Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Outcome Prediction after Cardiac Arrest Treated with Hypothermia

Rationale: Clinical and electrophysiological prognostic markers of brain anoxia have been mostly evaluated in comatose survivors of out hospital cardiac arrest (OHCA) after standard resuscitation, but their predictive value in patients treated with mild induced hypothermia (IH) is unknown. The objective of this study was to identify a predictive score of independent clinical and electrophysiological variables in comatose OHCA survivors treated with IH, aiming at a maximal positive predictive value (PPV) and a high negative predictive value (NPV) for mortality. Methods: We prospectively studied consecutive adult comatose OHCA survivors from April 2006 to May 2009, treated with mild IH to 33-34_C for 24h at the intensive care unit of the Lausanne University Hospital, Switzerland. IH was applied using an external cooling method. As soon as subjects passively rewarmed (body temperature >35_C) they underwent EEG and SSEP recordings (off sedation), and were examined by experienced neurologists at least twice. Patients with status epilepticus were treated with AED for at least 24h. A multivariable logistic regression was performed to identify independent predictors of mortality at hospital discharge. These were used to formulate a predictive score. Results: 100 patients were studied; 61 died. Age, gender and OHCA etiology (cardiac vs. non-cardiac) did not differ among survivors and nonsurvivors. Cardiac arrest type (non-ventricular fibrillation vs. ventricular fibrillation), time to return of spontaneous circulation (ROSC) >25min, failure to recover all brainstem reflexes, extensor or no motor response to pain, myoclonus, presence of epileptiform discharges on EEG, EEG background unreactive to pain, and bilaterally absent N20 on SSEP, were all significantly associated with mortality. Absent N20 was the only variable showing no false positive results. Multivariable logistic regression identified four independent predictors (Table). These were used to construct the score, and its predictive values were calculated after a cut-off of 0-1 vs. 2-4 predictors. We found a PPV of 1.00 (95% CI: 0.93-1.00), a NPV of 0.81 (95% CI: 0.67-0.91) and an accuracy of 0.93 for mortality. Among 9 patients who were predicted to survive by the score but eventually died, only 1 had absent N20. Conclusions: Pending validation in a larger cohort, this simple score represents a promising tool to identify patients who will survive, and most subjects who will not, after OHCA and IH. Furthermore, while SSEP are 100% predictive of poor outcome but not available in most hospitals, this study identifies EEG background reactivity as an important predictor after OHCA. The score appears robust even without SSEP, suggesting that SSEP and other investigations (e.g., mismatch negativity, serum NSE) might be principally needed to enhance prognostication in the small subgroup of patients failing to improve despite a favorable score.

Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

Rgtsp: a generalized top scoring pairs package for class prediction.

SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.

Localization of HLA-A2.1-restricted T cell epitopes in the circumsporozoite protein of Plasmodium falciparum.

Localization of human MHC class I-restricted T cell epitopes in the circumsporozoite (CS) protein of the human parasite Plasmodium falciparum is an important objective in the development of antimalarial vaccines. To this purpose, we synthesized a series of overlapping synthetic 20-mer peptides, spanning the entire sequence of the 7G8 CS molecule except for the central repeat B cell domain. The P.f.CS peptides were first tested for their ability to bind to the human MHC class I HLA-A2.1 molecule on T2, a human cell line. Subsequently, the use of a series of shorter peptide analogues allowed us to determine the optimal A2.1 binding sequence present in several of the 20-mers. Binding P.f.CS peptides were further tested for their capacity to activate PBL from HLA-A2.1+ immune donors living in a malaria-endemic area. Specific IFN-gamma production was detected in the supernatant of cultures of PBL from exposed individuals. Cytotoxic T cell lines and clones were derived from the PBL of one responder, and their activity was shown to be HLA-A2.1-restricted and specific for the peptide 334-342 of the CS protein. In addition, double transgenic HLA-A2.1 x human beta 2-microglobulin mice were immunized with peptide 1-10 of the CS protein. T cells derived from immune lymph nodes displayed a peptide-specific HLA-A2.1-restricted cytolytic activity after one in vitro stimulation.

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

A mechanism for localized lignin deposition in the endodermis.

The precise localization of extracellular matrix and cell wall components is of critical importance for multicellular organisms. Lignin is a major cell wall modification that often forms intricate subcellular patterns that are central to cellular function. Yet the mechanisms of lignin polymerization and the subcellular precision of its formation remain enigmatic. Here, we show that the Casparian strip, a lignin-based, paracellular diffusion barrier in plants, forms as a precise, median ring by the concerted action of a specific, localized NADPH oxidase, brought into proximity of localized peroxidases through the action of Casparian strip domain proteins (CASPs). Our findings in Arabidopsis provide a simple mechanistic model of how plant cells regulate lignin formation with subcellular precision. We speculate that scaffolding of NADPH oxidases to the downstream targets of the reactive oxygen species (ROS) that they produce might be a widespread mechanism to ensure specificity and subcellular precision of ROS action within the extracellular matrix.

Cellular localization, expression and regulation of neuropeptide Y in kidneys of hypertensive rats.

Neuropeptide Y (NPY) is a key modulator of the autonomic nervous system playing pivotal roles in cardiovascular and neuronal functions. In this study, we assessed the cellular localization and gene expression of NPY in rat kidneys. We also examined the relationship between NPY gene expression and renin in two rat models of hypertension (two-kidney, one-clip renal hypertension (2K1C), and deoxycorticosterone-salt-induced hypertension (DOCA-salt)) characterized by a similar blood pressure elevation. In situ hybridization and immunohistochemistry, using anti-NPY or anti-C-flanking peptide of NPY (CPON) antibodies, showed that NPY transcript and protein were colocalized in the tubules of rat kidneys. During experimental hypertension, NPY mRNA was decreased in both kidneys of the 2K1C animals, but not in the kidney of DOCA-salt rats. In 2K1C rats, renal NPY content was also decreased. The difference in NPY gene expression between 2K1C rats (a high renin model of hypertension) and DOCA-salt rats (a low renin model of hypertension) suggests that circulating angiotensin II plays a role in local renal NPY gene expression and that the elevated blood pressure per se is not the primary factor responsible for the control of NPY gene expression in the kidney.

Immunoelectron microscopic localization of transforming growth factor alpha in rat colon

Transforming growth factor alpha (TGF alpha) is a polypeptide, which binds to the epidermal growth factor receptor to carry out its function related to cell proliferation and differentiation. The ultrastructural localisation of TGF alpha was studied in both the proximal and the distal colon. The columnar cells, lining the surface epithelium of the proximal colon, showed a strong immunoreactivity in the polyribosomes and in the interdigitations of the lateral membrane. The columnar cells of the crypts and the goblet cells in both the proximal and the distal colon showed the immunostaining in the cis and trans cisternae of the Golgi apparatus. TGF alpha seems to be processed differently in the surface columnar cells and in the crypt columnar cells and goblet cells. Moreover, it probably has different roles in proliferation and differentiation.

The t-SNAREs syntaxin 1 and SNAP-25 are present on organelles that participate in synaptic vesicle recycling

Syntaxin 1 and synaptosome-associated protein of 25 kD (SNAP-25) are neuronal plasmalemma proteins that appear to be essential for exocytosis of synaptic vesicles (SVs). Both proteins form a complex with synaptobrevin, an intrinsic membrane protein of SVs. This binding is thought to be responsible for vesicle docking and apparently precedes membrane fusion. According to the current concept, syntaxin 1 and SNAP-25 are members of larger protein families, collectively designated as target-SNAP receptors (t-SNAREs), whose specific localization to subcellular membranes define where transport vesicles bind and fuse. Here we demonstrate that major pools of syntaxin 1 and SNAP-25 recycle with SVs. Both proteins cofractionate with SVs and clathrin-coated vesicles upon subcellular fractionation. Using recombinant proteins as standards for quantitation, we found that syntaxin 1 and SNAP-25 each comprise approximately 3% of the total protein in highly purified SVs. Thus, both proteins are significant components of SVs although less abundant than synaptobrevin (8.7% of the total protein). Immunoisolation of vesicles using synaptophysin and syntaxin specific antibodies revealed that most SVs contain syntaxin 1. The widespread distribution of both syntaxin 1 and SNAP-25 on SVs was further confirmed by immunogold electron microscopy. Botulinum neurotoxin C1, a toxin that blocks exocytosis by proteolyzing syntaxin 1, preferentially cleaves vesicular syntaxin 1. We conclude that t-SNAREs participate in SV recycling in what may be functionally distinct forms.

The prediction of chemical reactivity from first principles: Collision and reaction dynamics

Aquest treball fa una revisió de mesures experimentals i càlculs teòrics sobre la dinàmica de col·lisions i reaccions moleculars. Els experiments se centren en col·lisions, a energies intermèdies, que involucren sistemes del tipus ió-àtom i iómolècula, per les quals es mesuren seccions eficaces totals, estat a estat, així com aquelles que discerneixen les diferents contribucions del moment angular d'espín. Els resultats obtinguts s'interpreten satisfactòriament en termes d'acoblaments no adiabàtics entre els diferents estats electrònics dels sistemes col·lisionants. Els càlculs teòrics utilitzen la metodologia quasiclàssica, així com metodologies mecanoquàntiques recentment desenvolupades, tant aproximades com exactes. S'han obtingut resultats totalment convergits per sistemes tipus, mentre que s'han analitzat, de manera detallada i extensiva, les característiques dinàmiques de sistemes triatòmic, tetraatòmic i pentaatòmic.

Midregional pro-atrial natriuretic peptide and procalcitonin improve survival prediction in VAP.

Ventilator-associated pneumonia (VAP) affects mortality, morbidity and cost of critical care. Reliable risk estimation might improve end-of-life decisions, resource allocation and outcome. Several scoring systems for survival prediction have been established and optimised over the last decades. Recently, new biomarkers have gained interest in the prognostic field. We assessed whether midregional pro-atrial natriuretic peptide (MR-proANP) and procalcitonin (PCT) improve the predictive value of the Simplified Acute Physiologic Score (SAPS) II and Sequential Related Organ Failure Assessment (SOFA) in VAP. Specified end-points of a prospective multinational trial including 101 patients with VAP were analysed. Death <28 days after VAP onset was the primary end-point. MR-proANP and PCT were elevated at the onset of VAP in nonsurvivors compared with survivors (p = 0.003 and p = 0.017, respectively) and their slope of decline differed significantly (p = 0.018 and p = 0.039, respectively). Patients with the highest MR-proANP quartile at VAP onset were at increased risk for death (log rank p = 0.013). In a logistic regression model, MR-proANP was identified as the best predictor of survival. Adding MR-proANP and PCT to SAPS II and SOFA improved their predictive properties (area under the curve 0.895 and 0.880). We conclude that the combination of two biomarkers, MR-proANP and PCT, improve survival prediction of clinical severity scores in VAP.

Comparative localization of glioma-reactive monoclonal antibodies in vivo in an athymic mouse human glioma xenograft model.

Radioiodinated murine monoclonal antibodies (Mabs) 81C6, Me 1-14, C12, D12, and E9, made against or reactive with human gliomas but not normal brain, and Mab UJ13A, a pan-neuroectodermal Mab reactive with normal human glial and neural cells, were evaluated in paired label studies in the D-54 MG subcutaneous human glioma xenograft model system in nude mice. Following intravenous injection in the tail vein of mice bearing 200-400 mm3 tumors, specific localization of Mabs to tumor over time (6 h-9 days) was evaluated by tissue counting; each Mab demonstrated a unique localization profile. The comparison of localization indices (LI), determined as a ratio of tissue level of Mab to control immunoglobulin with simultaneous correction for blood levels of each, showed Mabs 81C6 and Me 1-14 to steadily accumulate in glioma xenografts, maintaining LI from 5-20 at 7-9 days after Mab injection. Mab UJ13A peaked at day 1, maintaining this level through day 2, and declining thereafter. Mabs D12 and C12 peaked at days 3 and 4, respectively, and E9 maintained an LI of greater than 3 from days 3-9. Percent injected dose localized/g of tumor varied from a peak high of 16% (81C6) to a low of 5% (Me 1-14 and UJ13A). Immunoperoxidase histochemistry, performed with each Mab on a battery of primary human brain neoplasms, revealed that Mabs 81C6 and E9, which demonstrated the highest levels of percent injected dose localized/g of tumor over time, reacted with antigens expressed in the extracellular matrix. This finding suggests that extracellular matrix localization of antigen represents a biologically significant factor affecting localization and/or binding in the xenograft model used. The demonstration of significant localization, varied kinetics and patterns of localization of this localizing Mab panel warrants their continued investigation as potential imaging and therapeutic agents for human trials.