The seeming lack of CF···HO intramolecular hydrogen bonds in linear aliphatic fluoroalcohols in solution.

No CF···HO intramolecular hydrogen bonds (IHBs) in 2-fluoroethanol, 3-fluoropropanol and 4-fluorobutanol can be detected experimentally in solution by NMR and infrared spectroscopies. According to ab initio (MP2/aug-cc-pVDZ) and DFT calculations (B3LYP), a CF···HO IHB has no influence on the conformational behavior of 2-fluoroethanol, while it stabilises the global minima of 3-fluoropropanol and 4-fluorobutanol for the isolated molecules. Entropy and bulk solvation effects, even in nonpolar media, such as CCl4, cyclohexane and dichloromethane, are indicated to diminish the population of these global minima, apparently below the detection limit.

Theoretical and infrared spectroscopy study of the conformational preferences for some 3-monosubstituted-2-methylpropenes.

The infrared spectra of 3-X-2-methylpropenes (X = Cl, Br, I, NMe(2), NEt(2), OH, OMe, OEt, SH, SMe and SEt) have been recorded at room temperature in CCl(4) solution. The C=C stretching mode was analyzed and compared to theoretically calculated data to give insight about the conformational isomerism of these compounds. A combination band systematically appears in all spectra (except for amines); the remaining ν(C=C) band and the corresponding intensities were used to obtain the conformer populations. For second-period atoms bonded to C-3, two or more conformers are observed in CCl(4) solution, but when substitution by heavier atoms takes place, only one conformer is observed under the tested conditions, i.e., the gauche form with respect to the C=C-C-X dihedral angle. Therefore, steric hindrance between X and =CH(2) in the s-cis form is strongly dependent on the heteroatom size, while the effect of the alkyl chain bonded to the heteroatom seems to be of secondary importance.

Multinuclear magnetic resonance and theoretical calculations in the study of structure and tautomerism of some 2-amino-N'-(aryl)-benzamidines.

1H, 13C and 15N NMR spectra of eight 2-amino-N'-(aryl)-benzamidines and of the parent compound were recorded, and unequivocal chemical shift assignments through the use of COSY, 1H-J resolved, HETCOR and COLOC sequences were performed. 1H and 13C chemical shifts for the nuclei of the benzamidine aromatic ring were not affected by the substituents present at N'-phenyl group, while the substituent effects in the chemical shifts of the same nuclei of N'-phenyl ring were very similar to the ones reported for the corresponding monosubstituted benzenes, indicating that there is no interaction between the two aromatic rings. 15N NMR spectra (DEPT sequence) show just two hydrogenated nitrogen atoms, which confirm that the amino form is the most stable tautomer, but the observation of a sharp signal and two broad signals (15N decoupled spectra), and the corresponding broad signal for the =C-NH(2) protons (in the 1H spectra), indicates the occurrence of tautomerism between the amino and imino forms, observable for some of the studied benzamidines. Theoretical calculations lead to the conclusion that these compounds occur mostly as the amino tautomer with Z configuration, which is stabilized by hydrogen bonding.

The utility of infrared spectroscopy for quantitative conformational analysis at a single temperature.

The carbonyl stretching vibration of 2-bromocyclohexanone (1) has been measured in a variety of solvents. It is shown that its component intensities are not only dependent on the populations of the axial and equatorial conformers, but are also dependent on the molar absorptivities (epsilon ) which are specific for each conformer in each solvent. In CCl(4), the axial and equatorial conformers have epsilon values of 417 and 818 l mol(-1) x cm(-1), respectively, while in CH(3)CN solution, the values were 664 and 293 l mol(-1) x cm(-1). These results are supported by results of theoretical calculations of frequencies, which gave an intensity of 223.8 kM mol(-1) x(1782 cm(-1)) for the axial and 174.4 kM mol(-1) x (1802 cm(-1)) for the equatorial conformer, indicating that the axial conformer presents a larger molar absorptivity than the equatorial one in the vapor phase. Moreover, the results presented here clearly demonstrate that although infrared spectroscopy at a single temperature can be an important auxiliary technique for conformational analysis, it must not be used to quantify conformational preferences of a molecule if the absorption molar coefficients for each conformer are not known or not amenable to experimental determination.

Infrared spectroscopy and theoretical calculations as tools for the conformational analysis of 2-methoxycyclohexanone.

The conformational equilibrium of 2-methoxycyclohexanone has been analyzed through infrared spectroscopy and theoretical calculations. These calculations indicate that six conformations may be present in the vapor phase, due to the rotation of the methoxy group around the O-C(2) bond, leading to axial (g(+), g(-) and anti) and equatorial (g(+), g(-) and anti) conformers. However, the infrared spectrum in CCl(4) solution shows just three carbonyl stretching bands, corresponding to the conformers of lower energies. An additional band is observed for the CH(3)CN solution, attributed to a fourth conformer stabilized by a dipole-dipole interaction between this conformer, having a high dipole moment, and the very polar solvent. An interpretation of the governing factors of 2-methoxycyclohexanone equilibria is also given.

Recognition of lead reversals in pediatric electrocardiograms.

We have trained artificial neural networks to detect right/left arm lead reversals in pediatric electrocardiograms with a performance significantly higher than that of currently used methods. We believe that this type of neural network can be a valuable type of quality control in pediatric electrocardiography.

Acute myocardial infarction detected in the 12-lead ECG by artificial neural networks.

BACKGROUND: The 12-lead ECG, together with patient history and clinical findings, remains the most important method for early diagnosis of acute myocardial infarction. Automated interpretation of ECG is widely used as decision support for less experienced physicians. Recent reports have demonstrated that artificial neural networks can be used to improve selected aspects of conventional rule-based interpretation programs. The purpose of this study was to detect acute myocardial infarction in the 12-lead ECG with artificial neural networks. METHODS AND RESULTS: A total of 1120 ECGs from patients with acute myocardial infarction and 10,452 control ECGs, recorded at an emergency department with computerized ECGs, were studied. Artificial neural networks were trained to detect acute myocardial infarction by use of measurements from the 12 ST-T segments of each ECG, together with the correct diagnosis. After this training process, the performance of the neural networks was compared with that of a widely used ECG interpretation program and the classification of an experienced cardiologist. The neural networks showed higher sensitivities and discriminant power than both the interpretation program and cardiologist. The sensitivity of the neural networks was 15.5% (95% confidence interval [CI], 12.4 to 18.6) higher than that of the interpretation program compared at a specificity of 95.4% (P<.00001) and 10.5% (95% CI, 7.2 to 13.6) higher than the cardiologist at a specificity of 86.3% (P<.00001). CONCLUSIONS: Artificial neural networks can be used to improve automated ECG interpretation for acute myocardial infarction. The networks may be useful as decision support even for the experienced ECG readers.

Artery blood pressure oscillation after active standing up: an indicator of sympathetic function in diabetic patients.

Dynamic artery blood pressure (Finapres) response to active standing up, normally consisting of initial rise, fall and recovery above the baseline (overshoot), was compared with the early steady-state artery blood pressure level to measure sympathetic vasomotor function in healthy subjects (n = 23, age 35 +/- 9 years; mean +/-SD) and in type I diabetic patients without autonomic neuropathy (AN) (group 1: n = 18, 38 +/- 13 years), with AN but no cardiovascular drugs (group 2a: n = 7, 44 +/- 11 years) and with both AN and cardiovascular drugs (group 2b: n = 10, 47 +/- 7 years). Systolic and diastolic overshoot were similar in the control (15 +/- 13/15 +/- 11 mmHg) and group 1 subjects. Systolic overshoot disappeared in 57% of patients in group 2a (-1 +/- 9 mmHg; P < 0.03), whereas artery blood pressure still overshot in diastole (8 +/- 7 mmHg; NS). Systolic overshoot disappeared in all patients in group 2b (-22 +/- 22 mmHg; P < 0.0006) and diastolic overshoot disappeared in 60% of these patients (-6 +/- 16 mmHg; P = 0.0006). Systolic early steady-state level was not lower in group 2a than in group 1 (NS), but it was impaired in group 2b (P < 0.006), in which six diabetic patients had a pathological response beyond the age-related reference values. There was a strong association between the overshoot and steady-state levels (P for chi 2 < 0.001, n = 58). Overshoot of the control subjects and patients in group 2b correlated to their respective steady-state blood pressure levels (r > or = 0.76; P < or = 0.001). In conclusion, baroreceptor reflex-dependent overshoot of the artery blood pressure after active standing up diminishes with the development of AN and it is associated with the early steady-state level of the artery blood pressure.

Agreement between artificial neural networks and experienced electrocardiographer on electrocardiographic diagnosis of healed myocardial infarction.

OBJECTIVES: The purpose of this study was to compare the diagnoses of healed myocardial infarction made from the 12-lead electrocardiogram (ECG) by artificial neural networks and an experienced electrocardiographer. BACKGROUND: Artificial neural networks have proved of value in pattern recognition tasks. Studies of their utility in ECG interpretation have shown performance exceeding that of conventional ECG interpretation programs. The latter present verbal statements, often with an indication of the likelihood for a certain diagnosis, such as "possible left ventricular hypertrophy." A neural network presents its output as a numeric value between 0 and 1; however, these values can be interpreted as Bayesian probabilities. METHODS: The study was based on 351 healthy volunteers and 1,313 patients with a history of chest pain who had undergone diagnostic cardiac catheterization. A 12-lead ECG was recorded in each subject. An expert electrocardiographer classified the ECGs in five different groups by estimating the probability of anterior myocardial infarction. Artificial neural networks were trained and tested to diagnose anterior myocardial infarction. The network outputs were divided into five groups by using the output values and four thresholds between 0 and 1. RESULTS: The neural networks diagnosed healed anterior myocardial infarctions at high levels of sensitivity and specificity. The network outputs were transformed to verbal statements, and the agreement between these probability estimates and those of an expert electrocardiographer was high. CONCLUSIONS: Artificial neural networks can be of value in automated interpretation of ECGs in the near future.

Detection of frequently overlooked electrocardiographic lead reversals using artificial neural networks.

Artificial neural networks can be used to recognize lead reversals in the 12-lead electrocardiogram at very high specificity, and the sensitivity is much higher than that of a conventional interpretation program. The neural networks developed in this and an earlier study for detection of lead reversals, in combination with an algorithm for the right arm/right foot lead reversal, would recognize approximately 75% of lead reversals encountered in clinical practice.

Artificial neural networks for recognition of electrocardiographic lead reversal.

Misplacement of electrodes during the recording of an electrocardiogram (ECG) can cause an incorrect interpretation, misdiagnosis, and subsequent lack of proper treatment. The purpose of this study was twofold: (1) to develop artificial neural networks that yield peak sensitivity for the recognition of right/left arm lead reversal at a very high specificity; and (2) to compare the performances of the networks with those of 2 widely used rule-based interpretation programs. The study was based on 11,009 ECGs recorded in patients at an emergency department using computerized electrocardiographs. Each of the ECGs was used to computationally generate an ECG with right/left arm lead reversal. Neural networks were trained to detect ECGs with right/left arm lead reversal. Different networks and rule-based criteria were used depending on the presence or absence of P waves. The networks and the criteria all showed a very high specificity (99.87% to 100%). The neural networks performed better than the rule-based criteria, both when P waves were present (sensitivity 99.1%) or absent (sensitivity 94.5%). The corresponding sensitivities for the best criteria were 93.9% and 39.3%, respectively. An estimated 300 million ECGs are recorded annually in the world. The majority of these recordings are performed using computerized electrocardiographs, which include algorithms for detection of right/left arm lead reversals. In this study, neural networks performed better than conventional algorithms and the differences in sensitivity could result in 100,000 to 400,000 right/left arm lead reversals being detected by networks but not by conventional interpretation programs.