Employment Protection and Productivity: Evidence from firm-level panel data in Japan

Recent developments in the literature on employment protection legislation (EPL) have revealed that changing the stringency of employment protection can lead to extensive consequences outside of the labour market, by affecting firms' production decisions or workers' commitment levels. This paper provides the first empirical evaluation of the comprehensive effect of restrictions on firing employees in Japan, by exploiting the variations in court decisions. We find that judgments lenient to workers significantly reduce firms' total-factor productivity growth rate. The effect on capital is mixed and inconclusive, although we obtain modest evidence that an increase in firing costs induces a negative scale effect on capital inputs.

Does Employment Protection Reduce Productivity?: An analysis using Basic Survey of Japanese Business Structure and Activities microdata (Japanese)

The purpose of this paper is to examine the impact on firm-level productivity of Japan's regulatory restrictions on the dismissal of employees. First, with regard to the route through which restrictions on employee dismissal affect firm-level productivity we set out hypotheses indicated by economic theory, and we then use firm-level microdata to conduct an empirical analysis of the impact on firm-level productivity of Japan's regulatory restrictions on employee dismissal. From the results of this analysis we learn that companies' total factor productivity growth is significantly lower when there is a relatively high cumulative number of court rulings voiding employee dismissals. In addition, although we do not observe that the stiffening of restrictions on dismissals stimulates the substitution of labor by capital inputs, it is clear that there is a significant overall lowering of labor productivity. The effect of employment protection for specific workers does not remain solely at the level of the labor market, and by exerting a negative impact on firm-level productivity it impacts the entire economy.

Pulmonary function after segmentectomy for small peripheral carcinoma of the lung

AbstractObjective: The aim of this study is to compare the pulmonary function after a segmentectomy with that after a lobectomy for small peripheral carcinoma of the lung. Patients And Methods: Between 1993 and 1996, segmentectomy and lobectomy were performed on 48 and 133 good-risk patients, respectively. Lymph node metastases were detected after the operation in 6 and 24 patients of the segmentectomy and lobectomy groups, respectively. For bias reduction in comparison with a nonrandomized control group, we paired 40 segmentectomy patients with 40 lobectomy patients using nearest available matching method on the estimated propensity score. Results: Twelve months after the operation, the segmentectomy and lobectomy groups had forced vital capacities of 2.67 ± 0.73 L (mean ± standard deviation) and 2.57 ± 0.59 L, which were calculated to be 94.9% ± 10.6% and 91.0% ± 13.2% of the preoperative values (P = .14), respectively. The segmentectomy and lobectomy groups had postoperative 1-second forced expiratory volumes of 1.99 ± 0.63 L and 1.95 ± 0.49 L, which were calculated to be 93.3% ± 10.3% and 87.3% ± 14.0% of the preoperative values, respectively (P = .03). The multiple linear regression analysis showed that the alternative of segmentectomy or lobectomy was not a determinant for postoperative forced vital capacity but did affect postoperative 1-second forced expiratory volume. Conclusion: Pulmonary function after a segmentectomy for a good-risk patient is slightly better than that after a lobectomy. However, segmentectomy should be still the surgical procedure for only poor-risk patients because of the difficulty in excluding patients with metastatic lymph nodes from the candidates for the procedure. (J Thorac Cardiovasc Surg 1999;118:536-41

Usefulness of fluorine-18 fluorodeoxyglucose-positron emission tomography in management strategy for thymic epithelial tumors

Background: This study investigated the usefulness of fluorine-18 fluorodeoxyglucose-positron emission tomography (FDG-PET) during the treatment of thymic epithelial tumors in combination with Ki-67 evaluation based on surgical cases in our department. Methods: Between November 2003 and May 2011, 39 patients with thymic epithelial tumor underwent preoperative FDG-PET. The maximum standardized uptake value (SUVmax) of each category within Masaoka stage, World Health Organization classification, tumor diameter, myasthenia gravis, and Ki-67 label index were compared. To examine risk factors for relapse, SUVmax, age, sex, and surgical radicality were investigated in addition to those items. Results: The mean SUVmax was 4.5 (range, 1.2 to 14.6) and was significantly higher for Masaoka stage IV than for I and II (all p < 0.008) and for World Health Organization classified thymic cancer compared with all other types (all p < 0.0001). Mean SUVmax revealed significantly higher values for large tumors than for small tumors (p = 0.02). Mean SUVmax was significantly higher for high Ki-67-positive samples (p = 0.0004), indicating a strong correlation between SUVmax and the Ki-67 label index (ρ = 0.77, p = 0.0001). SUVmax accurately reflected therapeutic efficacy in patients with induction therapy. Univariate analysis revealed Masaoka stages III and IV and pathologically incomplete resection as risk factors for relapse. On multivariate analysis, independent risk factors for relapse comprised only Masaoka stages III and IV. Conclusions: FDG-PET SUVmax does reflect proliferation and invasiveness of thymic epithelial tumors and can provide an index for diagnosis and treatment, although it is not a risk factor for relapse. FDG-PET is also useful for evaluating induction therapy efficacy and detecting relapse. © 2013 The Society of Thoracic Surgeons

Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data

Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA biomarkers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk prediction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction, and with further improvement may contribute to practical clinical use in dementia

Use of Non-Amplified RNA Samples for Microarray Analysis of Gene Expression

Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC) project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer

Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data

Mini-EUSO is a wide-angle fluorescence telescope that registers ultraviolet (UV) radiation in the nocturnal atmosphere of Earth from the International Space Station. Meteors are among multiple phenomena that manifest themselves not only in the visible range but also in the UV. We present two simple artificial neural networks that allow for recognizing meteor signals in the Mini-EUSO data with high accuracy in terms of a binary classification problem. We expect that similar architectures can be effectively used for signal recognition in other fluorescence telescopes, regardless of the nature of the signal. Due to their simplicity, the networks can be implemented in onboard electronics of future orbital or balloon experiments.Comment: 15 page