Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

A multifactorial histopathologic score for the prediction of prognosis of resected esophageal adenocarcinomas after neoadjuvant chemotherapy

BACKGROUND For esophageal adenocarcinoma treated with neoadjuvant chemotherapy, postoperative staging classifications initially developed for non-pretreated tumors may not accurately predict prognosis. We tested whether a multifactorial TNM-based histopathologic prognostic score (PRSC), which additionally applies to tumor regression, may improve estimation of prognosis compared with the current Union for International Cancer Control/American Joint Committee on Cancer (UICC) staging system. PATIENTS AND METHODS We evaluated esophageal adenocarcinoma specimens following cis/oxaliplatin-based therapy from two separate centers (center 1: n = 280; and center 2: n = 80). For the PRSC, each factor was assigned a value from 1 to 2 (ypT0-2 = 1 point; ypT3-4 = 2 points; ypN0 = 1 point; ypN1-3 = 2 points; ≤50 % residual tumor/tumor bed = 1 point; >50 % residual tumor/tumor bed = 2 points). The three-tiered PRSC was based on the sum value of these factors (group A: 3; group B: 4-5; group C: 6) and was correlated with patients' overall survival (OS). RESULTS The PRSC groups showed significant differences with respect to OS (p < 0.0001; hazard ratio [HR] 2.2 [95 % CI 1.7-2.8]), which could also be demonstrated in both cohorts separately (center 1 p < 0.0001; HR 2.48 [95 % CI 1.8-3.3] and center 2 p = 0.015; HR 1.7 [95 % CI 1.1-2.6]). Moreover, the PRSC showed a more accurate prognostic discrimination than the current UICC staging system (p < 0.0001; HR 1.15 [95 % CI 1.1-1.2]), and assessment of two goodness-of-fit criteria (Akaike Information Criterion and Schwarz Bayesian Information Criterion) clearly supported the superiority of PRSC over the UICC staging. CONCLUSION The proposed PRSC clearly identifies three subgroups with different outcomes and may be more helpful for guiding further therapeutic decisions than the UICC staging system.

Novel biomarkers for the prediction of metastasis in colorectal cancer

INTRODUCTION In patients with metastatic colorectal cancers, multimodal management and the use of biological agents such as monoclonal antibodies have had major positive effects on survival. The ability to predict which patients may be at 'high risk' of distant metastasis could have major implications on patient management. Histomorphological, immunohistochemical or molecular biomarkers are currently being investigated in order to test their potential value as predictors of metastasis. AREAS COVERED Here, the author reviews the clinical and functional data supporting the investigation of three novel promising biomarkers for the prediction of metastasis in patients with colorectal cancer: tumor budding, Raf1 kinase inhibitor protein (RKIP) and metastasis-associated in colon cancer-1 (MACC1). EXPERT OPINION The lifespan of most potential biomarkers is short as evidenced by the rare cases that have successfully made their way into daily practice such as KRAS or microsatellite instability (MSI) status. Although the three biomarkers reviewed herein have the potential to become important predictive biomarkers of metastasis, they have similar hurdles to overcome before they can be implemented into clinical management: standardization and validation in prospective patient cohorts.

Prediction of outcome in patients with low-grade squamous intraepithelial lesions by fluorescence in situ hybridization analysis of human papillomavirus, TERC, and MYC

BACKGROUND Cytology is an excellent method with which to diagnose preinvasive lesions of the uterine cervix, but it suffers from limited specificity for clinically significant lesions. Supplementary methods might predict the natural course of the detected lesions. The objective of the current study was to test whether a multicolor fluorescence in situ hybridization (FISH) assay might help to stratify abnormal results of Papanicolaou tests. METHODS A total of 219 liquid-based cytology specimens of low-grade squamous intraepithelial lesions (LSIL), 49 atypical squamous cells of undetermined significance (ASCUS) specimens, 52 high-grade squamous intraepithelial lesion (HSIL) specimens, and 50 normal samples were assessed by FISH with probes for the human papillomavirus (HPV), MYC, and telomerase RNA component (TERC). Subtyping of HPV by polymerase chain reaction (PCR) was performed in a subset of cases (n=206). RESULTS There was a significant correlation found between HPV detection by FISH and PCR (P<.0001). In patients with LSILs, the presence of HPV detected by FISH was significantly associated with disease progression (P<.0001). An increased MYC and/or TERC gene copy number (>2 signals in>10% of cells) prevailed in 43% of ASCUS specimens and was more frequent in HSIL (85%) than in LSIL (33%) (HSIL vs LSIL: P<.0001). Increased TERC gene copy number was significantly correlated with progression of LSIL (P<.01; odds ratio, 7.44; area under the receiver operating characteristic curve, 0.73; positive predictive value, 0.30; negative predictive value, 0.94) CONCLUSIONS: The detection of HPV by FISH analysis is feasible in liquid-based cytology and is significantly correlated with HPV analysis by PCR. The analysis of TERC gene copy number may be useful for risk stratification in patients with LSIL.

Prediction of the thermal release of transactinide elements (112 ≤ Z ≤ 116) from metals

Metallic catcher foils have been investigated on their thermal release capabilities for future superheavy element studies. These catcher materials shall serve as connection between production and chemical investigation of superheavy elements (SHE) at vacuum conditions. The diffusion constants and activation energies of diffusion have been extrapolated for various catcher materials using an atomic volume based model. Release rates can now be estimated for predefined experimental conditions using the determined diffusion values. The potential release behavior of the volatile SHE Cn (E112), E113, Fl (E114), E115, and Lv (E116) from polycrystalline, metallic foils of Ni, Y, Zr, Nb, Mo, Hf, Ta, and W is predicted. Example calculations showed that Zr is the best suited material in terms of on-line release efficiency and long-term operation stability. If higher temperatures up to 2773 K are applicable, tungsten is suggested to be the material of choice for such experiments.

Prediction of water–rock interaction and porosity evolution in a granitoid-hosted enhanced geothermal system, using constraints from the 5 km Basel-1 well

Numerical simulations based on plans for a deep geothermal system in Basel, Switzerland are used here to understand chemical processes that occur in an initially dry granitoid reservoir during hydraulic stimulation and long-term water circulation to extract heat. An important question regarding the sustainability of such enhanced geothermal systems (EGS), is whether water–rock reactions will eventually lead to clogging of flow paths in the reservoir and thereby reduce or even completely block fluid throughput. A reactive transport model allows the main chemical reactions to be predicted and the resulting evolution of porosity to be tracked over the expected 30-year operational lifetime of the system. The simulations show that injection of surface water to stimulate fracture permeability in the monzogranite reservoir at 190 °C and 5000 m depth induces redox reactions between the oxidised surface water and the reduced wall rock. Although new calcite, chlorite, hematite and other minerals precipitate near the injection well, their volumes are low and more than compensated by those of the dissolving wall-rock minerals. Thus, during stimulation, reduction of injectivity by mineral precipitation is unlikely. During the simulated long-term operation of the system, the main mineral reactions are the hydration and albitization of plagioclase, the alteration of hornblende to an assemblage of smectites and chlorites and of primary K-feldspar to muscovite and microcline. Within a closed-system doublet, the composition of the circulated fluid changes only slightly during its repeated passage through the reservoir, as the wall rock essentially undergoes isochemical recrystallization. Even after 30 years of circulation, the calculations show that porosity is reduced by only ∼0.2%, well below the expected fracture porosity induced by stimulation. This result suggests that permeability reduction owing to water–rock interaction is unlikely to jeopardize the long-term operation of deep, granitoid-hosted EGS systems. A peculiarity at Basel is the presence of anhydrite as fracture coatings at ∼5000 m depth. Simulated exposure of the circulating fluid to anhydrite induces a stronger redox disequilibrium in the reservoir, driving dissolution of ferrous minerals and precipitation of ferric smectites, hematite and pyrite. However, even in this scenario the porosity reduction is at most 0.5%, a value which is unproblematic for sustainable fluid circulation through the reservoir.

Prediction of Cranio-Maxilofacial Surgical Planning using an Inverse Soft Tissue Modelling Approach

In cranio-maxillofacial surgery, the determination of a proper surgical plan is an important step to attain a desired aesthetic facial profile and a complete denture closure. In the present paper, we propose an efficient modeling approach to predict the surgical planning on the basis of the desired facial appearance and optimal occlusion. To evaluate the proposed planning approach, the predicted osteotomy plan of six clinical cases that underwent CMF surgery were compared to the real clinical plan. Thereafter, simulated soft-tissue outcomes were compared using the predicted and real clinical plan. This preliminary retrospective comparison of both osteotomy planning and facial outlook shows a good agreement and thereby demonstrates the potential application of the proposed approach in cranio-maxillofacial surgical planning prediction.

Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms

OBJECTIVE Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion "cognitive disturbances" (COGDIS) is superior in predicting first-episode psychosis. METHOD In a naturalistic 48-month follow-up study, the conversion rate to first-episode psychosis was studied in 246 outpatients of an early detection of psychosis service (FETZ); thereby, the association between conversion, and the combined and singular use of UHR criteria and COGDIS was compared. RESULTS Patients that met UHR criteria and COGDIS (n=127) at baseline had a significantly higher risk of conversion (hr=0.66 at month 48) and a shorter time to conversion than patients that met only UHR criteria (n=37; hr=0.28) or only COGDIS (n=30; hr=0.23). Furthermore, the risk of conversion was higher for the combined criteria than for UHR criteria (n=164; hr=0.56 at month 48) and COGDIS (n=158; hr=0.56 at month 48) when considered irrespective of each other. CONCLUSIONS Our findings support the merits of considering both COGDIS and UHR criteria in the early detection of persons who are at high risk of developing a first psychotic episode within 48months. Applying both sets of criteria improves sensitivity and individual risk estimation, and may thereby support the development of stage-targeted interventions. Moreover, since the combined approach enables the identification of considerably more homogeneous at-risk samples, it should support both preventive and basic research.

PREDICTION OF DNA METHYLATION BASED ON GENOMIC ARCHITECTURE AND APPLICATIONS OF POSITIONAL WEIGHT MATRICES

Gene silencing due to epigenetic mechanisms shows evidence of significant contributions to cancer development. We hypothesis that the genetic architecture based on retrotransposon elements surrounding the transcription start site, plays an important role in the suppression and promotion of DNA methylation. In our investigation we found a high rate of SINE and LINEs retrotransposon elements near the transcription start site of unmethylated genes when compared to methylated genes. The presence of these elements were positively associated with promoter methylation, contrary to logical expectations, due to the malicious effects of retrotransposon elements which insert themselves randomly into the genome causing possible loss of gene function. In our genome wide analysis of human genes, results suggested that 22% of the genes in cancer were predicted to be methylation-prone; in cancer these genes are generally down-regulated and function in the development process. In summary, our investigation validated our hypothesis and showed that these widespread genomic elements in cancer are highly associated with promoter DNA methylation and may further participate in influencing epigenetic regulation.

Prediction of cardiovascular disease risk factors in Mexican-American children from parental risk factors, and social and demographic characteristics in the HHANES

Objectives. Cardiovascular disease (CVD) including CVD secondary to diabetes type II, a significant health problem among Mexican American populations, originates in early childhood. This study seeks to determine risk factors available to the health practitioner that can identify the child at potential risk of developing CVD, thereby enabling early intervention. ^ Design. This is a secondary analysis of cross-sectional data of matched Mexican American parents and children selected from the HHANES, 1982–1984. ^ Methods. Parents at high risk for CVD were identified based on medical history, and clinical and physical findings. Factor analysis was performed on children's skinfold thicknesses, height, weight, and systolic and diastolic blood pressures, in order to produce a limited number of uncorrelated child CVD risk factors. Multiple regression analyses were then performed to determine other CVD markers associated with these Factors, independently for mothers and fathers. ^ Results. Factor analysis of children's measurements revealed three uncorrelated latent variables summarizing the children's CVD risk: Factor1: ‘Fatness’, Factor2: ‘Size and Maturity’, and Factor3: ‘Blood Pressure’, together accounting for the bulk of variation in children's measurements (86–89%). Univariate analyses showed that children from high CVD risk families did not differ from children of low risk families in occurrence of high blood pressure, overweight, biological maturity, acculturation score, or social and economic indicators. However, multiple regression using the factor scores (from factor analysis) as dependent variables, revealed that higher CVD risk in parents, was significantly associated with increased fatness and increased blood pressure in the children. Father's CVD risk status was associated with higher levels of body fat in his children and higher levels of blood pressure in sons. Mother's CVD risk status was associated with higher blood pressure levels in children, and occurrence of obesity in the mother associated with higher fatness levels in her children. ^ Conclusion. Occurrence of cardiovascular disease and its risk factors in parents of Mexican American children, may be used to identify children at potentially higher risk for developing CV disease in the future. Obesity in mothers appears to be an important marker for the development of higher levels of body fatness in children. ^

Applications of random set theory in econometrics

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.