A cost-effective approach to identify conservation priority for 30 × 30 biodiversity target on the premise of food security.

There is a growing consensus on expanding protected and conserved areas for biodiversity conservation. Nevertheless, it remains uncertain where to expand conserved areas as well as what appropriate management modalities to choose. Moreover, conserved areas expansion should be balanced with crop-related food security challenges. We developed a framework to identify cost-effective areas for expanding protected areas and other effective area-based conservation measures (OECMs), and applied it to China. By combining templates for biodiversity conservation priorities at global scale and the priority conservation areas based on 2413 vertebrates' extinction risk in China, we identified areas with high biodiversity conservation value. We then categorized the priority areas according to human impact, indicating the potential cost of management. As a result of combining the two aspects above, we identified the most cost-effective areas for expanding protected areas and OECMs while excluding both the current and predicted croplands that can be used for food security. The results show that China could expand its protected areas to 22.81 % of the country's land area and establish OECMs in areas accounting for 9.82 % and 17.37 % of the country's land area in a cost-effective approach in two scenarios. In the ambitious scenario, protected and conserved areas would account for a maximum of 40.18 % of terrestrial area, with an average 62.67 % coverage of the 2413 species' suitable habitat. To achieve the goals of protected and conserved areas in Kunming-Montreal Global Biodiversity Framework, countries could apply this framework to identify their protected areas and OECM expansion priorities.

simKAP: simulation framework for the kidney allocation process with decision making model.

Organ shortage is a major barrier in transplantation and rules guarding organ allocation decisions should be robust, transparent, ethical and fair. Whilst numerous allocation strategies have been proposed, it is often unrealistic to evaluate all of them in real-life settings. Hence, the capability of conducting simulations prior to deployment is important. Here, we developed a kidney allocation simulation framework (simKAP) that aims to evaluate the allocation process and the complex clinical decision-making process of organ acceptance in kidney transplantation. Our findings have shown that incorporation of both the clinical decision-making and a dynamic wait-listing process resulted in the best agreement between the actual and simulated data in almost all scenarios. Additionally, several hypothetical risk-based allocation strategies were generated, and we found that these strategies improved recipients' long-term post-transplant patient survival and reduced wait time for transplantation. The importance of simKAP lies in its ability for policymakers in any transplant community to evaluate any proposed allocation algorithm using in-silico simulation.

Is Apparent Diffusion Coefficient Established as an Imaging Biomarker for Stereotactic Body Radiation Therapy Assessment in Hepatocellular Carcinoma?

ABSTRACT: In this article, as part of this special issue on biomarkers of early response, we review currently available reports regarding magnetic resonance imaging apparent diffusion coefficient (ADC) changes in hepatocellular carcinoma (HCC) in response to stereotactic body radiation therapy. We compare diffusion image acquisition, ADC analysis, methods for HCC response assessment, and statistical methods for prediction of local tumor progression by ADC metrics. We discuss the pros and cons of these studies. Following detailed analyses of existing investigations, we cannot conclude that ADC is established as an imaging biomarker for stereotactic body radiation therapy assessment in HCC.

Environmental Adaptability and Energy Investment Strategy of Different Cunninghamia lanceolata Clones Based on Leaf Calorific Value and Construction Cost Characteristics.

The calorific value and construction cost of leaves reflect the utilization strategy of plants for environmental resources. Their genetic characteristics and leaf functional traits as well as climate change affect the calorific values. This study explores the differences in energy investment strategies and the response characteristics of energy utilization in leaves to climate change among nine clones of Chinese fir (Cunninghamia lanceolata). Considering the objectives, the differences in the energy utilization strategies were analyzed by determining the leaf nutrients, specific leaf area, and leaf calorific value and by calculating the construction cost. The results showed a significant difference in the ash-free calorific value and construction cost of leaves among different Chinese fir clones (p < 0.05). There were also significant differences in leaf carbon (C) content, leaf nitrogen (N) content, specific leaf area, and ash content. The correlation analysis showed that leaves' ash-free calorific value and construction cost were positively correlated with the C content. Principal component analysis (PCA) showed that P2 is inclined to the "fast investment return" energy investment strategy, while L27 is inclined to the "slow investment return" energy investment strategy. Redundancy analysis (RDA) indicates that the monthly average temperature strongly correlates positively with leaf construction cost, N content, and specific leaf area. The monthly average precipitation positively impacts the ash-free calorific value and construction cost of leaves. In conclusion, there are obvious differences in energy investment strategies among different Chinese fir clones. When temperature and precipitation change, Chinese fir leaves can adjust their energy investment to adapt to environmental changes. In the future, attention should be paid to the impact of climate change-related aspects on the growth and development of Chinese fir plantations.

Identifying the evolution of ecological poverty alleviation efficiency and its influencing factors: evidence from counties in Northeast China.

Ecological poverty alleviation (EPA) is an effective strategy to address the vicious circle of poverty and environmental destruction in poor areas. However, it remains controversial whether this strategy has really succeeded in this respect. Previous research investigated the impact of a certain factor on EPA, and only few studies integrated them to explore their differential effects, thereby overlooking the complexity of EPA. Therefore, this study quantified the overall efficiency of the EPA strategies of 28 poor counties in three provinces of Northeast China from 2005 to 2018 by using a super-efficiency slacks-based measure model. This model can take into account undesirable outputs; as such, it has significant advantages in measuring the coordination among economic and social development and environmental protection. The Tobit model was used to explore the factors influencing EPA efficiency. The results show that, first, the majority of counties investigated had an EPA efficiency below the overall national average. Second, as for the factors influencing EPA efficiency, it was found that (1) GDP per capita and investment in environmental governance favored EPA efficiency, as they are conducive to stimulating regional consumption dynamics and achieving green economic development; (2) science and technology expenditure and urbanization were not conducive to EPA efficiency; and (3) industrial structure and trade had insignificant effects on EPA efficiency, due to the small scale of industry and the inadequacy of the policy system. This study assessed EPA efficiency from a holistic perspective, and addressed the controversies over EPA's influencing factors, thereby providing an effective method to conduct regional EPA assessment and improve EPA performance in poor regions of China.

Nexus amongst environmental regulations, carbon emission intensity and technological innovation in China's construction industry.

China's construction industry confronts with the dilemma of carbon emissions in adjusting the environmental regulations. Many studies are neglected on discovering the potential nexus amongst environmental regulations (ERs), technological innovation (TI) and CEI (CEI) and ignores the relationships amongst TI for reducing CEI. To mitigate this gap, this study bridges institutional theory to integrate the practices in the construction industry. This study applies a panel dataset on the construction industry from 30 provinces during 2004-2018 and uses it with a two-step system-generalised method of moments for analysis. The proposed method enables the prevention of the interference of the heteroscedasticity problem and improves certain analytical efficiency. The results are as a guideline for policymakers in rechecking the policies and regulations adequacy. The findings indicate that (1) the forced emission reduction effect is proven by command-and-control and market-based ERs, which can inhibit CEI; (2) voluntary ERs have an inverted U-shaped nexus with CEI; in other words, the green paradox effect shifts to the forced emission reduction effect once the intensity of voluntary ERs increases; and (3) market-based and voluntary ERs reduce CEI effectively by using TI as the mediator in construction industry.

An Efficient and Uncertainty-Aware Decision Support System for Disaster Response Using Aerial Imagery.

Efficient and robust search and rescue actions are always required when natural or technical disasters occur. Empowered by remote sensing techniques, building damage assessment can be achieved by fusing aerial images of pre- and post-disaster environments through computational models. Existing methods pay over-attention to assessment accuracy without considering model efficiency and uncertainty quantification in such a life-critical application. Thus, this article proposes an efficient and uncertain-aware decision support system (EUDSS) that evolves the recent computational models into an efficient decision support system, realizing the uncertainty during building damage assessment (BDA). Specifically, a new efficient and uncertain-aware BDA integrates the recent advances in computational models such as Fourier attention and Monte Carlo Dropout for uncertainty quantification efficiently. Meanwhile, a robust operation (RO) procedure is designed to invite experts for manual reviews if the uncertainty is high due to external factors such as cloud clutter and poor illumination. This procedure can prevent rescue teams from missing damaged houses during operations. The effectiveness of the proposed system is demonstrated on a public dataset from both quantitative and qualitative perspectives. The solution won the first place award in International Overhead Imagery Hackathon.

Evaluating the dynamic effects of mitigation instruments on CO2 emissions in China's nonferrous metal industry: A vector autoregression analysis.

Reducing carbon dioxide (CO2) emissions in China's nonferrous metal industry is important for reaching China's ambitious goals for carbon peaking and neutrality. Prior research identified several carbon abatement instruments for the industry. However, the dynamic influence of different mechanisms on CO2 emissions in the industry remains unclear, and few studies have researched CO2 emission reductions in two nonferrous metal related industrial subsectors: nonferrous metal ore mining and nonferrous metal smelting. This research evaluated the dynamic effect of abatement instruments on the CO2 emissions in these two subsectors. The research discovered the factors that are highly linked with CO2 emissions by using an enhanced Stochastic Impacts by Regression on Population, Affluence, and Technology model. The dynamic influence of these factors on CO2 emissions in the two subsectors was investigated using a vector autoregressive model. Findings show that in the two subsectors, labour productivity and industrial value-added are the most important factors explaining CO2 changes. The two variables have a negative long-term effect on CO2 emissions in the nonferrous metal ores mining, and increase CO2 emissions in the smelting of nonferrous metals. Improving energy efficiency in the nonferrous metal smelting industry decreases the CO2 emissions only in the short term. In all sectors, lowering the electrical carbon emission factors and changing the energy structure using different techniques are expected to help reduce long-term CO2 emissions. These results are critical for the Chinese government in creating long- and short-term energy plans for the nonferrous metal sector.

An immediate postoperative response to therapy assessment can help avoid unnecessary RAI therapy.

Background: Radioiodine (RAI) therapy plays a vital role in the postoperative treatment of differentiated thyroid cancer (DTC) patients underwent total thyroidectomy (TT). However, even in the presence of capsular invasion and lymph node metastasis prognosis can be excellent and a postoperative RAI treatment might not be necessary for all patients. Therefore, this study explored the criteria for avoiding unnecessary RAI therapy in these patients. Method: We applied response to therapy assessment immediately after surgery and prospectively recruited 179 excellent or indeterminate response DTC patients with capsular invasion and/or LNM who underwent TT without RAI therapy. During the follow-up, thyroglobulin (Tg), thyroglobulin antibody (TgAb) levels, and cervical ultrasonography were collected and analyzed. Disease-free survival (DFS) was calculated using the Kaplan-Meier method. In addition, response to therapy assessments was performed on patients during each follow-up. Results: The mean follow-up period was 29.85 ± 17.44 months, and the 3- and 5-year DFS for all the patients was 99.3% in each. At the last follow-up, 165 (92.2%) patients had excellent responses, while 12 (6.7%) had an indeterminate response, and one (0.6%) each had biochemical and incomplete responses. No significant difference was observed in response to therapy between the subgroups of LNM and tumor invasion (P>0.05). For patients with capsular invasion and a number of metastatic lymph nodes ≤5 and >5, the proportions of recorded excellent responses were 95.9%, 91.0%, and 85.7%, respectively. Better responses were observed in females (excellent response: 95.5%, P=0.023), patients with stimulated Tg (s-Tg) ≤1ng/ml (excellent response: 100%, P<0.001), s-Tg ≤ 2ng/ml (excellent response: 98.4%, P<0.001), and excellent response for the immediate postoperative assessment (excellent response: 98.5%, P=0.004). Conclusions: The current study suggested that the response to therapy assessment immediately applied postoperatively could help avoid unnecessary RAI therapy among DTC patients with capsular invasion and/or LNM. Moreover, excellent response patients and patients with indeterminate response and s-Tg ≤ 2ng/ml could be managed without RAI therapy.

Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China.

This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.

Response assessment during chemoradiation using a hypercellular/hyperperfused imaging phenotype predicts survival in patients with newly diagnosed glioblastoma.

BACKGROUND: Adversely prognostic hypercellular and hyperperfused regions of glioblastoma (GBM) predict progression-free survival, and are a novel target for dose-intensified chemoradiation (chemoRT) recently implemented in a phase II clinical trial. As a secondary aim, we hypothesized that dose-intensified chemoRT would induce greater mid-treatment response of hypercellular/hyperperfused tumor regions vs standard chemoradiation, and that early response would improve overall survival (OS). METHODS: Forty-nine patients with newly diagnosed GBM underwent prospective, multiparametric high b value diffusion-weighted MRI (DW-MRI) and perfusion dynamic contrast-enhanced MRI (DCE-MRI) pre-RT and 3-4 weeks into RT. The hypercellular tumor volume (TVHCV, mean contralateral normal brain + 2SD) and hyperperfused tumor volume (TVCBV, contralateral normal frontal gray matter + 1SD) were generated using automated thresholding. Twenty-six patients were enrolled on a dose-escalation trial targeting TVHCV/TVCBV with 75 Gy in 30 fractions, and 23 non-trial patients comprised the control group. OS was estimated using the Kaplan-Meier method and compared using the log-rank test. The effect of TVHCV/TVCBV and Gd-enhanced tumor volume on OS was assessed using multivariable Cox proportional-hazard regression. RESULTS: Most patients had gross total (47%) or subtotal resection (37%), 25% were MGMT-methylated. Patients treated on the dose-escalation trial had significantly greater reduction in TVHCV/TVCBV (41% reduction, IQR 17%-75%) vs non-trial patients (6% reduction, IQR 6%-22%, P = .002). An increase in TVHCV/TVCBV during chemoRT was associated with worse OS (adjusted hazard ratio [aHR] 1.2, 95%CI 1.0-1.4, P = .02), while pre-treatment tumor volumes (P > .5) and changes in Gd-enhanced volume (P = .9) were not. CONCLUSIONS: Multiparametric MRI permits identification of therapeutic resistance during chemoRT and supports adaptive strategies in future trials.

Quantifying and leveraging predictive uncertainty for medical image assessment.

The interpretation of medical images is a challenging task, often complicated by the presence of artifacts, occlusions, limited contrast and more. Most notable is the case of chest radiography, where there is a high inter-rater variability in the detection and classification of abnormalities. This is largely due to inconclusive evidence in the data or subjective definitions of disease appearance. An additional example is the classification of anatomical views based on 2D Ultrasound images. Often, the anatomical context captured in a frame is not sufficient to recognize the underlying anatomy. Current machine learning solutions for these problems are typically limited to providing probabilistic predictions, relying on the capacity of underlying models to adapt to limited information and the high degree of label noise. In practice, however, this leads to overconfident systems with poor generalization on unseen data. To account for this, we propose a system that learns not only the probabilistic estimate for classification, but also an explicit uncertainty measure which captures the confidence of the system in the predicted output. We argue that this approach is essential to account for the inherent ambiguity characteristic of medical images from different radiologic exams including computed radiography, ultrasonography and magnetic resonance imaging. In our experiments we demonstrate that sample rejection based on the predicted uncertainty can significantly improve the ROC-AUC for various tasks, e.g., by 8% to 0.91 with an expected rejection rate of under 25% for the classification of different abnormalities in chest radiographs. In addition, we show that using uncertainty-driven bootstrapping to filter the training data, one can achieve a significant increase in robustness and accuracy. Finally, we present a multi-reader study showing that the predictive uncertainty is indicative of reader errors.

The association between secondary health conditions and indirect costs after spinal cord injury.

STUDY DESIGN: Cross-sectional. OBJECTIVE: Identify the association between secondary health conditions (SHC) and the indirect costs of traumatic spinal cord injury (SCI) based on the pre-injury and post-injury changes in employment and earnings. SETTING: Medical university in the southeastern United States (US). METHODS: A population-based cohort of 304 participants met the following eligibility criteria: received treatment for acute SCI within the state, residual effects resulting from traumatic SCI, at least 1-year post injury, age between 23 and 64 years at the time of injury onset, and younger than 65 years at the time of study measurement. The indirect costs estimate was measured by the annual forgone earnings and fringe benefits calculated as the difference in the sum of earnings and benefits between before injury and after injury adjusting for inflation in 2019 US dollars. We considered seven SHC in this study: bowel accidents, urine accidents, urinary tract infections, pressure sores, unintentional injury, severe pain, and depressive disorder. We used multivariate ordinary least squares regression models to examine their relationship controlling for age, sex, race/ethnicity, marital status, years of education, injury level, and ambulatory status. RESULTS: The indirect costs were significantly associated with the total number of SHC and with the individual conditions of bowel accidents, urine accidents, pressure sores, and depressive disorder after controlling for age, sex, race/ethnicity, marital status, years of education, injury level, and ambulatory status. CONCLUSIONS: Preventing SHC relates to better economic consequences for individuals, their families, and society, even after accounting for differences in severity of SCI.

Cost-effective priorities for the expansion of global terrestrial protected areas: Setting post-2020 global and national targets.

Biodiversity loss is a social and ecological emergency, and calls have been made for the global expansion of protected areas (PAs) to tackle this crisis. It is unclear, however, where best to locate new PAs to protect biodiversity cost-effectively. To answer this question, we conducted a spatial meta-analysis by overlaying seven global biodiversity templates to identify conservation priority zones. These are then combined with low human impact areas to identify cost-effective zones (CEZs) for PA designation. CEZs cover around 38% of global terrestrial area, of which only 24% is currently covered by existing PAs. To protect more CEZs, we propose three scenarios with conservative, moderate, and ambitious targets, which aim to protect 19, 26, and 43% of global terrestrial area, respectively. These three targets are set for each Convention on Biological Diversity party with spatially explicit CEZs identified, providing valuable decision support for the post-2020 global biodiversity framework.

Performances of the Canadian Agility and Movement Skill Assessment (CAMSA), and validity of timing components in comparison with three commonly used agility tests in Chinese boys: an exploratory study.

BACKGROUND: The practical application of the Canadian Agility and Movement Skill Assessment (CAMSA) has been reported in some Western countries. However, a few studies reported the application of the CAMSA in Chinese children. In addition, given that the CAMSA was designing to incorporate both movement skills and agility assessment, the value and validity of the timing component of the CAMSA are worth discussing. METHODS: By choosing the Illinois Agility Test, Repeated Side Step-1 m distance, and the newly designed Repeated Side Step-half of height as the benchmark, we evaluate the performance of the CAMSA, further establish the concurrent validity of the CAMSA timing components (completion time and time score). In total, 149 male children (mean age 9.0 ± 0.8 years) from public schools in Shanghai, China, participated in the study. RESULTS: The mean CAMSA completion time was 19.3 ± 5.3 (s), and mean time score was 8.7 ± 3.9 (range of 1-14) for all participants (n = 149). After adjusted the sprint speed, older age was positively associated with the performance of the CAMSA. Being overweight was not associated with the performance of the CAMSA comparing with healthy body mass children, however, being obese was negatively associated with the CAMSA timing components and total score. Children having extracurricular sports activities (e.g., athletic experiences), mostly soccer, were more likely to demonstrated better performances of the CAMSA completion time, time score and total score. However, overweight and obese, also athletic experiences were not significantly contributed to the CAMSA skill score, although the association was slight (Adj R 2 = 0.13). Besides, the CAMSA completion time has a strong correlation with the IAT, r = 0.77; RSS-1MD, r =  - 0.76; and RSS-HHD, r =  - 0.77, p < 0.01. The same pattern of correlation was also found between the CAMSA time score and three agility tests: IAT, r =  - 0.79; RSS-1MD, r = 0.76; RSS-HHD, r = 0.78, p < 0.01. DISCUSSION: Overall, a few participants in the study were able to reach the recommended level of the total CAMSA score referring to the Canadian criterion. The strong concurrent validity was found between the CAMSA timing components and three selected agility tests, respectively.

Estimation of indirect costs based on employment and earnings changes after spinal cord injury: an observational study.

STUDY DESIGN: Cross-sectional. OBJECTIVES: (1) Identify changes in employment status and earnings after spinal cord injury (SCI). (2) Estimate annual indirect costs and lifetime indirect costs due to lost earnings for various age and neurologic categories of those with SCI. (3) Compare our estimates with previous research. SETTING: Medical university in southeastern United States. METHODS: A population-based cohort of 307 participants met eligibility criteria of: (1) residual impairment resulting from traumatic SCI, (2) at least 1 year post injury, (3) between 23 and 64 years old at time of injury, (4) <65 years old at time of measurement, and (5) complete information on injury level, injury completeness, employment status, and earnings before and after injury. Main outcomes were employment status and earnings at the time of injury and post injury. Earnings were adjusted for inflation and the value of fringe benefits. RESULTS: Employment rate decreased from 87% at the time of injury to 35% after injury. Average annual indirect costs were $29,354 in 2019 dollars. Lifetime indirect costs for persons injured at age 25 varied by severity of injury, ranging from 0.5 to 2.3 million dollars. Lifetime indirect costs for persons injured at age 50 ranged from 0.3 to 0.6 million dollars. CONCLUSIONS: Our estimate of indirect costs is lower than the previously estimated number. However, the higher unemployment rate and decreased earnings after SCI still make a heavy economic burden. With improvements in employment outcomes after SCI, the indirect costs affecting individuals, their families, and society can be further reduced.

Metabolic Tumor Volume Response Assessment Using (11)C-Methionine Positron Emission Tomography Identifies Glioblastoma Tumor Subregions That Predict Progression Better Than Baseline or Anatomic Magnetic Resonance Imaging Alone.

PURPOSE: To evaluate whether response assessment of newly diagnosed glioblastoma at 3 months using 11C-methionine-positron emission tomography (MET-PET) is better associated with patient outcome compared with baseline MET-PET or anatomic magnetic resonance imaging alone. METHODS AND MATERIALS: Patients included were participants in a phase I/II trial of dose-escalated chemoradiation based on anatomic magnetic resonance imaging. Automated segmentation of metabolic tumor volume (MTV) was performed at a threshold of 1.5 times mean cerebellar uptake. Progression-free (PFS) and overall survival were estimated with the Kaplan-Meier method and compared with log-rank tests. Multivariate analysis for PFS and overall survival was performed using Cox proportional hazards, and spatial overlap between imaging and recurrence volumes were analyzed. RESULTS: Among 37 patients, 15 had gross total resection, of whom 10 (67%) had residual MTV, 16 subtotal resection, and 6 biopsy alone. Median radiation therapy dose was 75 Gy (range, 66-81). Median baseline T1 Gd-enhanced tumor volume (GTV-Gd) was 38.0 cm3 (range, 8.0-81.5). Median pre-CRT MTV was 4.9 cm3 (range, 0-43.8). Among 25 patients with 3-month MET-PET, MTV was only 2.4 cm3 (range, 0.004-18.0) in patients with uptake. Patients with MTV = 0 cm3 at 3 months had superior PFS (18.2 vs 10.1 months, P = .03). On multivariate analysis, larger 3-month MTV (hazard ratio [HR] 2.4, 95% confidence interval [CI], 1.4-4.3, P = .03), persistent MET-PET subvolume (overlap of pre-CRT and 3 month MTV; HR 2.0, 95% CI, 1.2-3.4, P = .06), and increase in MTV (HR 1.8, 95% CI, 1.1-3.1, P = .09) were the only imaging factors significant for worse PFS. GTV-Gd at recurrence encompassed 97% of the persistent MET-PET subvolume (interquartile range 72%-100%), versus 71% (interquartile range 39%-93%) of baseline MTV, 54% of baseline GTV-Gd (18%-87%), and 78% of 3-month MTV (47%-95%). CONCLUSIONS: The majority of patients with apparent gross total resection of glioblastoma have measurable postoperative MTV. Total and persisting MTV 3 months post-CRT were significant predictors of PFS, and persistent MET-PET subvolume was the strongest predictor for localizing tumor recurrence.

Robust Tracking of a Cost-Effective Micro-Stereolithography System Based on a Compliant Nanomanipulator.

Micro-stereolithography (MSL) has emerged as a promising and challenging technique in micro-/nano-scale additive manufacturing. Besides the requirement of the light source, the motion system requires ultra-high-precision tracking capability to reach the right location for every solidification event. To achieve single-digit micron feature size of the fabrication, we propose a robust control strategy to support a self-developed cost-effective MSL prototype based on a compliant nanomanipulator and a blue light-emitting diode (LED) module. In particular, the nonlinearity and parameter-variation of the compliant manipulator are dealt with by a robust radial basis function (RBF)-based neural network, and the repetitive control (RC) is innovatively integrated with RBF to improve the tracking performance of a closed pattern. Various simulations and real-time experiments are conducted to validate the proposed control strategy. The fabrication of a closed pattern will not begin by turning on the laser source until the tracking error reaches submicrons, and the fabrication results demonstrate that the cost-effective MSL system is capable of fabricating 2.5 µm feature size in a 0.5 mm working range.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants.

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

Real-Time Quantitative Assessment of Accuracy and Precision of Blood Volume Derived from DCE-MRI in Individual Patients During a Clinical Trial.

Accuracy and precision of quantitative imaging (QI) metrics should be assessed in real time in each patient during a clinical trial to support QI-based decision-making. We developed a framework for real-time quantitative assessment of QI metrics and evaluated accuracy and precision of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI)-derived blood volume (BV) in a clinical trial for head and neck cancers. Patients underwent DCE-MRI before and after 2 weeks of radiation therapy (2wkRT). A mean as a reference value and a repeatability coefficient (RC) of BV values established from n patients in cerebellum volumes of interest (VOIs), which were normal and affected little by therapy, served as accuracy and precision measurements. The BV maps of a new patient were called accurate and precise if the values in cerebellum VOIs and the difference between the 2 scans agreed with the respective mean and RC with 95% confidence. The new data could be used to update reference values. Otherwise, the data were flagged for further evaluation before use in the trial. BV maps from 62 patients enrolled on the trial were evaluated. Mean BV values were 2.21 (±0.14) mL/100 g pre-RT and 2.22 (±0.17) mL/100 g at 2wkRT; relative RC was 15.9%. The BV maps from 3 patients were identified to be inaccurate and imprecise before use in the clinical trial. Our framework of real-time quantitative assessment of QI metrics during a clinical trial can be translated to different QI metrics and organ-sites for supporting QI-based decision-making that warrants success of a clinical trial.