, 29 ± 11, 33 ± 12, 50 ± 17, 331 ± 301, and 83 ± 75 pg/mg, respectively, whereas SD cultures had levels of 470 ± 297, 17,738 ± 4,864, 27 ± 12, 34 ± 18, 38 ± 22, 457 ± 518, and 134 ± 51 pg/mg, respectively. The reduction in cytokines in the SD-treated cultures at 1 day of recovery resulted in significantly decreased levels of IL-1α and IL-1β (P < 0.05, Student’s t-test) compared with the sham-treated cultures, whereas no differences between conditions were detected in the other cytokines (n = 5 to 9 samples for each). In addition, TNF-α decreased dramatically in both groups, compared with their levels at the 6-hour recovery time point, and fell below the detection limit of 4 pg/mL.

At 3 days of recovery, measurable cytokines levels in both treatment groups continued to decline except for IFN-γ levels in sham-treated cultures, which increased. Although the decline for most cytokines was slight, noticeable exceptions were observed in IL-1α and IL-1β. These cytokines in sham and SD groups were reduced by nearly 20-fold and 3-fold, respectively. Furthermore, these two cytokines now were significantly greater (P < 0.05, Student’s t-test) in the SD group compared with their sham counterparts. Sham-treated cultures had tissue levels of IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, and IFN-γ of 56 ± 39, 1,166 ± 962, 21 ± 8, 23 ± 14, 23 ± 12, 157 ± 147, and 174 ± 141 pg/mg, respectively, whereas SD cultures had levels of 153 ± 65, 5,067 ± 2,548, 22 ± 6, 30 ± 21, 30 ± 15, 95 ± 112, and 131 ± 16 pg/mg, respectively (n = 5 to 9 samples for each). As seen in the 1-day results, TNF-α levels remained below detectable limits in both treatment groups.

In addition to tissue sample determinations of cytokine levels, culture media were also analyzed. Media samples were obtained from 3-day-recovery cultures at 6 hour, 1 and 3 day recovery time points to measure extracellular cytokine levels. In culture media obtained from age-matched normal cultures, none of the 9 cytokines were measurable (i.e., below the standard curve detection limits). After recovery from recurrent SD or sham treatment, detectable levels of 4 out of 9 cytokines were present in both conditions at each time point (Fig. 4). At 6 hours of recovery, sham-treated cultures had media levels of IL-1β, IL-6, IL-10, and TNF-α of 10 ± 5, 43 ± 16, 113 ± 17, and 96 ± 60 pg/mL, respectively, whereas SD-treated cultures had levels of 8 ± 4, 71 ± 55, 78 ± 13, and 287 ± 240 pg/mL, respectively (n = 5 for each measurement). IL-10 was significantly greater (P < 0.05, Student’s t-test) in the media of sham-treated cultures compared with media obtained from SD-treated cultures at 6 hours recovery. By 1 day recovery, the levels of IL-6 and TNF-α were significantly greater (P < 0.05, Student’s t-test) in the media of SD-treated cultures. Sham-treated cultures at 1 day of recovery had media levels of IL-1β, IL-6, IL-10, and TNF-α of 22 ± 15, 94 ± 58, 89 ± 11, and 128 ± 72 pg/mL, respectively, whereas media from SD-treated cultures had levels of IL-1β, IL-6, and TNF-α of 44 ± 25, 258 ± 95, and 585 ± 260 pg/mL, respectively (n = 5 for each measurement). Levels of IL-10 in the SD treated cultures fell below the assay detection limit for this analyte (50 pg/mL).

Cytokine levels at 3 days of recovery varied little from those measured at 1 day. Levels of IL-6 and TNF-α remained significantly greater (P < 0.05, Student’s t-test) in the media of SD-treated cultures compared with the sham-treated cultures. Sham-treated cultures had media levels of IL-1β, IL-6, IL-10, and TNF-α of 20 ± 11, 90 ± 56, 87 ± 18, and 86 ± 11 pg/mL, respectively, whereas media from SD-treated cultures had levels of 61 ± 50, 257 ± 77, 92 ± 20, and 437 ± 212 pg/mL, respectively (n = 5 for each measurement).

Immunohistochemistry

To confirm the results of the multiplexed MFCA and begin to define sources for increased cytokine expression, we performed immunostaining studies with selected cytokine antibodies. In addition, we performed labeling studies with the microglial marker OX-42 to determine if SD in HOTCs induced activation of microglia similar to that seen in vivo (Caggiano and Kraig, 1996; Gehrman et al., 1993). In normal HOTCs, OX-42 positive microglia typically displayed a small soma from which extended numerous finely branched processes (Fig. 5). By 1 day of recovery in both the sham and SD-treated cultures, OX-42–positive microglia appeared slightly larger with shorter processes. This morphologic transformation from a resting to an active species (Streit, 1995) was more evident by 3 days of recovery in the SD-treated cultures, where OX-42–positive microglia were more densely localized and displayed an increased staining intensity. Immunostaining for IL-1α, IL-1β, and IFN-γ were also found in both the sham and SD-treated cultures. Labeling for each cytokine was observed throughout the cultures but was expressed in cells with morphology typical of microglia (Fig. 5E–G). Although several TNF-α antibodies from commercial sources were used, no consistent cellular immunostaining was achieved, a result noted by Jander and coworkers (2001).

FIG. 5
Representative photomicrographs showing immunostaining changes in hippocampal organotypic culture after SD treatment and recovery. Top panel of images shows OX-42 immunostaining in normal HOTC (A), 1-day sham recovery (B), 1-day SD recovery (C), and 3-day ...

DISCUSSION

Our results show several fundamentally new findings about cytokine protein changes from SD in HOTCs. First, SD triggered cellular responses in HOTCs that parallel those seen in vivo. Second, sham treatment alone was sufficient to prompt increased tissue cytokine content for eight of nine targeted proteins. Third, recurrent SD nonetheless triggered a significant rise in seven of nine cytokines 6 hours later, which included localization to microglia (i.e., IL-1α, IL-1β, IFN-γ) and in some instances (i.e., IL-6 and TNF-α) extended to include the surrounding media by 1 and 3 days. The remaining cytokine (i.e., IL-1β) became significantly different at 1 and 3 days. Fourth, IL-10 content, although significantly higher in HOTC tissue 6 hours after SD, was significantly lower in surrounding media at this time and at 1 day. Finally, this generalized early increase in tissue cytokines later settled to a pattern centering on changes in IL-1α, IL-1β, and TNF-α, cytokines known to be capable of modulating ischemic injury severity.

Cellular responses of HOTCs to spreading depression

Hippocampal organotypic cultures cellular responses to SD are consistent with those seen in vivo. For example, neocortical SD (Nedergaard and Hansen, 1988) does not irreversibly injure neurons. Similarly, SD in HOTCs shows no evidence of irreversible neuronal injury. Indeed, the thin-section histologic staining does not show evidence of reversible neuronal injury (e.g., see Fig. 2) (Duchen, 1992). Furthermore, SD in vivo activates astrocytes (Kraig, et al., 1991) and microglia (Caggiano and Kraig, 1996; Gehrman et al., 1993). In parallel with these in vivo glial changes, SD in HOTCs similarly triggered astrocytes and microglia to show evidence of activation. Finally, preliminary evidence indicates SD can induce IT in HOTCs (Kunkler and Kraig, 1998b).

Multiplexed determination of cytokines in HOTCs

The cytokines used here (i.e., IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, GM-CSF, IFN-γ, and TNF-α) are categorized for ease in understanding as principally either pro-inflammatory (i.e., IL-1α, IL-1β, IL-2, IL-6, GM-CSF, IFN-γ, and TNF-α) or antiinflammatory (i.e., IL-4 and IL-10) (Oppenheim and Feldmann, 2001). Our intent with their use was to begin determining whether brain tissue and SD could trigger a cytokine-cascade phenomenon (Oppenheim and Feldmann, 2001) like those defined for systemic organ systems (Feldmann and Brennan, 2001; Oppenheim and Feldmann, 2001). We believe (Hulse et al., 2004), like others (del Zoppo et al., 2000; Stoll et al., 2000), such cascade behavior also is likely to be important for brain function, including SD. Furthermore like others (Wang et al., 2000a, b), these investigators also suggest that to more fully understand cytokine impact, measurement of targeted cytokine proteins is preferable (when possible) to measurement of related mRNA species. This sentiment stems from the fact that mRNAs (including those for cytokines) are not always transcribed to their related proteins (Wang et al., 2000a,b).

Cytokine levels in normal HOTCs are generally consistent with those seen in vivo in brain tissue using single enzyme-linked immunosorbent assays and MFCAs. For example, levels for IL-1α, IL-1β, and IFN-γ were 15, 123, and 9 pg/mg tissue, respectively, in normal HOTCs. These values compare favorably with single enzyme-linked immunosorbent assay measurements from brain in vivo. Dinkel and coworkers (2003) report values of 25 and 6 pg/mg for IL-1β and TNF-α. Similarly, Alan and coworkers (2001) report IL-1α as 35 pg/mg and IL-6 as 150 pg/mg in brain. Using MFCAs as employed here, Hulse and coworkers (2004) report levels for IL-1α, IL-1β, IL-6, and IFN-γ of 78, 24, 226, and 44 pg/mg, respectively for sham control animals. Notably, the latter workers also report levels for IL-2, IL-4, IL-10, GM-CSF and TNF-α of 22, 12, 810, 26 and 6 pg/mg tissue, respectively, cytokines not seen (or too low for measurement) in HOTCs at rest.

Variations between cytokine levels reported here for HOTCs and those in the literature for their in vivo counterparts may be due to differences in animal or sample handling, differences in choice of antibody pairs for assays, differences in laboratory techniques, and of course differences between animal preparations (i.e., whole brain and HOTCs) (for review see Hulse et al., 2004).

Cytokine changes after sham manipulations in HOTCs

Sham manipulations alone (i.e., that included transient NaAc-Ringer’s exposure) were sufficient to trigger a generalized increase in HOTC cytokine production. This begins to show several noteworthy features of cytokine protein behavior in HOTCs (and perhaps brain in vivo). First, cytokines not evident at rest (i.e., IL-2, IL-4, IL-10 and TNF-α) could be robustly produced, thus revealing an inherent capacity for their synthesis by HOTCs, like that seen in vivo. Second, increased cytokine protein production by HOTCs may stem from increased neural activity due to reduced inhibition due to NaAc exposure (Kunkler and Kraig, 2004). Neural activity triggers increased expression of TNF-α (Beattie et al., 2002), which in turn may augment production of other cytokines (Oppenheim and Feldmann, 2001). Finally, other factors such as mechanical injury from microelectrode placement, media-to-Ringer’s change, and rinsing could conceivably increase cytokine levels.

Cytokine changes after SD in HOTCs

Our work confirms and extends the in vivo work of Jander et al. (2001). They noted increases in IL-1β and TNF-α mRNAs 4 hours after recurrent SD, which return toward baseline by 16 hours. Furthermore, they noted maximally increased immunostaining for IL-1β at 8 hours in microglia. We found that IL-1α, IL-2, IL-4, IL-6, IL-10, IFN-γ, and TNF-α proteins increased significantly at 6 hours after SD with localization of IL-1α and IFN-γ to cells morphologically consistent with microglia. At the same time, no spillage of cytokines to surrounding media occurred other than that for IL-10, which was significantly less in the SD group. By 1 day, the significant HOTC tissue cytokine changes from SD were a decrease of IL-1α and IL-1β with IL-1β also localized to microglia via immunostaining. This was coupled to a continued significantly lower level of IL-10 in media that also now included significant media rises in IL-6 and TNF-α. Finally by 3 days after SD, HOTC tissue levels of IL-1α and IL-1β had returned to significantly greater levels whereas media continued to show a significant rise of IL-6 and TNF-α.

Features of these changes warrant specific comment. First, the initial significant increase in seven cytokines resembles the generalized burst production seen in other organ systems that functionally operate as a cascade, with TNF-α as the key triggering cytokine change (Feldmann and Brennan, 2001; Oppenheim and Feldmann, 2001). Measurements made with finer temporal resolution that include use of neutralization antibodies in the future will help confirm this notion. Second, media changes included alterations in IL-6 and IL-10. Significantly elevated IL-6 by SD could be involved in neuroprotection at 3 days (Carlson et al., 1999; Stoll et al., 2000), although elevated serum IL-6 significantly correlates with infarct volume in humans (Smith et al., 2004). The significant decline of IL-10 in media 6 hours and 1 day after SD seems unlikely to stem from diminished production because absolute levels in all groups are above baseline. Instead, the SD-related decline in media may be due to a more “active” retention of IL-10 by SD-treated HOTCs. This could be due to interaction of IL-10 with receptors found on microglia (de Waal Malefyt, 2001a). Perhaps this reflects an initial attempt to limit tissue proinflammatory cytokine production including IL-1α, IL-1β, and TNF-α (de Waal Malefyt, 2001b), which were significantly reduced (or undetectable, respectively) at 1 day after SD.

Third, fluctuations in IL-1α and IL-1β levels after SD correlate with the abilities of SD and IL-1 to modulate ischemic injury. For example, pretreatment with IL-1α before ischemic injury is neuroprotective whereas neutralization of IL-1β via IL-1 receptor antagonist can block IT-induced neuroprotection (Ohtsuki et al., 1996). SD worsens injury from ischemia that occurs 1 day later (Takano et al., 1996), a time when levels of IL-1α and IL-1β in HOTCs were significantly reduced. However, SD reduces ischemic injury at 3 days (Kawahara et al., 1995; Kobayashi et al., 1995; Matsushima et al., 1996), a time when levels of both IL-1α and IL-1β were significantly greater than in sham controls. This may seem contradictory to the fact that IL-1β antagonism also can lessen the severity of ischemic injury (Relton and Rothwell, 1992). However, the basis for this apparent paradox may lie in the levels of IL-1β. Pringle and coworkers (2001) show that low (10 to 100 pg/mL) levels of IL-1β potentiate hypoxic injury in HOTCs whereas high levels (1 to 100 ng/mL) have no additional impact. In contrast, these high levels are neuroprotective against NMDA neurotoxicity. These differential IL-1β effects may be due to parallel effects on neuronal calcium homeostasis. Low levels of IL-1β (50 pg/mL) enhance NMDA receptor mediated intracellular calcium rise from NMDA exposure by 45% whereas high levels (1,000 pg/mL) reduce it by 20% (Viviani et al., 2003).

Fourth, the timing of cytokine changes could also have pathophysiologic significance. For example, neurotoxicity is seen with acutely elevated TNF-α whereas more prolonged elevation occurs with neuroprotection (for review see Saha and Pahan, 2003). SD triggered a significant rise in TNF-α evident in HOTC tissue only at 6 hours with media levels significantly elevated at 1 and 3 days after SD. Conceivably, this TNF-α pattern of change could contribute to the early worsening and later lessening of ischemic injury associated with the phenomenon. Why HOTC tissue levels of TNF-α were too low for measurement (yet elevated in media) at 1 and 3 days after SD remains unclear. Perhaps activated tissue more rapidly degrades TNF-α.

Finally, the increase in IFN-γ seen after SD and its localization to microglia (like that of IL-1α and IL-1β) provide important support to indicate that brain tissue has an intrinsic ability to synthesize this cytokine. IFN-γ is the main activator of macrophages (Billeau and Vandenbroek, 2001) and, most likely, microglia. Furthermore, recent evidence suggests that IFN-γ activate microglia by autocrine signaling via production of TNF-α (Nguyen and Benveniste, 2002). If also true for SD, increased IFN-γ from microglia may well be the first signal heralding a cytokine-cascade–based modulation of ischemic injury by SD.

Acknowledgments

The authors thank Marcia P. Kraig for hippocampal organ culture maintenance and Ms. Jennifer Lowe for secretarial assistance.

This work was supported by a grant from the National Institute of Neurological Disorders and Stroke (NS-19108), and grants from the American Heart Association (Bugher Award to R.P.K. and SDG award to P.E.K.).

References

  • Allan SM, Harrison DC, Read S, Collins B, Parsons AA, Philpott K, Rothwell NJ. Selective increases in cytokines expression in the rat brain in response to striatal injections of α-amino-3-hydroxy-5-methyl-4-isoxazoleproprianate and interleukin-1. Mol Brain Res. 2001;93:180–189. [PubMed]
  • Arvin B, Neville LF, Barone FC, Feuerstein GZ. The role of inflammation and cytokines in brain injury. Neurosci Biobehav Rev. 1996;20:445–452. [PubMed]
  • Bahr BA. Long-term hippocampal slices: a model system for investigating synaptic mechanisms and pathological processes. J Neurosci Res. 1995;42:294–305. [PubMed]
  • Bahr BA, Kessler M, Rivera S, Vanderklish PW, Hall RA, Mutneja MS, Gall C, Hoffman KB. Stable maintenance of glutamate receptors and other synaptic components in long-term hippocampal slices. Hippocampus. 1995;5:425–439. [PubMed]
  • Barone FC, Arvin B, White RF, Willette RN, Feuerstein GZ. Tumor necrosis factor-α: a mediator of focal ischemic brain injury. Stroke. 1997;28:1233–1244. [PubMed]
  • Beattie EC, Stellwagen D, Morishita W, Bresnahan JC, Ha BK, Von Zastrow M, Beattie MS, Malenka RC. Control of synaptic strength by glial TNFα Science. 2002;295:2282–2285. [PubMed]
  • Billeau A, Vandenbroek K. In: IFNγ Cytokine reference. Oppenheim JJ, Feldmann M, editors. Vol. 1. New York, NY: Academic Press; 2001. pp. 641–680.
  • Caggiano AO, Kraig RP. Eicosanoids and nitric oxide influence induction of reactive gliosis from spreading depression in microglia but not astrocytes. J Comp Neurol. 1996;369:93–108. [PMC free article] [PubMed]
  • Carlson NG, Wieggel WA, Chen J, Bacchi A, Rogers SW, Gahring LC. Inflammatory cytokines IL-1α, IL-1β, IL-6, and TNF-α impart neuroprotection to an excitotoxin through distinct pathways. J Immunol. 1999;163:3963–3968. [PubMed]
  • Davies C. Concepts. In: Wild D, editor. The immunoassay handbook. 2. Vol. 99. New York, NY: Nature Publ. Group; 2001. pp. 78–110.
  • Debanne D, Guerineau NC, Gähwiler BH, Thompson SM. Physiology and pharmacology of unitary synaptic connections between pairs of cells in areas CA3 and CA1 of rat hippocampal slice cultures. J Neurophysiol. 1995;73:1282–1294. [PubMed]
  • de Waal Malefyt R. IL-10. In: Oppenheim JJ, Feldmann M, editors. Cytokine Reference. Vol. 1. New York, NY: Academic Press; 2001a. pp. 165–185.
  • de Waal Malefyt R. IL-10 receptor. In: Oppenheim JJ, Feldmann M, editors. Cytokine reference. Vol. 2. New York, NY: Academic Press; 2001b. pp. 1495–1502.
  • del Zoppo G, Ginis I, Hallenbeck JM, Iadecola C, Wang Z, Feuerstein GZ. Inflammation and stroke: putative role for cytokines, adhesion molecules and iNOS in brain response to ischemia. Brain Pathol. 2000;10:95–112. [PubMed]
  • Dinkel K, MacPherson A, Sapolsky RM. Novel glucocorticoid effects on acute inflammation in the CNS. J Neurochem. 2003;84:705–716. [PubMed]
  • Dirnagl U, Simon RP, Hallenbeck JM. Ischemic tolerance and endogenous neuroprotection. Trends Neurosci. 2003;26:248–254. [PubMed]
  • Duchen LW. General pathology of neurons and neuroglia. In: Adams JH, Duchen LW, editors. Greenfield’s neuropathology. 5. New York: Oxford; 1992. pp. 1–68.
  • Feldmann M, Brennan FM. Cytokines and disease. In: Oppenheim JJ, Feldmann M, editors. Cytokine reference. Vol. 1. New York, NY: Academic Press; 2001. pp. 35–51.
  • Gähwiler BH, Capogna M, Debanne D, McKinney RA, Thompson SM. Organotypic slice cultures: a technique has come of age. Trends Neurosci. 1997;20:471–477. [PubMed]
  • Gehrman J, Mies G, Bonnekoh P, Banati R, Iijima T, Kreutzberg GW, Hossmann KA. Microglial reaction in the rat cerebral cortex induced by cortical spreading depression. Brain Pathol. 1993;3:11–17. [PubMed]
  • Ginis I, Jaiswal R, Klimanis D, Liu J, Greenspon J, Hallenbeck JM. TNF-alpha-induced tolerance to ischemic injury involves differential control of NF-kappaB translocation: the role of NF-kappaB association with p300 adaptor. J Cereb Blood Flow Metab. 2002;22:142–152. [PubMed]
  • Gutierrez R, Heinemann U. Synaptic reorganization in explanted cultures of rat hippocampus. Brain Res. 1999;815:304–316. [PubMed]
  • Harris KM, Jensen FE, Tsao B. Three-dimensional structure of dendritic spines and synapses in rat hippocampus (CA1) at postnatal day 15 and adult ages: implications for the maturation of synaptic physiology and long-term potentiation. J Neurosci. 1992;12:2685–2705. [PubMed]
  • Herreras O, Somjen GG. Analysis of potential shifts associated with recurrent spreading depression and prolonged unstable SD induced by microdialysis of elevated K+ in hippocampus of anesthetized rats. Brain Res. 1993;610:283–294. [PubMed]
  • Hulse R, Kunkler PE, Fedynyshyn JP, Kraig RP. Optimization of multiplexed bead-based protein immunoassays for rat serum and brain tissue. J Neurosci Methods. 2004;136:87–98. [PMC free article] [PubMed]
  • Jander S, Schroeter M, Peters O, Witte OW, Stoll G. Cortical spreading depression induces proinflammatory cytokine gene expression in the rat brain. J Cereb Blood Flow Metab. 2001;21:218–225. [PubMed]
  • Kawahara N, Ruetzler CA, Klatzo I. Protective effect of spreading depression against neuronal damage following cardiac arrest cerebral ischemia. Neurol Res. 1995;17:9–16. [PubMed]
  • Kobayashi S, Harris VA, Welsh FA. Spreading depression induces tolerance of cortical neurons to ischemia in rat brain. J Cereb Blood Flow Metab. 1995;15:721–727. [PubMed]
  • Kraig RP, Dong L, Thisted R, Jaeger CB. Spreading depression increases immunohistochemical staining of glial fibrillary acidic protein. J Neurosci. 1991;11:2187–2198. [PMC free article] [PubMed]
  • Kunkler PE, Kraig RP. Reactive astrocytosis from excitotoxic injury in hippocampal organ culture parallels that seen in vivo. J Cereb Blood Flow Metab. 1997;17:26–43. [PMC free article] [PubMed]
  • Kunkler PE, Kraig RP. Calcium waves precede electrophysiological changes of spreading depression in hippocampal organ cultures. J Neurosci. 1998a;18:3416–3425. [PMC free article] [PubMed]
  • Kunkler PE, Kraig RP. Spreading depression induces tolerance to excitotoxic injury in hippocampal organ cultures. Soc Neurosci Abst. 1998b;24:2013.
  • Kunkler PE, Kraig RP. P/Q Ca2+ channel blockade stops spreading depression and related pyramidal neuronal Ca2+ rise in hippocampal organ culture. Hippocampus. 2004 doi: 10.1002/hipo.10181. published online 11/20/03. [PMC free article] [PubMed] [Cross Ref]
  • Kunkler PE, Hulse RE, Kraig RP. Spreading depression (SD) worsens and lessens stroke injury by intrinsic pro- and anti-inflammatory mediator profile changes. Abstr Soc Neurosci. 2003:951.4.
  • Ma XC, Gottschall PE, Chen LT, Wiranowska M, Phelps CP. –2003) Role and mechanisms of interleukin-1 in the modulation of neurotoxicity. Neuroimmunomodulation. 2002;10:199–207. [PubMed]
  • Matsushima K, Hogan MJ, Hakim AM. Cortical spreading depression protects against subsequent focal cerebral ischemia in rats. J Cereb Blood Flow & Met. 1996;16:221–226. [PubMed]
  • McKinney RA, Capogna M, Dürr R, Gähwiler BH, Thompson SM. Miniature synaptic events maintain dendritic spines via AMPA receptor activation. Nat Neurosci. 1999;2:44–49. [PubMed]
  • Nawashiro H, Tasaki K, Ruetzler CA, Hallenbeck JM. TNF-α pretreatment induces protective effects against focal cerebral ischemia in mice. J Cereb Blood Flow Metab. 1997;17:483–490. [PubMed]
  • Nedergaard M, Hansen AJ. Spreading depression is not associated with neuronal injury in the normal brain. Brain Res. 1988;449:395–398. [PubMed]
  • Nguyen VT, Benveniste ET. Critical role for tumor necrosis factor-α NF-κB in interferon-γ-induced CD40 expression in microglia/macrophages. J Biol Chem. 2002;277:13796–13803. [PubMed]
  • Ohtsuki T, Ruetzler CA, Tasaki K, Hallenbeck JM. Interleukin-1 mediates induction of tolerance to global ischemia in gerbil hippocampal CA1 neurons. J Cereb Blood Flow Metab. 1996;16:1137–1142. [PubMed]
  • Oppenheim JJ, Feldmann M. Introduction to the role of cytokines in inate host defense and adaptive immunity. In: Oppenheim JJ, Feldmann M, editors. Cytokine Reference. Vol. 1. New York, NY: Academic Press; 2001. pp. 3–20.
  • Pringle AK, Niyadurupola N, Johns P, Anthony DC, Iannotti F. Interleukin-1beta exacerbates hypoxia-induced neuronal damage, but attenuates toxicity produced by simulated ischemia and excitoxicity in rat organotypic slice cultures. Neurosci Lett. 2001;305:29–32. [PubMed]
  • Relton JK, Rothwell NJ. Interleukin-1 receptor antagonist inhibits ischemic and excitotoxic neuronal damage in the rat. Brain Res. 1992;29:243–246. [PubMed]
  • Saha RN, Pahan K. Tumor necrosis factor-α at the cross roads of neuronal life and death during HIV-associated dementia. J Neurochem. 2003;86:1057–1071. [PMC free article] [PubMed]
  • Schmitt M, Kunkler PE, Aptowicz CO, Kraig RP. Seizures and neuronal loss need not be expected responses of maturing hippocampal organ cultures. Abstr Soc Neurosci. 2002;28:95.6.
  • Schroeter M, Küry P, Jander S. Inflammatory gene expression in focal cortical brain ischemia: differences between rats and mice. Mol Brain Res. 2003;117:1–7. [PubMed]
  • Smith CJ, Emsley HCA, Gavin CM, Georgiou RF, Vail A, Barberan EM, del Zoppo G, Hallenbeck JM, Rothwell NJ, Hopkins SJ, Tyrell PJ. Peak plasma interleukin-6 and other peripheral markers of inflammation in the first week of ischemic stroke correlate with brain infarct volume, stroke severity and long-term outcome. BMC Neurol. 2004;4:2. [PMC free article] [PubMed]
  • Stoll G, Jander S, Schroeter M. Cytokines in CNS disorders: neurotoxicity versus neuroprotection. J Neural Transm Suppl. 2000;59:81–89. [PubMed]
  • Streit P, Thompson SM, Gähwiler BH. Anatomical and physiological properties of GABAergic neurotransmission in organotypic slice cultures of rat hippocampus. Eur J Neurosci. 1989;1:603–615. [PubMed]
  • Streit WJ. Microglial cells. In: Ransom B, Kettenmann H, editors. Neuroglia. New York, NY: Oxford Press; 1995. pp. 85–96.
  • Takano K, Latour LL, Formato JE, Carano RA, Helmer KG, Hasegawa Y, Sotek CH, Fisher M. The role of spreading depression in focal ischemia evaluated by diffusion mapping. Ann Neurol. 1996;39:308–318. [PubMed]
  • Viviani B, Bartesaghi S, Gardoni F, Vezzani A, Behrens MM, Bartfai T, Binaglia M, Corsini E, Di Luca M, Galli CL, Marinovich M. Interleukin-1β enhances NMDA receptor-mediated intracellular calcium increase through activation of the Src family kinases. J Neurosci. 2003;23:8692–8700. [PubMed]
  • Wang X, Li X, Currie RW, Willette RN, Barone FC, Feuerstein GZ. Application of real-time polymerase chain reaction to quantitate induced expression of interleukin-1beta mRNA in ischemic brain tolerance. J Neurosci Res. 2000a;59:238–246. [PubMed]
  • Wang X, Li X, Erhardt JA, Barone FC, Feuerstein GZ. Detection of tumor necrosis factor-α mRNA induction in ischemic brain tolerance by means of real-time polymerase chain reaction. J Cereb Blood Flow Metab. 2000b;20:15–20. [PubMed]
  • Zimmer J, Gähwiler BH. Cellular and connective organization of slice cultures of the rat hippocampus and fascia dentate. J Comp Neurol. 1984;228:432–446. [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • MedGen
    MedGen
    Related information in MedGen
  • PubMed
    PubMed
    PubMed citations for these articles
  • Substance
    Substance
    PubChem Substance links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...