Carexqingyuanensis (Cyperaceae), a new species from Guangdong, China.

Carexqingyuanensis, a new species of Cyperaceae from Guangdong Province, China, is described and illustrated. The new species is morphologically similar to Carexpeliosanthifolia F. T. Wang & Tang ex P. C. Li, but it can be distinguished by the racemose inflorescence branches appearing single (rarely binate or ternate) (vs. binate or ternate), one (rarely two or three) (vs. 1-3) spiked, male part of linear-cylindrical spikes much longer than the female part (vs. just male part short-cylindrical and slightly longer than female part), style base thickened (vs. not thickened) and perigynium horizontally patent with a short (vs. long and excurved) beak. Phylogenetic analysis, based on the two nuclear DNA regions (ETS 1f and ITS) and three chloroplast DNA regions (matK, ndhF and rps16), suggests that the new species belongs to sect. Siderostictaes.s. of subg. Siderosticta and shows a closer phylogenetic relationship to Carexscaposa C. B. Clarke.

An ultrasound-based radiomics model for survival prediction in patients with endometrial cancer.

PURPOSE: To establish a nomogram integrating radiomics features based on ultrasound images and clinical parameters for predicting the prognosis of patients with endometrial cancer (EC). MATERIALS AND METHODS: A total of 175 eligible patients with ECs were enrolled in our study between January 2011 and April 2018. They were divided into a training cohort (n = 122) and a validation cohort (n = 53). Least absolute shrinkage and selection operator (LASSO) regression were applied for selection of key features, and a radiomics score (rad-score) was calculated. Patients were stratified into high risk and low-risk groups according to the rad-score. Univariate and multivariable COX regression analysis was used to select independent clinical parameters for disease-free survival (DFS). A combined model based on radiomics features and clinical parameters was ultimately established, and the performance was quantified with respect to discrimination and calibration. RESULTS: Nine features were selected from 1130 features using LASSO regression in the training cohort, which yielded an area under the curve (AUC) of 0.823 and 0.792 to predict DFS in the training and validation cohorts, respectively. Patients with a higher rad-score were significantly associated with worse DFS. The combined nomogram, which was composed of clinically significant variables and radiomics features, showed a calibration and favorable performance for DFS prediction (AUC 0.893 and 0.885 in the training and validation cohorts, respectively). CONCLUSION: The combined nomogram could be used as a tool in predicting DFS and may assist individualized decision making and clinical treatment.

Commelinadanxiaensis (Commelinaceae), a new species from Guangdong, China.

Commelinadanxiaensis (Commelinaceae), a remarkable new species from Mount Danxia, Guangdong Province, China, is described and illustrated. This species is similar to C.communis in inflorescences and flowers but readily distinguishable in its nearly erect stems, larger flowers, and different petal colouration.

The relationship between online courses and mental health among Chinese children.

BACKGROUND: Previous studies on the association of online courses and mental health were mainly conducted in universities, and no study investigated the relationship between characteristics of online courses and children's mental health in primary and secondary school. This study aimed to explore the association of online courses and children's mental health in primary and secondary school. METHODS: A cross-sectional study was conducted through an online survey among 540 primary and secondary school students and their parents in the eastern, central and western region of China from April to May in 2020. Children's mental health was assessed by the Strengths and Difficulties Questionnaire (SDQ). Borderline mental health problems (SDQ total difficulties score ≥ 16) and mental health problems (SDQ total difficulties score ≥ 20) were defined according to Goodman's standard. Multivariable linear and logistic regression models were used to examine the association between online courses and children's mental health. RESULTS: Compared with those who did not have problems of online courses, children having the difficulty in understanding the content of online courses had a higher SDQ total difficulties score [ß = 1.80, 95% confidence interval (CI): 0.89, 2.71] and a higher risk of borderline mental health problems [odds ratio (OR) = 1.93, 95%CI: 1.07, 3.49], while device or internet connection problems were not significantly associated with children's mental health. Compared with children who had live courses, those having video-recorded courses had a higher SDQ total difficulties score (ß = 0.90, 95%CI: 0.01, 1.80). Children who spent more than 4 h on online courses had a higher SDQ total difficulties score than those of less than or equal to 4 h (ß = 0.95, 95%CI: 0.09, 1.81). CONCLUSION: We found that online courses with inappropriate characteristics were associated with children's mental health. The findings called for the efforts to optimize the online courses and improve children's mental health.

The epidemiological evidence linking exposure to ambient particulate matter with neurodevelopmental disorders: A systematic review and meta-analysis.

BACKGROUND: There has been increasing attention on the associations between ambient particulate matter (PM) in early-life and neurodevelopmental disorders (NDDs). However, the associations remained unclear when considering different types of NDDs and different sizes of PM, and vulnerable exposure windows during early-life were not identified yet. OBJECTIVE: To synthesize the published literature on the associations between ambient particulate matter (PM) and risk of different types of neurodevelopmental disorders (NDDs) in a systematic review and meta-analysis. METHODS: A systematic search of Medline, Embase, PubMed, Cochrane Library, and Web of Science was performed from inception through 24 January 2022. Two reviewers conducted the study selection, data extraction, and quality appraisal. A random-effects model was used for meta-analyses with two quality-of-evidence assessments (the Grading of Recommendations Assessment, Development, and Evaluation system and the best evidence synthesis system). RESULTS: A total of 6554 articles were screened, of which 31 were included in the review, and 20 provided adequate data for meta-analyses. Exposures to particulate matter of 2.5 µm or less (PM2.5) during prenatal periods (OR, 1.32 [95%CI, 1.03-1.69]), the first year after birth (OR, 1.62 [95%CI, 1.22-2.15]) and the second year after birth (OR, 3.13 [95%CI, 1.47-6.67]) were associated with increased risk of autism spectrum disorders (ASD) in children. The quality of evidence for these associations during early postnatal periods was somewhat moderate with limited studies. We found inconsistent evidence when considering other types of NDDs and different sizes of PM. CONCLUSIONS AND RELEVANCE: Current evidence indicated that there might be an association between PM2.5 exposure and higher risk of ASD, and early postnatal periods appeared to be the critical exposure window. High-quality studies are needed to assess the evidence for other types of NDDs.

Monte Carlo studies of bootstrap variability in ROC analysis with data dependency.

ROC analysis involving two large datasets is an important method for analyzing statistics of interest for decision making of a classifier in many disciplines. And data dependency due to multiple use of the same subjects exists ubiquitously in order to generate more samples because of limited resources. Hence, a two-layer data structure is constructed and the nonparametric two-sample two-layer bootstrap is employed to estimate standard errors of statistics of interest derived from two sets of data, such as a weighted sum of two probabilities. In this article, to reduce the bootstrap variance and ensure the accuracy of computation, Monte Carlo studies of bootstrap variability were carried out to determine the appropriate number of bootstrap replications in ROC analysis with data dependency. It is suggested that with a tolerance 0.02 of the coefficient of variation, 2,000 bootstrap replications be appropriate under such circumstances.

Intra- and Inter-rater Reliability of A Novel Hand-held MyotonPRO Device for Achilles Tendon Properties in Healthy Subjects / 中国康复理论与实践

Objective To evaluate the intra-and inter-rater reliability of MyotonPRO for Achilles tendon properties measured. Methods Twenty healthy subjects were recruited to measure Achilles tendon properties using a novel hand-held Myoton-PRO device by two testers, one of the testers re-tested five days later. The reliability was assessed using in-tra-class correlation coefficient (ICC) and Bland-Altman analysis, and minimum detectable changes (MDC) was calculated. The Achilles tendon properties of the dominant or non-dominant leg was compared. The correlation between body mass and Achilles tendon properties was examined. Results The intra-rater reliabilities of Achilles tendon properties were ICCleft=0.884 and ICCright=0.904; the inter-rater reli-abilities were ICCleft=0.883 and ICCright=0.945. The MDC was 36.64 N/m. Bland-Altman plots showed good agreement. There was no significant difference in Achilles tendon properties between dominant and non-domi-nant legs (t<1.236, P>0.05). The body mass positively correlated with Achilles tendon properties (r>0.477, P<0.05). Conclusion The intra-and inter-rater reliabilities of MyotonPRO were good in measuring Achilles tendon properties in healthy subjects. No significant difference was found between dominant and non-dominant legs. The body mass positively correlated with Achilles tendon properties in healthy subjects.

Polymer-lipid hybrid nanoparticles-based paclitaxel and etoposide combinations for the synergistic anticancer efficacy in osteosarcoma.

In this study, paclitaxel and etoposide-loaded lipid-polymer hybrid nanoparticles (PE-LPN) was successful prepared and evaluated for physicochemical and anticancer effect. Nanosized PE-LPN was obtained with a perfect spherical morphology. PE-LPN exhibited a controlled release of two drugs in a sequential manner. The nanoparticles exhibited a typical endocytosis-mediated cellular uptake in cancer cells. The ratiometric combination of paclitaxel (PTX) and etoposide (ETP) were significantly more cytotoxic than individual drugs. Importantly, superior cytotoxic effect was observed for dual-drug-loaded PE-LPN than cocktail combination at a much lower dose. Similarly, PE-LPN exhibited a significantly higher apoptosis of cancer cells (∼45%) compared to that of any other groups with higher caspase-3 and -8 activity. Importantly, PE-LPN showed a remarkable tumor regression effect and exhibited a 2-fold superior efficacy than free drugs. PE-LPN treated group showed significantly less Ki-67 positive cells (less than 25%) than PTX/ETP and single drug treated groups, suggesting less active cell proliferation and a considerably higher tumor growth inhibition effect. The results collectively showed that combination of drugs could greatly improve the therapeutic property of chemotherapeutic drugs. By combining ETP with PTX (a powerful anticancer drug) in a polymer-lipid hybrid nanoparticle system, therapeutic efficacy could be improved in osteosarcoma treatments.

The Impact of Data Dependence on Speaker Recognition Evaluation.

The data dependency due to multiple use of the same subjects has impact on the standard error (SE) of the detection cost function (DCF) in speaker recognition evaluation. The DCF is defined as a weighted sum of the probabilities of type I and type II errors at a given threshold. A two-layer data structure is constructed: target scores are grouped into target sets based on the dependency, and likewise for non-target scores. On account of the needed equal probabilities for scores being selected when resampling, target sets must contain the same number of target scores, and so must non-target sets. In addition to the bootstrap method with i.i.d. assumption, the nonparametric two-sample one-layer and two-layer bootstrap methods are carried out based on whether the resampling takes place only on sets, or subsequently on scores within the sets. Due to the stochastic nature of the bootstrap, the distributions of the SEs of the DCF estimated using the three different bootstrap methods are created and compared. After performing hypothesis testing, it is found that data dependency increases not only the SE but also the variation of the SE, and the two-layer bootstrap is more conservative than the one-layer bootstrap. The rationale regarding the different impacts of the three bootstrap methods on the estimated SEs is investigated.

A novel measure and significance testing in data analysis of cell image segmentation.

BACKGROUND: Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed. RESULTS: We propose the total error rate (TER), a novel performance measure for segmenting all cells in the supervised evaluation. The TER statistically aggregates all misclassification error rates (MER) by taking cell sizes as weights. The MERs are for segmenting each single cell in the population. The TER is fully supported by the pairwise comparisons of MERs using 106 manually segmented ground-truth cells with different sizes and seven CIS algorithms taken from ImageJ. Further, the SE and 95% confidence interval (CI) of TER are computed based on the SE of MER that is calculated using the bootstrap method. An algorithm for computing the correlation coefficient of TERs between two CIS algorithms is also provided. Hence, the 95% CI error bars can be used to classify CIS algorithms. The SEs of TERs and their correlation coefficient can be employed to conduct the hypothesis testing, while the CIs overlap, to determine the statistical significance of the performance differences between CIS algorithms. CONCLUSIONS: A novel measure TER of CIS is proposed. The TER's SEs and correlation coefficient are computed. Thereafter, CIS algorithms can be evaluated and compared statistically by conducting the significance testing.

Preoperative platelet count improves the prognostic prediction of the FIGO staging system for operable cervical cancer patients.

BACKGROUND: Increased platelet has been identified as an independent and unfavorable prognostic indicator in various cancers including cervical cancer. In our study, the prognostic value of preoperative platelet count combining with FIGO (International Federation of Gynecology and Obstetrics) stage in patients with operable cervical cancer was investigated. METHODS: A large cohort study including 800 operable cervical cancer patients was conducted from May 2005 to December 2012. Cancer-related biomarkers such as platelet count, hematocrit, hemoglobin, RDW was evaluated together with FIGO staging system in stage IA1-IIA2 cervical cancer patients. The prediction validity of platelet together with FIGO stage was then evaluated by receiver operating characteristic (ROC) curve, and the areas under the curve (AUCs) were compared by Z test. RESULTS: Univariate cox proportional hazard analysis demonstrated that hematocrit, platelet count, hemoglobin, FIGO stage, tumor differentiation, PLN (pelvic lymph node metastasis), LVSI (vascular lymph node invasion) were associated with overall survival (OS) and disease free survival (DFS), instead of RDW (red cell distribution width), age and histological subtype. Multivariate analysis demonstrated that preoperative platelet and FIGO stage were independent predictors for OS and DFS in cervical cancer. Furthermore, significant improvements were found after the combination of platelet count and FIGO stage in predicting OS and DFS for cervical cancer patients (P=0.0128 and P=0.0385, respectively). CONCLUSIONS: Combination of platelet count and FIGO stage improved the prediction performance of FIGO staging and provide additional risk stratification for operable cervical cancer patients.

Validation of Nonparametric Two-Sample Bootstrap in ROC Analysis on Large Datasets.

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in ROC analysis on large datasets in areas such as biometrics, speaker recognition, etc., when the analytical method cannot be used. Its validation was studied by computing the SE of the area under ROC curve using the well-established analytical Mann-Whitney-statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. They match very well. This validation provides a sound foundation for such computations.

A novel prognostic inflammation score predicts outcomes in patients with ovarian cancer.

BACKGROUND: Systemic inflammation and host immunological nutritional status play important roles in the tumorigenesis of malignant cancer. A novel prognostic inflammation score (PIS) based on preoperative serum albumin and neutrophil to lymphocyte ratio (NLR) was designed. We explored its prognostic value in ovarian cancer. METHODS: 143 patients with ovarian cancer were enrolled in this retrospective study. The association of the PIS with clinicopathologic parameters was analyzed. The prognostic significance was determined by univariate and multivariate cox survival analyses. RESULTS: Both univariate and multivariate analyses showed that NLR and albumin were independent prognostic factors for overall survival (OS) and progression-free survival (PFS). An inverse correlation was observed between the NLR and serum albumin concentration. The novel prognostic inflammation score (PIS) was shown to be a significant predictor for OS and PFS (both P<0.001) according to multivariate analysis. Additionally, low PIS was associated with advanced tumor stage (P<0.001), metastasis (P<0.001) and preoperative high PLR (P<0.001). CONCLUSIONS: The PIS is a novel but promising prognostic score in ovarian cancer. It is a significant prognostic marker adjusted for clinicopathologic characteristics to further identify patients' survival differences.

Cervical cancer systemic inflammation score: a novel predictor of prognosis.

Inflammation contributes to development and progression in a variety of cancers, including cervical cancer. We developed a novel cervical cancer systemic inflammation score (CCSIS) based on the preoperative platelet-to-lymphocyte ratio (PLR) and serum albumin levels. A retrospective analysis of clinical data from 795 patients with operable cervical cancer was then conducted to investigate the prognostic value of CCSIS and its association with the patients' clinicopathological features, overall survival (OS), and disease-free survival (DFS). CCSIS was predictive of OS and DFS. High CCSIS was correlated with more advanced FIGO stages, poor tumor differentiation, and the presence of PLN and LVSI. Both albumin levels and the PLR were independent prognostic indicators for operable cervical cancer. The use of the CCSIS could improve risk stratification and traditional clinicopathological analysis in cervical cancer.

[Discussion of the Application and Influence Factors of Low-Background Gamma Spectrometry in Distinguishing Sedimentary Rock Types].

The contents of radionuclides uranium, thorium and potassium in the sedimentary rocks mainly depend on the contents of clay in the rocks. And the content of clay is the main basis for distinguishing types of sedimentary rock. Therefore, the value of specific activity or content of uranium, thorium and potassium can be as the quantitative index to distinguish sedimentary rock type. The specific activity or content of radionuclides uranium, thorium and potassium with the method of low-background gamma spectrometry can distinguish the type of rock quickly and accurately. Because of the influence of geometry, mass and moisture content in the sample, the accuracy of distinguishing types of rocks is influenced. This paper makes a theoretical discussion and experimental verification on the influence of mass and moisture content on the results of low-background gamma spectrometry. Results show that there is a linear relationship between (cps) of characteristic peak of all radionuclides and the mass of sample while different energy ranges and lithologies have different linear coefficient and trend fitting degree; The moisture content which is no more than 10%(while collecting samples, the moisture content is no more than 10%) has a little influence on the measurement results( the change values are within the twice standard deviation), so the moisture content which has no significant influence on the accuracy of distinguishing types of sedimentary rock using the method of low-background gamma spectrometry could not be considered. The distinguishing experiment of drilling cuttings samples collected from one oil and gas exploration area in Shanxi Dingbian is done. By the mass correction of the measured data, normalized (cps) ((cps) of per unit mass) of uranium, thorium and potassium channel can only roughly divide the types of sedimentary rocks. Therefore, synthetic distinguishing mode is established with (cps) of combination peak of characteristic peak of uranium, thorium and potassium. The type of rocks is further subdivided, and the distinguishing accuracy is more than 75%.

[Research on the Background Subtraction Method for X-Ray Fluorescence Spectrum with X-Ray Tube Excitation].

X-ray tube is the most commonly used equipment in X-ray fluorescence spectrum analysis as excitation source whose primary spectrum has become a major source of the background of X-ray fluorescence spectrum. Background subtraction should go before further analysis of this spectrum. The accuracy of the estimation of the background directly affect the results of subsequent processing steps. In this paper, the tube excitation component of X fluorescence spectrum is analyzed with an estimation method of background intensity against their background characteristics, and structuring theoretical spectral lines based on the measured spectral lines in order to evaluate the effect of spectral processing algorithms. The method utilizes the measured X-ray fluorescence spectrum which does not contain the characteristic peak of the spectrum, In order to estimate the composition of the original spectrum of the X-ray tube. It uses the spectrum that contains the continuous background for interpolating the entire measured spectrum, thereby avoiding overlapping the spectral characteristic peaks or improperly estimating full width at half maximum. This paper compared SNIP, Fourier transform method and the background subtraction method using the measured spectral lines. Using this method to estimate the background is closer to the theoretical background. The results showe that the method for X-ray fluorescence spectrum by X-ray tube excitation is accurate in this article, this method can be used to deduct continuous background, and good applied effectiveness has been achieved in the background subtraction of the actually measured X-ray fluorescence spectrometry.

Clinical curative effect on non-small cell lung cancer patients by cinobufacini injection combined first-line chemotherapy / 国际肿瘤学杂志

Objective To explore the clinical curative effect on non-small cell lung cancer (NSCLC) patients by cinobufacini injection combined with first-line chemotherapy.Methods Eighty patients with NSCLC from January 2013 to January 2015 in our hospital were selected as the research objects.Then they were divided into the observation group (n =40)and the control group (n =40)by random number tables.The patients in control group accepted docetaxel and cisplatin combination chemotherapy regimens (TP).While the observation group accepted cinobufacini injection on the basis of the control group.Then the local control, adverse reactions and prognosis of the two groups were compared.Results The local control of observation group was 77.5%,while the control group was 62.5%,the local control of observation group was obviously higher than that of the control group (χ2 =5.36,P =0.03).Leucopenia incidence of the observation group was 27.5%,the control group was 50.0%,and the incidence of the observation group was obviously lower than that of the control group (χ2 =4.27,P =0.04).There was no statistically significant difference between the two groups in diarrhea,stomachache,vomiting,tinnitus (17.5% vs.27.5%,χ2 =1.15,P =0.28;25.0% vs.45.0%,χ2 =3.52,P =0.06;5.0% vs.7.5%,χ2 =0.34,P =0.56;7.5% vs.10.0%,χ2 =0.16,P =0.69).There was statistically significant difference between the two groups in median survival time (97 d vs.45 d,HR =8.934,χ2 =9.928,P <0.05).Conclusion The cinobufacini injection combined with docetaxel can effectively reduce the incidence of myelosuppression,and improve survival and local control with high safety,and the clinical effect is remarkable and can improve the prognosis of patients.

High CA-125 and CA19-9 levels in spontaneous ruptured ovarian endometriomas.

BACKGROUND: To evaluate the clinical significance of serum CA-125 and CA19-9 in women with spontaneous ruptured ovarian endometriomas. METHODS: From January 2006 to April 2015, a total of 1653 women were diagnosed with ovarian endometriomas, and 43 women were diagnosed with the spontaneous rupture of their ovarian endometrioma. In addition, 70 women diagnosed with unruptured ovarian endometriomas were chosen to serve as control subjects. Serum CA-125 and CA19-9 levels, together with the clinical materials, were collected. RESULTS: Serum CA-125, CA19-9, and the combined biomarkers were shown to be obviously elevated in the spontaneous ruptured ovarian endometrioma group (p=0.001, p=0.001, p=0.001, respectively). The AUC value for the combined biomarkers was 0.992 (95% CI, 0.981-1.000), with a high sensitivity and specificity of nearly 100% and 93.6%, respectively. Moreover, the maximum diameter of the mass was significantly (p=0.001) increased in the ruptured group. CONCLUSIONS: Serum CA-125 and CA19-9 were significantly increased in patients with spontaneous ruptured ovarian endometriomas. Moreover, the combined biomarkers were better than either CA-125 or CA19-9 alone in the diagnosis of a spontaneous rupture of the ovarian endometrioma.

Measures, Uncertainties, and Significance Test in Operational ROC Analysis.

In receiver operating characteristic (ROC) analysis, the sampling variability can result in uncertainties of performance measures. Thus, while evaluating and comparing the performances of algorithms, the measurement uncertainties must be taken into account. The key issue is how to calculate the uncertainties of performance measures in ROC analysis. Our ultimate goal is to perform the significance test in evaluation and comparison using the standard errors computed. From the operational perspective, based on fingerprint-image matching algorithms on large datasets, the measures and their uncertainties are investigated in the three scenarios: 1) the true accept rate (TAR) of genuine scores at a specified false accept rate (FAR) of impostor scores, 2) the TAR and FAR at a given threshold, and 3) the equal error rate. The uncertainties of measures are calculated using the nonparametric two-sample bootstrap based on our extensive studies of bootstrap variability on large datasets. The significance test is carried out to determine whether the difference between the performance of one algorithm and a hypothesized value, or the difference between the performances of two algorithms where the correlation is taken into account is statistically significant. Examples are provided.