Cannabidiol mitigates radiation-induced intestine ferroptosis via facilitating the heterodimerization of RUNX3 with CBFß thereby promoting transactivation of GPX4.

Radiation enteritis remains a major challenge for radiotherapy against abdominal and pelvic malignancies. Nevertheless, there is no approved effective therapy to alleviate irradiation (IR)-induced gastrointestinal (GI) toxicity. In the current study, Cannabidiol (CBD) was found to mitigate intestinal injury by GPX4-mediated ferroptosis resistance upon IR exposure. RNA-sequencing was employed to investigate the underlying mechanism involved in the radio-protective effect of CBD, wherein runt-related transcription factor 3 (RUNX3) and its target genes were changed significantly. Further experiment showed that the transactivation of GPX4 triggered by the direct binding of RUNX3 to its promoter region, or by stimulating the transcriptional activity of NF-κB via RUNX3-mediated LILRB3 upregulation was critical for the anti-ferroptotic effect of CBD upon IR injury. Specially, CBD was demonstrated to be a molecular glue skeleton facilitating the heterodimerization of RUNX3 with its transcriptional chaperone core-biding factor ß (CBFß) thereby promoting their nuclear localization and the subsequent transactivation of GPX4 and LILRB3. In short, our study provides an alternative strategy to counteract IR-induced enteritis during the radiotherapy on abdominal/pelvic neoplasms.

Evaluating the accuracy of a new robotically assisted system in cadaveric total knee arthroplasty procedures.

BACKGROUND: Robot-assisted total knee arthroplasty (TKA) has been shown to facilitate high-precision bone resection, which is an important goal in TKA. The aim of this cadaveric study was to analyze the accuracy of the target angle and bone resection thickness of a recently introduced robotic TKA system. METHODS: This study used 4 frozen cadaveric specimens (8 knees), 2 different implant designs, navigation, and a robotic system. The 4 surgeons who participated in this study were trained and familiar with the basic principles and operating procedures of this system. The angle of the bone cuts performed using the robotic system was compared with the target angles from the intraoperative plan. For each bone cut, the resection thickness was recorded and compared with the planned resection thickness. RESULTS: The mean angular difference for all specimens was less than 1°, and the standard deviation was less than 2°. The mean difference between the planned and measured angles was close to 0 and not significantly different from 0 except for the difference in the frontal tibial component angle, which was 0.88°. The mean difference in the hip-knee-ankle axis angle was - 0.21°± 1.06°. The mean bone resection difference for all specimens was less than 1 mm, and the standard deviation was less than 0.5 mm. CONCLUSIONS: The results of the cadaveric experimental study showed that the new TKA system can realize highly accurate bone cuts and achieve planned angles and resection thicknesses. Despite the limitations of small sample sizes and large differences between cadaveric and clinical patients, the accuracy of cadaveric experiments provides strong support for subsequent clinical trials.

Association of patient-level characteristics with long-term outcomes after Fontan palliation: Rationale, design, and baseline characteristics of the Pediatric Cardiac Care Consortium Fontan cohort study.

BACKGROUND: The Fontan operation is used to palliate single ventricle congenital heart defects (CHD) but poses significant morbidity and mortality risks. We present the design, planned analyses, and rationale for a long-term Fontan cohort study aiming to examine the association of patient characteristics at the time of Fontan with post-Fontan morbidity and mortality. METHODS AND RESULTS: We used the Pediatric Cardiac Care Consortium (PCCC), a US-based, multicenter registry of pediatric cardiac surgeries to identify patients who underwent the Fontan procedure for single ventricle CHD between 1 and 21 years of age. The primary outcomes are in-hospital Fontan failure (death or takedown) and post-discharge mortality through 2022. A total of 1461 (males 62.1%) patients met eligibility criteria and were included in the analytical cohort. The median age at Fontan evaluation was 3.1 years (IQR: 2.4-4.3). While 95 patients experienced in-hospital Fontan failure (78 deaths and 17 Fontan takedown), 1366 (93.5%) survived to discharge with Fontan physiology and formed the long-term analysis cohort. Over a median follow-up of 21.2 years (IQR: 18.4-24.5) 184 post-discharge deaths occurred. Thirty-year post Fontan survival was 75.0% (95% CI: 72.3%-77.8%) for all Fontan types with higher rates for current techniques such as lateral tunnel and extracardiac conduit 77.1% (95% CI: 73.5-80.8). CONCLUSION: The PCCC Fontan study aims to identify predictors for post-Fontan morbidity and mortality, enabling risk- stratification and informing surveillance practices. Additionally, the study may guide therapeutic interventions aiming to optimize hemodynamics and enhance Fontan longevity for individual patients.

I s pelvic support osteotomy (PSO) suitable for ordinary high-riding hip dysplasia?

PURPOSE: Pelvic support osteotomy (PSO) is regarded to provide pelvic stability and improve abductor function to delay or even avoid total hip arthroplasty (THA) in young patients with high-riding hip dysplasia. However, some of these patients eventually have to undergo THA. Because of the double-angulation deformity of the femur after PSO, subsequent THA is challenging. This study aimed to analyze whether PSO surgery is suitable for high-riding hip dysplasia and summarize orthopaedic strategy during THA for patients with previous PSO. METHODS: This case-control study included eight cases of THA for high-riding hip dysplasia patients with previous PSO (study group) and 24 cases of high-riding hip dysplasia patients without any hip surgical therapy (control group) by a 1:3 match (from May 2018 to January 2022). We compared demographics and joint function before and after THA between two groups and recorded all patients' preoperative imaging data, surgical procedures, postoperative imaging data, and complications. The surgical techniques for patients with previous PSO were highlighted. RESULTS: There was no statistical difference between the two groups in demographic (p > 0.05). The study group had worse hip Harris score (HHS), range of motion (ROM), visual analogue scale (VAS), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (p < 0.05) compared with the control group before THA. All patients had concurrent THA and osteotomy at the proximal femur, but the study group experienced longer operation time (p = 0.047) with more blood loss (p = 0.027) and higher complication rate compared with the control group (p = 0.009). At the last follow-up, the study group's HHS, ROM, VAS, and WOMAC were still worse than those in the control group. CONCLUSIONS: PSO did not improve the joint function of high-riding hip dysplasia patients but brought challenges to subsequent THA and affected the surgical outcomes. In short, we suggested that PSO is unsuitable for routine high-riding hip dysplasia patients.

Application and evaluation of artificial intelligence 3D preoperative planning software in developmental dysplasia of the hip.

BACKGROUND: Accurate preoperative planning is crucial for successful total hip arthroplasty (THA) for developmental dysplasia of the hip (DDH). The aim of this study was to compare the accuracy of an artificial intelligence-assisted three-dimensional (3D) planning system (AIHIP) with two-dimensional templates in predicting acetabular cup size in THA for DDH. METHOD: This study retrospectively analyzed image data from 103 DDH patients who had THA between May 2019 and August 2023. AIHIP was used for 3D planning, and two-dimensional (2D) templates were used by two experienced surgeons. Accuracy was assessed by comparing predicted and actual cup sizes, and potential factors affecting accuracy were analyzed, including gender, side, BMI, and dysplasia classification. RESULTS: AIHIP had higher accuracy in predicting the acetabular cup size compared to the 2D template. Within ± 0 size, AIHIP's accuracy was 84.1%, while the 2D template's was 64.0% (p < 0.05). Within ± 1 size, AIHIP's accuracy was 95.1%, while the 2D template's was 81.1% (p < 0.05). Accuracy was unaffected by gender, side, or BMI but was by DDH classification. In subgroup analysis, AIHIP's mean absolute error (0.21 ± 0.54) was significantly lower than the 2D template's (0.62 ± 0.95) for Crowe II and Crowe III (p < 0.05). CONCLUSION: AIHIP is superior to 2D templates in predicting the acetabular cup size accurately for THA in DDH patients. AIHIP may be especially beneficial for Crowe II and III DDH patients, as 2D templates may not accurately predict cup size in these cases.

Integrated Genomic Analysis of Primary Prostate Tumor Foci and Corresponding Lymph Node Metastases Identifies Mutations and Pathways Associated with Metastasis.

Prostate cancer is a highly heterogeneous disease and mortality is mainly due to metastases but the initial steps of metastasis have not been well characterized. We have performed integrative whole exome sequencing and transcriptome analysis of primary prostate tumor foci and corresponding lymph node metastases (LNM) from 43 patients enrolled in clinical trial. We present evidence that, while there are some cases of clonally independent primary tumor foci, 87% of primary tumor foci and metastases are descended from a common ancestor. We demonstrate that genes related to oxidative phosphorylation are upregulated in LNM and in African-American patients relative to White patients. We further show that mutations in TP53, FLT4, EYA1, NCOR2, CSMD3, and PCDH15 are enriched in prostate cancer metastases. These findings were validated in a meta-analysis of 3929 primary tumors and 2721 metastases and reveal a pattern of molecular alterations underlying the pathology of metastatic prostate cancer. We show that LNM contain multiple subclones that are already present in primary tumor foci. We observed enrichment of mutations in several genes including understudied genes such as EYA1, CSMD3, FLT4, NCOR2, and PCDH15 and found that mutations in EYA1 and CSMD3 are associated with a poor outcome in prostate cancer.

Interval estimation for operating characteristic of continuous biomarkers with controlled sensitivity or specificity.

The receiver operating characteristic (ROC) curve provides a comprehensive performance assessment of a continuous biomarker over the full threshold spectrum. Nevertheless, a medical test often dictates to operate at a certain high level of sensitivity or specificity. A diagnostic accuracy metric directly targeting the clinical utility is specificity at the controlled sensitivity level, or vice versa. While the empirical point estimation is readily adopted in practice, the nonparametric interval estimation is challenged by the fact that the variance involves density functions due to estimated threshold. In addition, even with a fixed threshold, many standard confidence intervals including the Wald interval for binomial proportion could have erratic behaviors. In this article, we are motivated by the superior performance of the score interval for binomial proportion and propose a novel extension for the biomarker problem. Meanwhile, we develop exact bootstrap and establish consistency of the bootstrap variance estimator. Both single-biomarker evaluation and two-biomarker comparison are investigated. Extensive simulation studies were conducted, demonstrating competitive performance of our proposals. An illustration with aggressive prostate cancer diagnosis is provided.

Covariate-specific evaluation of continuous biomarker.

Diagnostic tests usually need to operate at a high sensitivity or specificity level in practice. Accordingly, specificity at the controlled sensitivity, or vice versa, is a clinically sensible performance metric for evaluating continuous biomarkers. Meanwhile, the performance of a biomarker may vary across sub-populations as defined by covariates, and covariate-specific evaluation can be informative. In this article, we develop a novel modeling and estimation method for covariate-specific specificity at a controlled sensitivity level. Unlike existing methods which typically adopt elaborate models of covariate effects over the entire biomarker distribution, our approach models covariate effects locally at a specific sensitivity level of interest. We also extend our proposed model to handle the whole continuum of sensitivities via dynamic regression and derive covariate-specific ROC curves. We provide the variance estimation through bootstrapping. The asymptotic properties are established. We conduct extensive simulation studies to evaluate the performance of our proposed methods in comparison with existing methods, and further illustrate the applications in two clinical studies for aggressive prostate cancer.

Covariate adjustment in continuous biomarker assessment.

Continuous biomarkers are common for disease screening and diagnosis. To reach a dichotomous clinical decision, a threshold would be imposed to distinguish subjects with disease from nondiseased individuals. Among various performance metrics, specificity at a controlled sensitivity level (or vice versa) is often desirable because it directly targets the clinical utility of the intended clinical test. Meanwhile, covariates, such as age, race, as well as sample collection conditions, could impact the biomarker distribution and may also confound the association between biomarker and disease status. Therefore, covariate adjustment is important in such biomarker evaluation. Most existing covariate adjustment methods do not specifically target the desired sensitivity/specificity level, but rather do so for the entire biomarker distribution. As such, they might be more prone to model misspecification. In this paper, we suggest a parsimonious quantile regression model for the diseased population, only locally at the controlled sensitivity level, and assess specificity with covariate-specific control of the sensitivity. Variance estimates are obtained from a sample-based approach and bootstrap. Furthermore, our proposed local model extends readily to a global one for covariate adjustment for the receiver operating characteristic (ROC) curve over the sensitivity continuum. We demonstrate computational efficiency of this proposed method and restore the inherent monotonicity in the estimated covariate-adjusted ROC curve. The asymptotic properties of the proposed estimators are established. Simulation studies show favorable performance of the proposal. Finally, we illustrate our method in biomarker evaluation for aggressive prostate cancer.

LINEAR BIOMARKER COMBINATION FOR CONSTRAINED CLASSIFICATION.

Multiple biomarkers are often combined to improve disease diagnosis. The uniformly optimal combination, i.e., with respect to all reasonable performance metrics, unfortunately requires excessive distributional modeling, to which the estimation can be sensitive. An alternative strategy is rather to pursue local optimality with respect to a specific performance metric. Nevertheless, existing methods may not target clinical utility of the intended medical test, which usually needs to operate above a certain sensitivity or specificity level, or do not have their statistical properties well studied and understood. In this article, we develop and investigate a linear combination method to maximize the clinical utility empirically for such a constrained classification. The combination coefficient is shown to have cube root asymptotics. The convergence rate and limiting distribution of the predictive performance are subsequently established, exhibiting robustness of the method in comparison with others. An algorithm with sound statistical justification is devised for efficient and high-quality computation. Simulations corroborate the theoretical results, and demonstrate good statistical and computational performance. Illustration with a clinical study on aggressive prostate cancer detection is provided.

Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance.

PURPOSE: We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance. METHODS AND MATERIALS: We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (R1) vs clinical data+Prostate Health Index (R3). We considered an "or"-logic rule combining clinical score and Prostate Health Index (R4), and a "2-step" rule using clinical data followed by risk stratification based on Prostate Health Index (R2). Rules were applied to a validation set, where values of R2-R4 vs R1 for specificity and sensitivity were evaluated. RESULTS: We included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, R2 yielded highest specificity at 27% vs 17% for R1. In the validation set, R3 had best performance vs R1 with Δsensitivity = -4% and Δspecificity = +6%. There was slight improvement for R3 vs R1 for confirmatory biopsy (AUC 0.745 vs R1 0.724, ΔAUC 0.021, 95% CI 0.002-0.041) but not for subsequent biopsies (ΔAUC -0.012, 95% CI -0.031-0.006). R3 did not have better discrimination vs R1 among the biopsy cohort overall (ΔAUC 0.007, 95% CI -0.007-0.020). CONCLUSIONS: Among active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

Long-Term Risk of Heart Failure-Related Death and Heart Transplant After Congenital Heart Surgery in Childhood (from the Pediatric Cardiac Care Consortium).

We aimed to describe the longitudinal risk of advanced heart failure (HF) leading to death, heart transplantation, or ventricular assist device (VAD) placement after congenital heart surgery (CHS) and how it varies across the spectrum of congenital heart disease. We linked the records of patients who underwent first CHS in the Pediatric Cardiac Care Consortium between 1982 and 2003 with the United States National Death Index and Organ Procurement and Transplantation Network databases. Primary outcome was time from CHS discharge to HF-related death, heart transplant, or VAD placement, analyzed with proportional hazards models accounting for competing mortality. In 35,610 patients who survived a first CHS, there were 799 HF deaths, transplants, or VADs over a median of 23 years (interquartile range, 19 to 27). Cumulative incidence at 25 years was 2.3% (95% confidence interval [CI] 2.1% to 2.4%). Compared to mild 2-ventricle defects, the adjusted subhazard ratio for moderate and severe 2-ventricle defects was 3.21 (95% CI 2.28 to 4.52) and 9.46 (95% CI 6.71 to 13.3), respectively, and for single-ventricle defects 31.8 (95% CI 22.2 to 45.6). Systemic right ventricle carried the highest risk 2 years after CHS (subhazard ratio 2.76 [95% CI 2.08 to 3.68]). All groups had higher rates of HF-related death compared with the general population (cause-specific standardized mortality ratio 56.1 [95% CI 51.0 to 61.2]). In conclusion, the risk of advanced HF leading to death, transplantation, or VAD was high across the spectrum of congenital heart disease. While severe defects carry the highest risk, those with mild disease are still at greater risk than the general population.

A varying-coefficient model for gap times between recurrent events.

Recurrent events often arise in follow-up studies where a subject may experience multiple occurrences of the same type of event. Most regression models for recurrent events consider the time scale measured from the study origin and assume constant effects of covariates. In many applications, however, gap times between recurrent events are of natural interest and moreover the effects may actually vary over time. In this article, we propose a marginal varying-coefficient model for gap times between recurrent events that allows for the intra-individual correlation between events. Estimation and inference procedures are developed for the varying coefficients. Consistency and weak convergence of the proposed estimator are established. Monte Carlo simulation studies demonstrate that the proposed method works well with practical sample sizes. The proposed method is illustrated with an analysis of bladder tumor clinical data.

[18F]Fluciclovine Positron Emission Tomography/Computerized Tomography for Preoperative Staging in Patients with Intermediate to High Risk Primary Prostate Cancer.

PURPOSE: Accurate preoperative staging of prostate cancer is essential for treatment planning. Conventional imaging is limited in detection of metastases. Our primary aim was to determine if [18F]fluciclovine positron emission tomography/computerized tomography is an early indicator of subclinical metastasis among patients with high risk prostate cancer. MATERIALS AND METHODS: A total of 68 patients with unfavorable intermediate to very high risk prostate cancer without systemic disease on conventional imaging were recruited before robotic radical prostatectomy with extended pelvic lymph node dissection. Diagnostic performance of [18F]fluciclovine positron emission tomography/computerized tomography and conventional imaging for detection of metastatic disease, and correlation of positivity to node and metastatic deposit size were determined. RESULTS: Overall 57 of 68 patients completed the protocol, of whom 31 had nodal metastasis on histology. [18F]Fluciclovine positron emission tomography/computerized tomography sensitivity and specificity in detecting nodal metastasis was 55.3% and 84.8% per patient, and 54.8% and 96.4% per region (right and left pelvis, presacral and nonregional), respectively. Compared with conventional imaging [18F]Fluciclovine positron emission tomography/computerized tomography had significantly higher sensitivity on patient based (55.3% vs 33.3%, p <0.01) and region based (54.8% vs 19.4%, p <0.01) analysis, detecting metastasis in 7 more patients and 22 more regions, with similar high specificity. Four additional patients had distant disease or other cancer detected on [18F] fluciclovine positron emission tomography/computerized tomography which precluded surgery. Detection of metastasis was related to size of metastatic deposits within lymph nodes and overall metastatic burden. CONCLUSIONS: [18F]Fluciclovine positron emission tomography/computerized tomography detects occult metastases not identified on conventional imaging and may help guide treatment decisions and lymph node dissection due to high specificity for metastatic disease.

Renshen Shouwu extract enhances neurogenesis and angiogenesis via inhibition of TLR4/NF-κB/NLRP3 signaling pathway following ischemic stroke in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Renshen Shouwu extract (RSSW) is a patented Traditional Chinese Medicine included in Chinese Pharmacopoeia for neurasthenia, forgetfulness, insomnia, inappetence and excessive fatigue. Our previous study had demonstrated the neuroprotective effect of RSSW against ischemic stroke in rats with middle cerebral artery occlusion (MCAO). However, its underlying mechanism remains unknown. AIM OF THE STUDY: In this study, we investigated the neurogenesis and angiogenesis effects of RSSW in ischemic stroke rats, and further revealed its underlying mechanism focused on TLR4/NF-κB/NLRP3 signaling pathway. MATERIALS AND METHODS: Firstly, active compounds of RSSW were determined by High Performance Liquid Chromatography (HPLC). Secondly, Middle cerebral artery occlusion (MCAO) was performed to induce ischemic stroke in rats and 2, 3, 5-Triphenyltetrazolium chloride (TTC) staining was employed to evaluate whether MCAO surgery was successfully established. Neurological deficit evaluation was conducted according to the Zea Longa' method. Then, we explored the neurogenesis and angiogenesis effects after oral administration of RSSW (50 mg/kg, 100 mg/kg) in MCAO-induced rats by Immunofluorescence Staining. Moreover, the proteins involved in TLR4/NF-κB/NLRP3 signaling pathway (TLR4, p-NF-κB p65, NF-κB p65, NLRP3, pro-IL-1ß, IL-1ß, pro-Caspase-1, Caspase-1) were determined by western blotting. RESULTS: It was observed that RSSW treatment significantly increased the number of newborn neurons and brain microvessel density (MVD) after ischemic stroke. What's more, RSSW treatment significantly downregulated TLR4, p-NF-κB p65/p65, NLRP3, pro-IL-1ß, IL-1ß, pro-Caspase-1, Caspase-1 proteins involved in TLR4/NF-κB/NLRP3 signaling pathway. CONCLUSIONS: RSSW enhances neurogenesis and angiogenesis via inhibition of TLR4/NF-κB/NLRP3 inflammatory signaling pathway following ischemic stroke in rats. Hence, RSSW may be a promising Chinese Medicine for the treatment of ischemic stroke.

Ginkgo biloba extract improves brain uptake of ginsenosides by increasing blood-brain barrier permeability via activating A1 adenosine receptor signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Ginkgo biloba leaves and Panax ginseng are Chinese medicine commonly used in combination for cerebral disease. AIM OF THE STUDY: To investigate the effect of standard extract of Ginkgo biloba leaves (EGb) on facilitating brain uptake of ginsenoside and its underlying mechanisms. MATERIALS AND METHODS: The increasing uptake of ginsenosides in the brain of rats by EGb were detected by LC-MS/MS analysis. Evans blue and FITC-dextran leakage were determined to evaluate blood-brain barrier (BBB) permeability in vivo. Transendothelial electrical resistance (TEER) and Na-F penetration rate were measured with a co-culture of the human cerebral microvascular endothelial cell line (hCMEC/D3) and human normal glial cell line (HEB) in vitro BBB model. WB were used to analyzed the expression of BBB tight junctions (TJs) related protein (ZO-1, Occludin, Claudin-3, p-ERM, and p-MLC), ultrastructure of TJs was determined by transmission electron microscope. RESULTS: LC-MS/MS analysis demonstrated that EGb could improve brain uptake of ginsenoside Rg1, Re, Rd and Rb1. In vivo study showed that, BBB permeability was significantly increased after EGb administration, evidenced by the markedly increased penetration of FITC-dextran and Evans Blue into the mice brain parenchyma. In the in vitro BBB model, reduced TEER and increased Na-F penetration rate was observed in EGb group, which was associated with alteration of TJs ultrastructure. Furthermore, the expression of p-ERM and p-MLC in hCMEC/D3 as well as mice brain microvessels were significantly upregulated, but no significant change on the expression of TJs proteins (ZO-1, Occludin and Claudin-3). Moreover, the effect of EGb on in vitro BBB permeability and ERM, MLC phosphorylation was counteracted by DPCPX, an A1 adenosine receptor (A1R) antagonist. CONCLUSIONS: EGb might induce ERM/MLC phosphorylation and increase the cell-cell junction gaps to cause a reversible increase of the BBB permeability via A1R signaling pathway. Our results may contribute to better use of EGb in the treatment of brain diseases.

High-sensitivity gas pressure sensor based on hollow-core photonic bandgap fiber Mach-Zehnder interferometer.

We propose and experimentally demonstrate a highly sensitive gas pressure sensor based on a near-balanced Mach-Zehnder interferometer (MZI) and constructed by hollow-core photonic bandgap fiber (HC-PBF) in this paper. The MZI is simply constructed by fusion splicing two HC-PBFs, which are of slightly different lengths, between two 3-dB couplers. The two output ends of each coupler are approximately equal in length, to ensure that the optical path variations of the MZI only result from the differences in the lengths between the two HC-PBFs. To apply the MZI for gas pressure sensing, a femtosecond laser is employed to drill a micro-channel in one of the two HC-PBF arms. The experiment result shows that the proposed MZI based gas pressure sensor achieves an ultrahigh sensitivity, up to 2.39 nm/kPa, which is two orders of magnitude higher than that of the previously reported MZI-based gas pressure sensors. Additionally, the effects resulting from the absolute length and relative length of the two HC-PBFs on gas pressure sensing performance are also investigated experimentally and theoretically, respectively. The ultra-high sensitivity and ease of fabrication make this device suitable for gas pressure sensing in the field of industrial and environmental safety monitoring.

[Geographic spatial pattern of digestive system cancers in Yiwu city].

OBJECTIVE: To analyze the geographic spatial patterns and risk areas of main digestive system cancers in Yiwu city. METHODS: Newly diagnosed cases of esophageal, gastric and colorectal cancer during 2010-2014 were obtained from Yiwu Center for Disease Control and Prevention (CDC). The household registration population data in 2013 were obtained from public security bureau. Hierarchy clustering and partitioning regionalization method was used to generate geographic units. Global Moran's I was used to evaluate whether cancer incidence was significantly clustered in space, Anselin Local Moran's I was used to identify statistically significant hot spots, cold spots, and spatial outliers, and Spatial Scan Statistics was implemented to analyze the relative risk of cancers in different areas. RESULTS: The 5-year average incidence of esophageal, gastric and colorectal cancers were 9.99/100 000, 34.01/100 000 and 31.46/100 000, respectively. Males showed significantly higher incidence than females. The incidence was heterogeneous throughout the study area. Spatial Scan analysis revealed that southern Yiwu presented a significantly higher male esophageal cancer (RR=1.78) and gastric cancer (RR=1.87) risk. The central area of Yiwu showed a significantly lower female esophageal cancer risk (RR=0.00) and male stomach cancer risk (RR=0.63) and the northern Yiwu exhibited a significantly lower female colorectal cancer risk (RR=0.48). CONCLUSIONS: The incidence of main digestive tract cancers shows a heterogeneous distribution in Yiwu city.

Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events.

In survival analysis, quantile regression has become a useful approach to account for covariate effects on the distribution of an event time of interest. In this paper, we discuss how quantile regression can be extended to model counting processes, and thus lead to a broader regression framework for survival data. We specifically investigate the proposed modeling of counting processes for recurrent events data. We show that the new recurrent events model retains the desirable features of quantile regression such as easy interpretation and good model flexibility, while accommodating various observation schemes encountered in observational studies. We develop a general theoretical and inferential framework for the new counting process model, which unifies with an existing method for censored quantile regression. As another useful contribution of this work, we propose a sample-based covariance estimation procedure, which provides a useful complement to the prevailing bootstrapping approach. We demonstrate the utility of our proposals via simulation studies and an application to a dataset from the US Cystic Fibrosis Foundation Patient Registry (CFFPR).

Model selection and inference for censored lifetime medical expenditures.

Identifying factors associated with increased medical cost is important for many micro- and macro-institutions, including the national economy and public health, insurers and the insured. However, assembling comprehensive national databases that include both the cost and individual-level predictors can prove challenging. Alternatively, one can use data from smaller studies with the understanding that conclusions drawn from such analyses may be limited to the participant population. At the same time, smaller clinical studies have limited follow-up and lifetime medical cost may not be fully observed for all study participants. In this context, we develop new model selection methods and inference procedures for secondary analyses of clinical trial data when lifetime medical cost is subject to induced censoring. Our model selection methods extend a theory of penalized estimating function to a calibration regression estimator tailored for this data type. Next, we develop a novel inference procedure for the unpenalized regression estimator using perturbation and resampling theory. Then, we extend this resampling plan to accommodate regularized coefficient estimation of censored lifetime medical cost and develop postselection inference procedures for the final model. Our methods are motivated by data from Southwest Oncology Group Protocol 9509, a clinical trial of patients with advanced nonsmall cell lung cancer, and our models of lifetime medical cost are specific to this population. But the methods presented in this article are built on rather general techniques and could be applied to larger databases as those data become available.