Fatigue-related changes in torque output and electromyographic parameters of trunk muscles during isometric axial rotation exertion - An investigation in patients with back pain and in healthy subjects

Study Design. A cross-sectional case-control study. Objectives. To examine the effect of fatigue on torque output as well as electromyographic frequency and amplitude values of trunk muscles during isometric axial rotation exertion in back pain patients and to compare the results with a matched control group. Summary of Background Data. Back pain patients exhibited different activation strategies in trunk muscles during the axial rotation exertions. Fatigue changes of abdominal and back muscles during axial rotation exertion have not been examined in patients with back pain. Methods. Twelve back pain patients and 12 matched controls performed isometric fatiguing axial rotation to both sides at 80% maximum voluntary contraction in a standing position. During the fatiguing exertion, electromyographic changes of rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum, and multifidus were recorded bilaterally. The primary torque in the transverse plane and the coupling torques in sagittal and coronal planes were also measured. Results. No difference in the endurance capacity was found between back pain and control groups. At the initial period of the exertion, back pain patients demonstrated a statistical trend (P = 0.058) of greater sagittal coupling torque as well as lower activity of rectus abdominis and multifidus and higher activity in external oblique. During the fatigue process similar changes of coupling torque were demonstrated in both sagittal and coronal planes, but a smaller fatigue rate for right external oblique, increase in median frequency for latissimus dorsi, and lesser increase in activity for back muscles were found in the back pain group compared with the control group. Conclusions. Alterations in electromyographic activation and fatigue rates of abdominal and back muscles demonstrated during the fatigue process provide insights into the muscle dysfunctions in back pain and may help clinicians to devise more rational treatment strategies.

Crystallization of PNMT, the adrenaline-synthesizing enzyme, is critically dependent on a high protein concentration

Phenylethanolamine N-methyltransferase, PNMT, utilizes the methylating cofactor S-adenosyl-L-methionine to catalyse the synthesis of adrenaline. Human PNMT has been crystallized in complex with an inhibitor and the cofactor product S-adenosyl-L-homocysteine using the hanging-drop technique with PEG 6000 and lithium chloride as precipitant. A critical requirement for crystallization was a high enzyme concentration (>90 mg ml(-1)) and cryocrystallography was used for high-quality data measurement. Diffraction data measured from a cryocooled crystal extend to a resolution of 2.3 Angstrom. Cryocooled crystals belong to space group P4(3)2(1)2 and have unit-cell parameters a = b = 94.3, c = 187.7 Angstrom.

Indirect evidence of density-dependent population regulation in Aponomma hydrosauri (Acari : Ixodidae), an ectoparasite of reptiles

The extent to which density-dependent processes regulate natural populations is the subject of an ongoing debate. We contribute evidence to this debate showing that density-dependent processes influence the population dynamics of the ectoparasite Aponomma hydrosauri (Acari: Ixodidae), a tick species that infests reptiles in Australia. The first piece of evidence comes from an unusually long-term dataset on the distribution of ticks among individual hosts. If density-dependent processes are influencing either host mortality or vital rates of the parasite population, and those distributions can be approximated with negative binomial distributions, then general host-parasite models predict that the aggregation coefficient of the parasite distribution will increase with the average intensity of infections. We fit negative binomial distributions to the frequency distributions of ticks on hosts, and find that the estimated aggregation coefficient k increases with increasing average tick density. This pattern indirectly implies that one or more vital rates of the tick population must be changing with increasing tick density, because mortality rates of the tick's main host, the sleepy lizard, Tiliqua rugosa, are unaffected by changes in tick burdens. Our second piece of evidence is a re-analysis of experimental data on the attachment success of individual ticks to lizard hosts using generalized linear modelling. The probability of successful engorgement decreases with increasing numbers of ticks attached to a host. This is direct evidence of a density-dependent process that could lead to an increase in the aggregation coefficient of tick distributions described earlier. The population-scale increase in the aggregation coefficient is indirect evidence of a density-dependent process or processes sufficiently strong to produce a population-wide pattern, and thus also likely to influence population regulation. The direct observation of a density-dependent process is evidence of at least part of the responsible mechanism.

ATP-dependent K+ channels in renal ischemia reperfusion injury

ATP-dependent K+ channels (K-ATP) account for most of the recycling of K+ which enters the proximal tubules cell via Na, K-ATPase. In the mitochondrial membrane, opening of these channels preserves mitochondrial viability and matrix volume during ischemia. We examined KATP channel modulation in renal ischemia-reperfusion injury (IRI), using an isolated perfused rat kidney (IPRK) model, in control, IRI, IRI + 200 muM diazoxide (a K-ATP opener), IRI + 10 muM glibenclamide (a K-ATP blocker) and IRI + 200 muM diazoxide + 10 muM glibenclamide groups. IRI was induced by 2 periods of warm ischemia, followed by 45 min of reperfusion. IRI significantly decreased glomerular filtration rate (GFR) and increased fractional excretion of sodium (FENa) (p < 0.01). Neither diazoxide nor glibenclamide had an effect on control kidney function other than an increase in renal vascular resistance produced by glibenclamide. Pretreatment with 200 muM diazoxide reduced the postischemic increase in FENa (p < 0.05). Adding 10 muM glibenclamide inhibited the diazoxide effect on postischemic FENa (p < 0.01). Histology showed that kidneys pretreated with glibenclamide demonstrated an increase in injure in the thick ascending limb of outer medulla (p < 0.05). Glibenclamide significantly decreased post ischemic renal vascular resistance (p < 0.05). but had no significant effect on other renal function parameters. Our results suggest that sodium reabsorption is improved by K-ATP activation and blockade of K-ATP channels during IRI has an injury enhancing effect on renal epithelial function and histology. This may be mediated through K-ATP modulation in cell and or mitochondrial inner membrane.

New fluorescence parameters for monitoring photosynthesis in plants - 1. The effect of illumination on the fluorescence parameters of the JIP-test

Chlorophyll fluorescence measurements have a wide range of applications from basic understanding of photosynthesis functioning to plant environmental stress responses and direct assessments of plant health. The measured signal is the fluorescence intensity (expressed in relative units) and the most meaningful data are derived from the time dependent increase in fluorescence intensity achieved upon application of continuous bright light to a previously dark adapted sample. The fluorescence response changes over time and is termed the Kautsky curve or chlorophyll fluorescence transient. Recently, Strasser and Strasser (1995) formulated a group of fluorescence parameters, called the JIP-test, that quantify the stepwise flow of energy through Photosystem II, using input data from the fluorescence transient. The purpose of this study was to establish relationships between the biochemical reactions occurring in PS II and specific JIP-test parameters. This was approached using isolated systems that facilitated the addition of modifying agents, a PS II electron transport inhibitor, an electron acceptor and an uncoupler, whose effects on PS II activity are well documented in the literature. The alteration to PS II activity caused by each of these compounds could then be monitored through the JIP-test parameters and compared and contrasted with the literature. The known alteration in PS II activity of Chenopodium album atrazine resistant and sensitive biotypes was also used to gauge the effectiveness and sensitivity of the JIP-test. The information gained from the in vitro study was successfully applied to an in situ study. This is the first in a series of four papers. It shows that the trapping parameters of the JIP-test were most affected by illumination and that the reduction in trapping had a run-on effect to inhibit electron transport. When irradiance exposure proceeded to photoinhibition, the electron transport probability parameter was greatly reduced and dissipation significantly increased. These results illustrate the advantage of monitoring a number of fluorescence parameters over the use of just one, which is often the case when the F-V/F-M ratio is used.

Evaluation of the influence of the ADH3 ILE349VAL polymorphism in the frequency of genotoxicity biomarkers in workers exposed to formaldehyde and tobacco smoking

Formaldehyde (FA) is a colourless gas widely used in the industry and hospitals as an aqueous solution, formalin. It is extremely reactive and induces various genotoxic effects in proliferating cultured mammalian cells. Tobacco smoke has been epidemiologically associated to a higher risk of development of cancer, especially in the oral cavity, larynx and lungs, as these are places of direct contact with many carcinogenic tobacco’s compounds. Genetic polymorphisms in enzymes involved in the metabolism are very important and can make changes in the individual susceptibility to disease. Alcohol dehydrogenase class 3 (ADH3), also known as formaldehyde dehydrogenase dependent of glutathione, is the major enzyme involved in the formaldehyde oxidation, especially in the buccal mucosa. The polymorphism in study is a substitution of an isoleucine for a valine in codon 349. The cytokinesis-blocked micronucleus assay (CBMN) in human lymphocytes is one of the most commonly used methods for measuring DNA damage, namely the detection of micronucleus, nucleoplasmic bridges, and nuclear buds, classified as genotoxicity biomarkers.

Learning dependent sources using mixtures of Dirichlet: applications on hyperspectral unmixing

This paper is an elaboration of the DECA algorithm [1] to blindly unmix hyperspectral data. The underlying mixing model is linear, meaning that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. The proposed method, as DECA, is tailored to highly mixed mixtures in which the geometric based approaches fail to identify the simplex of minimum volume enclosing the observed spectral vectors. We resort then to a statitistical framework, where the abundance fractions are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. With respect to DECA, we introduce two improvements: 1) the number of Dirichlet modes are inferred based on the minimum description length (MDL) principle; 2) The generalized expectation maximization (GEM) algorithm we adopt to infer the model parameters is improved by using alternating minimization and augmented Lagrangian methods to compute the mixing matrix. The effectiveness of the proposed algorithm is illustrated with simulated and read data.

Influence of reconstruction parameters during filtered backprojection and ordered-subset expectation maximization in the measurement of the left-ventricular volumes and function during gated SPECT

A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). Methods: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. Results: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. Conclusion: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Effect of bioactive compounds extracted from euphorbious plants on hematological and biochemical parameters of Channa punctatus

Channa punctatus was exposed to four different concentrations of Rutin, Taraxerol and Apigenin. Changes in some hematological parameters of Channa punctatus were assessed to determine the influence of these compounds on test fish. Fish were exposed to sublethal concentrations (80% of LC50 of 24h) of these compounds for one week. Control fish were also administered for one week. Thereafter, blood samples were obtained from the control and experimental fish. Blood was assayed for selected hematological parameters (hematocrit, hemoglobin, red blood cell count, white blood cell count total plasma protein and plasma glucose concentration). The derived hematological indices of mean corpuscular hemoglobin concentration (MCHC), mean corpuscular hemoglobin (MCH) and mean corpuscular volume (MCV) were calculated. Sublethal concentrations of these compounds caused a dose dependent decrease in hemoglobin values coupled with a decrease in hematocrit values and red blood cell counts are an obvious indication of anemia. The total white blood cell counts and the differential white blood cell counts were decreased except for the lymphocytes, where there was a slight increase. Plasma protein and glucose were also lower in exposed fish when compared with control. The hematological indices MCH, MCHC, MCV were also lowered. The result from this study reveals high mortality rate and deleterious consequences on the health of fish subjected to acute exposure of Rutin, Taraxerol and Apigenin and therefore, should not be used directly in aquaculture without having the proper knowledge.

Deletions within COL11A1 in Type 2 Stickler Syndrome Detected by Multiplex Ligation - Syndrome Detected by Multiplex Ligation Dependent Probe Amplification (MLPA)

Background: COL11A1 is a large complex gene around 250 kb in length and consisting of 68 exons. Pathogenic mutations in the gene can result in Stickler syndrome, Marshall syndrome or Fibrochondrogenesis. Many of the mutations resulting in either Stickler or Marshall syndrome alter splice sites and result in exon skipping, which because of the exon structure of collagen genes usually leaves the message in-frame. The mutant protein then exerts a dominant negative effect as it co-assembles with other collagen gene products. To date only one large deletion of 40 kb in the COL11A1, which was detected by RT-PCR, has been characterized. However, commonly used screening protocols, utilizing genomic amplification and exon sequencing, are unlikely to detect such large deletions. Consequently the frequency of this type of mutation is unknown. Case presentations: We have used Multiplex Ligation-Dependent Probe Amplification (MLPA) in conjunction with exon amplification and sequencing, to analyze patients with clinical features of Stickler syndrome, and have detected six novel deletions that were not found by exon sequencing alone. Conclusion: Exon deletions appear to represent a significant proportion of type 2 Stickler syndrome. This observation was previously unknown and so diagnostic screening of COL11A1 should include assays capable of detecting both large and small deletions, in addition to exon sequencing.

Effect of feeding frequency on the reproductive efficiency of two species of Triatoma with different epidemiological importance

Introduction In Triatominae, reproductive efficiency is an important factor influencing population dynamics, and a useful parameter in measuring a species' epidemiological significance as a vector of Trypanosoma cruzi (Chagas, 1909). The reproductive efficiency of triatomines is affected by food availability; hence, we measured and compared the effects of feeding frequency on the reproductive parameters of Triatoma patagonica (Del Ponte, 1929) and Triatoma infestans (Klug, 1934), and the effects of starvation on T. patagonica. Methods Couples from both species were fed weekly, or every 3 weeks; in addition, females in couples of T. patagonica were not fed. Each couple was observed weekly and reproductive efficiency was assessed on the following parameters: fecundity (eggs/female), fertility (eggs hatched/eggs laid), initiation and end of oviposition, initiation of mating, number of matings/week, and number of reproductive weeks. Relative meal size index (RMS), blood consumption index (CI), and E values (eggs/mg blood) were also calculated. Results Changes in feeding frequency affected the reproductive parameters of T. patagonica only, with a decrease in fecundity and number of reproductive weeks for those fed every 3 weeks, or not fed. The reproductive period, RMS index, and CI were lower for T. patagonica than T. infestans. However, despite the lower fecundity of T. patagonica, this species required less blood to produce eggs, with an E values of 2 compared to 2.94 for T. infestans. Conclusions Our results suggest that the differences in fecundity observed between species reflect the availability of food in their natural ecotopes.

Structure dependent resistivity and dielectric characteristics of tantalum oxynitride thin films produced by magnetron sputtering

tThe main purpose of this work is to present and to interpret the change of electrical properties of TaxNyOzthin films, produced by DC reactive magnetron sputtering. Some parameters were varied during deposi-tion: the flow of the reactive gases mixture (N2and O2, with a constant concentration ratio of 17:3); thesubstrate voltage bias (grounded, −50 V or −100 V) and the substrate (glass, (1 0 0) Si or high speed steel).The obtained films exhibit significant differences. The variation of the deposition parameters inducesvariations of the composition, microstructure and morphology. These differences cause variation of theelectrical resistivity essentially correlated with the composition and structural changes. The gradualdecrease of the Ta concentration in the films induces amorphization and causes a raise of the resistivity.The dielectric characteristics of some of the high resistance TaxNyOzfilms were obtained in the sampleswith a capacitor-like design (deposited onto high speed steel, with gold pads deposited on the dielectricTaxNyOzfilms). Some of these films exhibited dielectric constant values higher than those reported forother tantalum based dielectric films.

Comorbidities of mental and behavioral disorders in chemically dependent patients in different periods of abstinence

OBJECTIVE: To assess the frequency of comorbidities of mental and behavioral disorders (CMBD) in psychoactive substance (PAS)-dependent patients with different periods of abstinence cared for at Alcohol and Other Drug Psychosocial Care Centers (CAPS-ad). METHOD: All patients under treatment in the two CAPS-ad of the city of Uberlândia-MG, between April and September 2010, were consecutively assessed. The ICD-10 symptom checklist was used to diagnose CMBD; additional information was obtained from interviews and medical records. The patients were divided according to duration of abstinence: < 1 week (Group 1); 1-4 weeks (Group 2); and > 4 weeks (Group 3). RESULTS: Of all patients assessed, 62.8% were diagnosed with CMBD, which were more frequent (p < 0.05) in Group 1 (72%) than Group 3 (54.2%), and both groups were similar to Group 2 (61%). Depressive and anxiety disorders were more frequent among patients of Group 1. Mood disorders were more frequent (p < 0.05) in women [22/34 (65%) vs. 54/154 (35.1%)], whereas psychotic disorders were more frequent (p = 0.05) in men [16/154 (10.4%) vs. 0]. The presence of CMBD was associated with more severe clinical conditions. CONCLUSIONS: The higher frequency of diagnosis of CMBD in patients of Group 1 may have resulted from the difficulties in distinguishing mental disorders that are due to PAS intoxication or withdrawal from those that are not. However, to make the diagnosis of CMBD, even during detoxification, can increase the likelihood of better response to treatment.