Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Image quality assessment and feasibility of three-dimensional amide proton transfer-weighted imaging for hepatocellular carcinoma.

Background: With the continuous innovation of magnetic resonance imaging (MRI) hardware and software technology, amide proton transfer-weighted (APTw) imaging has been applied in liver cancer. However, to our knowledge, no study has evaluated the feasibility of a three-dimensional amide proton transfer-weighted (3D-APTw) imaging sequence for hepatocellular carcinoma (HCC). This study thus aimed to conduct an image quality assessment of 3D-APTw for HCC and to explore its feasibility. Methods: 3D-APTw MRI examinations were completed in 134 patients with clinically suspected HCC. According to the uniformity of APTw signal in the liver and within the lesion and the proportion of artifact and missing signal regions, APTw images were subjectively scored using a 5-point scale. The scanning success rate of liver APTw imaging was calculated as the ratio of the number of cases with a quality assurance measurement of more than 3 to the total number of HCC cases. The intra- and interobserver quality assurance measurements for APTw images were compared via the Kappa consistency test. Within the HCC cases with a minimum image quality threshold of 3 points, the APT values of HCC and the liver parenchyma, signal-to-noise ratio of APT-weighted images (SNRAPTw), and contrast-to-noise ratio of HCC (CNRHCC) were measured by two observers. The intra- and interobserver agreement was assessed using the intraclass correlation coefficient (ICC). The differences in APT values between HCC and liver parenchyma was determined using the Mann-Whitney test. Results: Sixty-six HCC cases with a quality assurance measurement of APTw imaging were included in the final analysis, and the calculated success rate was 70.21% (66/94). The subjective APT image quality scores of the two observers were consistent (3.66±1.18, 3.50±1.19, and 3.68±1.18), and no intergroup or intragroup statistical differences were found (P=0.594, and P=0.091), but the consistency of inter- and intraobserver was not as satisfactory (κ=0.594 and κ=0.580). The APT values in HCC lesion were significantly higher than those in liver parenchyma (2.73%±0.91% vs. 1.62%±0.55%; P<0.001). The APT values in HCC showed favorable intra- and interobserver consistency between the two observers (ICC =0.808 and ICC =0.853); the APT values in liver parenchyma, SNRAPTw, and CNRHCC values had moderate intraobserver consistency (ICC =0.578, ICC =0.568, and ICC =0.508) and interobserver consistency (ICC =0.599, ICC =0.199, and ICC =0.650). The coefficients of variation of the APTw values in the HCC lesion and in liver parenchyma were 33.4% and 34.4%, respectively. The SNRAPTw and CNRHCC were 30.75±18.74 and 3.56±3.19, with a coefficient of variation of 60.9% and 74.9%, respectively. Conclusions: Liver 3D-APTw imaging was preliminarily demonstrated to be clinically feasible for evaluating HCC.

Using item scores and response times in person-fit assessment.

The use of joint models for item scores and response times is becoming increasingly popular in educational and psychological testing. In this paper, we propose two new person-fit statistics for such models in order to detect aberrant behaviour. The first statistic is computed by combining two existing person-fit statistics: one for the item scores, and one for the item response times. The second statistic is computed directly using the likelihood function of the joint model. Using detailed simulations, we show that the empirical null distributions of the new statistics are very close to the theoretical null distributions, and that the new statistics tend to be more powerful than several existing statistics for item scores and/or response times. A real data example is also provided using data from a licensure examination.

Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province.

BACKGROUND: Health impact assessment (HIA) is a procedure, method and tool for evaluating the potential health impacts of policies, plans and construction projects, as well as the distribution of these impacts on population. Majority of international studies on health impact assessment have focussed on conceptual papers or case evaluations, neglecting participants' views on policies. METHODS: A semi-structured interview with 30 health impact assessment experts was employed in this study, and the Nvivo software was utilized to analyse factors that influence policy identification. Subsequently, a multi-stage stratified random sampling method was adopted to survey 655 pilot staff members involved in health impact assessment in Zhejiang Province. Descriptive statistics were used to describe the current status and identify the factors influencing policy identification. In addition, hierarchical linear regression analysis and structural equation modelling were employed to determine the relationship between policy identification and influencing factors. RESULTS: Statistically significant differences were found among participants in the level of identification of policies across three dimensions. The policy sentiment dimension had the highest score (4.137 ± 0.664), followed by policy cognition (4.075 ± 0.632) and policy evaluation (3.631 ± 0.797) dimensions. Subject trust had a positive impact on policy cognition (ß = 0.503, P < 0.001), policy sentiment (ß = 0.504, P < 0.001) and policy evaluation (ß = 0.465, P < 0.001). Procedural justice had a positive impact on policy sentiment (ß = 0.085, P < 0.01) and policy evaluation (ß = 0.084, P < 0.05), but not policy cognition (ß = 0.056, P > 0.05). Policy identification is influenced by age and average monthly salary among other factors. CONCLUSION: These results highlight the importance of subjective trust and procedural justice in policy identification of health impact assessment. They provide valuable insights to developing interventions to overcome barriers to the implementation and enhancement of global identification of policies. Going forward, cross-sectoral synergies, enhanced international communication and training to increase participants' trust in the policy should be optimized to improve health impact assessment. Additional measures should be taken, such as ensuring seamless communication channels, embedding health impact assessment in administrative mechanisms, and establishing strong oversight and grievance mechanisms to improve fairness and transparency in the implementation and results of health impact assessment.

Housing wealth appreciation and heterogeneous household consumption: Evidence from China.

In this paper, we develop a DSGE model including heterogeneous households, introduce the financial friction of credit constraint mechanism, and study the impact of house price shocks on the consumption of heterogeneous household. Based on this, the CHFS data in 2011, 2013, 2015, 2017, and 2019 were used to test the marginal propensity to consume for housing wealth appreciation under different credit constraints. Results show that: Firstly, the financial accelerator mechanism plays an important role in the transmission of housing price shocks to household consumption. The looser the degree of credit constraints, the more obvious the rise in housing prices will be to the consumption expenditure of borrowing household. Secondly, the impact of housing wealth appreciation on household consumption under different credit constraints is heterogeneous. Among them, housing wealth appreciation has a significant positive impact on household consumption expenditure with multiple houses, credit cards, non-loan restrictions, while the marginal effect on the consumption expenditure of households with only one house, loan limited, and no credit cards decreases. Thirdly, for every 1% increase in the housing wealth appreciation, household consumption will increase significantly by 0.10-0.14%.

Severity assessment to guide empiric antibiotic therapy for cholangitis in children after Kasai portoenterostomy: a multicenter prospective randomized control trial in China.

BACKGROUND: Cholangitis is common in patients with biliary atresia following Kasai portoenterostomy (KPE). The prompt use of empiric antibiotics is essential due to the lack of identified microorganisms. The authors aimed to validate a severity grading system to guide empiric antibiotic therapy in the management of post-KPE cholangitis. MATERIALS AND METHODS: This multicenter, prospective, randomized, open-label study recruited patients with post-KPE cholangitis and was conducted from January 2018 to December 2019. On admission, patients were categorized into mild, moderate, and severe cholangitis according to the severity grading system. Patients in the mild cholangitis group were randomized to receive cefoperazone sodium tazobactam sodium (CSTS) or meropenem (MEPM). Patients with severe cholangitis were randomized to treatment with MEPM or a combination of MEPM plus immunoglobulin (MEPM+IVIG). Patients with moderate cholangitis received MEPM. RESULTS: The primary endpoint was duration of fever (DOF). Secondary outcomes included blood culture, length of hospital stay, incidence of recurrent cholangitis, jaundice clearance rate, and native liver survival (NLS). For mild cholangitis, DOF, and length of hospital stay were similar between those treated with CSTS or MEPM (all P >0.05). In addition, no significant difference in recurrence rate, jaundice clearance rate, and NLS was observed between patients treated with CSTS and MEPM at 1-month, 3-month, and 6-month follow-up. In patients with moderate cholangitis, the DOF was 36.00 (interquartile range: 24.00-48.00) h. In severe cholangitis, compared with MEPM, MEPM+IVIG decreased DOF and improved liver function by reducing alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, and direct bilirubin at 1-month follow-up. However, recurrence rate, jaundice clearance rate, and NLS did not differ significantly between MEPM+IVIG and MEPM at 1-month, 3-month, and 6-month follow-up. CONCLUSIONS: In patients with post-KPE cholangitis, MEPM is not superior to CSTS for the treatment of mild cholangitis. However, MEPM+IVIG treatment was associated with better short-term clinical outcomes in patients with severe cholangitis.

Rapid authentication of variants of Gastrodia elata Blume using near-infrared spectroscopy combined with chemometric methods.

The variety is one of the most important factors to generate difference of chemical compositions, which unavoidably influences the quality of natural medicine. Thus, simple and rapid authentication of different variants has great academic and practical significance. In this study, the goal was achieved with the help of near infrared spectroscopy (NIR) and chemometrics by using Gastrodia elata Blume as an example. A total of 540 samples including two classes of variants and their forms were investigated as a whole. The mean spectra of samples of each class and their 2-D synchronous correlation spectra were simultaneously applied to discover the difference of chemical characteristics. After hybrid pre-processing of the first and second derivative combined with Savitzky-Golay and Norris filtering, partial least squares discrimination analysis (PLS-DA) on the basis of latent variable projection was used to assess the feasibility for classification. The results show higher prediction accuracy in both internal test set and external prediction set. In order to further improve the robustness for modeling, three methods for wavelength selection were comprehensively compared to optimize PLS-DA models, including variable importance in the projection (VIP), random frog (RF), and Monte Carlo uninformative variable elimination (MC-UVE). The prediction accuracy of combination of the 2nd derivative, Norris, MC-UVE and PLS-DA achieved to 99.11% and 98.89% corresponding to the internal test set and external prediction set, respectively. The strategies proposed in this work perform effectiveness for rapid and accurate authentication of variants of plants with high chemical complexity.

Silk fibroin based wearable electrochemical sensors with biomimetic enzyme-like activity constructed for durable and on-site health monitoring.

Flexible biomimetic sensors have encountered a bottleneck of sensitivity and durability, as the sensors must directly work within complex body fluid with ultra-trace biomarkers. In this work, a wearable electrochemical sensor on a modified silk fibroin substrate is developed using gold nanoparticles hosted into N-doped porous carbonizated silk fibroin (AuNPs@CSF) as active materials. Taking advantage of the inherent biocompatibility and flexibility of CSF, and the high stability and enzyme-like catalytic activity of AuNPs, AuNPs@CSF-based sensor exhibits durable stability and superior sensitivity to monitor H2O2 released from cancer cell (4T1) and glucose in sweat. The detection limits for H2O2 and glucose are low to be 1.88 µM and 23 µM respectively, and the sensor can be applied in succession within 30 days at room temperature. Further, physical cross-linking of polyurethane (PU) with SF well matches with the skin tissue mechanically and provides a flexible, robust and stable electrode-tissue interface. AuNPs@CSF is applied successfully for wearable electrochemical monitoring of glucose in human sweat.The present AuNPs@CSF will possess a potential application in clinical diagnosing of H2O2- or glucose-related diseases in future.

Risk assessment and environmental determinants of urinary phthalate metabolites in pregnant women in Southwest China.

Pregnant women are widely exposed to phthalic acid esters (PAEs) that are commonly used in most aspects of modern life. However, few studies have examined the cumulative exposure of pregnant women to a variety of PAEs derived from the living environmental conditions in China. Therefore, this study aimed to determine the urinary concentrations of nine PAE metabolites in pregnant women, examine the relationship between urinary concentrations and residential characteristics, and conduct a risk assessment analysis. We included 1,888 women who were in their third trimester of pregnancy, and we determined their urinary concentrations of nine PAE metabolites using high-performance gas chromatography-mass spectrometry. The risk assessment of exposure to PAEs was calculated based on the estimated daily intake. A linear regression model was used to analyze the relationship between creatinine-adjusted PAE metabolite concentrations and residential characteristics. The detection rate of five PAE metabolites in the study population was > 90%. Among the PAE metabolites adjusted by creatinine, the urinary metabolite concentration of monobutyl phthalate was found to be the highest. Residential factors, such as housing type, proximity to streets, recent decorations, lack of ventilation in the kitchen, less than equal to three rooms, and the use of coal/kerosene/wood/wheat straw fuels, were all significantly associated with high PAE metabolite concentrations. Due to PAE exposure, ~ 42% (n = 793) of the participants faced potential health risks, particularly attributed to dibutyl phthalate, diisobutyl phthalate, and di(2-ethyl)hexyl phthalate exposure. Living in buildings and using coal/kerosene/wood/wheat straw as domestic fuel can further increase the risks.

Meranzin Hydrate Improves Depression-Like Behaviors and Hypomotility via Ghrelin and Neurocircuitry.

OBJECTIVE: To investigate whether meranzin hydrate (MH) can alleviate depression-like behavior and hypomotility similar to Chaihu Shugan Powder (CSP), and further explore the potential common mechanisms. METHODS: Totally 120 Spraque-Dawley rats were randomly divided into 5-8 groups including sham, vehicle, fluoxetine (20 mg/kg), mosapride (10 mg/kg), CSP (30 g/kg), MH (9.18 mg/kg), [D-Lys3]-GHRP-6 (Dlys, 0.5 mg/kg), and MH+Dlys groups by a random number table, 8 rats in each group. And 32 mice were randomly divided into wild-type, MH (18 mg/kg), growth hormone secretagogue receptor-knockout (GHSR-KO), and GHSR+MH groups, 8 mice in each group. The forced swimming test (FST), open field test (OFT), tail suspension test (TST), gastric emptying (GE) test, and intestinal transit (IT) test were used to assess antidepressant and prokinetic (AP) effects after drug single administration for 30 min with absorbable identification in rats and mice, respectively. The protein expression levels of brain-derived neurotrophic factor (BDNF) and phosphorylated mammalian target of rapamycin (p-mTOR) in the hippocampus of rats were evaluated by Western blot. The differences in functional brain changes were determined via 7.0 T functional magnetic resonance imaging-blood oxygen level-dependent (fMRI-BOLD). RESULTS: MH treatment improved depression-like behavior (FST, OFT) and hypomotility (GE, IT) in the acute forced swimming (FS) rats (all P<0.05), and the effects are similar to the parent formula CSP. The ghrelin antagonist [D-Lys3]-GHRP-6 inhibited the effect of MH on FST and GE (P<0.05). Similarly, MH treatment also alleviated depression-like behavior (FST, TST) in the wild-type mice, however, no effects were found in the GHSR KO mice. Additionally, administration of MH significantly stimulated BDNF and p-mTOR protein expressions in the hippocampus (both P<0.01), which were also prevented by [D-Lys3]-GHRP-6 (P<0.01). Besides, 3 main BOLD foci following acute FS rats implicated activity in hippocampus-thalamus-basal ganglia (HTB) circuits. The [D-Lys3]-GHRP-6 synchronously inhibited BOLD HTB foci. As expected, prokinetic mosapride only had effects on the thalamus and basal ganglia, but not on the hippocampus. Within the HTB, the hippocampus is implicated in depression and FD. CONCLUSIONS: MH accounts for part of AP effects of parent formula CSP in acute FS rats, mainly via ghrelin-related shared regulation coupled to BOLD signals in brain areas. This novel functionally connection of HTB following acute stress, treatment, and regulation highlights anti-depression unified theory.

Organophosphate ester exposure among Chinese waste incinerator workers: Urinary levels, risk assessment and associations with oxidative stress.

Organophosphate esters (OPEs), which are frequently used as flame retardants and plasticizers in versatile products, are readily released to the external environment. Although workers at municipal waste incineration plants may be extensively exposed to OPEs, only scarce health monitoring and risk assessments have been conducted in this population. In this study, we investigated the levels of eight metabolites of organophosphate esters (mOPEs) and the oxidative stress marker 8-hydroxy-2-deoxyguanosine (8-OHdG) in urine samples from 73 waste incinerator workers and 97 general residents from Shenzhen, China between September 2016 and June 2017. The overall detection rate of mOPEs was 82.2 %-100 %, and higher concentrations of di-p-cresyl phosphate and chlorinated mOPEs [bis(2-chloroethyl) phosphate (BCEP), bis(1-chloro-2propyl) phosphate (BCIPP), bis(1,3-dichloro-2-propyl) phosphate) (BDCIPP)] were found among incinerator workers than among general residents. The incinerator workers also showed significantly higher levels of 8-OHdG than general residents, but the measured levels of most mOPEs were not significantly correlated with the level of 8-OHdG; this may be because co-exposure to multiple toxic compounds can lead to oxidative stress. Risk assessment using Monte Carlo simulations revealed that 95 % of the incinerator workers were free from non-carcinogenic effects due to OPEs exposure (hazard index = 0.27, 95 % CI: 0.09, 0.77). However, the carcinogenic risk of tris(2-chloroethyl) phosphate (TCEP) for incinerator workers was between 10-6 and 10-4. These results indicate that incinerator workers are extensively exposed to OPEs, and better protective measures need to be implemented.

Silicon modulator based on omni junctions by effective 3D Monte-Carlo method.

3D doping structure has significant advantages in modulation efficiency and loss compared with 2D modulator doping profiles. However, to the best of our knowledge, previous work on 3D simulation methods for interdigitated doping designs applied simplified models, which prohibited complex 3D doping. In this work, innovative omni junctions, based on the effective 3D Monte-Carlo method, are believed to be the first proposed for high-performance modulators. Simulation results show that the modulation efficiency reaches 0.88 V·cm, while the loss is only 16 dB/cm, with capacitance below 0.42 pF/mm. This work provides a modulator design with superior modulation efficiency and serviceability for high-speed datacom.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation. OBJECTIVE: To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria. METHODS: One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort. RESULTS: In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)]. CONCLUSION: The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.

BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study was to investigate the effect of AI-assisted software on residents' inter-observer agreement and intra-observer reproducibility for the X-ray bone age assessment of preschool children. METHODS: This prospective study was approved by the Institutional Ethics Committee. Six board-certified residents interpreted 56 bone age radiographs ranging from 3 to 6 years with structured reporting by the modified TW3 method. The images were interpreted on two separate occasions, once with and once without the assistance of AI. After a washout period of 4 weeks, the radiographs were reevaluated by each resident in the same way. The reference bone age was the average bone age results of the three experts. Both TW3-RUS and TW3-Carpal were evaluated. The root mean squared error (RMSE), mean absolute difference (MAD) and bone age accuracy within 0.5 years and 1 year were used as metrics of accuracy. Interobserver agreement and intraobserver reproducibility were evaluated using intraclass correlation coefficients (ICCs). RESULTS: With the assistance of bone age AI software, the accuracy of residents' results improved significantly. For interobserver agreement comparison, the ICC results with AI assistance among 6 residents were higher than the results without AI assistance on the two separate occasions. For intraobserver reproducibility comparison, the ICC results with AI assistance were higher than results without AI assistance between the 1st reading and 2nd reading for each resident. CONCLUSIONS: For preschool children X-ray bone age assessment, in addition to improving diagnostic accuracy, bone age AI-assisted software can also increase interobserver agreement and intraobserver reproducibility. AI-assisted software can be an effective diagnostic tool for residents in actual clinical settings.

What Is the Mechanism of Government Green Development Behavior Considering Multi-Agent Interaction? A Meta-Analysis.

Worsening environmental problems have created more and more challenges for green development, and the government is often seen as an important guide in turning this situation around. A government generally enacts green development through green development behavior, but previous research has not revealed the mechanism of this behavior. In addition, the multi-agent interaction between the government and green development behavior also needs to be explored. Based on an integrated theoretical model, the authors of this study adopted a meta-analysis method to analyze 18 high-quality published pieces from 6 mainstream databases and described the mechanism of government green development behavior in exploring and thinking about multi-agent interactions. In addition, the authors of this study explored differences in the roles of central and local government green development behaviors and the moderating role of regional heterogeneity. The research results showed that: (1) Enterprise economic behavior, enterprise environmental behavior, enterprise social behavior, and public participation are all significantly positively affected by government green development behavior; (2) local government green development actions have stronger effects than central government actions; (3) regional heterogeneity moderates the effect of government green development behavior. Furthermore, the authors of this study propose relevant countermeasures and suggestions from the government's point of view. This research provides a theoretical and practical reference for governments to better improve their environmental systems and environmental supervision.

Preoperative prediction of pelvic lymph nodes metastasis in prostate cancer using an ADC-based radiomics model: comparison with clinical nomograms and PI-RADS assessment.

PURPOSE: To develop and test radiomics models based on manually corrected or automatically gained masks on ADC maps for pelvic lymph node metastasis (PLNM) prediction in patients with prostate cancer (PCa). METHODS: A primary cohort of 474 patients with PCa who underwent prostate mpMRI were retrospectively enrolled for PLNM prediction between January 2017 and January 2020. They were then randomly split into training/validation (n = 332) and test (n = 142) groups for model development and internal testing. Four radiomics models were developed using four masks (manually corrected/automatic prostate gland and PCa lesion segmentation) based on the ADC maps using the primary cohort. Another cohort of 128 patients who underwent radical prostatectomy (RP) with extended pelvic lymph node dissection (ePLND) for PCa was used as the testing cohort between February 2020 and October 2021. The performance of the models was evaluated in terms of discrimination and clinical usefulness using the area under the curve (AUC) and decision curve analysis (DCA). The optimal radiomics model was further compared with Memorial Sloan Kettering Cancer Center (MSKCC) and Briganti 2017 nomograms, and PI-RADS assessment. RESULTS: 17 (13.28%) Patients with PLNM were included in the testing cohort. The radiomics model based on the mask of automatically segmented prostate obtained the highest AUC among the four radiomics models (0.73 vs. 0.63 vs. 0.70 vs. 0.56). Briganti 2017, MSKCC nomograms, and PI-RADS assessment-yielded AUCs of 0.69, 0.71, and 0.70, respectively, and no significant differences were found compared with the optimal radiomics model (P = 0.605-0.955). CONCLUSION: The radiomics model based on the mask of automatically segmented prostate offers a non-invasive method to predict PLNM for patients with PCa. It shows comparable accuracy to the current MKSCC and Briganti nomograms.

Mechanistic insights into H2 evolution via water splitting at the expense of B2(OH)4: a theoretical study.

H2 has been comprehensively deemed a promising potential candidate to replace traditional fossil fuel-based energy. Typically, the hydrolysis of most hydrogen-rich boron hydrides (e.g. NaBH4, NH3BH3 and Me2NHBH3) catalyzed by nanomaterials generates H2 with only one H atom supplied by water and the other one by a hydrogen-rich boron hydride. Interestingly, both H atoms of produced H2 are provided by water upon hydrolysis of B2(OH)4. Herein, the catalytic mechanisms of H2 evolution upon water splitting at the expense of B2(OH)4 in its hydrolysis reactions catalyzed by acid, base or metal nanoparticles have been investigated by density functional theory (DFT) calculations. By computational studies, the mechanisms of catalysis by base and metal nanoparticles are basically the same as those speculated from our previous experiments. The previously proposed acid catalytic mechanism has been overturned, however. This study not only provides important insights into the catalytic mechanism for water splitting at the expense of B2(OH)4, but also opens up an exciting opportunity to use water to store H2.

Assessment of Occupational Exposure in Medical Practice in the Region of Hohhot, China, for the Period 2004-2020.

ABSTRACT: Individual monitoring is of great significance in efforts to protect the health of radiation workers and improve the level of radiation protection and management. This paper presents a retrospective analysis of occupational exposure to ionizing radiation from medical practice in the region of Hohhot, China, from 2004 to 2020. Results show that the average annual effective dose of occupationally exposed workers in medical practice significantly declined from 1.44 mSv in 2005 to 0.29 mSv in 2020 (Z = -5.23, P < 0.05). The number of medical radiation workers increased by 181%, the composition of radiation workers whose average annual effective dose exceeded 1 mSv decreased, and the number of radiation workers whose average annual effective dose was less than or equal to the minimum detection level (MDL) increased yearly over the 17-y study period. It was found that the dose of 1.106 mSv received by workers in interventional radiology is significantly higher than the doses of 0.52 mSv in dental radiology, 0.47 mSv in radiotherapy, and 0.33 mSv in all other medical uses (Z = 3.71, 9.13, 5.93, respectively; P < 0.05). The distribution ratios of workers in nuclear medicine and interventional radiology whose annual individual effective dose exceeded 5 mSv were 0.040 and 0.043, respectively, which are significantly higher than those in other occupational categories (χ2 = 307.11, P < 0.05). It was also shown that the average annual effective dose of 0.67 mSv in interventional radiology is significantly higher than that of 0.17 mSv in radiotherapy (Z = 3.39, P < 0.05) in 2020. According to these observations, the exposure of radiation workers in medical practice in Hohhot meets the requirements of the China standard. This study shows that the status of radiation workers in medical practice has obviously improved during the period 2004-2020. However, it is still necessary to focus on the protection of groups with high occupational exposure risk, and the continuous improvement of protection measures, monitoring means, and radiation workers' training, especially for the workers in the fields of interventional radiology and nuclear medicine.

Comparison Between Radial Forearm Free Flap and Pectora is Major Myocutaneous Flap for Reconstruction in Oral Cavity Cancer Patients: Assessment of the Quality of Life.

ABSTRACT: We aimed to evaluate the quality of life of Chinese patients after immediate reconstruction surgery on individuals with oral cavity cancer. In addition, we compared the differences between radial forearm free flap and pectoralis major myocuta- neous flap. Using the University of Washington quality of life v4 questionnaire, 1:1 matched research was performed on patients received PMM or RFF flap. Chi-square test was used to analyze the variables. One hundred twenty four of 179 questionnaires were returned (69.3%). Age, N stage, and postoperative radiotherapy were similar for both groups. However, there were significant differences between two groups in gender, T stage, operation duration, and complication rate. Oral cavity cancer patients reconstructed with radial forearm free flap had better shoulder and speech functions but worse appearance domains. The results of our research provide important information for patients and physicians during their discussion of treatment programs for oral cavity cancers.

Comorbid Depressive and Anxiety Symptoms and Their Correlates Among 93,078 Multiethnic Adults in Southwest China.

Background: Depressive symptoms and anxiety symptoms commonly coexist and severely increases the disease burden worldwide. Little is known about the patterns and correlates of comorbid depressive and anxiety symptoms among the multiethnic populations of China. Methods: This population-based study investigated the comprehensive associations of comorbid depressive and anxiety symptoms with lifestyles, stressful life events, chronic diseases, and physical and mental well-being among 93,078 participants (37,193 men, 55,885 women) aged 30-79 years across seven ethnic groups in Southwest China. Multivariable logistic regression models were used to estimate associations. Results: Overall, 2.9% (2.1% in men and 3.5% in women) participants had comorbid depressive and anxiety symptoms; there was considerable heterogeneity among multiethnic populations. Participants with chronic diseases were more likely to have comorbidity than those without them; people with rheumatic heart disease reported the highest risk, with an odds ratio (OR) of 6.25 and 95% confidence interval (CI) of 4.06-9.62. Having experienced 3 or more stressful life events (OR, 8.43, 95% CI: 7.27-9.77), very poor self-rated health status (OR, 33.60, 95%CI: 25.16-44.87), and very unsatisfied life (OR, 33.30, 95% CI: 23.73-46.74) had strong positive associations with comorbid depressive symptoms and anxiety symptoms, with a dose-response relationship (P < 0.05). High frequency of physical activity had negative associations. All the associations were stronger than depressive symptoms alone or anxiety symptoms alone. Conclusions: Our findings emphasize the need to focus on the vulnerable ethnic groups with comorbid depressive and anxiety symptoms, ultimate for help early prevention and improvement of health equity in the underdevelopment and high urbanization areas.