Diagnosis of the nutrient compositional space of fruit crops

Tissue analysis is a useful tool for the nutrient management of fruit orchards. The mineral composition of diagnostic tissues expressed as nutrient concentration on a dry weight basis has long been used to assess the status of 'pure' nutrients. When nutrients are mixed and interact in plant tissues, their proportions or concentrations change relatively to each other as a result of synergism, antagonism, or neutrality, hence producing resonance within the closed space of tissue composition. Ternary diagrams and nutrient ratios are early representations of interacting nutrients in the compositional space. Dual and multiple interactions were integrated by the Diagnosis and Recommendation Integrated System (DRIS) into nutrient indexes and by Compositional Nutrient Diagnosis into centered log ratios (CND-clr). DRIS has some computational flaws such as using a dry matter index that is not a part as well as nutrient products (e.g. NxCa) instead of ratios. DRIS and CND-clr integrate all possible nutrient interactions without defining an ad hoc interactive model. They diagnose D components while D-1 could be diagnosed in the D-compositional Hilbert space. The isometric log ratio (ilr) coordinates overcome these problems using orthonormal binary nutrient partitions instead of dual ratios. In this study, it is presented a nutrient interactive model as well as computation methods for DRIS and CND-clr and CND-ilr coordinates (CND-ilr) using leaf analytical data from an experimental apple orchard in Southwestern Quebec, Canada. It was computed the Aitchison and Mahalanobis distances across ilr coordinates as measures of nutrient imbalance. The effect of changing nutrient concentrations on ilr coordinates are simulated to identify the ones contributing the most to nutrient imbalance.

Pyogenic and tuberculous discitis: magnetic resonance imaging findings for differential diagnosis

Spondylodiscitis represents 2%–4% of all bone infections cases. The correct diagnosis and appropriate treatment can prevent complications such as vertebral collapse and spinal cord compression, avoiding surgical procedures. The diagnosis is based on characteristic clinical and radiographic findings and confirmed by blood culture and biopsy of the disc or the vertebra. The present study was developed with Clementino Fraga Filho University Hospital patients with histopathologically and microbiologically confirmed diagnosis of spondylodiscitis, submitted to magnetic resonance imaging of the affected regions. In most cases, pyogenic spondylodiscitis affects the lumbar spine. The following findings are suggestive of the diagnosis: segmental involvement; ill-defined abscesses; early intervertebral disc involvement; homogeneous vertebral bodies and intervertebral discs involvement. Tuberculous spondylodiscitis affects preferentially the thoracic spine. Most suggestive signs include: presence of well-defined and thin-walled abscess; multisegmental, subligamentous involvement; heterogeneous involvement of vertebral bodies; and relative sparing of intervertebral discs. The present pictorial essay is aimed at showing the main magnetic resonance imaging findings of pyogenic and tuberculous discitis.

Early screening for preeclampsia

Preeclampsia, which affects about 3 to 5% of pregnant women, is the most frequent medical complication in pregnancy and the most important cause of maternal and perinatal morbidity and mortality. During the past three decades, numerous clinical, biophysical, and biochemical screening tests have been proposed for the early detection of preeclampsia. Literature shows large discrepancies in the sensitivity and predictive value of several of these tests. No single screening test used for preeclampsia prediction has gained widespread acceptance into clinical practice. Instead, its value seems to be in increasing the predictive value of panels of tests, which include other clinical measurements. The aim of this review was to examine the combination of maternal risk factors, mean arterial blood pressure, and uterine artery Doppler, together with biomarkers in the preeclampsia prediction.

Criteria for prediction of metastatic axillary lymph nodes in early-stage breast cancer

PURPOSE: To estimate the likelihood of axillary lymph node involvement for patients with early-stage breast cancer, based on a variety of clinical and pathological factors. METHODS: A retrospective analysis was done in hospital databases from 1999 to 2007. Two hundred thirty-nine patients were diagnosed with early-stage breast cancer. Predictive factors, such as patient age, tumor size, lymphovascular invasion, histological grade and immunohistochemical subtype were analyzed to identify variables that may be associated with axillary lymph node metastasis. RESULTS: Patients with tumors that are negative for estrogen receptor, progesterone receptor, and HER2 had approximately a 90% lower chance of developing lymph node metastasis than those with luminal A tumors (e.g., ER+ and/or PR+ and HER2-) - Odds Ratio: 0.11; 95% confidence interval: 0.01-0.88; p=0.01. Furthermore, the risk for lymph node metastasis of luminal A tumors seemed to decrease as patient age increased, and it was directly correlated with tumor size. CONCLUSION: The molecular classification of early-stage breast cancer using immunohistochemistry may help predicting the probability of developing axillary lymph node metastasis. Further studies are needed to optimize predictions for nodal involvement, with the aim of aiding the decision-making process for breast cancer treatment.

Serological diagnosis of visceral leishmaniasis by an enzyme immunoassay using protein A in naturally infected dogs

A rapid indirect enzyme-linked immunosorbent assay (ELISA) was developed for measuring antibodies against Leishmania chagasi using total antigen from lysed promastigotes. Fifty symptomatic mixed breed dogs from a region of high incidence of visceral leishmaniasis in Brazil were examined. The results showed that in the positive animals, diagnosed by cytological examination, the ELISA using protein A assay system (mean optical density ± SD / 2.078 ± 0.631) detected more antibodies than the anti-IgG assay (mean optical density ± SD / 1.008 ± 0.437), while in the negative animals, the results by both systems were similar. These results suggest that the ELISA assay using protein A peroxidase conjugated could be useful to detect early infected animals in endemic areas, and thus help to control the spread of the infection.

Identification of clonally rearranged T-cell receptor beta chain genes in HTLV-I carriers as a potential instrument for early detection of neoplasia

We analyzed the genetic recombination pattern of the T-cell receptor beta-chain gene (TCR-beta) in order to identify clonal expansion of T-lymphocytes in 17 human T-lymphotropic virus type I (HTLV-I)-positive healthy carriers, 7 of them with abnormal features in the peripheral blood lymphocytes. Monoclonal or oligoclonal expansion of T-cells was detected in 5 of 7 HTLV-I-positive patients with abnormal lymphocytes and unconfirmed diagnosis by using PCR amplification of segments of TCR-beta gene, in a set of reactions that target 102 different variable (V) segments, covering all members of the 24 V families available in the gene bank, including the more recently identified segments of the Vbeta-5 and Vbeta-8 family and the two diversity beta segments. Southern blots, the gold standard method to detect T-lymphocyte clonality, were negative for all of these 7 patients, what highlights the low sensitivity of this method that requires a large amount of very high quality DNA. To evaluate the performance of PCR in the detection of clonality we also analyzed 18 leukemia patients, all of whom tested positive. Clonal expansion was not detected in any of the negative controls or healthy carriers without abnormal lymphocytes. In conclusion, PCR amplification of segments of rearranged TCR-beta is reliable and highly suitable for the detection of small populations of clonal T-cells in asymptomatic HTLV-I carriers who present abnormal peripheral blood lymphocytes providing an additional instrument for following up these patients with potentially higher risk of leukemia.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Cost-effective analysis of different algorithms for the diagnosis of hepatitis C virus infection

We compared the cost-benefit of two algorithms, recently proposed by the Centers for Disease Control and Prevention, USA, with the conventional one, the most appropriate for the diagnosis of hepatitis C virus (HCV) infection in the Brazilian population. Serum samples were obtained from 517 ELISA-positive or -inconclusive blood donors who had returned to Fundação Pró-Sangue/Hemocentro de São Paulo to confirm previous results. Algorithm A was based on signal-to-cut-off (s/co) ratio of ELISA anti-HCV samples that show s/co ratio ³95% concordance with immunoblot (IB) positivity. For algorithm B, reflex nucleic acid amplification testing by PCR was required for ELISA-positive or -inconclusive samples and IB for PCR-negative samples. For algorithm C, all positive or inconclusive ELISA samples were submitted to IB. We observed a similar rate of positive results with the three algorithms: 287, 287, and 285 for A, B, and C, respectively, and 283 were concordant with one another. Indeterminate results from algorithms A and C were elucidated by PCR (expanded algorithm) which detected two more positive samples. The estimated cost of algorithms A and B was US$21,299.39 and US$32,397.40, respectively, which were 43.5 and 14.0% more economic than C (US$37,673.79). The cost can vary according to the technique used. We conclude that both algorithms A and B are suitable for diagnosing HCV infection in the Brazilian population. Furthermore, algorithm A is the more practical and economical one since it requires supplemental tests for only 54% of the samples. Algorithm B provides early information about the presence of viremia.

Antibodies to citrullinated peptides are not associated with the rate of joint destruction in patients with a well-established diagnosis of rheumatoid arthritis

Antibodies to citrullinated peptides are highly specific for rheumatoid arthritis (RA) and represent a significant risk factor for undifferentiated polyarthritis. This prognostic ability may be related to the very diagnostic performance of these autoantibodies, since RA is a more erosive disease than other forms of arthritis. The present study evaluated an association of antibodies to citrullinated peptides and the rate of joint destruction in patients with a well-established diagnosis of RA. Seventy-one patients with RA were evaluated in 1994 and again in 2002 (functional class, joint count, Health Assessment Questionnaire score, hands X-ray). Autoantibodies (rheumatoid factor (RF), anti-perinuclear factor, anti-cyclic citrullinated peptide (CCP) antibodies) and Sharp's index were analyzed blindly. Delta Sharp was calculated as the difference in Sharp's index obtained in 1994 and 2002. During the follow-up the Health Assessment Questionnaire score increased from 0.91 ± 0.74 to 1.39 ± 0.72 (P < 0.001). Similarly, the number of swollen joints increased from 4.6 ± 5.71 to 6.4 ± 4.1 (P = 0.002). The frequency of autoantibodies and anti-CCP titer remained stable; however, serum RF concentration increased from 202.8 ± 357.6 to 416.6 ± 636.5 IU/mL (P = 0.003). Sharp's index increased from 56.7 ± 62.1 to 92.4 ± 80.9 (P < 0.001). No correlation was observed between Delta Sharp and the presence of RF, anti-perinuclear factor, and anti-CCP antibodies at baseline. Antibodies to citrullinated epitopes are specific and early markers for the diagnosis of RA but do not seem to be associated with the rate of joint destruction in patients with a well-established diagnosis of RA.

Wrist ultrasound analysis of patients with early rheumatoid arthritis

In the present study, we evaluated 42 wrists using the semi-quantitative scales power Doppler ultrasound (PDUS) and gray scale ultrasound (GSUS) with scores ranging from 0 to 3 and correlated the results with clinical, laboratory and radiographic data. Twenty-one patients (17 women and 4 men) with rheumatoid arthritis according to criteria of the American College of Rheumatology were enrolled in the study from September 2008 to July 2009 at Universidade Estadual de Campinas (UNICAMP). The average disease duration was 14 months. The patients were 66.6% Caucasians and 33.3% non-Caucasians, with a mean age of 42 and 41 years, respectively. A dorsal longitudinal scan was performed by ultrasound on the radiocarpal and midcarpal joints using GE LOGIQ XP-linear ultrasound and a high frequency (8-10 MHz) transducer. All patients were X-rayed, and the Larsen score was determined for the joints, with grades ranging from 0 to V. This study showed significant correlations between clinical, sonographic and laboratory data: GSUS and swollen right wrist (r = 0.546), GSUS of right wrist and swelling of left wrist (r = 0.511), PDUS of right wrist and pain in left wrist (r = 0.436), PDUS of right wrist and C-reactive protein (r = 0.466). Ultrasound can be considered a useful tool in the diagnosis of synovitis in early rheumatoid arthritis mainly when the anti-cyclic citrullinated peptide and rheumatoid factor are negative, and can lead to an early change in the therapeutic decision.

Analysis of acylcarnitine profiles in umbilical cord blood and during the early neonatal period by electrospray ionization tandem mass spectrometry

Acylcarnitine profiling by electrospray ionization tandem mass spectrometry (ESI-MS/MS) is a potent tool for the diagnosis and screening of fatty acid oxidation and organic acid disorders. Few studies have analyzed free carnitine and acylcarnitines in dried blood spots (DBS) of umbilical cord blood (CB) and the postnatal changes in the concentrations of these analytes. We have investigated these metabolites in healthy exclusively breastfed neonates and examined possible effects of birth weight and gestational age. DBS of CB were collected from 162 adequate for gestational age neonates. Paired DBS of heel-prick blood were collected 4-8 days after birth from 106 of these neonates, the majority exclusively breastfed. Methanol extracts of DBS with deuterium-labeled internal standards were derivatized before analysis by ESI-MS/MS. Most of the analytes were measured using a full-scan method. The levels of the major long-chain acylcarnitines, palmitoylcarnitine, stearoylcarnitine, and oleoylcarnitine, increased by 27, 12, and 109%, respectively, in the first week of life. Free carnitine and acetylcarnitine had a modest increase: 8 and 11%, respectively. Propionylcarnitine presented a different behavior, decreasing 9% during the period. The correlations between birth weight or gestational age and the concentrations of the analytes in DBS were weak (r £ 0.20) or nonsignificant. Adaptation to breast milk as the sole source of nutrients can explain the increase of these metabolites along the early neonatal period. Acylcarnitine profiling in CB should have a role in the early detection of metabolic disorders in high-risk neonates.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.