Macroeconomic Impact of Population Aging in Japan: A Perspective from an Overlapping Generations Model

Due to a sharp decline in the fertility rate and a rapid increase in longevity, Japan's population aging is the furthest advanced in the world. In this study we explore the macroeconomic impact of population aging using a full-fledged overlapping generations model. Our model replicates well the time paths of Japan’s macroeconomic variables from the 1980s to the 2000s and yields future paths for these variables over a long horizon. We find that Japan’s population aging as a whole adversely affects GNP growth by dampening factor inputs. It also negatively impacts on GNP per capita, especially in the future, mainly due to the decline in the fraction of the population of working-age. For these findings, fertility rate decline plays a dominant role as it reduces both labor force and saver populations. The effects of increased longevity are expansionary, but relatively minor. Our simulations predict that the adverse effects will expand during the next few decades. In addition to closed economy simulations, we examine the consequences of population aging in a small open economy setting. In this case a decline in the domestic capital return encourages investment in foreign capital, mitigating the adverse effects of population aging on GNP

Image Synthesis-based Late Stage Cancer Augmentation and Semi-Supervised Segmentation for MRI Rectal Cancer Staging

Rectal cancer is one of the most common diseases and a major cause of mortality. For deciding rectal cancer treatment plans, T-staging is important. However, evaluating the index from preoperative MRI images requires high radiologists' skill and experience. Therefore, the aim of this study is to segment the mesorectum, rectum, and rectal cancer region so that the system can predict T-stage from segmentation results. Generally, shortage of large and diverse dataset and high quality annotation are known to be the bottlenecks in computer aided diagnostics development. Regarding rectal cancer, advanced cancer images are very rare, and per-pixel annotation requires high radiologists' skill and time. Therefore, it is not feasible to collect comprehensive disease patterns in a training dataset. To tackle this, we propose two kinds of approaches of image synthesis-based late stage cancer augmentation and semi-supervised learning which is designed for T-stage prediction. In the image synthesis data augmentation approach, we generated advanced cancer images from labels. The real cancer labels were deformed to resemble advanced cancer labels by artificial cancer progress simulation. Next, we introduce a T-staging loss which enables us to train segmentation models from per-image T-stage labels. The loss works to keep inclusion/invasion relationships between rectum and cancer region consistent to the ground truth T-stage. The verification tests show that the proposed method obtains the best sensitivity (0.76) and specificity (0.80) in distinguishing between over T3 stage and underT2. In the ablation studies, our semi-supervised learning approach with the T-staging loss improved specificity by 0.13. Adding the image synthesis-based data augmentation improved the DICE score of invasion cancer area by 0.08 from baseline.Comment: 10 pages, 7 figures, Accepted to Data Augmentation, Labeling, and Imperfections (DALI) at MICCAI 202

Preliminary results of phase I trial of oral uracil/tegafur (UFT), leucovorin plus irinotecan and radiation therapy for patients with locally recurrent rectal cancer

BACKGROUND: Surgical attempts for locally recurrent rectal cancer often fail due to local re-recurrence and distant metastasis. Preoperative chemoradiation may enhance better local control and survival. The aim of this study was to assess the safety of oral uracil and tegafur (UFT) plus leucovorin (LV), and irinotecan combined with radiation and determine the maximum-tolerated dose (MTD) and dose limiting toxicity (DLT) of the triple drug regimen. PATIENTS AND METHODS: Patients with locally recurrent rectal cancer received escalating doses of irinotecan on days 1, 8, 15, and 22 (starting at 30 mg/m(2), with 10 mg increments between consecutive cohorts) and fixed doses of UFT (300 mg/m(2)) plus LV (75 mg/day) on days 3 to 7, 10 to 14, 17 to 21, and 24 to 28. Radiation was given 5 days per week totaling 40 to 50 Gy (2Gy/day). RESULTS: Six patients were treated at the starting dose, and 2 received the full scheduled chemoradiotherapy. The other 4 patients had grade 3 diarrhea and diarrhea was the DLT. One patient had partial response and he had subsequently radical surgical resection. Median progression free survival for local recurrence was 320 days. CONCLUSION: Irinotecan plus UFT/LV with concomitant radiotherapy in patients with locally recurrent rectal cancer was not feasible due to diarrhea in this setting. Modification of the treatment is needed

The unreasonable effectiveness of AI CADe polyp detectors to generalize to new countries

$\textbf{Background and aims}$: Artificial Intelligence (AI) Computer-Aided Detection (CADe) is commonly used for polyp detection, but data seen in clinical settings can differ from model training. Few studies evaluate how well CADe detectors perform on colonoscopies from countries not seen during training, and none are able to evaluate performance without collecting expensive and time-intensive labels. $\textbf{Methods}$: We trained a CADe polyp detector on Israeli colonoscopy videos (5004 videos, 1106 hours) and evaluated on Japanese videos (354 videos, 128 hours) by measuring the True Positive Rate (TPR) versus false alarms per minute (FAPM). We introduce a colonoscopy dissimilarity measure called "MAsked mediCal Embedding Distance" (MACE) to quantify differences between colonoscopies, without labels. We evaluated CADe on all Japan videos and on those with the highest MACE. $\textbf{Results}$: MACE correctly quantifies that narrow-band imaging (NBI) and chromoendoscopy (CE) frames are less similar to Israel data than Japan whitelight (bootstrapped z-test, |z| > 690, p < $10^{-8}$ for both). Despite differences in the data, CADe performance on Japan colonoscopies was non-inferior to Israel ones without additional training (TPR at 0.5 FAPM: 0.957 and 0.972 for Israel and Japan; TPR at 1.0 FAPM: 0.972 and 0.989 for Israel and Japan; superiority test t > 45.2, p < $10^{-8}$). Despite not being trained on NBI or CE, TPR on those subsets were non-inferior to Japan overall (non-inferiority test t > 47.3, p < $10^{-8}$, $\delta$ = 1.5% for both). $\textbf{Conclusion}$: Differences that prevent CADe detectors from performing well in non-medical settings do not degrade the performance of our AI CADe polyp detector when applied to data from a new country. MACE can help medical AI models internationalize by identifying the most "dissimilar" data on which to evaluate models

Metabolic system alterations in pancreatic cancer patient serum: potential for early detection

BACKGROUND: The prognosis of pancreatic cancer (PC) is one of the poorest among all cancers, due largely to the lack of methods for screening and early detection. New biomarkers for identifying high-risk or early-stage subjects could significantly impact PC mortality. The goal of this study was to find metabolic biomarkers associated with PC by using a comprehensive metabolomics technology to compare serum profiles of PC patients to healthy control subjects. METHODS: A non-targeted metabolomics approach based on high-resolution, flow-injection Fourier transform ion cyclotron resonance mass spectrometry (FI-FTICR-MS) was used to generate comprehensive metabolomic profiles containing 2478 accurate mass measurements from the serum of Japanese PC patients (n=40) and disease-free subjects (n=50). Targeted flow-injection tandem mass spectrometry (FI-MS/MS) assays for specific metabolic systems were developed and used to validate the FI-FTICR-MS results. A FI-MS/MS assay for the most discriminating metabolite discovered by FI-FTICR-MS (PC-594) was further validated in two USA Caucasian populations; one comprised 14 PCs, six intraductal papillary mucinous neoplasims (IPMN) and 40 controls, and a second comprised 1000 reference subjects aged 30 to 80, which was used to create a distribution of PC-594 levels among the general population. RESULTS: FI-FTICR-MS metabolomic analysis showed significant reductions in the serum levels of metabolites belonging to five systems in PC patients compared to controls (all p<0.000025). The metabolic systems included 36-carbon ultra long-chain fatty acids, multiple choline-related systems including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins, as well as vinyl ether-containing plasmalogen ethanolamines. ROC-AUCs based on FI-MS/MS of selected markers from each system ranged between 0.93 ±0.03 and 0.97 ±0.02. No significant correlations between any of the systems and disease-stage, gender, or treatment were observed. Biomarker PC-594 (an ultra long-chain fatty acid), was further validated using an independently-collected US Caucasian population (blinded analysis, n=60, p=9.9E-14, AUC=0.97 ±0.02). PC-594 levels across 1000 reference subjects showed an inverse correlation with age, resulting in a drop in the AUC from 0.99 ±0.01 to 0.90 ±0.02 for subjects aged 30 to 80, respectively. A PC-594 test positivity rate of 5.0% in low-risk reference subjects resulted in a PC sensitivity of 87% and a significant improvement in net clinical benefit based on decision curve analysis. CONCLUSIONS: The serum metabolome of PC patients is significantly altered. The utility of serum metabolite biomarkers, particularly PC-594, for identifying subjects with elevated risk of PC should be further investigated

Neoadjuvant chemotherapy with docetaxel, nedaplatin, and fluorouracil for resectable esophageal cancer : A phase II study

Cisplatin plus 5‐fluorouracil is regarded as standard neoadjuvant chemotherapy for esophageal squamous cell carcinoma (ESCC) in Japan, but the prognosis remains poor. We have previously described how definitive chemoradiotherapy with docetaxel, nedaplatin, and 5‐fluorouracil (DNF) led to a very high response rate and promising survival times. We therefore undertook a phase II trial to evaluate the feasibility and efficacy of neoadjuvant DNF. The study included patients with clinical stage Ib‐III ESCC. Chemotherapy consisted of i.v. docetaxel (30 mg/m2) and nedaplatin (50 mg/m2) on days 1 and 8, and a continuous infusion of 5‐fluorouracil (400 mg/m2/day) on days 1‐5 and 8‐12, every 3 weeks. After three courses of chemotherapy, esophagectomy was carried out. The primary end‐point was the completion rate of the protocol treatment. Twenty‐eight patients were enrolled (cStage Ib/II/III, 2/3/23) and all received at least two cycles of chemotherapy. Twenty‐five patients underwent surgery, all of whom achieved an R0 resection, leading to a completion rate of 89.3%. The overall response rate was 87.0%. A pathological complete response was confirmed in eight (32.0%) cases. Grade 3/4 adverse events included leukopenia (32.1%), neutropenia (39.3%), febrile neutropenia (10.7%), thrombocytopenia (10.7%), and diarrhea (14.3%), but were manageable. Treatment‐related deaths and major surgical complications did not occur. Estimated 2‐year progression‐free and overall survival rates were 70.4% and 77.2%, respectively. Thus, DNF therapy was well tolerated and deemed feasible, with a strong tumor response in a neoadjuvant setting for ESCC. This trial is registered with the University Hospital Medical Information Network (UMIN ID: 000014305)