How to tell causes from effects: Kant’s causal theory of time and modern approaches

I attempt a reconstruction of Kant’s version of the causal theory of time that makes it appear coherent. Two problems are at issue. The first concerns Kant’s reference to reciprocal causal influence for characterizing simultaneity. This approach is criticized by pointing out that Kant’s procedure involves simultaneous counterdirected processes—which seems to run into circularity. The problem can be defused by drawing on instantaneous processes such as the propagation of gravitation in Newtonian mechanics. Another charge of circularity against Kant’s causal theory was leveled by Schopenhauer. His objection was that Kant’s approach is invalidated by the failure to deliver non-temporal criteria for distinguishing between causes and effects. I try to show that the modern causal account has made important progress toward a successful resolution of this difficulty. The fork asymmetry, as based on Reichenbach’s principle of the common cause, provides a means for the distinction between cause and effect that is not based on temporal order (if some preconditions are realized).     

Conceptual approaches to avian navigation systems

Summary The general basis of migratory orientation in birds is most probably an endogenous time-and-direction program. Directions are selected with respect to celestial and geomagnetic clues. Using these clues, a bird may reach a large population-specific area; however, it will hardly be able to find a particular location, for instance its previous breeding site. Homing to a familiar site over several hundred kilometres of unfamiliar terrain appears to be based on the smelling of atmospheric trace compounds. Conceptual approaches to the mechanism of olfactory navigation have as yet only reached an early state of speculation.     

Chemical approaches to intermediates of enzyme catalysis

Zusammenfassung Die Untersuchung von Enzymsubstratkomplexen auf katalyse-induzierte Änderungen der chemischen Reaktivität hat sich als ein aufschlussreicher experimenteller Zugang zum Mechanismus enzymatischer Reaktionen erwiesen. Ternäre Systeme bestehend aus Enzym, Substrat und einem geeigneten Reagens (Tetranitromethan=TNM) sind auf katalyse-abhängige Reaktionen geprüft worden, die nur im vollständigen System, jedoch nicht mit Reagens und Enzym allein oder Reagens und Substrat allein beobachtet werden. Untersuchungen mit Aldolasen und Aspartat-Aminotransferase haben ergeben, dass katalyseinduzierte Reaktivität sowohl auf dem Substrat-als auch auf dem Enzymteil eines Enzym-Substratkomplexes nachgewiesen werden kann.Im Reaktionsmechanismus von Muskelaldolase (eine Lysinaldolase) und von Hefealdolase (eine Metallaldolase) lässt sich mit TNM ein intermediäres Carbanion des Substrats nachweisen. Die TNM-carbanion-Reaktion lässt sich spektralphotometrisch verfolgen und ist benutzt worden, um carboxypeptidase-behandelte Muskelaldolase und den Effekt von Cofaktoren auf die Hefealdolase zu untersuchen.Katalyse-induzierte Reaktivitätsveränderungen einer Enzymseitenkette sind bei der Aspartat-Aminotransferase beobachtet worden. Ein essentieller Tyrosylrest, der in der Abwesenheit von Substrat nicht mit TNM reagiert, wird ungewöhnlich reaktiv im Laufe der Katalyse und ermöglicht dabei seine selektive Nitrierung.Die katalyse-synchrone oder synkatalytische Aktivierung dieses Aminosäurerests scheint ein integraler Bestandteil des katalytischen Mechanismus von Aspartat-Aminotransferase zu sein und wird vermutlich durch katalyse-induzierte Konformationsänderungen des Enzym-Coenzym-Substratkomplexes hervorgebracht. Mögliche funktioneile Zusammenhänge synkatalytischer Reaktivitätsänderungen funktioneller Gruppen mit der Konformationsflexibilität des Enzymproteins und dem Vorkommen metastabiler Zwischenprodukte in der Enzymkatalyse werden diskutiert.     

Multi-model approaches to phylogenetics: Implications for idealization

Phylogenetic models traditionally represent the history of life as having a strictly-branching tree structure. However, it is becoming increasingly clear that the history of life is often not strictly-branching; lateral gene transfer, endosymbiosis, and hybridization, for example, can all produce lateral branching events. There is thus motivation to allow phylogenetic models to have a reticulate structure. One proposal involves the reconciliation of genealogical discordance. Briefly, this method uses patterns of disagreement – discordance – between trees of different genes to add lateral branching events to phylogenetic trees of taxa, and to estimate the most likely cause of these events. I use this practice to argue for: (1) a need for expanded accounts of multiple-models idealization, (2) a distinction between automatic and manual de-idealization, and (3) recognition that idealization may serve the meso-level aims of science in a different way than hitherto acknowledged.     

On the forecasting of high-frequency financial time series based on ARIMA model improved by deep learning

Through empirical research, it is found that the traditional autoregressive integrated moving average (ARIMA) model has a large deviation for the forecasting of high-frequency financial time series. With the improvement in storage capacity and computing power of high-frequency financial time series, this paper combines the traditional ARIMA model with the deep learning model to forecast high-frequency financial time series. It not only preserves the theoretical basis of the traditional model and characterizes the linear relationship, but also can characterize the nonlinear relationship of the error term according to the deep learning model. The empirical study of Monte Carlo numerical simulation and CSI 300 index in China show that, compared with ARIMA, support vector machine (SVM), long short-term memory (LSTM) and ARIMA-SVM models, the improved ARIMA model based on LSTM not only improves the forecasting accuracy of the single ARIMA model in both fitting and forecasting, but also reduces the computational complexity of only a single deep learning model. The improved ARIMA model based on deep learning not only enriches the models for the forecasting of time series, but also provides effective tools for high-frequency strategy design to reduce the investment risks of stock index.     

Experimental approaches to study functional recovery following cerebral ischemia

Valid experimental models and behavioral tests are indispensable for the development of therapies for stroke. The translational failure with neuroprotective drugs has forced us to look for alternative approaches. Restorative therapies aiming to facilitate the recovery process by pharmacotherapy or cell-based therapy have emerged as promising options. Here we describe the most common stroke models used in cell-based therapy studies with particular emphasis on their inherent complications, which may affect behavioral outcome. Loss of body weight, stress, hyperthermia, immunodepression, and infections particularly after severe transient middle cerebral artery occlusion (filament model) are recognized as possible confounders to impair performance in certain behavioral tasks and bias the treatment effects. Inherent limitations of stroke models should be carefully considered when planning experiments to ensure translation of behavioral data to the clinic.     

Novel approaches to the treatment of small-cell lung cancer

Small-cell lung cancer (SCLC) is characterized by its initial responsiveness to chemotherapy and the appearance of early metastases. Although combination chemotherapy, in some instances together with radiation, has improved the prognosis of this disease, in most patients SCLC ultimately recurs in a drug-resistant form. Several new strategies for the eradication of SCLC are being explored at the preclinical level. The identification of selective target molecules on the surface of SCLC cells, together with the progress made in antibody engineering, have provided new generations of antibodies and immunoconjugates as well as growth factor antagonists and inhibitors. In addition, recent advances in understanding the biology of SCLC have stimulated new investigations searching to counter the molecular basis underlying the increased proliferation and the apoptosis deficiency of SCLC cells. This can be achieved using antisense oligodeoxynucleotides that repress the expression of growth factor receptors and anti-apoptosis genes, or by gene replacement to compensate for the loss or inactivation of tumor suppressor genes.     

Systems microscopy approaches to understand cancer cell migration and metastasis

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration.     

A Helmholtzian approach to space and time

A slight modification of Helmholtz’s metrical approach to the foundations of geometry leads to the locally Euclidian character of space without restriction of the curvature. A bolder generalization involving time measurement leads to the locally Minkowskian character of spacetime. Some philosophical consequences of these results are drawn.     

Human body temperature and new approaches to constructing temperature-sensitive bacterial vaccines

Many of the live human and animal vaccines that are currently in use are attenuated by virtue of their temperature-sensitive (TS) replication. These vaccines are able to function because they can take advantage of sites in mammalian bodies that are cooler than the core temperature, where TS vaccines fail to replicate. In this article, we discuss the distribution of temperature in the human body, and relate how the temperature differential can be exploited for designing and using TS vaccines. We also examine how one of the coolest organs of the body, the skin, contains antigen-processing cells that can be targeted to provoke the desired immune response from a TS vaccine. We describe traditional approaches to making TS vaccines, and highlight new information and technologies that are being used to create a new generation of engineered TS vaccines. We pay particular attention to the recently described technology of substituting essential genes from Arctic bacteria for their homologues in mammalian pathogens as a way of creating TS vaccines.     

Molecular and engineering approaches to regenerate and repair teeth in mammals

Continuous replacement of teeth throughout the lifespan of an individual is possibly basal for most of the vertebrates including fish and reptiles; however, mammals generally have a limited capacity of tooth renewal. The ability to induce cellular differentiation in adults to replace lost or damaged cells in mammals, or to tissue-engineer organs in vitro, has hence become one of the major goals of regenerative medicine. In this article, we will revisit some of the important signals and tissue interactions that regulate mammalian tooth development, and will offer a synopsis of the latest progress in tooth regeneration and repair via molecular and engineering approaches. It is hoped that this article will not only offer an overview of recent technologies in tooth regeneration and repair but will also stimulate more interdisciplinary research in this field to turn the pursuit of tooth regeneration and repair into practical reality.     

Technical approaches to induce selective cell death of pluripotent stem cells

Despite the recent promising results of clinical trials using human pluripotent stem cell (hPSC)-based cell therapies for age-related macular degeneration (AMD), the risk of teratoma formation resulting from residual undifferentiated hPSCs remains a serious and critical hurdle for broader clinical implementation. To mitigate the tumorigenic risk of hPSC-based cell therapy, a variety of approaches have been examined to ablate the undifferentiated hPSCs based on the unique molecular properties of hPSCs. In the present review, we offer a brief overview of recent attempts at selective elimination of undifferentiated hPSCs to decrease the risk of teratoma formation in hPSC-based cell therapy.     

Bushfire rate-of-spread forecasting: Deterministic and statistical approaches to fire modelling

The three basic modelling approaches used to explain forest fire behaviour are theoretically, laboratory or empirically based. Results of all three approaches are reviewed, but it is noted that only the laboratory- and empirically based models have led to forecasting techniques that are in widespread use. These are the Rothermel model and the McArthur meters, respectively. Field tests designed to test the performance of these operational models were carried out in tropical grasslands. A preliminary analysis indicated that the Rothermel model overpredicted spread rates while the McArthur model underpredicted. To improve the forecast of bushfire rate of spread available to operational firefighting crews it is suggested that a time-variable parameter (TYP) recursive least squares algorithm can be used to assign weights to the respective models, with the weights recursively updated as information on fire-front location becomes available. Results of this methodology when applied to US Grasslands fire experiment data indicate that the quality of the input combined with a priori knowledge of the performance of the candidate models plays an important role in the performance of the TVP algorithm. With high-quality input data, the Rothermel model on its own outperformed the TVP algorithm, but with slightly inferior data both approaches were comparable. Though the use of all available data in a multiple linear regression produces a lower sum of squared errors than the recursive, time-variable weighting approach, or that of any single model, the uncertainties of data input and consequent changes in weighting coefficients during operational conditions suggest the use of the TVP algorithm approach.     

Biochemical approaches to the study of plant-fungal interactions in arbuscular mycorrhiza

This communication compares some biochemical methods for quantifying colonization by arbuscular mycorrhizal (AM) fungi. The degree of mycorrhizal colonization can conveniently be measured by determining fungal specific sterols. AM-colonized plants show a specific synthesis of 24-methylene cholesterol and an enhanced level of campesterol (=24-methyl cholesterol). A gene probe for nitrate reductase, the key enzyme for nitrogen assimilation, has been developed, which allows the monitoring of the distribution of this enzyme in fungi. Among the phytohormones tested, only abscisic acid (ABA) is found at a considerably higher level in AM-colonized plants than in controls. The concentration of ABA is about twenty times higher in spores and hyphae of the AM fungusGlomus than in maize roots. Other phytohormones (auxins, cytokinins) do not show such alterations after mycorrhizal colonization. The roots of gramineous plants become yellow as a result of mycorrhizal colonization. The yellow pigment(s) formed is (are) deposited in larger quantities in the vacuole(s) of the root parenchyma and endodermis cells during the development of the gramineous plants. A substance isolated from such roots has now been identified as a C-14 carotenoid with two carboxylic groups, and named mycorradicin.