Ciclos económicos y variables monetarias y financieras en México, 1980-2019: un enfoque de cambio estructural

El objetivo de este documento es analizar la relación entre el ciclo económico y diversas variables monetarias y financieras con el fin de determinar si han sido estables en el tiempo, teniendo en cuenta los efectos de las modificaciones en las condiciones económicas generales, la estrategia específica adoptada de política monetaria en diferentes subperiodos y las condiciones institucionales en que esta se maneja. Para probar la estabilidad de estas relaciones, una vez que se obtienen los indicadores del ciclo mediante los filtros convencionales, se emplea la metodología de cambio estructural de Bai y Perron (1998). Los resultados destacan dos cambios estructurales en la relación entre el indicador del ciclo y las variables de inflación, tasa de interés, tipo de cambio nominal y agregados monetarios nominales, uno a mediados de los años ochenta y el otro a mediados de los noventa. Abstract This paper aims to analyze the relationship between the business cycle and various monetary and financial variables. In particular, the paper seeks to determine whether this relationship has been stable over time, considering the effects of the changes in the general economic conditions, the specific monetary policy strategy adopted in different subperiods, and the institutional framework in which this is managed. To test the stability of these relationships, once the cycle indicators are obtained using conventional filters, the structural change methodology of Bai and Perron (1998) is used. The results highlight two structural changes in the relationship between the cycle indicator and inflation, interest rate, nominal exchange rate, and nominal monetary aggregates, one in the mid-eighties and the other in the middle of the nineties.

Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany

This paper introduces a Business Cycle Indicator to compile a transparent and reliable chronology of past business cycle turning points for Germany. The Indicator is derived applying the statistical method of Principal Component Analysis, based on information from 20 economic time series. In this way, the Business Cycle Indicator grasps the development of the broader economic activity and has several advantages over a business cycle assessment based on quarterly series of Gross Domestic Product.

A constitutively expressed fluorescence ubiquitin cell cycle indicator (FUCCI) in axolotls for studying tissue regeneration

Regulation of cell cycle progression is essential for cell proliferation during regeneration following injury. After appendage amputation, the axolotl (Ambystoma mexicanum) regenerates missing structures through an accumulation of proliferating cells known as the blastema. To study cell division during blastema growth, we generated a transgenic line of axolotls that ubiquitously expresses a bicistronic version of the Fluorescent Ubiquitination-based Cell Cycle Indicator (FUCCI). We demonstrate near-ubiquitous expression of FUCCI expression in developing and adult tissues and validate these expression patterns with DNA synthesis and mitosis phase markers. We demonstrate the utility of FUCCI for live and whole-mount imaging, showing the predominantly local contribution of cells during limb and tail regeneration. We also show that spinal cord amputation results in increased proliferation at least 5 mm from the injury. Finally, we use multimodal staining to provide cell type information for cycling cells by combining fluorescence in-situ hybridization, EdU click-chemistry, and immunohistochemistry on a single FUCCI tissue section. This new line of animals will be useful for studying cell cycle dynamics using in-situ endpoint assays and in-vivo imaging in developing and regenerating animals.

Rapid initiation of cell cycle reentry processes protects neurons from amyloid-β toxicity

Neurons are postmitotic cells. Reactivation of the cell cycle by neurons has been reported in Alzheimer’s disease (AD) brains and models. This gave rise to the hypothesis that reentering the cell cycle renders neurons vulnerable and thus contributes to AD pathogenesis. Here, we use the fluorescent ubiquitination-based cell cycle indicator (FUCCI) technology to monitor the cell cycle in live neurons. We found transient, self-limited cell cycle reentry activity in naive neurons, suggesting that their postmitotic state is a dynamic process. Furthermore, we observed a diverse response to oligomeric amyloid-β (oAβ) challenge; neurons without cell cycle reentry activity would undergo cell death without activating the FUCCI reporter, while neurons undergoing cell cycle reentry activity at the time of the oAβ challenge could maintain and increase FUCCI reporter signal and evade cell death. Accordingly, we observed marked neuronal FUCCI positivity in the brains of human mutant Aβ precursor protein transgenic (APP23) mice together with increased neuronal expression of the endogenous cell cycle control protein geminin in the brains of 3-mo-old APP23 mice and human AD brains. Taken together, our data challenge the current view on cell cycle in neurons and AD, suggesting that pathways active during early cell cycle reentry in neurons protect from Aβ toxicity.

Construction of an Industry Cycle Indicator for Profitability Prediction Analysis of Aggregate Firms in Bangladesh

Purpose of this study: In the aggregate industrial sector, government intervention to influence demand within the economy is generally counterproductive, while the optimal policy is to concentrate on supply-side reforms that help the economy become efficient. The objective of this study was to construct a unique industry cycle indicator for Bangladeshi aggregate firms within this industrial sector. The specific objectives were to assemble a unique industry cycle indicator which recommends early signals of a firm’s industrial vulnerability, identify industry cycle indicator turning points and evaluate the predictive performance of the industry. The industry cycle indicator model demonstrates the macroeconomic fluctuations in the industrial sector. Methodology: The industry cycle indicator was constructed following the approach of the Conference Board (2000). The result wasthen tested for robustness with a macro-stress test. Lagged independent variables were used in this study to allow early predictions by the ICI for the year in which the financial crisis happened. Main Findings: The industry cycle indicator model underplays the role of aggregate industrial efficiency in influencing the economic cycle. By forecasting directional changes, this leading indicator allows policymakers to be made aware of revolutions in the financial industry and to undertake early precautionary steps to prevent vulnerability. Here, the constructed industry cycle indicator demonstrates a remarkable lead time of around 6 months for predictions and outperforms by the leading against the reference series. Research Limitations/Implications: The industry cycle indicator model rejects the Keynesian approach and also rejects monetarism. It tends to be associated with neo-classical economics. The ICI generally assumes that shocks to productivity lead to economic fluctuations. In other words, a temporary fall in output is an inevitable consequence of a drop in productivity within the industrial sector. It also leads to adjustments to this new equilibrium and enables resources to discover more productive uses. Novelty/Originality: This research demonstrates that enhanced knowledge of components of the macro-prudential policy framework combined with the existence of a certain degree of standardisation of the macro-prudential tools and indicators is essential. This can significantly develop the capability of the financial markets supervisory authorities to forecast systemic risk and to avoid or reduce the consequences of industrial crises. The present study reflects a situation for upcoming researchers who intend to study and develop their interests in this area.

CD15 and CD15s expression is associated with G1 phase of the cell cycle in glioma cell lines

Overexpression of the tetrasaccharide carbohydrate epitopes, CD15 and CD15s are associated with non-central nervous system malignancies. While CD15 and CD15s expression is rare in gliomas, recent reports suggest that CD15 may serve as a marker for brain tumour ‘stem-like’ cells. The aim of this study was to determine if this apparent discrepancy may, in part, be explained by temporal expression of CD15 and CD15s at different phases of the cell cycle. We used flow cytometry, immunocytochemistry and a fluorescence cell cycle indicator (FUCCI) system to examine expression in glioblastoma (GBM) cells (UP-007 and SNB-19) and non-neoplastic astrocytes (SC-1800) synchronised via serum starvation, Hydroxyurea and Nocodazole, respectively. CD15 and CD15s expression was significantly increased in glioma cells synchronised to G1 phase compared with non-synchronised cells (p<0.001). This was supported by qualitative results obtained with the (FUCCI) system. Few studies have considered the possibility of cell-cycle dependent CD15 and CD15s expression which may explain the inconsistencies reported in the literature in terms of expression in ‘glioma stem-like cells’ where cells are more likely in S phase where CD15 and CD15s expression would be low.

Two new coral fluorescent proteins of distinct colors for sharp visualization of cell-cycle progression

We cloned and characterized two new coral fluorescent proteins: h2-3 and 1-41. h2-3 formed an obligate dimeric complex and exhibited bright fluorescence. On the other hand, 1-41 formed a highly multimeric complex and exhibited dim red fluorescence. We engineered 1-41 into AzaleaB5, a practically useful red-emitting fluorescent protein for cellular labeling applications. We fused h2-3 and AzaleaB5 to the ubiquitination domains of human Geminin and Cdt1, respectively, to generate a new color variant of Fucci (Fluorescent Ubiquitination-based Cell-Cycle Indicator): Fucci5. We found Fucci5 provided brighter nuclear labeling for monitoring cell cycle progression than the 1st and 2nd generations that used mAG/mKO2 and mVenus/mCherry, respectively.