大胆的反应和伽马振荡反应不同于诱发电位交叉EEG-fMRI研究

大胆的反应和伽马振荡反应不同于诱发电位交叉EEG-fMRI研究
大胆的反应和伽马振荡反应不同于诱发电位交叉EEG-fMRI研究

Bio Med Central BMC Neuroscience

Open Access Research article

The BOLD response and the gamma oscillations respond differently than evoked potentials: an interleaved EEG-fMRI study

Jack R Foucher*1, Hélène Otzenberger2 and Daniel Gounot2

Address: 1Clinique Psychiatrique – INSERM U405, H?pitaux Universitaires – BP 406 – 67091 Strasbourg Cedex – France and 2UMR 7004 – CNRS/

ULP – Institut de Physique Biologique, 4 rue Kirschleger – 67085 Strasbourg Cedex – France

Email: Jack R Foucher*-jf@https://www.360docs.net/doc/0417218486.html,; Hélène Otzenberger-otzenber@alsace.u-strasbg.fr; Daniel Gounot-gounot@alsace.u-strasbg.fr

* Corresponding author

Abstract

Background: The integration of EEG and fMRI is attractive because of their complementary

precision regarding time and space. But the relationship between the indirect hemodynamic fMRI

signal and the more direct EEG signal is uncertain. Event-related EEG responses can be analyzed in

two different ways, reflecting two different kinds of brain activity: evoked, i.e. phase-locked to the

stimulus, such as evoked potentials, or induced, i.e. non phase-locked to the stimulus such as event-

related oscillations. In order to determine which kind of EEG activity was more closely related with

fMRI, EEG and fMRI signals were acquired together, while subjects were presented with two kinds

of rare events intermingled with frequent distractors. Target events had to be signaled by pressing

a button and Novel events had to be ignored.

Results: Both Targets and Novels triggered a P300, of larger amplitude in the Novel condition. On

the opposite, the fMRI BOLD response was stronger in the Target condition. EEG event-related

oscillations in the gamma band (32–38 Hz) reacted in a way similar to the BOLD response.

Conclusions: The reasons for such opposite differential reactivity between oscillations / fMRI on

the one hand, and evoked potentials on the other, are discussed in the paper. Those results provide

further arguments for a closer relationship between fast oscillations and the BOLD signal, than

between evoked potentials and the BOLD signal.

Background

There are two core methods to explore human brain func-tion: direct measurement of the electrical activity, as with the electro-encephalogram (EEG), or measurement of the vascular response that is indirectly related to the neuronal activity, as in functional MRI (fMRI) [1]. Because both approaches have complementary advantages, attempts have been made to fuse the high temporal resolution of EEG, with the high spatial resolution of fMRI. Although animal data have made it possible to elucidate some of the relationships between neuronal activity and the Blood Oxygen Level-Dependant contrast (BOLD) [2–5], there is much left to be worked out about the actual relationship between E E G and fMRI. This paper aims at presenting some data showing, through differential reactivity, that not all kinds of E E G responses might be related to the BOLD contrast.

Published: 19 September 2003 BMC Neuroscience 2003, 4:22Received: 03 June 2003 Accepted: 19 September 2003

This article is available from: https://www.360docs.net/doc/0417218486.html,/1471-2202/4/22

? 2003 Foucher et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.

It has been reported that variations in BOLD contrast in response to the presentation of two kinds of rare events, i.e. oddballs, presented a differential reactivity opposite to that observed using Evoked Potentials (EPs). Oddballs are known to evoke a P300, a positive EP around 300–400 ms [6]. EPs are computed by averaging the EEG signal time-locked to the presentation of a stimulus. Activity time-locked to the stimulus emerges from background E E G activity, which is not time-locked and averages to zero [7]. The P300 is mainly perceived on the medial electrodes (Fz, Cz, Pz), although it originates from the temporo-pari-etal junction and the inferior frontal gyrus [8–10]. When an oddball has to be detected, i.e. a Target, this potential is of lower amplitude than when it is presented as an event unrelated to the task, i.e. a Novel [6,11,12]. On the other hand, there are fMRI studies in which no Novel-related activation has been reported although the temporal-pari-etal junction and the inferior frontal gyrus were activated by Targets [13–16].

This study attempts to replicate these findings using com-bined EEG and fMRI measurements so that both record-ings relate to the same brain activity [17,18]. Moreover, E vent-Related Oscillations (E ROs) were computed in order to reveal brain responses not necessarily time-locked to the stimulus. EROs are computed by averaging the time-frequency decomposition of each peristimulus signal. Accordingly, a small jitter in the initiation of an oscillatory response will not average to zero, which is especially valuable in the high-frequency components [19–21]. E ROs in response to auditory oddballs have been described in the gamma band (20–100 Hz), mainly in the 37–40 Hz interval, 360 ms after a Target is pre-sented [22–25]. But the reactivity of E ROs to Novels remains to be assessed.

Five subjects were presented with Targets (the letter "X") and Novels (various pictures) mixed with frequent dis-tractors (the letter "O") while E E G and fMRI data were simultaneously recorded. Results are provided as a fixed effect one-tail t-test, and as multi-subject conjunction analysis to ascertain that all the subjects did present the same differential reactivity. The present study replicates the differential reactivity of EPs and BOLD contrast, with respect to Targets and Novels: the P300 was of signifi-cantly greater amplitude in response to Novels as opposed to Targets. Oppositely, Targets elicited much more fMRI activation than Novels. In accordance with fMRI results, Target-related gamma oscillations were more intense than their Novel-related counterparts, around 300 ms. The rea-sons for such opposite differential reactivity between oscillations / fMRI on the one hand, and evoked poten-tials on the other, are discussed below. Our results sup-port evidence demonstrating that the BOLD signal is better correlated with high-than with low-frequency oscillations.

Results

Behavioral results

the subjects performed the task with an accuracy rate of 98± 2%, with a response time of 474 ms ± 71 ms.

fMRI results

The Target condition is related with activations especially in regions said to be the sources of the P300: the inferior frontal gyrus bilaterally and the right temporo-parietal junction (posterior supramarginal gyrus). Other regions were also activated: the right antero-basal frontal region (BA 10), the anterior cingulate and the supplementary motor areas, bilaterally, the inferior parietal lobule and intraparietal sulcus, and the left central sulcus and thala-mus (pulvinar and dorso-median nuclei) (table 1 – see Additional file 1, fig. 1). Deactivated regions in the Target condition, were the superior frontal sulcus bilaterally, the left inferior frontal gyrus, the right posterior insula, the precuneus and the posterior cingulate bilaterally, the pos-terior part of the superior temporal sulcus, and infero-temporal areas (table 1 – see Additional file 1, fig. 1). The Novel condition induced activation in the left inferior frontal sulcus and the occipital regions bilaterally extend-ing to the left lateral temporal and posterior parietal areas (table 1 – see Additional file 1, fig. 1). The graphs in figure 1 represent the peristimulus BOLD signal for each condi-tion in relevant regions after regressing the effect of the other conditions. The absence of Novel-related activation in the regions said to be the sources of the P300, as shown by peristimulus BOLD responses, allowed to ascertain that this observation, was neither due to a threshold effect nor to an inappropriate statistical analysis model.

EEG results

The N200 and P300 potentials were recorded for both Target and Novel conditions on the medial electrodes (Fz, Cz, Pz), with extension on both centrals (C3, C4). Signif-icant differences in amplitude were found at the local, time-cluster and global levels, that were even greater in the Novel than in the Target condition for Cz, Pz, C3 and C4 (fig. 2). This was evidenced in all the subjects on electrode Cz, with a conjunction probability of p = 0.000025 (see table 1 for subject by subject results at 400 ms).

E ROs also presented a statistical difference between the Target and Novel conditions, but in an opposite manner. Figure 2 shows the statistical comparison map between Targets (red) and Novels (blue). Targets evoked a greater increase in power than Novels between 200 and 500 ms in the 32-Hz band in F7, Cz, C3, C4 and Pz, and in the 34-Hz band in Fz and F8. Figure 3 (top) shows the time

frequency chart for all the electrodes, for Targets (right) and Novels (left), with color-coded standard deviation relative to the reference distribution (-320 to 0 ms). There was a greater difference between the Target and Novel conditions in the 200 to 500 ms interval for the 32- to 38-Hz band. This was confirmed by the statistical map used to compare the two conditions (fig. 3 lower part), with two significant time-frequency clusters between 200 and 500 ms at 32 Hz (p = 0.002) and 38 Hz (p = 0.001) and a global significance of p < 0.0005. There was no significant time-frequency point for the reverse statistics (Novels > Targets). Subject-by-subject conjunction analysis pro-duced the same results, with a multi-subject conjunction probability of p = 0.0014 on electrode Cz at 38 Hz and 320 ms (see table 1 for subject by subject results). It could be argued that EROs were found to be larger in the Target condition, relative to the Novel condition, owing to the limited frequency range explored, so that we performed

Figure 1

fMRI results Lateral views of the normalized brain of 1 subject, colored as a function of contrast: Target-related activation (red and "X" marks), Target-related deactivation (green and "no-smoking" marks), and Novel-related activation (blue) (thresh-olds p ≤ 0.001, 100 voxel). The network that deactivated on target presentation comprised the superior frontal sulcus (SFS), the parietal cortex and the inferior frontal sulcus (IFS). The latter is supposed to be related with distractor inhibition since its posterior part is over-activated by Novels together with the posterior parietal cortex (PP). The network activated by targets comprised the supra-marginal gyrus (SMG) and the inferior frontal gyrus (IFG). Note that the TPJ is composed of the SMG (BA 40) in its upper part, and of the superior temporal gyrus (BA 39) in its lower part. The peristimulus BOLD signals are displayed for each relevant region for Targets (red), Novels (blue) and frequent distractors (gray). The curves are computed by simple averaging after regressing the other condition effect and removing high- and low-frequency components. The variation in signal intensity is indicated as a percentage of the MRI signal, and the scale is similar for all except the parietal area. Notice the bal-ance between the anterior cingulate area (ACA) and the posterior cingulate area (PCA). Those charts also exclude the possi-

bility for a threshold effect to account for the absence of Novel-related activation of the EXO network.

Figure 2

Evoked potentials and event-related oscillations for each electrode and for all the subjects. The upper part presents three different views of the average electrode position relative to the areas with BOLD activation (threshold p ≤ 0.001, 100 voxels, Target-related activation – red, Target-related deactivation – green, and rare Distractor (Novel) activation – blue). It is provided for better appreciation of electrical signals, considering fMRI activation. The lower part displays the evoked potentials (EPs) and event-related oscillations (EROs) for each electrode, for the 5 subjects. For C3, Cz, C4, Pz, the "no-smoking" symbol, which is an instance of Novels (blue), yielded larger EPs than Targets (red). Distractors are represented in gray. For all the electrodes, the reverse is true as far as EROs are concerned, with significantly more oscillations around 300–400 ms, regarding Targets. In the case of EPs, signals have been plotted from -325 to +625 ms and the voltage range was kept constant from -9 to +9 μV. The shaded region around 474 ms corresponds to the response time and its standard deviation. The statistics for the comparison of Target-related and Novel-related EPs are computed every 10 ms, between 100 ms and 600 ms, and represented by the gray and black stars above the curves (1 star for p nc ≤ 0.05, 2 starsfor p nc ≤ 0.01). The time-cluster significance, cor-rected for multiple comparison is indicated by the color of the stars: black if above p c ≤ 0.05, gray if not significant at the cor-rected time-clusterlevel. The set level is given for each electrode by the number of stars beside the electrode label (1 star for p ≤ 0.05, 2 stars for p ≤ 0.01). For EROs, only the statistics comparing Targets and Novels is given for the 24- to 44-Hz band, and between -320 to 600 ms. The solid and dotted black lines correspond to the response time and standard deviation, respec-tively. The color code for the statistics is shown on the upper right hand side, and represents the cumulative p distribution stated in percent. Cold colors code for a higher Novel-related power level, and hot colors code for greater Target-related power intensity. Regions above the .05 and .01 thresholds are contoured in black (notice that the numbers 1, 5, 95 and 99 rep-

resent the cumulative p values stated in percent).

further analysis in the 25- to 200-Hz range, every 5 Hz. Between 100 and 400 ms, and considering an uncorrected p ≤ 0.01 for report, Novels failed to present larger EROs than Targets, whereas the latter presented larger EROs at 35, 95, 110 and 140 Hz (additional material available on request).

Discussion

After confronting these results with those of prior reports, we propound physiological hypotheses to account for this discrepancy between EPs and fMRI/EROs.

In accordance with previous experiments, Novels yielded a P300 of significantly greater amplitude than Targets [6]. The relatively low amplitude of the P300, about 8 μV, compared to the expected 10 to 20 μV [6], might well be related to the use of a common reference [26]. However, we cannot rule out the possibility that part of the P300 could have been regressed with the electro-cardio-balisto-graphic artifact in some trials. The principal component of the pulse artifact looks like a damped oscillation around 7.5 Hz [27] (Otzenberger et al. submitted) which includes part of the theta component of the P300 [6,28]. However discarding trials in which the largest part of the pulse arti-fact covered the 300 to 400-ms post-stimulus period in two subjects did not modify their results. E ven so, the pulse artifact should equally affect Target- and Novel-related P300 without affecting the difference between them.

Our fMRI results are also in line with the literature [13,14,16,29–36]. The putative sources of the P300, the temporal-parietal junction and the inferior frontal gyrus [8], were only activated in the Target condition by all the subjects. Novels activated the left inferior frontal sulcus that was part of a network deactivated by Targets. This region might well support response inhibition [37–44].Our E ROs results not only nicely reproduce results reported in previous studies, regarding the frequency (38 Hz) and the delay (360 ms) [22–25], but go one step fur-ther by showing that over a large frequency range, and between 100 and 400 ms, Targets triggered larger EROs than Novels. Accordingly, the differential reactivity of Tar-get- and Novel-related EROs was in line with that of fMRI. An important limitation of this study however, is that, owing to the limited number of electrodes, we were una-ble to ascertain whether E ROs arose from the same sources as E Ps. Yet, the differential effect seems to take place on the same electrodes, as if the dipoles had the same scalp projection. Subsequent intra-cranial or inverse solution experiments are required to establish this point. From a cognitive point of view, this discrepancy between EPs on one hand and EROs and fMRI on the other hand, may originate from several, possibly interacting, proc-esses: i) different processing for Targets and Novels, related with differences in attentional requirement, ii) dif-ferent visual processing for the letter "X" and pictures, iii) a different susceptibility to stimulus repetition. Further studies are required to clarify this point, but the interest-ing fact is that E Ps react in an opposite way to fMRI, whereas EROs responds in the same way.

Such discrepancy between EPs and the fMRI signal may not be unique. There is at least one other condition where EPs and fMRI may not present the same differential reac-tivity. In episodic memory, the contrast between correct recognition of old items vs. correct rejection of distractors activates the left frontal lobe in fMRI [45–47]. On the other hand, performing a source analysis based on E Ps from E E G and magneto-encephalographic (ME G) data fails to evidence activity in this region [21]. Interestingly enough, in this last study, the time frequency analysis showed a difference in the gamma range projecting on the

Table 2: Subject by subject EPs and EROs results

Cz P300 et 400 ms (μV)EROs at 32 Hz and 320 ms (std)

subjects Targets Novels perm-test Targets Novels perm-test 115.615.80.089.7 2.10.01

2 1.1 4.60.0112.2 4.80.04

3 3.07.6< 0.0110.

4 5.80.08

4 2.0 2.90.12 5.0 4.20.27

5 6.57.60.089.7 6.50.25

Mean 5.67.79.4 4.7

Std 5.9 5.0 2.7 1.7

Both are given for the Cz electrode, the P300 is given in micro-Volts (μV), 400 ms after stimulus presentation, (highest statistical difference in the group analysis), and EROs are given in standard deviation relative to the pre-stimulus period, at 38 Hz, 320 ms after stimulus presentation (highest value in the group analysis). The results of the permutation test were obtained for each subject as explained in the method section.

Figure 3

Event-related oscillations for all the electrodes. The upper part presents the event-related oscillations (EROs) time-fre-quency chart for Targets on the left (X-mark), and rare distractors (Novels) on the right ("no-smoking" symbol). It is shown for the 24- to 44-Hz band, and between -320 to 600 ms, summing up all 9 electrodes for all the subjects. The color scale rep-resents the relative amount of power in standard deviation (reference period from -320 to 0 ms). This illustrates that the 32- to 38-Hz EROs in response to Targets are quite low in response to Novels. It thus does not come as a surprise that the statis-tical comparison of Target-related vs. Novel-related power for all electrodes is significant (lower time-frequency chart). Cold colors code for a trend towards greater power in the Novel condition, whereas hot colors represent greater power level in the Target condition. The scale represents the cumulative p distribution stated in percent. Regions above the .05 and .01 threshold are contoured in black. The numbers 1, 5, 95 and 99 represent the cumulative p value in percent, respectively equiv-alent to.01, .05 for Novels and .05, .01 for Targets. The solid and dotted black lines correspond to the response time and standard deviation, respectively. The result table provides the statistics for the time interval from 200 to 500 ms, and from 24 to 44 Hz, using a threshold p ≤ 0.01. Volume and time-frequency cluster p values are given corrected for multiple comparisons. Note that the ensemble statistics represent the probability to have the given amount of time-frequency points above the threshold (12 over 165 time-frequency points), and not the number of clusters as in EPs or fMRI. At the same threshold, there

were no significantly larger power emissions in the Novel than in the Target condition (not even at the .05 threshold).

left fronto-temporal electrodes / ME G sensor position [21].

Our study provides direct evidence that gamma oscilla-tions better match the BOLD signal than E Ps do. This observation is well in line with other works on animals. Logothetis and co-workers successfully recorded the BOLD response together with the equivalent of local field potentials in the visual cortex of anesthetized monkeys. They observed that the best correlation was achieved when taking frequencies in the gamma range [5,48].

The reason why E ROs seem to correlate better with the BOLD signal than EPs do, remains, as yet, uncertain. The EEG and BOLD signals both reflect synaptic activity [2–5,49,50]. But E E G and fMRI integrate synaptic activity over different time windows [2–5]. The former reflects synchronous firing of synapses within milliseconds [49,50]. On the other hand, fMRI represents the integra-tion of synaptic activity over several hundreds of millisec-onds [1]. Thus a small jitter of the neuronal response relative to a stimulus e.g. tens of milliseconds, will dra-matically affect the averaging of E Ps [20] but will only have a limited impact on the averaging of BOLD responses. On the other hand, EROs do not require to be time-locked to the stimulus so precisely, and will average well despite such jitter [20]. Taking this jitter into account might even become crucial as one considers higher cogni-tive tasks. With the involvement of decisions requiring longer response times, uncertainty about the time of involvement of some areas might well increase [21]. This however only provides partial explanation, as there is no reason to believe that the jitter affecting Target-related P300 should exceed that affecting Novel-related P300.

A second reason could be related to the fact that EEG and BOLD signals reflect the activity of different cell popula-tions. EEG reflects the synaptic input function of pyrami-dal cells only, i.e. post-synaptic potential, either excitatory or inhibitory [49,50], whereas fMRI reflects the synaptic activity of all neural cells [2–5]. There is no particular rea-son for EPs to rely on anything else than pyramidal cell synaptic activity, but it has been demonstrated that syn-chronous oscillations require the involvement of inhibi-tory interneurons together with pyramidal cells [51,52]. Accordingly, EPs and EROs might reflect different kinds of neuronal activity, and the BOLD signal might be more sensitive to EROs because of the larger amount of contrib-uting cells and synapses. Animal works illustrate how those two kinds of activity emerge in a task similar to the one we used. If a behaving monkey is presented with an object, but attends to another (analogous to the Novel condition), one only observes a phasic rise in spiking activity lasting for about 50 ms that could well go with an EP on the scalp [53,54]. But if the object attended to is presented (analogous to the Target condition), the phasic rise is followed by gamma oscillations for 300 ms [55,56]. Last, it must be noted that positive correlation with the BOLD signal seems only to apply to fast oscillations (> 15-Hz), whereas slow waves, below 12 Hz, were reported to be negatively correlated with the fMRI signal [57] (Foucher et al. submitted). This should not be surprising as low and high frequencies have been described to corre-late negatively [58]. The discrepancy observed between EROs and EPs, might be considered not so much as a mat-ter of whether activity is phase-locked or not, but rather as a matter of frequency. Should this be the case, the P300, which ranges in the theta frequency spectrum (4-8Hz) [6], may not be well suited to be positively correlated with BOLD. Unfortunately our methodology did not allow us to test whether or not theta EROs differed from the P300 reactivity (the 7-cycle wavelet would not have fitted in the E E G window limited by gradient artifacts). However, it has been shown in different protocols, that EP frequencies are not necessarily enhanced on the EROs analysis [59]. This calls into question the kind of neuronal activity responsible for the generation of an evoked potential. It has been suggested that part of an EP could correspond to the simple phase resetting of ongoing cerebral activity [59,60]. Should this turn out to be true, since phase reset-ting should not consume much energy, it could be another reason why EPs and BOLD signals are not well correlated.

Conclusion

This is the first direct demonstration of an inverse differ-ential reactivity between EPs and the BOLD signal arising from the same brain activity. This observation has to be taken into account for the integration of the EEG and the fMRI data. In the light of this attempt, these results plead for taking into account the EEG oscillatory response, as it was shown to share the same differential reactivity as the BOLD signal. Further explorations are called for to work out the reasons underlying this phenomenon, but it can be suggested that this is because the BOLD signal and E ROs are less sensitive to random jitter of the brain response, and because they rely on neural activity of another kind than EPs, involving different population of cells. Differential reactivity is an interesting paradigm to explore the relationship between the BOLD and EEG sig-nals, since the level of noise makes direct correlation between EPs, EROs and BOLD difficult. Further studies, involving different tasks and stimuli, should also consider the localization of the electrical activity using a larger amount of electrodes.

Methods

Subjects and task

Five subjects with no prior history of neurological injury (4 right-handed, 1 left-handed, 3 females, aged 18 to 23 years) gave informed consent prior to participating in this study approved by the local ethical committee. Visual stimuli were presented to them, consisting in series of Fre-quent Distractors (repeating the same letter "O", 47%), Novels (7%, black and white namable pictures, never repeated), and rare Targets (always the same letter "X", 7%). The proportion of white pixels was kept in the same range for all stimuli to avoid stimulus intensity changes (~20%). Although pictures were kept as simple as possible (pictograms such as a heart, flash of lightning) some were more complex than the letters (e.g. no-smoking, danger or nuclear signs). All the stimuli were square pictures cover-ing ~5° of the visual field, which were presented for 70 ms using the software expe6 [61]. The subjects were instructed to signal Targets by pressing a response key with the right forefinger, and to ignore other stimuli. The remaining 39% were null events (empty screen). All the stimuli were presented pseudo-randomly to maximize the contrasts [62]. Inter-stimuli intervals were homogene-ously distributed from 0.4 to 3.6 s (median of 2 s) and intervals between two Targets ranged from 5.2 to 96 s [63]. Each subject performed two sessions involving this 3-stimulus paradigm.

fMRI acquisition

In order to record gradient artifact-free EEG data simulta-neously with fMRI, the volumes were separated by a 1,6-s period during which gradients were not commuted [17,18]. Single-shot gradient echo, echo planar imaging was used for the functional study, relying on the BOLD effect (Bruker 2T / 270 volumes preceded by 5 dummy scans for steady state of T1 partial saturation effect / TR = 4 s / Imaging time = 2.6 s / flip angle of 90° / TE = 43 ms / 4-mm in-plane resolution, FOV = 256 mm, gridding 642, 4-mm slice thickness / 24 slices covering the whole brain except for the cerebellum). Thirty-five rare stimuli out of 40 were presented during the no-gradient period for each condition. This asymmetry escaped all participants' notice. A RARE sequence was used for the acquisition of anatomical images including electrode positioning, thanks to accompanying MRI markers (2T / TR = 15 s / TE = 73.8 ms / 2-mm in-plane resolution, FOV = 256 mm, gridding 1282, 2-mm slice thickness / 60 slices).

fMRI processing

The volumes were realigned, normalized (voxel size after re-sampling : 2 mm isotropic) and smoothed with an 8-mm kernel under SPM99 [64]. The data were further proc-essed through pass-band filtering (the hemodynamic response for low-pass filter, and 47-s cut-off for high-pass filter) and the voxel intensity was scaled relative to the global volume. For the purpose of the statistical analysis, the brain responses to Targets, Novels and Distractors were modeled as stick functions convolved with a hemo-dynamic response and its temporal derivative. The analy-sis was looking for regions significantly correlated with those functions in the context of the general linear model [65]. The statistics are provided in two ways: i) a fixed effect, one-tail t-test, to enable comparison between fMRI and EEG results (p ≤ 0.001 uncorrected, cluster size > 100 voxels = 800 mm3), and ii) multi-subject conjunction analysis to allow the extrapolation of the results obtained to the population [66,67]. The results are given using a threshold p ≤ 0.05 uncorrected for each individual t-map, which is equivalent to a conjunction probability of p ≤ 3.1 10-7 (uncorrected). For all maximally activated voxel per cluster, the minimal percentage of the population that should display activity at p ≤ 0.05 is given uncorrected, using a 95% confidence interval, and assuming the test sensitivity to be 100% (formula n°3 in [67]).

EEG acquisition

The EEG was recorded using 10 shielded electrodes at the F7-Fz-F8-C3-Cz-C7-Pz-O1-O2-A2 sites according to the international 10/20 standard [68], with ground on the nasion. Data were recorded with a referential montage to a common reference, using an MRI-compatible device (Schwarzer – GE). Conductances were tested out of the magnet and remained below 5 kOhm, except for C3 in 2 sessions (data excluded from the analysis). The ECG was amplified separately (Bruker – GE). Signals were sampled at 1000 Hz with pre-amplification filters set from 0.003 to 300 Hz.

EEG processing

The electro-cardio-balisto-graphic artifact [69] (or pulse artifact) was removed by regression of the first eigenvector computed from a set of pulse artifacts taken as a reference at the beginning of the experiment (~80 of 700 ms each, the first eigenvector accounted for more than 30 % of the variance). The signal was further band filtered from 0.1 to 20 Hz using a Fourier-based method [70], and EPs were computed by averaging the signals between -325 and +625 ms, after having discarded the trials whose ampli-tude variation exceeded 100 μV (there remained 26 ± 4 tri-als out of 35, per condition and per session) [63]. EROs were computed from the same data set without prior fil-tering. For each trial and electrode, the signal was first fil-tered in the ± 2-Hz band every 2 Hz between 24 and 44 Hz, then convoluted with a complex 7-cycle Morlet wave-let [71–73]. The module of the convolution product rep-resents the power integrated over a window equivalent to 7 cycles, thus adapted to each frequency [71,73]. The result was normalized for each frequency using the first 320-ms period before stimulus presentation, and down-sampled to 50 Hz (20-ms period).

The statistical comparison of Target- and Novel-related E Ps and E ROs was carried out using a randomization approach [74]. First, the effective difference between Tar-gets and Novels was computed. Next, Target and Novel tri-als were put together and randomized, subsequently separated into two groups from which a new difference was computed. By repeating this procedure 2000 times, a reference distribution of the differences was established every 10 ms for E Ps and every 50 ms for E ROs. The effective difference was compared to this distribution for each electrode and each time point, using a threshold of 0.05 and 0.01 (one-tail). In order to take into account multiple comparisons, the probability to obtain a given time-cluster size and the total amount of significant points (ensemble level) was assessed from the same rand-omized set between 200 and 500 ms for each electrode (in the 24- to 44-Hz band for EROs) and using a threshold of 0.01 for report (one-tail). The same statistics were also used to perform subject-by-subject conjunction analysis on electrode Cz to verify that the results thus obtained were not due to a few subjects out of the five, and to allow extrapolation to the population.

List of abbreviations

fMRI Functional Magnetic Resonance

BOLD Blood Oxygen Level Dependent

EEG Electro-Encephalography

ECG Electro-Cardiograph

MEG Magneto-Encephalography

ERO Event Related Oscillations

EP Evoked Potentials

Authors' contributions

JF contributed to the conception, design and analysis of the study, and drafted the manuscript. HO contributed to setting up E E G-fMRI recording and to the analysis of evoked potentials data. DG contributed to the design, E E G-fMRI settings, and fMRI analysis. All authors have read and approved the final manuscript.

Additional material Acknowledgments

We are thankful to Dr Jean-Philippe Lachaux, Dr Jean-Baptiste Poline, Pr Daniel Grucker, and Pr Jean-Marie Danion for reading the manuscript and fruitful criticism, as well as to the whole Dynamic Neuronal Activity group of the LENA for their contribution to data analysis. A special thanks to Pr John Polich who provided critical advice, especially about how to adapt our treatment of EP data and about their interpretation. We would also like to thank Mrs Corinne Marrer for her hard-working contribution in the acqui-sition of fMRI data, Mrs Monique No?l and the whole neurological ward for skillful electrode placement. We are grateful to Pr Guy Foucher, and Ms Nathalie Heider for correcting our manuscript. The UMR 7004 ULP/CNRS – Strasbourg, supported this work.

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Neurobiol 2000, 14:199-224.

Additional File 1Description of the clusters activated (Targets+) or deactivated (Targets-) by the Targets, and activated by rare distractors (Novels+), together with their respective projection on a transparent brain. The fixed effect statisti-cal values are given for a threshold t = 3.10 (p nc = 0.001 one-tail, df = 1593.7) with an extent threshold of 100 voxels (p nc = 0.004, p c = 0.059 corrected, 1 resel = 106 voxels). The first column presents the probability to obtain the specified number of clusters (second column). The third col-umn indicates the corrected probability for each cluster, and the fourth col-umn, the number of voxels per cluster. The fifth column presents the corrected probability for the given voxel together with the uncorrected Tar-get and p values (sixth and seventh column). For the same voxel, the eighth column provides the results of the subject conjunction analysis for "population inference" in two ways. If the voxel is active in all the subjects at p nc ≤ 0.05, then the minimal percentage of the population that should present at least the same significance level is given (95% confidence inter-val). If one or more subjects are below that threshold, then the lowest sig-nificance is given in p value. The MNI coordinates together with the anatomical sites and Brodmann areas are provided in the subsequent col-umns. Smoothness: FWHM = 9.6 × 9.6 × 9.3 mm. Search volume: 1337 cm3 (167142, 2 × 2 × 2-mm voxels).

Click here for file

[https://www.360docs.net/doc/0417218486.html,/content/supplementary/1471-2202-4-22-S1.pdf]

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实验五氧化还原反应与电极电势(精)

实验五氧化还原反应与电极电势 一、实验目的 1、掌握电极电势对氧化还原反应的影响。 2、定性观察浓度、酸度对电极电势的影响。 3、定性观察浓度、酸度、温度、催化剂对氧化还原反应的方向、产物、速度的影响。 4、通过实验了解原电池的装置。 二、实验原理 氧化剂和还原剂的氧化、还原能力强弱,可根据她们的电极电势的相对大小来衡量。电极电势的值越大,则氧化态的氧化能力越强,其氧化态物质是较强氧化剂。电极电势的值越小,则还原态的还原能力越强,其还原态物质是较强还原剂。只有较强的氧化剂才能和较强还原剂反应。即φ氧化剂-φ还原剂﹥0时,氧化还原反应可以正方向进行。故根据电极电势可以判断氧化还原反应的方向。 利用氧化还原反应而产生电流的装置,称原电池。原电池的电动势等于正、负两极的电极电势之差:E = φ正-φ负。根据能斯特方程: 其中[氧化型]/[还原型]表示氧化态一边各物质浓度幂次方的乘积与还原态一边各物质浓度幂次方乘积之比。所以氧化型或还原型的浓度、酸度改变时,则电极电势φ值必定发生改变,从而引起电动势E将发生改变。准确测定电动势是用对消法在电位计上进行的。本实验只是为了定性进行比较,所以采用伏特计。浓度及酸度对电极电势的影响,可能导致氧化还原反应方向的改变,也可以影响氧化还原反应的产物。 三、仪器和药品 仪器:试管,烧杯,伏特计,表面皿,U形管 药品:2 mol·L-1 HCl,浓HNO3, 1mol·L-1 HNO3,3mol·L-1HAc,1mol·L-1 H2SO4,3mol·L-1 H2SO4,0.1mol·L-1 H2C2O4,浓NH3·H2O(2mol·L-1),6mol·L- 1NaOH,40%NaOH。 1mol·L-1 ZnSO4,1mol·L-1 CuSO4,0.1mol·L-1KI,0.1mol·L-

氨基酸

氨基酸 氨基酸定义 氨基酸(amino acids):含有氨基和羧基的一类有机化合物的通称。生物功能大分子蛋白质的基本组成单位,是构成动物营养所需蛋白质的基本物质。是含有一个碱性氨基和一个酸性羧基的有机化合物,氨基一般连在α-碳上。 氨基酸的结构通式:构成蛋白质的氨基酸都是一类含有羧基并在与羧基相连的碳原子下连有氨基的有机化合物,目前自然界中尚未发现蛋白质中有氨基和羧基不连在同一个碳原子上的氨基酸。 氨基酸分类 天然的氨基酸现已经发现的有300多种,其中人体所需的氨基酸约有22种,分非必需氨基酸和必需氨基酸(人体无法自身合成)。另有酸性、碱性、中性、杂环分类,是根据其化学性质分类的。 1、必需氨基酸(essential amino acid):指人体(或其它脊椎动物)不能合成或合成速度远不适应机体的需要,必需由食物蛋白供给,这些氨基酸称为必需氨基酸。共有8种其作用分别是: ①赖氨酸(Lysine ):促进大脑发育,是肝及胆的组成成分,能促进脂肪代谢,调节松果腺、乳腺、黄体及卵巢,防止细胞退化; ②色氨酸(Tryptophane):促进胃液及胰液的产生; ③苯丙氨酸(Phenylalanine):参与消除肾及膀胱功能的损耗; ④蛋氨酸(又叫甲硫氨酸)(Methionine);参与组成血红蛋白、组织与血清,有促进脾脏、胰脏及淋巴的功能; ⑤苏氨酸(Threonine):有转变某些氨基酸达到平衡的功能; ⑥异亮氨酸(Isoleucine ):参与胸腺、脾脏及脑下腺的调节以及代谢;脑下腺属总司令部作用于甲状腺、性腺; ⑦亮氨酸(Leucine ):作用平衡异亮氨酸; ⑧缬氨酸(Viline):作用于黄体、乳腺及卵巢。 其理化特性大致有: 1)都是无色结晶。熔点约在230°C以上,大多没有确切的熔点,熔融时分解并放出CO2;都能溶于强酸和强碱溶液中,除胱氨酸、酪氨酸、二碘甲状腺素外,均溶于水;除脯氨酸和羟脯氨酸外,均难溶于乙醇和乙醚。 2)有碱性[二元氨基一元羧酸,例如赖氨酸(lysine)];酸性[一元氨基二元羧酸,例如谷氨酸(Glutamic acid)];中性[一元氨基一元羧酸,例如丙氨酸(Alanine)]

BZ振荡实验

BZ振荡实验 一、实验目的及要求 1.了解BZ(Belousov-Zhobotinski)振荡反应的基本原理,观察BZ化学振荡 实验。 2.了解化学振荡反应中的电势测定方法,通过测定电位-时间曲线求得化学振荡反应的表观活化能。 二、实验原理 振荡反应 化学振荡是指反应系统中的某些量(如某组分的浓度)随时间做周期性的变化。BZ振荡实验是由贝诺索夫(Belousov)和柴波廷斯基(Zhobotinski)发现和发展 起来的,是指在酸性介质中,有机物在有金属离子催化的条件下被溴酸盐氧化,某些组分的浓度发生周期性的变化。 大量实验研究表明,化学振荡反应的发生必须满足三个条件:(1)必须是远离平衡态体系;(2)反应历程中含有自催化步骤;(3)体系必须具有双稳态性,即可在稳态间来回振荡。 机理 菲尔德(Field)、科罗什(Koros)、诺伊斯(Noyes)三位科学家对BZ振荡反应 实验进行了解释,称为FKN机理。下面以BrO 3~Ce4+~CH 2 (COOH) 2 ~H 2 SO 4 体系为例说 明。在该体系中发生的总反应为: 该反应的的核心内容是系统中存在受Br-浓度控制的A和B两个过程。具体的说, 当Br-的浓度高于某个浓度(这个浓度被称为临界浓度C 临)时,BrO 3 -被还原成Br 2 , 即发生A过程。 过程A: (注:HOBr产生后立即被丙二酸消耗,反应过程如下: 当Br-的浓度低于临界浓度时,或者说Br-的浓度较低时,Ce3+被氧化为Ce4+,发生B过程。 过程B:

(自由基反应瞬间完成) Br-再生过程: 过程A是消耗Br-并产生能进一步发生反应的HBrO 2 ,HOBr是中间产物,产 生之后立即被丙二酸消耗。 过程B是一个自催化的过程(HBrO 2 充当催化剂),在Br-消耗到一定程度后, HBrO 2 才按③和④进行,并使反应不断加速,与此同时,Ce3+被氧化为Ce4+。 HBrO 2 的累积还受⑤的制约。 ⑥反应为丙二酸被溴化为BrCH(COOH) 2 ,与Ce4+反应生成Br-使Ce4+转化为Ce3+。这个反应使得Br-和Ce3+再生,形成周期振荡,并且控制A过程和B过程发生的离子是Br-。 -的临界浓度 过程A中,慢反应②控制整个A过程的速度,当过程A达到准定态,即υ ①=υ ② ,这时: k 1[BrO 3 -][Br-][H+]2=k 2 [HBrO 2 ][Br-][H+],得:[HBrO 2 ] A =k 1 /k 2 [BrO 3 -][H+]。 过程B中,慢反应③产生的自由基BrO 2 ·立即反应,当反应达到准定态, 即υ ③=υ ⑤ ,这时 k 3[BrO 3 -][HBrO 2 ][H+]=k 5 [HBrO 2 ]2,得:[HBrO 2 ] B =k 3 /k 5 [BrO 3 -][H+]。 观察②反应和③反应,Br-和BrO 3 -均要与HBrO 2 反应,形成竞争反应。当 k 2[HBrO 2 ][Br-][H+]>k 3 [BrO 3 -][HBrO 2 ][H+]时,即k 2 [Br-]>k 5 [BrO 3 -]时,反应②进 行,反应③不能进行。而k 2[Br-]

氨基酸的常见化学反应

氨基酸的常见化学反应 ? -氨基的反应 ?亚硝酸反应 ?范围:可用于Aa定量和蛋白质水解程度的测定(Van slyke法) ?注意:生成的氮气只有一半来自于Aa,ε氨基酸也可反应,速度较 慢. ?与酰化试剂的反应 ?Aa+酰氯,酸酐-→Aa被酰基化 ?丹磺酰氯用于多肽链末端Aa的标记和微量Aa的定量测量. ?烃基化反应 ?Aa的氨基的一个氢原子可被羟基(包括环烃及其衍生物)取代. ?与2,4-二硝基氟苯(DNFB,FDNB)反应 ?最早Sanger用来鉴定多肽或蛋白质的氨基末端的Aa ?与苯异硫氰酸酯(PITC)的反应 ?Edman用于鉴定多肽或蛋白质的N末端Aa.在多肽和蛋白 质的Aa顺序分析方面占有重要地位(Edman降解法) ?形成西佛碱反应 ?Aa的α-NH2能与醛类化合物反应生成弱碱,即西佛碱(schiff ‘s base) ?前述甲醛滴定:甲醛与H2N-CH2-COO-结合,有效地减低了后者的 浓度,所以对于加入任何量的碱, [H2N-CH2-COO- ]/ [+H3N-CH2-COO- ]的比值总要比不存在甲醛的情况下小得多。加入 甲醛的甘氨酸溶液用标准盐酸滴定时,滴定曲线B并不发生改变。 ?脱氨基反应 ?Aa在生物体内经Aa氧化酶催化即脱去α-NH2而转变成酮酸 ?α-COOH参加的反应 ?成盐和成酯反应 ?Aa + 碱-→盐 ?Aa + NaOH -→氨基酸钠盐(重金属盐不溶于水) ?Aa-COOH + 醇-→酯 ?Aa+ EtOH ---→氨基酸乙酯的盐酸盐 ?当Aa的COOH变成甲酯,乙酯或钠盐后,COOH的化学反 应性能被掩蔽或者说COOH被保护,NH2的化学性能得到 了加强或活化,易与酰基结合。Aa酯是制备Aa的酰氨or 酰肼的中间物 ?成酰氯反应 ?当氨基酸的氨基用适当的保护基保护以后,其羧基可与二氯亚砜作 用生成酰氯 ?用于多肽人工合成中的羧基激活 ?叠氮反应 ?氨基酸的氨基通过酰化保护后,羧基经酯化转变为甲酯,然后与肼 和亚硝酸变成叠氮化合物 ?用于多肽人工合成中的羧基激活 ?脱羧基反应

化学振荡

化学震荡 一、目的要求 1、了解、熟悉化学振荡反应的机理。 2、通过测定电位——时间曲线求得振荡反应的表观活化能。 二、基本原理 有些自催化反应有可能使反应体系中某些物质的浓度随时间(或空间)发生周期性的变化,这类反应称为化学振荡反应。 最著名的化学振荡反应是1959年首先由别诺索夫(Belousov)观察发现,随后柴波廷斯基(Zhabotinsky)继续了该反应的研究。他们报道了以金属铈离子作催化剂时,柠檬酸被HBrO3氧化可发生化学振荡现象,后来又发现了一批溴酸盐的类似反应,人们把这类反应称为BZ振荡反应。例如丙二酸在溶有硫酸铈的酸性溶液中被溴酸钾氧化的反应就是一个典型的BZ振荡反应。典型的BZ系统中,铈离子和溴离子浓度的振荡曲线如图1所示。 对于以BZ反应为代表的化学振荡现象,目前被普遍认同的是Field,K?r?s和Noyes在1972年提出的FKN机理。FKN机理提出反应由三个主过程组成:过程A (1) Br-+BrO3-+2H+→HBrO2+HBrO (2) Br-+HBrO2+H+→2HBrO 过程B (3) HBrO2+BrO3-+H+→2BrO2+H2O (4) BrO2+Ce3++H+→HBrO2+Ce4+ (5) 2HBrO2→BrO3-+H++HBrO 过程C (6) 4Ce4++BrCH(COOH)2+H2O+HBrO→2Br-+4Ce3++3CO2+6H+ 过程A是消耗Br-,产生能进一步反应的HBrO2,HBrO为中间产物。 过程B是一个自催化过程,在Br-消耗到一定程度后,HBrO2才按式(3)、(4)进行反应,并使反应不断加速,与此同时,Ce3+被氧化为Ce4+。HBrO2的累积还受到式(5)的制约。 过程C为丙二酸溴化为BrCH(COOH)2与Ce4+反应生成Br-使Ce4+还原为Ce3+。 过程C对化学振荡非常重要,如果只有A和B,就是一般的自催化反应,进行一次就完成了,正是C的存在,以丙二酸的消耗为代价,重新得到Br-和Ce3+,反应得以再启动,形成周期性的振荡。 该体系的总反应为: 2H++2 BrO3-+3CH2(COOH)2? ?→ ?+3Ce2BrCH(COOH)2+3CO2+4H2O 振荡的控制离子是Br-。 由上述可见,产生化学振荡需满足三个条件: 1.反应必须远离平衡态。化学振荡只有在远离平衡态,具有很大的不可逆程度时才能发生。在封闭体系中振荡是衰减的,在敞开体系中,可以长期持续振荡。 2.反应历程中应包含有自催化的步骤。产物之所以能加速反应,因为是自催化反应,如过程A中的产物HBrO2同时又是反应物。 3.体系必须有两个稳态存在,即具有双稳定性。 化学振荡体系的振荡现象可以通过多种方法观察到,如观察溶液颜色的变化,

大学实验化学 氧化还原反应与电极电位

氧化还原反应与电极电位 难题解析[TOP] 例8-1 写出并配平下列各电池的电极反应、电池反应,注明电极的种类。 (1)(-) Ag(s)│AgCl(s) │HCl(sln)│Cl2(100kp)│Pt(s) (+) (2)(-) Pb(s)│PbSO4(s)│K2SO4(sln)‖KCl(sln)│PbCl2(s)│Pb(s) (+) (3)(-) Zn(s)│Zn2+(c1)‖MnO4-(c2), Mn2+(c3), H+(c4)│Pt(s) (+) (4)(-) Ag(s) | Ag+ (c1) ‖Ag+(c2) │Ag(s) (+) 分析将所给原电池拆分为两个电极。负极发生氧化反应,正极发生还原反应,写出正、负极反应式,由正极反应和负极反应相加构成电池反应。 解(1)正极反应Cl2(g)+2e-→ 2 Cl-(aq) 属于气体电极 负极反应Ag(s)+Cl-(aq) → AgCl(s)+e-属于金属-难溶盐-阴离子电极 电池反应2Ag(s)+ Cl2(g) →2AgCl(s) n=2 (2)正极反应PbCl2(s)+2e-→Pb(s)+2Cl- (aq) 属于金属-难溶盐-阴离子电极 负极反应Pb(s)+SO42-(aq)→PbSO4(s)+2e-属于金属-难溶盐-阴离子电极 电池反应PbCl2(s) +SO42-(aq)→PbSO4(s) +2Cl-(aq) n=2 (3)正极反应MnO4-(aq) +8H+(aq)+5e-→Mn2+(aq)+ 4H2O(l) 属于氧化还原电极 负极反应Zn(s) → Zn2+(aq)+2e-属于金属-金属离子电极电池反应2MnO4- (aq)+16H+(aq)+5Zn(s)→2Mn2+(aq)+8H2O(l)+5Zn2+ (aq)n=10 (4)正极反应Ag+(c2) +e- → Ag(s) 属于金属-金属离子电极 负极反应Ag(s) → Ag+ (c1) + e-属于金属-金属离子电极 电池反应Ag+(c2) → Ag+ (c1) n=1 例8-2 25℃时测得电池(-) Ag(s)│AgCl(s)│HCl(c)│Cl2(100kp)│Pt(s) (+) 的电动势为1.136V,已知θ ?( Cl2/Cl-)=1.358V, θ?( Ag+/Ag)=0.799 6V,求AgCl的溶度积。 ?AgCl/Ag 。其次:AgCl的分析首先根据电池电动势和已知的标准电极电位,由Nernst方程求出θ 平衡AgCl(s)Ag+ (aq)+ Cl-(aq),方程式两侧各加Ag: AgCl(s) + Ag(s)Ag+ (aq)+ Cl-(aq) + Ag(s) AgCl与产物Ag组成AgCl/Ag电对;反应物Ag与Ag+组成Ag+/Ag电对。AgCl(s)的溶度积常数为:

电化学与电位分析法

电化学与电位分析法 一、简答题 ⒈ 化学电池由哪几部分组成?如何表达电池的图示式?电池的图示式有那些规定? ⒉ 电池的阳极和阴极,正极和负极是怎样定义的?阳极就是正极,阴极就是负极的说法对吗?为什么? ⒊ 电池中"盐桥"的作用是什么?盐桥中的电解质溶液应有什么要求? ⒋ 电极电位及电池电动势的表示式如何表示?应注意什么问题?何谓式量电位?如何表示? ⒌ 电极有几种类型?各种类型电极的电极电位如何表示? ⒍ 何谓指示电极、工作电极、参比电极和辅助电极? ⒎ 何谓电极的极化?产生电极极化的原因有哪些?极化过电位如何表示? ⒏ 写出下列电池的半电池反应和电池反应,计算电动势。这些电池是原电池还是电解池?极性为何?(设T 为25℃,活度系数均为1) ⑴ Pt│Cr 3+(1.0×10-4mol·L -1),Cr 2+(0.10mol·L -1)‖Pb 2+(8.0× 10-2mol·L -1)│Pb 已知: 322//E 0.41,E 0.126Cr Cr Pb Pb V V θθ +++=-=- 已知: 2332//E 1.00,E 0.77VO VO Fe Fe V V θθ ++++== ⑶ Pt,H 2(20265Pa)│HCl (0.100mol·L -1)‖HClO 4(0.100mol·L -1)│Cl 2(50663Pa),Pt 已知: 22//E 0.0,E 1.359H H Cl Cl V V θθ +-== ⑷Bi│BiO +(8.0×10-2mol·L -1),H +(1.00×10-2mol·L -1)‖I -(0.100mol·L -1),AgI(饱和)│Ag 已知: 17 ,//E 0.32,E 0.799,8.310 sp AgI BiO Bi Ag Ag V V K θθ++-===? 9. 电位分析法的理论基础是什么?它可以分成哪两类分析方法?它们各有何特点? 10. 以氟离子选择性电极为例,画出离子选择电极的基本结构图,并指出各部分的名称。 11. 何谓扩散电位和道南电位(相间电位)?写出离子选择电极膜电位和电极电 ⑵

物化实验报告-BZ振荡实验

B-Z振荡反应 2011011743 分1 黄浩 同组人姓名:李奕 实验日期:2013-11-2 提交报告日期:2013-11-8 指导教师:王振华 1 引言 1.1. 实验目的 (1)了解Belousov-Zhabotinski反应(简称B-Z反应)的机理。 (2)通过测定电位——时间曲线求得振荡反应的表观活化能。 1.2 实验原理 所谓化学振荡就是反应系统中某些物理量如组分的浓度随时间作周期性的变化。1958年,Belousov首次报道在以金属铈离子作催化剂的条件下,柠檬酸被溴酸氧化的均相系统可呈现这种化学振荡现象。随后,Zhabotinsky继续了该反应的研究。到目前为止,人们发现了一大批可呈现化学振荡现象的含溴酸盐的反应系统。例如,除了柠檬酸外,还有许多有机酸(如丙二酸、苹果酸、丁酮二酸等)的溴酸氧化反应系统能出现振荡现象,而且所用的催化剂也不限于金属铈离子,铁和锰等金属离子可起同样的作用。后来,人们笼统地称这类反应为B- Z反应。目前,B-Z反应是最引人注目的实验研究和理论分析的对象之一。该系统相对来说比较简单,其振荡现象易从实验中观察到。由实验测得的B-Z体系典型铈离子和溴离子浓度的振荡曲线如图2-11-1所示。 图1. B-Z体系典型铈离子和溴离子浓度的振荡曲线 关于B-Z反应的机理,目前为人们普遍接受的是关于在硫酸介质中以金属铈离子作催化剂的条件下,丙二酸被溴酸氧化的机理,简称为FKN机理。其主要的反应步骤及各步骤的速率或速率系数归纳如下表:

i 222按照FKN 机理,可对化学振荡现象解释如下: 当[Br -]较大时,反应主要按表中的(1)、(2)、(3)进行,总反应为: O H Br H Br BrO 2233365+→+++-- (11) 生成的Br 2按步骤(7)消耗掉。步骤(1)、(2)、(3)、(7)组成了一条反应链,称为过程A ,其总反应为: O H COOH BrCH H COOH CH Br BrO 222233)(33)(32+→++++-- (12) 当[Br -]较小时,反应按步骤(5)和(6)进行,总反应为: O H HBrO Ce H HBrO BrO Ce 2242332232++→+++++- + (13) 步骤(5)为该反应的速度控制步骤((5)的逆反应速率可忽略),这样有 ]][][[] [2352+-=H HBrO BrO k dt HBrO d (14) 上式表明HBrO 2的生成具有自催化的特点,但HBrO 2的增长要受到步骤(4)的限制。(4)、(5)、(6)组成了另一个反应链,称为过程B 。其总反应为: O H Ce HOBr H Ce BrO 24332454++→+++++- (15) 最后Br - 可通过步骤(9)和(10)而获得再生,这一过程叫做C 。总反应为: ++-++++→+++H CO Ce Br O H COOH BrCH Ce HOBr 6342)(423224 (16) 过程A 、B 、C 合起来组成了反应系统中的一个振荡周期。 当[Br -]足够大时,HBrO 2按A 中的步骤(2)消耗。随着[Br -]的降低,B 中的步骤(5)

第八章 氧化还原反应与电极电位(大纲)

第八章
1 1.1 基本要求 [TOP]
氧化还原反应与电极电位
掌握离子-电子法配平氧化还原反应式、电池组成式的书写;根据标准电极电位判断氧化还原反应 方向;通过标准电动势计算氧化还原反应的平衡常数;电极电位的 Nernst 方程、影响因素及有关 计算。
1.2 熟悉氧化值的概念和氧化还原反应的定义,熟练计算元素氧化值;熟悉原电池的结构及正负极反应 的特征;熟悉标准电极电位概念;熟悉电池电动势与自由能变的关系。 1.3 了解电极类型、电极电位产生的原因;了解电位法测量溶液 pH 的原理及 pH 操作定义;了解电化学 与生物传感器及其应用。 2 重点难点 [TOP]
2.1 重点 2.1.1 标准电极电位表的应用。 2.1.2 电极反应与电池反应,电池组成式的书写。 2.1.3 通过标准电动势计算氧化还原反应的平衡常数。 2.1.4 电极电位的 Nernst 方程、影响因素及有关计算。 2.2 难点 2.2.1 电极电位的产生 2.2.2 用设计原电池的方法计算平衡常数 2.2.3 Nernst 方程的推导
3
讲授学时 建议 6 学时
[TOP]
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内容提要
[TOP]
第一节
第二节
第三节
第四节
第五节
4.1 第一节 氧化还原反应 4.1.1 氧化值
1

氧化值是某元素原子的表观荷电数,这种荷电数是假设把化学键中的电子指定给电负性较大的原子 而求得。确定元素氧化值的规则:1)单质中原子的氧化值为零。2)单原子离子中原子的氧化值等于离 子的电荷。3)氧的氧化值在大多数化合物中为-2,但在过氧化物中为-1。4)氢的氧化值在大多数化合 物中为+1,但在金属氢化物中为-1。5)卤族元素:氟的氧化值在所有化合物中均为-1,其它卤原子的 氧化值在二元化合物中为-1,但在卤族的二元化合物中,列周期表靠前的卤原子的氧化数为-1;在含氧 化合物中按氧的氧化值为-2 决定。6)电中性化合物中所有原子的氧化值之和为零。 4.1.2 氧化还原反应 元素的氧化值发生了变化的化学反应称为氧化还原反应。氧化还原反应可被拆分成两个半反应。 半反应中元素的氧化值升高称为氧化,元素的氧化值降低称为还原。氧化还原反应中,氧化反应和还原 反应同时存在,还原剂被氧化,氧化剂被还原,且得失电子数相等。 半反应的通式为 或 氧化型 + ne Ox + ne
-
还原型 Red
式中 n 为得失电子数,氧化型(Ox)包括氧化剂及相关介质,还原型(Red)包括还原剂及相关介质。氧化 型物质及对应的还原型物质称为氧化还原电对(Ox/Red) 。 4.1.3 氧化还原反应方程式的配平 离子-电子法(或半反应法)配平氧化还原反应方程式的方法是:1)写出氧化还原反应的离子方程 式。2)将离子方程式拆成氧化和还原两个半反应。3)根据物料平衡和电荷平衡,分别配平半反应(注意 不同介质中配平方法的差异) 。4)根据氧化剂和还原剂得失电子数相等,找出两个半反应的最小公倍数, 并把它们配平合并。5)可将配平的离子方程式写为分子方程式。 4.2 第二节 原电池与电极电位 4.2.1 原电池 将化学能转化成电能的装置称为原电池。原电池中电子输出极为负极;电子输入极为正极。正极发 生还原反应;负极发生氧化反应,正极反应和负极反应构成电池反应,即氧化还原反应。 常用的电极有金属-金属离子电极、气体电极、金属-金属难溶盐-阴离子电极、氧化还原电极四种 类型。 将两个电极组合起来构成一个原电池,原电池可用电池组成式表示。习惯上把正极写在右边,负极 写在左边;用“|”表示两相之间的界面;中间用“‖”表示盐桥。如 Zn-Cu 电池的电池组成式: (-) Zn(s)│Zn (c1) ‖Cu (c2)│Cu(s) 4.2.2 电极电位的产生和电池电动势
2+ 2+
[TOP]
(+)
2

BZ振荡反应

北京理工大学 物理化学实验报告 BZ震荡反应 班级:09111101 实验日期:2013-4-9

一、 实验目的 1) 了解BZ 反应的基本原理。 2) 观察化学振荡现象。 3) 练习用微机处理实验数据和作图。 二、 实验原理 化学振荡:反应系统中某些物理量随时间作周期性的变化。 BZ 体系是指由溴酸盐,有机物在酸性介质中,在有(或无)金属离子催化剂作用下构成的体系。 本实验以BrO - 3 ~ Ce + 4 ~ CH 2(COOH)2 ~ H 2SO 4作为反映体系。该体系的总 反应为: ()()O 4H 3CO COOH 2BrCH COOH 2CH 2BrO 2H 222223++?→?++- + 体系中存在着下面的反应过程。 过程A : HOBr HBrO 2H Br BrO 2K 32+?→?+++-- 2HOBr H Br HBrO 3K 2?→?+++- 过程B : O H 2BrO H HBrO BrO 22K 234+?→?+++- 42K 32Ce HBrO H Ce BrO 5++++?→?++ +++?→?H HOBr BrO 2HBrO -3K 26 Br - 的再生过程:

()+ +- ++++?→?+++6H 3CO 4Ce 2Br HOBr O H COOH BrCH 4Ce 23 K 2247 当[Br -]足够高时,主要发生过程A ,研究表明,当达到准定态时,有 [][][]+- =H BrO K K HBrO 3 3 22。 当[Br -]低时,发生过程B ,Ce +3被氧化。,达到准定态时,有 [][][] +- ≈ H BrO 2K K HBrO 36 42。 可以看出:Br - 和BrO -3是竞争HbrO 2的。当K 3 [Br - ]>K 4[BrO - 3]时,自催 化过程不可能发生。自催化是BZ 振荡反应中必不可少的步骤。否则该振荡不能发生。研究表明,Br -的临界浓度为: [] [][] - --?== 3 633 4crit - BrO 105BrO K K Br 若已知实验的初始浓度[BrO - 3],可由上式估算[Br - ]crit 。 体系中存在着两个受溴离子浓度控制的过程A 和过程B ,当[Br - ]高于临界浓度[Br - ]crit 时发生过程A ,当[Br - ]低于[Br -]crit 时发生过程B 。这样体系就在过程A 、过程B 间往复振荡。 在反应进行时,系统中[Br - ]、[HbrO 2]、[Ce +3]、[Ce +4]都随时间作周期性的变化,实验中,可以用溴离子选择电极测定[Br - ],用铂丝电极测定[Ce +4]、[Ce +3]随时间变化的曲线。溶液的颜色在黄色和无色之间振荡,若再加入适量的FeSO 4邻菲咯啉溶液,溶液的颜色将在蓝色和红色之间振荡。 从加入硫酸铈铵到开始振荡的时间为t 诱 ,诱导期与反应速率成反比,即 ??? ? ??-=∝RT E A k t 表诱exp 1 ,并得到

氨基酸代谢 重要知识点

蛋白质降解及氨基酸代谢 1、细胞内的蛋白质降解 (1)不依赖ATP的溶酶体途径,主要降解细胞通过胞吞作用摄取的外源蛋白、膜蛋白及长寿命的细胞内蛋白。在营养充足的细胞内没有选择性。饥饿细胞:选择性降解含有五肽Lys-Phe-Glu-Arg-Gln或相关的序列的胞内蛋白。 (2)依赖ATP的泛素途径,在胞质中进行,主要降解异常蛋白和短寿命蛋白(调节蛋白),此途径在不含溶酶体的红细胞中尤为重要。(选择性降解) 2、细胞内蛋白质降解的意义 (1)清除异常蛋白; (2)细胞对代谢进行调控的一种方式; (3)在需要时降解供肌体需要。 3、氨基酸的分解代谢主要在肝脏中进行。包括:脱氨基作用(最主要的反应)和脱羧基作用。 4、氧化脱氨基作用:α-氨基酸在酶的催化下氧化生成α-酮酸,此时消耗氧并产生氨。 5、L谷氨酸——α-酮戊二酸+ NH3 是L-Glu脱氢酶催化下的可逆反应,一般情况下偏向于谷氨酸的合成,因为高浓度氨对机体有害。L-谷氨酸脱氢酶为不需氧脱氢酶,辅酶为NAD+或NADP+,此酶为别构酶,此反应与能量代谢密切相关,ADP、GDP是其别构激活剂。

6、转氨基作用:指在转氨酶催化下将α-氨基酸的氨基转给另一个α-酮酸,结果原来的α-氨基酸生成相应的α-酮酸,而原来的α-酮酸则形成了相应的α-氨基酸。它是体内各种氨基酸脱氨基的主要形式,其逆反应也是体内生成非必需氨基酸的途径。 7、转氨酶种类很多:其中谷草转氨酶(GOT)在心脏中活力最大,其次为肝脏;谷丙转氨酶(GPT)在肝脏中活力最大,用于诊断肝功能。转氨酶的辅酶均为磷酸吡哆醛(VB6的磷酸酯)。 8、联合脱氨基作用:(1)转氨酶与L-谷氨酸脱氢酶作用相偶联:大多数转氨酶优先利用α-酮戊二酸作为氨基的受体,生成Glu,约占生物体的10%;(2)转氨基作用与嘌呤核苷酸循环相偶联:肝脏中90%谷氨酸经转氨基作用转化为天冬氨酸。 9、脱羧基作用:氨基酸经脱羧基作用生成伯胺类化合物和CO2。AA脱羧酶专一性很强,每一种AA都有一种脱羧酶,辅酶都是磷酸吡哆醛。AA脱羧反应广泛存在于动、植物和微生物中,有些产物具有重要生理功能。但大多数胺类对动物有毒。体内的胺氧化酶能将胺氧化为醛和氨,醛进一步氧化成脂肪酸。 10、NH3去向。(1)重新利用:合成AA、核酸。(2)贮存:高等植物将氨基氮以Gln和Asn的形式储存在体内。(3)排出体外:高等动物通过尿素循环在肝中将NH3生成尿素,通过肾脏排出体外。 11、尿素循环(鸟氨酸循环):在排尿动物体内由NH3合成尿素是在肝脏中通过一个循环机制完成的,这一个循环称为尿素循环。 过程:(1)NH3、CO2与鸟氨酸作用合成瓜氨酸;(2)瓜氨酸与天

第四章电化学与电位分析法

第四章 电化学与电位分析法 一、简答题 1.化学电池由哪几部分组成?如何表达电池的图示式?电池的图示式有那些规定? 2.电池的阳极和阴极,正极和负极是怎样定义的?阳极就是正极,阴极就是负极的说法对吗?为什么? 3.电池中"盐桥"的作用是什么?盐桥中的电解质溶液应有什么要求? 4.电极电位及电池电动势的表示式如何表示?应注意什么问题?何谓式量电位?如何表示? 5.电极有几种类型?各种类型电极的电极电位如何表示? 6.何谓指示电极、工作电极、参比电极和辅助电极? 7.何谓电极的极化?产生电极极化的原因有哪些?极化过电位如何表示? 8.写出下列电池的半电池反应和电池反应,计算电动势。这些电池是原电池还是电解池?极性为何?(设T 为25℃,活度系数均为1) (1)Pt│Cr 3+(1.0×10-4mol·L -1),Cr 2+(0.10mol·L -1)‖Pb 2+(8.0× 10-2mol·L -1)│Pb 已知: 322//E 0.41,E 0.126Cr Cr Pb Pb V V θθ++ +=-=- 已知: 2332//E 1.00,E 0.77VO VO Fe Fe V V θθ++++ == (3)Pt,H 2(20265Pa)│HCl (0.100mol·L -1)‖HClO 4(0.100mol·L -1)│Cl 2(50663Pa),Pt 已知: 2 2//E 0.0,E 1.359H H Cl Cl V V θθ+-== (4)Bi│BiO +(8.0×10-2mol·L -1 ),H +(1.00×10-2mol·L -1)‖I-(0.100mol·L -1),AgI(饱和)│Ag 已知: 17,//E 0.32,E 0.799,8.310sp AgI BiO Bi Ag Ag V V K θθ++-===? 9. 电位分析法的理论基础是什么?它可以分成哪两类分析方法?它们各有何特点? 10.以氟离子选择性电极为例,画出离子选择电极的基本结构图,并指出各部分的名称。 11.写出离子选择电极膜电位和电极电位的能斯特方程式。 ⑵

一个奇妙的化学振荡实验 趣味

实验教学与  教具研制一个奇妙的化学振荡实验新设计 3 熊言林 (安徽师范大学化学与材料科学学院 安徽芜湖 241000) 摘要 培养学生学习化学的兴趣,化学实验是最直接、最直观、最生动、最现实的教学素材。在参阅前人研究的基础上,用过氧化氢、碘酸钾等试剂设计了一个操作十分简单、适合中学条件的化学振荡实验方案,其奇妙的振荡现象十分明显、有趣,引人入胜。 关键词 中学化学 振荡实验 方案设计 过氧化氢 碘酸钾 学生的学习兴趣是激发学习动机的重要因素[1]。所以,我无论是在本科生、函授生、研究生的课堂教学中,还是在国家级骨干教师、省级骨干教师、全省高中化学教师的培训课上,以及在给中学生开展化学讲座上都要演示一些自己设计的、很有趣的新实验来配合相关内容的讲授,收到了较好的教学效果[2]。 在查阅B-Z反应、B-R反应及其相关振荡实验文献的基础上[3,4],我设计了一个操作十分简单、适合中学条件的化学振荡实验方案,并在多年的课堂教学、报告讲座上亲自演示过该实验,反复循环变色(无色→琥珀色→蓝色)的奇妙实验现象非常吸引学生、学员的眼球,引起了他们对该实验产生很大的兴趣。为此,笔者现将这一化学振荡实验方案设计出来,对该实验感兴趣的化学教师,不妨在新学年的第一次化学课上或在化学活动课上按照该实验方案做一做,看看学生有什么反应。 1 实验目的 (1)初步了解化学振荡实验原理,知道振荡现象广泛地存在于自然界中; (2)探究化学振荡实验的最佳条件,掌握化学振荡实验的基本操作; (3)体验化学振荡实验的新颖性、趣味性和知识性,激发学生学习化学的兴趣。 2 实验原理 在一定条件下,过氧化氢既可以作为还原剂,又可以作为氧化剂。在本实验条件下(室温,淀粉溶液),过氧化氢在Mn2+催化下分别跟碘酸钾、单质碘发生振荡反应,使溶液的颜色呈现周期性的变化(无色→琥珀色→蓝色),直至过氧化氢完全反应,溶液的颜色才不会再变化。上述颜色变化的反应机理很复杂,有人认为,可能反应机理是: 5H2O2+2IO-3+2H+→5O2↑+6H2O+I2(在Mn2+催化下)使淀粉溶液变蓝 I2+5H2O2→2HIO3+4H2O使蓝色淀粉溶液褪色I2+CH2(COO H)2→IC H(COO H)2+I-+H+ I2+ICH(COO H)2→I2C(COO H)2+I-+H+溶液呈琥珀色 3 实验用品 413g碘酸钾(C1P),4mL2mol/L H2SO4溶液,41mL30%的H2O2溶液,0134g硫酸锰晶体(C1P),116g丙二酸(C1P),0103g可溶性淀粉(C1P),蒸馏水(可用自来水代替)。 400mL烧杯1只,100mL烧杯2只,100mL 量筒1只,10mL量筒1只,台称1台,玻璃棒1支,酒精灯1盏,石棉网1块,白纸片1张。 4 实验步骤 411 溶液的配制 (1)无色溶液A 在400mL烧杯中,加入41mL30%的H2O2溶液,再加入59mL蒸馏水,用玻璃棒搅拌均匀,即为无色溶液A。 (2)无色溶液B 称取413g碘酸钾,放入到100mL烧杯中(为了配制方便,在此操作前,向烧杯里加入100mL的水,标出水面高度的记号后,倒出水),加入约60mL的蒸馏水,加热溶解,冷却后,再加入4mL2mol/L H2SO4溶液,用蒸馏水稀释到100mL的标记处,用玻璃棒搅拌均匀,即为无色溶液B。 (3)无色溶液C 称取116g丙二酸、0134g硫酸锰晶体,放入到100mL烧杯中(为了配制方便,在此操作前,向烧杯里加入100mL的水,标出水面高度的记号后,倒出水),用少量的蒸馏水溶解,加入含有0103g可溶性淀粉的溶液(如,10mL013%的可溶性淀粉溶液),再用蒸馏水稀释到100mL的标记处,搅拌均匀,即为无色溶液C。 412 混合溶液 在盛有100mL无色溶液A的400mL烧杯底部垫一张白纸片(便于观察),向烧杯中同时加入100mL无色溶液B和100mL无色溶液C,立即充分搅拌片刻。停止搅拌后,静置、观察振荡实验现象,并将颜色周期性变化的时间记入下表(每隔10~20s记一次): ? 4 4 ?化 学 教 育 2008年第10期3安徽师范大学“化学教育专业实验—化学教学论实验”精品课程建设项目(校教字[2006]69号)基金资助

教学指导氧化还原反应与电极电位

第八章 氧化还原反应与电极电位
首页
基本要求
重点难点
讲授学时
内容提要
1 基本要求 [TOP] 1.1 掌握离子-电子法配平氧化还原反应式、电池组成式的书写;根据标准电极电位判断氧化还原反应
方向;通过标准电动势计算氧化还原反应的平衡常数;电极电位的 Nernst 方程、影响因素及有关 计算。 1.2 熟悉氧化值的概念和氧化还原反应的定义,熟练计算元素氧化值;熟悉原电池的结构及正负极反应 的特征;熟悉标准电极电位概念;熟悉电池电动势与自由能变的关系。 1.3 了解电极类型、电极电位产生的原因;了解电位法测量溶液 pH 的原理及 pH 操作定义;了解电化学 与生物传感器及其应用。
2 重点难点 [TOP] 2.1 重点 2.1.1 标准电极电位表的应用。 2.1.2 电极反应与电池反应,电池组成式的书写。 2.1.3 通过标准电动势计算氧化还原反应的平衡常数。 2.1.4 电极电位的 Nernst 方程、影响因素及有关计算。 2.2 难点 2.2.1 电极电位的产生 2.2.2 用设计原电池的方法计算平衡常数 2.2.3 Nernst 方程的推导
3 讲授学时 [TOP] 建议 6 学时
4 内容提要 [TOP] 第一节 第二节 第三节 第四节 第五节
1

4.1 第一节 氧化还原反应
4.1.1 氧化值
氧化值是某元素原子的表观荷电数,这种荷电数是假设把化学键中的电子指定给电负性较大的原子
而求得。确定元素氧化值的规则:
1)单质中原子的氧化值为零。
2)单原子离子中原子的氧化值等于离子的电荷。
3)氧的氧化值在大多数化合物中为-2,但在过氧化物中为-1。
4)氢的氧化值在大多数化合物中为+1,但在金属氢化物中为-1。
5)卤族元素:氟的氧化值在所有化合物中均为-1,其它卤原子的氧化值在二元化合物中为-1,但
在卤族的二元化合物中,列周期表靠前的卤原子的氧化数为-1;在含氧化合物中按氧的氧化值为
-2 决定。
6)电中性化合物中所有原子的氧化值之和为零。
4.1.2 氧化还原反应
元素的氧化值发生了变化的化学反应称为氧化还原反应。氧化还原反应可被拆分成两个半反应。
半反应中元素的氧化值升高称为氧化,元素的氧化值降低称为还原。氧化还原反应中,氧化反应和还原
反应同时存在,还原剂被氧化,氧化剂被还原,且得失电子数相等。
半反应的通式为 氧化型 + ne-
还原型

Ox + ne-
Red
式中 n 为得失电子数,氧化型(Ox)包括氧化剂及相关介质,还原型(Red)包括还原剂及相关介质。氧化
型物质及对应的还原型物质称为氧化还原电对(Ox/Red)。
4.1.3 氧化还原反应方程式的配平
离子-电子法(或半反应法)配平氧化还原反应方程式的方法是:
1)写出氧化还原反应的离子方程式。
2)将离子方程式拆成氧化和还原两个半反应。
3)根据物料平衡和电荷平衡,分别配平半反应(注意不同介质中配平方法的差异)。
4)根据氧化剂和还原剂得失电子数相等,找出两个半反应的最小公倍数,并把它们配平合并。
5)可将配平的离子方程式写为分子方程式。
4.2 第二节 原电池与电极电位 4.2.1 原电池
[TOP]
2

B-Z振荡反应

B-Z振荡反应 姓名:*** 学号:2015012*** 班级:化学**班 实验日期:2018年3月21日提交报告日期:2018年3月23日 带课老师/助教:*** 1 引言(简明的实验目的/原理) 2 实验操作 2.1 实验药品、仪器型号及测试装置示意图 计算机及接口1套,THGD-0506高精度低温恒温槽 (宁波天恒仪器厂)1台,电磁搅拌器1台,反应器1 个,铂电极1个,饱和甘汞电极1个,滴瓶3个,量筒 3个,2mL移液管1支,洗瓶1个,镊子1把。 0.02mol?L-1硝酸铈铵,0.5mol?L-1丙二酸和0.2mol?L-1 溴酸钾(均由0.8mol?L-1硫酸溶液配制);0.8mol?L-1硫酸。 2.2 实验条件 恒温槽初始温度设定在25.00℃。

2.3 实验操作步骤及方法要点 1. 检查仪器药品。 2. 按装置图(如上)接好线路。 3. 接通电源。打开计算机,运行“数据采集”程序,准备采集数据。 4. 调节恒温槽温度为25℃。分别取7mL丙二酸、15mL溴酸钾、18mL硫酸溶液于干净的反应器中,开动搅拌。点击“开始”,待基线走稳后,用移液管加入2mL硝酸铈铵溶液。出现振荡后,待振荡周期完整重复8~10次后,点击“完成”,停止记录,命名存盘。记录恒温槽温度。实验中注意观察溶液的颜色变化。 5. 升高温度3~5℃,重复步骤4,直到35℃左右。 注意事项: 1. 实验开始前,要检查甘汞电极是否满足使用条件(溶液接触汞的部分,有固体KCl颗粒,没有气泡,甘汞电极与外部盐桥接通)。若不满足,应事先调整; 2. 全部溶液都用稀硫酸配制。防止反应液滴到皮肤、衣物、仪器、家具上。反应液流到电磁搅拌器上,应及时擦拭干净,更换滤纸,以免腐蚀仪器甚至发生漏电。若反应液滴到其他地方,应根据情况,及时冲洗或擦拭干净; 3. 橡皮塞及电极应保持竖直状态,避免平放或倒置,避免甘汞电极出现气泡; 4. 注意控制转子位置,避免损坏电极。反应前清洗反应器和电极,反应时控制转子转速保持稳定,可保证数据准确以及振荡反应出现。 3 结果与讨论 3.1 原始实验数据 3.1.1 不同温度下的电位振荡曲线图 实验得到不同温度下的电位振荡曲线图如下所示。

氨基酸的常见化学反应

-氨基的反应 亚硝酸反应 范围:可用于Aa定量和蛋白质水解程度的测定(Van slyke法) 注意:生成的氮气只有一半来自于Aa,ε氨基酸也可反应,速度较 慢. 与酰化试剂的反应 Aa+酰氯,酸酐-→Aa被酰基化 丹磺酰氯用于多肽链末端Aa的标记和微量Aa的定量测量.烃基化反应 Aa的氨基的一个氢原子可被羟基(包括环烃及其衍生物)取代. 与2,4-二硝基氟苯(DNFB,FDNB)反应 最早Sanger用来鉴定多肽或蛋白质的氨基末端的Aa 与苯异硫氰酸酯(PITC)的反应 Edman用于鉴定多肽或蛋白质的N末端Aa.在多肽和蛋白 质的Aa顺序分析方面占有重要地位( Edman降解法)形成西佛碱反应 Aa的α-NH2能与醛类化合物反应生成弱碱,即西佛碱(schiff ‘s base) 前述甲醛滴定:甲醛与H2N-CH2-COO-结合,有效地减低了后者的浓 度,所以对于加入任何量的碱, [H2N-CH2-COO- ]/ [+H3N-CH2-COO- ] 的比值总要比不存在甲醛的情况下小得多。加入甲醛的甘氨酸溶液 用标准盐酸滴定时,滴定曲线B并不发生改变。 脱氨基反应 Aa在生物体内经Aa氧化酶催化即脱去α-NH2而转变成酮酸 α-COOH参加的反应 成盐和成酯反应 Aa + 碱-→盐 Aa + NaOH -→氨基酸钠盐(重金属盐不溶于水) Aa-COOH + 醇-→酯 Aa+ EtOH ---→氨基酸乙酯的盐酸盐 当Aa的COOH变成甲酯,乙酯或钠盐后,COOH的化学反应性 能被掩蔽或者说COOH被保护,NH2的化学性能得到了加强或 活化,易与酰基结合。Aa酯是制备Aa的酰氨or酰肼的中间 物 成酰氯反应 当氨基酸的氨基用适当的保护基保护以后,其羧基可与二氯亚砜作 用生成酰氯 用于多肽人工合成中的羧基激活 叠氮反应 氨基酸的氨基通过酰化保护后,羧基经酯化转变为甲酯,然后与肼 和亚硝酸变成叠氮化合物

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