A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)²PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)²PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)²PCA to forecast the next day''s stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.     

Nitrogen acquisition, PEP carboxylase, and cellular pH homeostasis: new views on old paradigms

The classic biochemical pH-stat model of cytosolic pH regulation in plant cells presupposes a pH-dependent biosynthesis and degradation of organic acids, specifically malic acid, in the cytosol. This model has been used to explain the higher tissue accumulation of organic acids in nitrate (NO₃^–)-grown, relative to ammonium (NH₄⁺)-grown, plants, the result of proposed cytosolic alkalinization by NO₃^– metabolism, and acidification by NH₄⁺ metabolism. Here, a critical examination of the model shows that its key assumptions are fundamentally problematic, particularly in the context of the effects on cellular pH of nitrogen source differences. Specifically, the model fails to account for proton transport accompanying inorganic nitrogen transport, which, if considered, renders the H⁺ production of combined transport and assimilation (although not the accumulation) to be equal for NO₃^– and NH₄⁺ as externally provided N sources. We show that the model's evidentiary basis in total-tissue mineral ion and organic acid analysis is not directly relevant to subcellular (cytosolic) pH homeostasis, while the analysis of the ionic components of the cytosol is relevant to this process. A literature analysis further shows that the assumed greater activity of the enzyme phosphoenolpyruvate (PEP) carboxylase under nitrate nutrition, which is a key characteristic of the biochemical pH-stat model as it applies to nitrogen source, is not borne out in numerous instances. We conclude that this model is not tenable in its current state, and propose an alternative model that reaffirms the anaplerotic role of PEP carboxylase within the context of N nutrition, in the production of carbon skeletons for amino acid synthesis.     

Multiple pathway-based genetic variations associated with tobacco related multiple primary neoplasms

Background

In order to elucidate a combination of genetic alterations that drive tobacco carcinogenesis we have explored a unique model system and analytical method for an unbiased qualitative and quantitative assessment of gene-gene and gene-environment interactions. The objective of this case control study was to assess genetic predisposition in a biologically enriched clinical model system of tobacco related cancers (TRC), occurring as Multiple Primary Neoplasms (MPN).

Methods

Genotyping of 21 candidate Single Nucleotide Polymorphisms (SNP) from major metabolic pathways was performed in a cohort of 151 MPN cases and 210 cancer-free controls. Statistical analysis using logistic regression and Multifactor Dimensionality Reduction (MDR) analysis was performed for studying higher order interactions among various SNPs and tobacco habit.

Results

Increased risk association was observed for patients with at least one TRC in the upper aero digestive tract (UADT) for variations in SULT1A1 Arg²¹³His, mEH Tyr¹¹³His, hOGG1 Ser³²⁶Cys, XRCC1 Arg²⁸⁰His and BRCA2 Asn³⁷²His. Gene - environment interactions were assessed using MDR analysis. The overall best model by MDR was tobacco habit/p53(Arg/Arg)/XRCC1(Arg³⁹⁹His)/mEH(Tyr¹¹³His) that had highest Cross Validation Consistency (8.3) and test accuracy (0.69). This model also showed significant association using logistic regression analysis.

Conclusion

This is the first Indian study on a multipathway based approach to study genetic susceptibility to cancer in tobacco associated MPN. This approach could assist in planning additional studies for comprehensive understanding of tobacco carcinogenesis.     

Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking

We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized.We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters ^1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique ''HYPR'' spatial filter ⁸ that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on ¹¹C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model ⁷ to a conventional model ⁹. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.     

Transepithelial Na+ transport and the intracellular fluids: A computer study

Summary Computer simulations of tight epithelia under three experimental conditions have been carried out, using the rheogenic nonlinear model of Lew, Ferreira and Moura (Proc. Roy. Soc. London. B 206:53–83, 1979) based largely on the formulation of Koefoed-Johnsen and Ussing (Acta Physiol. Scand.42:298–308, 1958). First, analysis of the transition between the short-circuited and open-circuited states has indicated that (i) apical Cl^– permeability is a critical parameter requiring experimental definition in order to analyze cell volume regulation, and (ii) contrary to certain experimental reports, intracellular Na⁺ concentration (c _Na ^c ) is expected to be a strong function of transepithelial clamping voltage. Second, analysis of the effects of lowering serosal K⁺ concentration (c _K ^s ) indicates that the basic model cannot simulate several well-documented observations; these defects can be overcome, at least qualitatively, by modifying the model to take account of the negative feedback interaction likely to exist between the apical Na⁺ permeability andc _Na ^c . Third, analysis of the effects induced by lowering mucosal Na⁺ concentration (c _Na ^m ) strongly supports the concept that osmotically induced permeability changes in the apical intercellular junctions play a physiological role in conserving the body's stores of NaCl. The analyses also demonstrate that the importance of Na⁺ entry across the basolateral membrane is strongly dependent upon transepithelial potential,c _Na ^m andc _K ^s ; under certain conditions, net Na⁺ entry could be appreciably greater across the basolateral than across the apical membrane.     

The efficacy of 18F-FDG PET/CT-based diagnostic model in the diagnosis of colorectal cancer regional lymph node metastasis

In order to assess the efficacy of ¹⁸F-FDG PET/CT-based diagnostic model in diagnosing colorectal cancer (CRC) lymph node metastasis (LNM), the ¹⁸F-FDG PET/CT medical records of CRC patients were acquired, and the CRC regional LNM diagnostic model was constructed through the combination of image and grain factors of ¹⁸F-FDG PET/CT. The specific analysis methods include univariate analysis, multivariate analysis, ROC curve analysis, and statistical analysis. The research results showed statistical differences in TNM staging, intestinal obstructions, tumor infiltration, regional lymph node (LN) SUVmax, regional LN minimum dimension, and remote metastasis between the CRC patients in the LNM positive group and the LNM negative group. Through the comparisons between the diagnostic model proposed in the research and other diagnostic methods, it was found that the AUC (95%CI) and sensitivity of the proposed diagnostic model were the highest, the comprehensive diagnostic efficacy of the diagnostic model was optimal. Therefore, it was concluded that the diagnostic model was of significant application values, which provided the basis for subsequent clinical diagnosis of CRC.     

Biosorption of Cadmium from Aqueous Solution by Shell Dust of the Fresh Water Snail Melanoides tuberculata

ABSTRACT The metal bioadsorption potential of shell dust of the freshwater snail Melanoides tuberculata (MTSD) was evaluated under laboratory conditions using cadmium as a model metal. As bioadsorbent, MTSD exhibited a biosorption capacity of 27.03 mg g^?1 at pH 6, indicating potential to remove cadmium from aqueous solution. The adsorption data fit more to the Langmuir (R² = 0.998) equation than the Freundlich (R² = 0.761) equation at equilibrium condition. The kinetics of biosorption followed the pseudo-second-order model (R² = 0.999) better than the Lagergren model (R² = 0.676), as was evident from the regression analysis. The presence of calcium ions appears to have facilitated ion exchange with cadmium along with the binding of different functional groups, as revealed through Fourier transform infrared (FT-IR) analysis. It is apparent from these observations that MTSD can act as low-cost and efficient bioadsorbent for cadmium bioremediation from aquatic habitats. Use of the shells of M. tuberculata for metal biosorption will promote the utility of a waste material of biological origin for bioremediation of heavy metals such as cadmium.     

Caffeine-induced Ca2+ oscillations in type I horizontal cell of carp retina: A mathematical model

Oscillations in intracellular free Ca²⁺ concentration ([Ca²⁺]_i) have been observed in a variety of cell types. In the present study, we constructed a mathematical model to simulate the caffeine-induced [Ca²⁺]_i oscillations based on experimental data obtained from isolated type I horizontal cell of carp retina. The results of model analysis confirm the notion that the caffeine-induced [Ca²⁺]_i oscillations involve a number of cytoplasmic and endoplasmic Ca²⁺ processes that interact with each other. Using this model, we evaluated the importance of store-operated channel (SOC) in caffeine-induced [Ca²⁺]_i oscillations. The model suggests that store-operated Ca²⁺ entry (SOCE) is elicited upon depletion of the endoplasmic reticulum (ER). When the SOC conductance is set to 0, caffeine-induced [Ca²⁺]_i oscillations are abolished, which agrees with the experimental observation that [Ca²⁺]_i oscillations were abolished when SOC was blocked pharmacologically, verifying that SOC is necessary for sustained [Ca²⁺]_i oscillations.     

Caffeine-induced Ca2+ oscillations in type I horizontal cell of carp retina: A mathematical model

Oscillations in intracellular free Ca²⁺ concentration ([Ca²⁺]_i) have been observed in a variety of cell types. In the present study, we constructed a mathematical model to simulate the caffeine-induced [Ca²⁺]_i oscillations based on experimental data obtained from isolated type I horizontal cell of carp retina. The results of model analysis confirm the notion that the caffeine-induced [Ca²⁺]_i oscillations involve a number of cytoplasmic and endoplasmic Ca²⁺ processes that interact with each other. Using this model, we evaluated the importance of store-operated channel (SOC) in caffeine-induced [Ca²⁺]_i oscillations. The model suggests that store-operated Ca²⁺ entry (SOCE) is elicited upon depletion of the endoplasmic reticulum (ER). When the SOC conductance is set to 0, caffeine-induced [Ca²⁺]_i oscillations are abolished, which agrees with the experimental observation that [Ca²⁺]_i oscillations were abolished when SOC was blocked pharmacologically, verifying that SOC is necessary for sustained [Ca²⁺]_i oscillations.     

A mathematical model of adult GnRH neurons in mouse brain and its bifurcation analysis

GnRH neurons are hypothalamic neurons that secrete gonadotropin-releasing hormone (GnRH) which stimulates the release of gonadotropins, one of the crucial hormones for sexual development, fertility and maturation. A mathematical model was built to help elucidate the mechanisms underlying electrical bursting and synchronous [Ca²⁺] transients in GnRH neurons (Lee et al., 2010). The model predicted that bursting in GnRH neurons (at least of the short-bursting type) requires the existence of a [Ca²⁺]-dependent slow after-hyperpolarisation current (sI_AHP-UCL), and this predicted current was found experimentally. GnRH behaviour under a wide range of conditions (inhibition of Na⁺ channels, IP₃ receptors, [Ca²⁺]-dependent K⁺ channels, or Ca²⁺ pumps, or in the presence of zero extracellular [Ca²⁺]) is successfully reproduced by the model. In this paper, a simplified version of the previous model, with the same qualitative behaviour, is constructed and studied using timescale separation techniques and bifurcation analysis.     

Technical note: A linear model for predicting δ13Cprotein

Objective : Development of a model for the prediction of δ¹³C_protein from δ¹³C_collagen and Δ¹³C_ap‐co. Model‐generated values could, in turn, serve as “consumer” inputs for multisource mixture modeling of paleodiet. Methods : Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ¹³C_protein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ¹³C_co and Δ¹³C_ap‐co). Results : Regression analysis resulted in a two‐term linear model (δ¹³C_protein (%) = (0.78 × δ¹³C_co) ? (0.58× Δ¹³C_ap‐co) ? 4.7), possessing a high R‐value of 0.93 (r² = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ¹³C_protein. This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. Conclusions : The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. Am J Phys Anthropol 157:694–703, 2015. © 2015 Wiley Periodicals, Inc.     

A bidomain threshold model of propagating calcium waves

We present a bidomain fire-diffuse-fire model that facilitates mathematical analysis of propagating waves of elevated intracellular calcium (Ca²⁺) in living cells. Modeling Ca²⁺ release as a threshold process allows the explicit construction of traveling wave solutions to probe the dependence of Ca²⁺ wave speed on physiologically important parameters such as the threshold for Ca²⁺ release from the endoplasmic reticulum (ER) to the cytosol, the rate of Ca²⁺ resequestration from the cytosol to the ER, and the total [Ca²⁺] (cytosolic plus ER). Interestingly, linear stability analysis of the bidomain fire-diffuse-fire model predicts the onset of dynamic wave instabilities leading to the emergence of Ca²⁺ waves that propagate in a back-and-forth manner. Numerical simulations are used to confirm the presence of these so-called ‘tango waves’ and the dependence of Ca²⁺ wave speed on the total [Ca²⁺].      

Cross Species Genomic Analysis Identifies a Mouse Model as Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma

Undifferentiated pleomorphic sarcoma/Malignant Fibrous Histiocytoma (MFH) is one of the most common subtypes of human soft tissue sarcoma. Using cross species genomic analysis, we define a geneset from the LSL-Kras^G12D; Trp53^Flox/Flox mouse model of soft tissue sarcoma that is highly enriched in human MFH. With this mouse geneset as a filter, we identify expression of the RAS target FOXM1 in human MFH. Expression of Foxm1 is elevated in mouse sarcomas that metastasize to the lung and tissue microarray analysis of human MFH correlates overexpression of FOXM1 with metastasis. These results suggest that genomic alterations present in human MFH are conserved in the LSL-Kras^G12D; p53^Flox/Flox mouse model of soft tissue sarcoma and demonstrate the utility of this pre-clinical model.     

A Mathematical Model of the Pancreatic Ductal Epithelium

A mathematical model of the HCO⁻ ₃-secreting pancreatic ductal epithelium was developed using network thermodynamics. With a minimal set of assumptions, the model accurately reproduced the experimentally measured membrane potentials, voltage divider ratio, transepithelial resistance and short-circuit current of nonstimulated ducts that were microperfused and bathed with a CO₂/HCO⁻ ₃-free, HEPES-buffered solution, and also the intracellular pH of duct cells bathed in a CO₂/HCO⁻ ₃-buffered solution. The model also accurately simulated: (i) the effect of step changes in basolateral K⁺ concentration, and the effect of K⁺ channel blockers on basolateral membrane potential; (ii) the intracellular acidification caused by a Na⁺-free extracellular solution and the effect of amiloride on this acidification; and (iii) the intracellular alkalinization caused by a Cl⁻-free extracellular solution and the effect of DIDS on this alkalinization. In addition, the model predicted that the luminal Cl⁻ conductance plays a key role in controlling both the HCO⁻ ₃ secretory rate and intracellular pH during HCO⁻ ₃ secretion. We believe that the model will be helpful in the analysis of experimental data and improve our understanding of HCO⁻ ₃-transporting mechanisms in pancreatic duct cells. Received: 18 October 1995/Revised: 5 July 1996     

Spatio-temporal modelling of particulate matter concentrations using satellite derived aerosol optical depth over coastal region of Chennai in India

The present study primarily focuses on describing aerosol optical depth (AOD), its distribution pattern and seasonal variation, and modelling Particulate Matter Concentrations in Chennai. The frequency distribution of AOD and PM_2.5 demonstrates that AOD can be used as a proxy for estimating PM_2.5 in the study region as the occurrence of AOD almost resonates with that of PM_2.5. The seasonal variation of AOD and PM_2.5 revealed that during the winter (October–January) and summer (February–May) seasons, AOD reasonably followed the trend of PM_2.5. However, during the monsoon period, AOD showed random variations. Different models like linear and non-linear regression models and machine learning models such as random forest (RF) have been developed for PM_2.5 estimation. The model's performance in different stations and seasons has been assessed. The effect of meteorology and other factors in the model has also been assessed. From linear and non-linear model analysis, AOD was a significant parameter in estimating PM_2.5. The Random Forest model was the stable model for the study region, with a model R² of 0.53 and an RMSE of 15.89 μg/m³. The inclusion of meteorological parameters like relative humidity, wind speed, and wind direction decreased the error in prediction by 17.45 μg/m³. The seasonal and spatial analysis indicates that the prediction capability of models varies with stations and seasons. The best performing model was found to be Model RF, and the model could explain about 53.14% of the variability in PM_2.5 concentration occurrence in the study region with a prediction error of 15.89 μg/m³.     

Multiple timescale mixed bursting dynamics in a respiratory neuron model

Experimental results in rodent medullary slices containing the pre-Bötzinger complex (pre-BötC) have identified multiple bursting mechanisms based on persistent sodium current (I _NaP) and intracellular Ca²⁺. The classic two-timescale approach to the analysis of pre-BötC bursting treats the inactivation of I _NaP, the calcium concentration, as well as the Ca²⁺-dependent inactivation of IP ₃ as slow variables and considers other evolving quantities as fast variables. Based on its time course, however, it appears that a novel mixed bursting (MB) solution, observed both in recordings and in model pre-BötC neurons, involves at least three timescales. In this work, we consider a single-compartment model of a pre-BötC inspiratory neuron that can exhibit both I _NaP and Ca²⁺ oscillations and has the ability to produce MB solutions. We use methods of dynamical systems theory, such as phase plane analysis, fast-slow decomposition, and bifurcation analysis, to better understand the mechanisms underlying the MB solution pattern. Rather surprisingly, we discover that a third timescale is not actually required to generate mixed bursting solutions. Through our analysis of timescales, we also elucidate how the pre-BötC neuron model can be tuned to improve the robustness of the MB solution.     

Quantification of dead ectomycorrhizae from forest soils using computerized image analysis

A first-generation regression model is presented, describing a linear relationship between dead ectomycorrhizal biomass (mg dry weight) and mycorrhizal area in the xy-plane (mm²) (r²=0.996). This model enables reliable estimates of dead ectomycorrhizal biomass in soils through area measurements of mycorrhizae using computerized image analysis.     

From global to local: exploring the relationship between parameters and behaviors in models of electrical excitability

Models of electrical activity in excitable cells involve nonlinear interactions between many ionic currents. Changing parameters in these models can produce a variety of activity patterns with sometimes unexpected effects. Further more, introducing new currents will have different effects depending on the initial parameter set. In this study we combined global sampling of parameter space and local analysis of representative parameter sets in a pituitary cell model to understand the effects of adding K ⁺ conductances, which mediate some effects of hormone action on these cells. Global sampling ensured that the effects of introducing K ⁺ conductances were captured across a wide variety of contexts of model parameters. For each type of K ⁺ conductance we determined the types of behavioral transition that it evoked. Some transitions were counterintuitive, and may have been missed without the use of global sampling. In general, the wide range of transitions that occurred when the same current was applied to the model cell at different locations in parameter space highlight the challenge of making accurate model predictions in light of cell-to-cell heterogeneity. Finally, we used bifurcation analysis and fast/slow analysis to investigate why specific transitions occur in representative individual models. This approach relies on the use of a graphics processing unit (GPU) to quickly map parameter space to model behavior and identify parameter sets for further analysis. Acceleration with modern low-cost GPUs is particularly well suited to exploring the moderate-sized (5-20) parameter spaces of excitable cell and signaling models.     

Assessing the impact of substrate-level enzyme regulations limiting ethanol titer in Clostridium thermocellum using a core kinetic model

Clostridium thermocellum is a promising candidate for consolidated bioprocessing because it can directly ferment cellulose to ethanol. Despite significant efforts, achieved yields and titers fall below industrially relevant targets. This implies that there still exist unknown enzymatic, regulatory, and/or possibly thermodynamic bottlenecks that can throttle back metabolic flow. By (i) elucidating internal metabolic fluxes in wild-type C. thermocellum grown on cellobiose via ¹³C-metabolic flux analysis (¹³C-MFA), (ii) parameterizing a core kinetic model, and (iii) subsequently deploying an ensemble-docking workflow for discovering substrate-level regulations, this paper aims to reveal some of these factors and expand our knowledgebase governing C. thermocellum metabolism. Generated ¹³C labeling data were used with ¹³C-MFA to generate a wild-type flux distribution for the metabolic network. Notably, flux elucidation through MFA alluded to serine generation via the mercaptopyruvate pathway. Using the elucidated flux distributions in conjunction with batch fermentation process yield data for various mutant strains, we constructed a kinetic model of C. thermocellum core metabolism (i.e. k-ctherm138). Subsequently, we used the parameterized kinetic model to explore the effect of removing substrate-level regulations on ethanol yield and titer. Upon exploring all possible simultaneous (up to four) regulation removals we identified combinations that lead to many-fold model predicted improvement in ethanol titer. In addition, by coupling a systematic method for identifying putative competitive inhibitory mechanisms using K-FIT kinetic parameterization with the ensemble-docking workflow, we flagged 67 putative substrate-level inhibition mechanisms across central carbon metabolism supported by both kinetic formalism and docking analysis.     

The case for cytosolic NO3– heterostasis: a critique of a recently proposed model

A model recently proposed by Siddiqi & Glass (Plant, Cell, and Environment 25, 1211–1217, 2002) attempts to reconcile discrepancies in the measurement of cytosolic nitrate concentrations ([NO₃^–]_cyt) in plant root cells, specifically between low (～ 4 mm ) homeostatic values reported in studies using ion‐specific microelectrodes on the one hand, and wide fluctuations in [NO₃^–]_cyt reported in other studies, especially those using compartmental analysis by tracer efflux (CATE). Although Siddiqi & Glass concede that cytosolic NO₃^– homeostasis, as determined by microelectrodes, is at odds with certain experimental observations, they nevertheless promote a model that takes microelectrode readings at face value, and assert that the variations seen using CATE methodology are artefacts attributable to contributions from substantial, rapidly exchanging, and highly variable NO₃^– pools putatively residing in organelles such as plastids and the endoplasmic reticulum. We show here that such a model is not tenable, drawing upon experimental evidence from previous studies, and from a more comprehensive model that examines the characteristics and consequences of subcompartmented cytoplasmic exchange in root cells.