Eigenvector spatial filtering (ESF) is a spatial modeling approach, which has been applied in urban and regional studies, ecological studies, and so on. However, it is computationally demanding, and ...may not be suitable for large data modeling. The objective of this study is developing fast ESF and random effects ESF (RE‐ESF), which are capable of handling very large samples. To achieve it, we accelerate eigen‐decomposition and parameter estimation, which make ESF and RE‐ESF slow. The former is accelerated by utilizing the Nyström extension, whereas the latter is by small matrix tricks. The resulting fast ESF and fast RE‐ESF are compared with nonapproximated ESF and RE‐ESF in Monte Carlo simulation experiments. The result shows that, while ESF and RE‐ESF are slow for several thousand samples, fast ESF and RE‐ESF require only several seconds for the samples. It is also suggested that the proposed approaches effectively remove positive spatial dependence in the residuals with very small approximation errors when the number of eigenvectors considered is 200 or more. Note that these approaches cannot deal with negative spatial dependence. The proposed approaches are implemented in an R package “spmoran.”
In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and ...computational efficiency. Especially, due to an identification problem, Poisson regression can be unstable for small samples with many zeros. Provided this, we develop a closed-form inference for an over-dispersed Poisson regression including Poisson additive mixed models. The approach is derived via mode-based log-Gaussian approximation. The resulting method is fast, practical, and free from the identification problem. Monte Carlo experiments demonstrate that the estimation error of the proposed method is a considerably smaller estimation error than the closed-form alternatives and as small as the usual Poisson regressions. For counts with many zeros, our approximation has better estimation accuracy than conventional Poisson regression. We obtained similar results in the case of Poisson additive mixed modeling considering spatial or group effects. The developed method was applied for analyzing COVID-19 data in Japan. This result suggests that influences of pedestrian density, age, and other factors on the number of cases change over periods.
This study discusses the importance of balancing spatial and non‐spatial variation in spatial regression modeling. Unlike spatially varying coefficients (SVC) modeling, which is popular in spatial ...statistics, non‐spatially varying coefficients (NVC) modeling has largely been unexplored in spatial fields. Nevertheless, as we will explain, consideration of non‐spatial variation is needed not only to improve model accuracy but also to reduce spurious correlation among varying coefficients, which is a major problem in SVC modeling. We consider a Moran eigenvector approach modeling spatially and non‐spatially varying coefficients (S&NVC). A Monte Carlo simulation experiment comparing our S&NVC model with existing SVC models suggests both modeling accuracy and computational efficiency for our approach. Beyond that, somewhat surprisingly, our approach identifies true and spurious correlations among coefficients nearly perfectly, even when usual SVC models suffer from severe spurious correlations. It implies that S&NVC model should be used even when the analysis purpose is modeling SVCs. Finally, our S&NVC model is employed to analyze a residential land price data set. Its results suggest existence of both spatial and non‐spatial variation in regression coefficients in practice. The S&NVC model is now implemented in the R package spmoran.
Background & Aims The use of esophageal endoscopic submucosal dissection (ESD) to remove superficial esophageal neoplasms is gradually becoming more common in Japan. However, large-scale esophageal ...ESD often requires subsequent multiple balloon dilations to prevent postoperative esophageal stricture. We investigated the safety and efficacy of endoscopic transplantation of tissue-engineered autologous oral mucosal epithelial cell sheets in preventing formation of strictures after ESD. Methods We performed an open-label, single-arm, single-institute study. We collected specimens of oral mucosal tissue from 9 patients with superficial esophageal neoplasms. Epithelial cell sheets were fabricated ex vivo by culturing isolated cells for 16 days on temperature-responsive cell culture surfaces. After a reduction in temperature, these sheets were endoscopically transplanted directly to the ulcer surfaces of patients who had just undergone ESD. All patients were monitored by endoscopy once a week until epithelialization was complete. Results Autologous cell sheets were successfully transplanted to ulcer surfaces using an endoscope. Complete re-epithelialization occurred within a median time of 3.5 weeks. No patients experienced dysphagia, stricture, or other complications following the procedure, except for one patient who had a full circumferential ulceration that expanded to the esophagogastric junction. Conclusions Sutureless, endoscopic transplantation of carrier-free cell sheets composed of autologous oral mucosal epithelial cells safely and effectively promotes re-epithelialization of the esophagus after ESD. Patients in this study did not experience any serious complications. This procedure might be used to prevent stricture formation following ESD and improve patients' quality of life. Further study will be needed to show that stricture formation can be prevented.
While spatially varying coefficient (SVC) modeling is popular in applied science, its computational burden is substantial. This is especially true if a multiscale property of SVC is considered. Given ...this background, this study develops a Moran’s eigenvector-based spatially varying coefficients (M-SVC) modeling approach that estimates multiscale SVCs computationally efficiently. This estimation is accelerated through a (i) rank reduction, (ii) pre-compression, and (iii) sequential likelihood maximization. Steps (i) and (ii) eliminate the sample size N from the likelihood function; after these steps, the likelihood maximization cost is independent of N. Step (iii) further accelerates the likelihood maximization so that multiscale SVCs can be estimated even if the number of SVCs, K, is large. The M-SVC approach is compared with geographically weighted regression (GWR) through Monte Carlo simulation experiments. These simulation results show that our approach is far faster than GWR when N is large, despite numerically estimating 2K parameters while GWR numerically estimates only 1 parameter. Then, the proposed approach is applied to a land price analysis as an illustration. The developed SVC estimation approach is implemented in the R package “spmoran.”
The recent emergence of antibiotic-resistant bacteria requires the development of new antibiotics or new agents capable of enhancing antibiotic activity. This study evaluated the antibacterial ...activity of lysozyme-chitosan oligosaccharide conjugates (LYZOX) against Pseudomonas aeruginosa, Acinetobacter baumannii and methicillin-resistant Staphylococcus aureus (MRSA), which should resolve the problem of antibiotic-resistant bacteria. Bactericidal tests showed that LYZOX killed 50% more P. aeruginosa (NBRC 13275), A. baumannii and MRSA than the control treatment after 60 min. In addition, LYZOX was shown to inhibit the growth of P. aeruginosa (NBRC 13275 and PAO1), A. baumannii and MRSA better than its components. To elucidate the antibacterial mechanism of LYZOX, we performed cell membrane integrity assays, N-phenyl-1-naphthylamine assays, 2-nitrophenyl β-D-galactopyranoside assays and confocal laser scanning microscopy. These results showed that LYZOX affected bacterial cell walls and increased the permeability of the outer membrane and the plasma membrane. Furthermore, each type of bacteria treated with LYZOX was observed by electron microscopy. Electron micrographs revealed that these bacteria had the morphological features of both lysozyme-treated and chitosan oligosaccharide-treated bacteria and that LYZOX destroyed bacterial cell walls, which caused the release of intracellular contents from cells. An acquired drug resistance test revealed that these bacteria were not able to acquire resistance to LYZOX. The hemolytic toxicity test demonstrated the low hemolytic activity of LYZOX. In conclusion, LYZOX exhibited antibacterial activity and low drug resistance in the presence of P. aeruginosa, A. baumannii and MRSA and showed low hemolytic toxicity. LYZOX affected bacterial membranes, leading to membrane disruption and the release of intracellular contents and consequent bacterial cell death. LYZOX may serve as a novel candidate drug that could be used for the control of refractory infections.
Background and aims
The withdrawal of antithrombotic therapy from patients at high risk of thromboembolism is controversial. Previously, treatment with anticoagulants, such as warfarin and ...dabigatran, was recommended for heparin bridge therapy (HBT) during endoscopic submucosal dissection (ESD). However, HBT is associated with a high risk of bleeding during and after ESD. This study aimed to investigate the clinical outcomes of colorectal ESD in patients treated with warfarin and direct oral anticoagulants (DOAC).
Methods
This study included 412 patients with superficial colorectal neoplasms that were resected by ESD between June 2010 and June 2018. The patients were classified into two groups: without antithrombotics (
n
= 286) and with anticoagulants (
n
= 51). The anticoagulants group was further divided into two groups: warfarin (
n
= 26) and DOAC (
n
= 25).
Results
Among all patients, delayed bleeding occurred in 35 (8.5% 35/412) patients. The bleeding rate in the anticoagulants group (11.8% 6/51) was higher than that in the group without antithrombotics (6.6% 19/286), but the difference was not statistically significant (
P
= 0.240). The bleeding rate in the DOAC group (16.0% 4/25) was higher than that in the warfarin group (7.7% 2/26), but the difference was not statistically significant (
P
= 0.419). All delayed bleeding was successfully managed with endoscopic hemostasis. Thromboembolic events were not observed in any patients.
Conclusions
The bleeding rate with anticoagulants was relatively high. However, all bleeding events with anticoagulants were minor and clinically controllable. Colorectal ESD with DOAC and warfarin may be feasible and acceptable.
Objectives We examined the neointimal characteristics of bare-metal stents (BMS) in extended late phase by the use of optical coherence tomography (OCT). Background The long-term neointimal features ...after BMS implantation have not yet been fully characterized. Methods Intracoronary OCT observation of BMS segments was performed during the early phase (<6 months, n = 20) and late phase (≥5 years, n = 21) after implantation. Internal tissue of the BMS was categorized into normal neointima, characterized by a signal-rich band without signal attenuation, or lipid-leaden intima, with marked signal attenuation and a diffuse border. In addition, the presence of disrupted intima and thrombus was evaluated. Neovascularization was defined as small vesicular or tubular structures, and the location of the microvessels was classified into peristent or intraintima. Results Normal neointima proliferated homogeneously, and lipid-laden intima was not observed in the early phase. In the late phase, lipid-laden intima, intimal disruption, and thrombus frequently were found in comparison with the early phase (67% vs. 0%, 38% vs. 0%, and 52% vs. 5%, respectively; p < 0.05). Peristent neovascularization demonstrated a similar incidence between the 2 phases. The appearance of intraintima neovascularization was more prevalent in the late phase than the early phase (62% vs. 0%, respectively; p < 0.01) and in segments with lipid-laden intima than in nonlipidic segments (79% vs. 29%, respectively; p = 0.026). Conclusions This OCT study suggests that neointima within the BMS often transforms into lipid-laden tissue during an extended period of time and that expansion of neovascularization from peristent to intraintima contributes to atherosclerotic progression of neointima.
Preoperative ctDNA status in relation to recurrence in cases of CRC remains unclear. We examined preoperative ctDNA detection by targeting KRAS gene mutations as a predictive marker for recurrence ...after CRC surgery. We measured the preoperative KRAS mutated ctDNA status and analyzed the correlation with clinicopathologic features of 180 patients that underwent surgery for CRC. We studied the association between preoperative KRAS mutated ctDNA and postoperative recurrence in patients (n = 150) that underwent radical surgery. KRAS mutated ctDNA was detected in 59 patients (32.8%). Median mutant allele frequency of KRAS in ctDNA was 0.20%. KRAS status in ctDNA and lymph node metastasis and distant metastasis were not significantly different. Among patients that underwent radical resection, recurrence occurred in 21 (14.0%, median follow-up 24 months). In Kaplan-Meier analysis, preoperative detection of KRAS mutated ctDNA was associated with inferior recurrence-free interval (RFI) (p = 0.002) and recurrence-free survival (RFS) (p = 0.025). In a multivariate Cox proportional hazards model, preoperative detection of KRAS mutated ctDNA was an independent factor related to both RFI (HR = 3.08; p = 0.012) and RFS (HR = 2.18; p = 0.044). Preoperative measurement of KRAS mutated ctDNA could be useful to decide postoperative treatment.
Although spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study is to show that ...capturing the "spatial scale" of each data relationship is crucially important to make SVC modeling more stable and, in doing so, adds flexibility. Here, the analytical properties of six SVC models are summarized in terms of their characterization of scale. Models are examined through a series of Monte Carlo simulation experiments to assess the extent to which spatial scale influences model stability and the accuracy of their SVC estimates. The following models are studied: (1) geographically weighted regression (GWR) with a fixed distance or (2) an adaptive distance bandwidth (GWRa); (3) flexible bandwidth GWR (FB-GWR) with fixed distance or (4) adaptive distance bandwidths (FB-GWRa); (5) eigenvector spatial filtering (ESF); and (6) random effects ESF (RE-ESF). Results reveal that the SVC models designed to capture scale dependencies in local relationships (FB-GWR, FB-GWRa, and RE-ESF) most accurately estimate the simulated SVCs, where RE-ESF is the most computationally efficient. Conversely, GWR and ESF, where SVC estimates are naïvely assumed to operate at the same spatial scale for each relationship, perform poorly. Results also confirm that the adaptive bandwidth GWR models (GWRa and FB-GWRa) are superior to their fixed bandwidth counterparts (GWR and FB-GWR). Key Words: flexible bandwidth geographically weighted regression, Monte Carlo simulation, nonstationarity, random effects eigenvector spatial filtering, spatial scale.
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