Self-organized network design by link survivals and shortcuts

One of the challenges for future infrastructures is how to design a network with high efficiency and strong connectivity at low cost. We propose self-organized geographical networks beyond the vulnerable scale-free structure found in many real systems. The networks with spatially concentrated nodes emerge through link survival and path reinforcement on routing flows in a wireless environment with a constant transmission range of a node. In particular, we show that adding some shortcuts induces both the small-world effect and a significant improvement of the robustness to the same level as in the optimal bimodal networks. Such a simple universal mechanism will open prospective ways for several applications in wide-area ad hoc networks, smart grids, and urban planning.Comment: 15 pages, 8 figures, 2 table

Study for Efficient Management of Disaster Response Personnel and Activities

特集2 安全な都市基盤の再生のために(ICUS

Phase II study of combined chemotherapy with irinotecan and S-1 (IRIS) plus bevacizumab in patients with inoperable recurrent or advanced colorectal cancer

Background. In Japan, a study comparing the effectiveness and safety of irinotecan plus S-1 (IRIS) with those of a combination of 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) as second-line treatment in patients with advanced or recurrent colorectal cancer demonstrated that IRIS was non-inferior to FOLFIRI. We previously reported that IRIS is also effective as first-line treatment. Patients and Methods. Eligibility criteria included inoperable recurrent colorectal cancer with a confirmed diagnosis of adenocarcinoma, age ≥ 20 years, and no history of prior chemotherapy. S-1 (40-60 mg twice daily) was given orally on days 1 to 14, and irinotecan (100 mg/m2) and bevacizumab (5 mg/kg) were given intravenously on days 1 and 15 of a 28-day cycle. The primary endpoint was safety. The secondary endpoints included overall response (OR), progression-free survival (PFS), and overall survival (OS). Results. A total of 52 eligible patients were enrolled from October 2007 through March 2009. In safety analysis, the incidences of grade 3 or 4 adverse reactions were as follows: neutropenia, 27%; hypertension, 21%; and diarrhea, 17%. The overall response rate was 57.7%. Median progression-free survival was 16.7 months. Conclusion. IRIS plus bevacizumab is a well-tolerated, highly effective chemotherapeutic regimen that is easy to administer

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the potential to enhance cancer screening while also providing quantitative, objective, and highly reproducible testing. However, constructing high-accuracy deep learning models necessitates a significant amount of manually labeled data, which takes time. To address this issue, we used the Noisy Student Training technique to create a binary classification deep learning model for cervical cytology screening, which reduces the quantity of labeled data necessary. We used 140 whole-slide images from liquid-based cytology specimens, 50 of which were low-grade squamous intraepithelial lesions, 50 were high-grade squamous intraepithelial lesions, and 40 were negative samples. We extracted 56,996 images from the slides and then used them to train and test the model. We trained the EfficientNet using 2,600 manually labeled images to generate additional pseudo labels for the unlabeled data and then self-trained it within a student-teacher framework. Based on the presence or absence of abnormal cells, the created model was used to classify the images as normal or abnormal. The Grad-CAM approach was used to visualize the image components that contributed to the classification. The model achieved an area under the curve of 0.908, accuracy of 0.873, and F1-score of 0.833 with our test data. We also explored the optimal confidence threshold score and optimal augmentation approaches for low-magnification images. Our model efficiently classified normal and abnormal images at low magnification with high reliability, making it a promising screening tool for cervical cytology

Green tea extracts ameliorate high-fat diet-induced muscle atrophy in senescence-accelerated mouse prone-8 mice.

Muscle atrophy (loss of skeletal muscle mass) causes progressive deterioration of skeletal function. Recently, excessive intake of fats was suggested to induce insulin resistance, followed by muscle atrophy. Green tea extracts (GTEs), which contain polyphenols such as epigallocatechin gallate, have beneficial effects on obesity, hyperglycemia, and insulin resistance, but their effects against muscle atrophy are still unclear. Here, we found that GTEs prevented high-fat (HF) diet-induced muscle weight loss in senescence-accelerated mouse prone-8 (SAMP8), a murine model of senescence. SAMP8 mice were fed a control diet, an HF diet, or HF with 0.5% GTEs (HFGT) diet for 4 months. The HF diet induced muscle weight loss with aging (measured as quadriceps muscle weight), whereas GTEs prevented this loss. In HF diet-fed mice, blood glucose and plasma insulin concentrations increased in comparison with the control group, and these mice had insulin resistance as determined by homeostasis model assessment of insulin resistance (HOMA-IR). In these mice, serum concentrations of leukocyte cell-derived chemotaxin 2 (LECT2), which is known to induce insulin resistance in skeletal muscle, were elevated, and insulin signaling in muscle, as determined by the phosphorylation levels of Akt and p70 S6 kinases, tended to be decreased. In HFGT diet-fed mice, these signs of insulin resistance and elevation of serum LECT2 were not observed. Although our study did not directly show the effect of serum LECT2 on muscle weight, insulin resistance examined using HOMA-IR indicated an intervention effect of serum LECT2 on muscle weight, as revealed by partial correlation analysis. Accordingly, GTEs might have beneficial effects on age-related and HF diet-induced muscle weight loss, which correlates with insulin resistance and is accompanied by a change in serum LECT2

Green Tea Extracts Attenuate Brain Dysfunction in High-Fat-Diet-Fed SAMP8 Mice

Unhealthy diet promotes progression of metabolic disorders and brain dysfunction with aging. Green tea extracts (GTEs) have various beneficial effects and alleviate metabolic disorders. GTEs have neuroprotective effects in rodent models, but their effects against brain dysfunction in models of aging fed unhealthy diets are still unclear. Here, we showed that GTEs attenuate high-fat (HF) diet-induced brain dysfunction in senescence-accelerated mouse prone-8 (SAMP8), a murine model of senescence. SAMP8 mice were fed a control diet, HF diet, or HF diet with 0.5% GTEs (HFGT) for four months. The HF diet reduced memory retention and induced amyloid β1–42 accumulation, whereas GTEs attenuated these changes. In HF diet-fed mice, lipid oxidative stress, assessed by malondialdehyde levels, was increased. The levels of proteins that promote synaptic plasticity, such as brain-derived neurotrophic factor (BDNF) and postsynaptic density protein 95 (PSD95), were reduced. These alterations related to brain dysfunction were not observed in HFGT diet-fed mice. Overall, our data suggest that GTEs intake might attenuate brain dysfunction in HF diet-fed SAMP8 mice by protecting synaptic plasticity as well as via anti-oxidative effects. In conclusion, GTEs might ameliorate unhealthy diet-induced brain dysfunction that develops with aging