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Currently, China's soybean self-sufficiency rate is only 15%, highlighting the soybean crisis and the supply chain risks that pose a major threat to China's food security. Thus, it has become imperative to step up efforts to boost soybean production capacity while promoting the green and sustainable development of regional farmland ecosystems. In this context, the present study comprehensively investigated the effects of intercropping and nitrogen application rate on soybean yield, as well as the changes in gradients generated by different levels of nitrogen application. Based on six consecutive years of maize–soybean intercropping planting patterns, the inter-root soils of soybeans were collected at the flowering stage and evaluated for soil nitrogen content, nitrogen-assimilating enzyme activities, and microbial community composition of soybean, which were correlated with yield, to clarify the main pathways and modes of intercropping effects. The N2 level (80 kg·ha−1) was favourable for higher yield. In comparison to monocropping, the intercropping reduced yield by 9.65–13.01%, photosynthetic characteristics by 1.33–7.31%, and plant nitrogen-assimilating enzyme activities by 8.08–32.01% at the same level of N application. Likewise, soil urease and catalase activities were reduced by 9.22 and 1.80%, while soil nitrogen content declined by an average of 6.38%. Gemmatimonas and Bradyrhizobium enrichment significantly increased soil nitrogen content, photosynthetic characteristics, and soybean yield, while it was reduced by Candidatus_Udaeobacter and Candidatus_Solibacte enrichment. The results of this study provide a theoretical basis for further optimising maize–soybean intercropping, which is crucial for enhancing the agricultural production structure and improving the overall soybean production capacity. [ABSTRACT FROM AUTHOR]

With mounting demand for high-quality agricultural products and the relentless exploitation of arable land resources, finding sustainable ways to safely cultivate food crops is becoming ever more important. Here, we investigated the effects of the integrated cropping technique "straw return + intercropping" on the soil aggregates as well as the microbial biomass carbon (MBC) content, enzyme activities and microbial diversity in soils of maize and soybean crops. Our results show that in comparison to straw removal and monoculture, straw return and intercropping increase the rhizosphere's MBC content (59.10%) of soil, along with urease (47.82%), sucrase (57.14%), catalase (16.14%) and acid phosphatase (40.66%) activities as well as the microbial diversity under maize and soybean. Under the same straw treatment, the yield of maize when intercropped surpassed that when grown in monoculture, with the land equivalent ratio of the intercropping treatment under straw return being highest. Overall, the intercropping of maize and soybean is beneficial for the healthy development of sustainable agriculture in the black soil region of northeast China, especially when combined with straw return to fields. [ABSTRACT FROM AUTHOR]

Ocean salinity is a pivotal aspect of the ocean dynamic environment. Spaceborne L-band radiometers, like SMOS, Aquarius, and SMAP, offer a comprehensive approach to mapping out large-scale ocean salinity patterns. As China prepares for the launch of the Chinese Ocean Salinity and Soil Moisture Mission (COSM), it is essential to delve into the intricacies of radio frequency interference (RFI) detection, localization, and mitigation. The L-band, in particular, is highly susceptible to RFI. COSM will carry not one but two advanced instruments: a 2-D L-band aperture synthesis microwave radiometer (LASMR) and a 1-D L-C-K band microwave imager combined active and passive (MICAP). This article delves into the current state of RFI research, particularly in recent years, and introduces a fusion method that integrates MICAP and LASMR for more accurate RFI detection, localization, and mitigation. This fusion method relies on an algorithm that constructs localization and intensity objective functions based on the principle of least squares. By optimizing these functions, we can pinpoint the precise location and intensity of RFI. The resulting minimum mitigation residual offers a blueprint for achieving optimal RFI detection, localization, and mitigation. The experimental results, achieved in a controlled anechoic chamber, confirm that this fusion method—when weighted by variance—boosts detection accuracy, refines localization precision, and minimizes residual mitigation errors compared with standalone MICAP or LASMR techniques. [ABSTRACT FROM AUTHOR]

China contributed nearly one-fifth of the world maize production over the past few years. Mapping the distributions of maize cropland in China is crucial to ensure global food security. Nonetheless, 10 m maize cropland maps in China are still unavailable, restricting the promotion of sustainable agriculture. In this paper, we collect numerous samples to produce annual 10-m maize cropland maps in China from 2017 to 2021 with a machine learning based classification framework. To overcome the temporal variations of plants, the proposed framework takes Sentinel-2 sequence images as input and utilizes deep neural networks and random forest as classifiers to map maize in a zone-specific way. The generated maps have an overall accuracy (OA) spanning from 0.87 to 0.95 and the maize-cultivated areas estimated by the maps are highly consistent with the records in statistical yearbooks (R2 varying from 0.83 to 0.95). To the best of our knowledge, this is the first annual 10-m maize maps across China, which largely facilitates the sustainable agriculture development in China dominated by smallholder farmlands. [ABSTRACT FROM AUTHOR]

As the major maize-cultivated areas, the one-season cropland of China is increasingly threatened by rapid urbanization and soybean rejuvenation. Quantifying the area changes of maize cropland is crucial for both food and energy security. Nonetheless, due to the lack of survey data related to planting types, long-term and fine-grained maize cropland maps in China dominated by small-scale farmlands are still unavailable. In this paper, we collect 75,657 samples based on field surveys and propose a deep learning-based method according to the phenology information of maize. With the generalization capability, the proposed method produces maize cropland maps with a resolution of 30 m from 2013 to 2021 in the one-season planting areas of China. The maize-cultivated areas derived from the maps are highly consistent with the data recorded by statistical yearbooks (R2 = 0.85 on average), which indicates that the produced maps are reliable to facilitate the research on food and energy security. [ABSTRACT FROM AUTHOR]

The effective use of nutrient-rich crop straw is an important way to use resources efficiently and to sustain agricultural development. This meta-analysis study collected and analyzed the data of 6788 observations published in 238 peer-reviewed papers to investigate differences in soil C-N fractions and yields of paddy soils under different straw-return amounts. This large dataset was also used to quantify the degree of influence of factors such as climate characteristics, soil properties, N fertilizer application rates, straw-rotting agent addition, rice varieties, and straw return methods. The results showed that straw return amounts improved soil alkaline-hydrolysable N (7%), total N (10%), organic C (11%), the C:N ratio (8%), rice N accumulation (12%), and overall yield (18%). The most significant effect was in northeast China fields for total soil nitrogen (TN) content and yield with increases of 13% and 22%, respectively. We also found more effective N utilization and a greater rice yield when 220–260 kg ha−1 N fertilizer was applied with 20–30 kg ha−1 straw-rotting agent with the total amount of straw return. These findings have important implications for choosing appropriate conditions and field management practices and to improve rice yield in China. [ABSTRACT FROM AUTHOR]

To solve the problems of difficult treatment of desulfurized gypsum and overmining of limestone, a kind of lime/gypsum flue gas desulfurization (FGD) collaborative desulfurized gypsum resource utilization process (LCS) was proposed. The system mainly includes the LCS-LFGD (lime/gypsum flue gas desulfurization system), LCS-C (desulfurized gypsum reduction calcining process), and carbon monoxide-coupled activated carbon reduction of SO2 to sulfur process (LCS-S). Taking a typical wet FGD unit of 300 MW power plant in China as an example, the limestone/gypsum flue gas desulfurization system (L-FGD) process was compared with the LCS by using the method of life cycle assessment and life cycle cost (LCC). The result shows that the overall environmental impact of the LCS is 0.2913. The environmental impacts of LCS-LFGD, LCS-C, and LCS-S were 0.1322, 0.1543, and 0.0048, respectively. Both LCS-LFGD and LCS-C are the key processes in this case study, and electricity consumption and coal gas consumption are the key substances in each key process. LCC analysis showed that although the initial investment of LCS was 4.32 × 106 USD ∼5.76 × 106 USD more compared with L-FGD, the running cost of LCS was 1.41 × 106 USD per year lower compared with L-FGD. Besides, the cost of ore mining, the quality of calcined products, and environmental protection policy will affect the financial cost of the process. [ABSTRACT FROM AUTHOR]

Primary porosity is an important parameter in studies of reservoir and porosity evolution. However, the applicable conditions for the few existing mathematical models of primary porosity have yet to be clarified. A mathematical model based on the packing texture was proposed by the authors in a previous study; however, the proposed model was only applicable to well-sorted and well-rounded modern beach sands. In this study, the model was modified and applied to poorly-sorted and poorly-rounded braided river sands. The applicable conditions for the proposed models and the previous empirical formula were investigated based on 41 modern braided river sand samples from the Kuqa River in the Tarim Basin and 40 modern beach sand samples from eastern China. Modern sands can be divided into three types based on the particle size distribution. Modified mathematical formulas were derived for each type of sands. The constant parameters in the mathematical model, such as the filling coefficients, embedment coefficients, and packing void ratios were obtained through experiments and through linear fitting. Based on the mathematical model, the errors between the measured and the calculated primary porosities ranged from −3% to 3% for the modern braided sands and from −2% to 2% for the modern beach sands. Using the empirical formula, the primary porosity errors in the modern braided river sands were large, and the formula could not be appropriately applied except to well-sorted and well-rounded modern beach sands. Compared with the modified mathematical model, the original mathematical model could not be applied well to braided river sands owing to the additional errors caused by e f1. The modified mathematical model based on the packing texture was more credible when applied to poorly-sorted and angular braided river sands; further, it was applicable to all types of unconsolidated sands. • A modified model based on packing texture is applied to braided river sands. • Braided river sands are divided into three types by grain size distribution. • The effect of grain shape on primary porosity error is avoided by the new models. • The modified model is found to be more credible over a wider application range. [ABSTRACT FROM AUTHOR]

In this study, characterises of the microbial community structures of three typical Chinese liquor Daqu, as well as different kinds of light flavour Daqu were investigated using nested PCR-denaturing gradient gel electrophoresis (DGGE). The results showed that microbial diversity was considerably different, and the microfloral compositions were highly variable among various Daqu. Lactic acid bacteria, which accounted for 30.95 % of all identified bacteria, were dominant in all Daqu samples, whereas Bacillus species were also predominant in the Luzhou (14.8 %) and Langjiu Daqu (18.2 %). Citrobacter and Burkholderia were first identified in light flavour Daqu. Aspergillus was the dominant moulds, and the non- Saccharomyces yeast species, Saccharomycopsis fibuligera, Wallemia sebi, Wallemia muriae, and Pichia subpelliculosa, were the dominant yeasts. Rasamsonia, Galactomyces, Geotrichum and Wallemia were first identified using nested PCR-DGGE. Cluster analysis indicated that the microbial community structures of different Daqu samples exhibited some differences. These may be ascribed to the different peak production temperatures, raw material constituents and microhabitats around the liquor enterprises. The current study provides insights into the microbial community structures of three typical Daqu samples, and may facilitate the development of starter cultures for manufacturing Chinese liquor. [ABSTRACT FROM AUTHOR]

Yellow catfish (Pelteobagrus fulvidraco) is an important freshwater cultured fish in China. Enteric septicemia of catfish (ESC) and red-head disease (RHD), caused by Edwardsiella ictaluri , result in huge economic losses to yellow catfish farming industry. Rapid and handy detection of E. ictaluri is a pressing demand for diagnosis. In this study, we developed rapid, convenient, sensitive and accurate detection methods RPA (recombinase polymerase amplification), real-time RPA (based on real-time fluorescent detection) and RPA-LFD (combining RPA with lateral flow dipsticks (LFD)), targeting the conserved sequence of serC gene in E. ictaluri. The RPA-LFD and real-time RPA methods could achieve detection within 30 min at 38 °C. All the three methods had high analytical sensitivity (102 copies/μl) and were 10 times more sensitive than that in general PCR. They were highly specific for identification of E. ictaluri. 24 samples of yellow catfish from farm were examined through RPA, real-time RPA and RPA-LFD methods, the results showed the consistency with the general PCR detection. In short, RPA, real-time RPA and RPA-LFD methods characterize rapid, simple, sensitive and accurate detection and demonstrate great potential for diagnosis of E. ictaluri disease in fish farms. • Developed RPA, RPA-LFD and qRPA methods for Edwardsiella ictaluri detection. • RPA, RPA-LFD and qRPA detected E. ictaluri genome DNA at 38 °C in 10–30 min. • The detection limit of RPA, RPA-LFD and real-time RPA methods was 102 copies/μl. • The RPA-LFD method achieved rapid detection of E. ictaluri without professional equipment. [ABSTRACT FROM AUTHOR]

Abstract: Phosphorus (P) in soils has an important influence on the development and productivity of wetland. The objective of this study was to investigate the distribution, bioavailability and seasonal variations of inorganic phosphorus (IP) in soils of Yeyahu Wetland. The results showed that the concentration of Ca-bound P (Ca-P) remained the main occurrence in all IP fractions despite the season, at the same time the Al-bound P (Al-P) was always the lowest IP fraction despite the season. Al-P and Fe-bound P (Fe-P) concentration were all reached the highest value in May and the lowest in November, which was opposite to the occluded P (Oc-P) fraction. The notable higher Oc-P concentration in November observed in this study was probably due to the decomposition of plants and the subsequently releasing of oxides to soils. Ca-P didn''t change much with season variations. Exchangeable P (Ex-P) and Oc-P were all positively correlated with soil moisture content and organic matter content, but Al-P was negatively correlated with these two soil properties. As a stable form, Ca-P was not associated with soil properties. Al-P, Fe-P and Ca-P might contribute to the storage of P in studied wetland with the principle component analysis results. The concentration rank order of the bio-available P in soils was generally as follows: Olsen-P > Algal available P (AAP) > Water soluble P (WSP) > Readily desorbed P (RDP). Olsen-P was positively correlated with Ex-P and Oc-P, and it was thought to be a more suitable indicator for bio-available P in soils. [Copyright &y& Elsevier]

Tarim Basin contains long and continuous records of marine and terrestrial paleogeographic evolution in the northern hemisphere. The Silurian Kalpintage Formation provides a window through which siliciclastic coasts can be reconstructed and examined. Seventeen measured sections of superbly-exposed Sishichang area in northwest Tarim Basin, are studied to interpret depositional system, establish sequence stratigraphic framework, reconstruct paleogeographic evolution, and discuss heterogeneity of variable systems. Ten sedimentary facies have been identified within the stratigraphic framework, comprising shoreface-, shelf-, tidal bar-, and tidal complex-dominated depositional systems. Different depositional systems show considerable variability in sedimentary and diagenetic features. Shoreface- and tidal bar-dominated sandstones tend to have high ductile lithic content, which induces severe mechanical compaction and formation of pseudomatrix. Tidal complex-dominated sandstones tend to have high quartz content, contributing to intensive quartz overgrowth. Sedimentary facies determine the fundamental differences of sandstone reservoirs in composition, sedimentary texture and structure, and diagenesis intensifies the differences of sandstone reservoirs in their quality and heterogeneity. The results provide understandings for the development, evolution, and heterogeneity of depositional systems at northwestern Tarim Basin, and serve as a foundation for future hydrocarbon exploration of Silurian Kalpintage Formation and other coastal marine reservoirs in the world. • Shoreface-, tidal bar-, and tidal complex-dominated systems are newly interpreted. • Ten sedimentary facies constitute two stratigraphic sequences. • Diagenetic processes are closely associated with sedimentary facies. • Heterogeneity is resulted from interaction between sedimentary facies and diagenesis. [ABSTRACT FROM AUTHOR]

Clinical experience suggests increased incidences of neonatal jaundice when air quality worsens, yet no studies have quantified this relationship. Here we reports investigations in 25,782 newborns showing an increase in newborn's bilirubin levels, the indicator of neonatal jaundice risk, by 0.076 (95% CI: 0.027–0.125), 0.029 (0.014–0.044) and 0.009 (95% CI: 0.002–0.016) mg/dL per μg/m3 for PM2.5 exposure in the concentration ranges of 10–35, 35–75 and 75–200 μg/m3, respectively. The response is 0.094 (0.077–0.111) and 0.161 (0.07–0.252) mg/dL per μg/m3 for SO2 exposure at 10–15 and above 15 μg/m3, respectively, and 0.351 (0.314–0.388) mg/dL per mg/m3 for CO exposure. Bilirubin levels increase linearly with exposure time between 0 and 48 h. Positive relationship between maternal exposure and newborn bilirubin level is also quantitated. The jaundice−pollution relationship is not affected by top-of-atmosphere incident solar irradiance and atmospheric visibility. Improving air quality may therefore be key to lowering the neonatal jaundice risk. Air pollution has become a major health risk in China. Here Zhang et al. report that maternal and neonatal exposure to particulate matter increases the risk of neonatal jaundice based on the study of 25,782 newborns born in China between 2014 and 2017. [ABSTRACT FROM AUTHOR]

• We estimated maize yields at the county level in China using a novel deep learning approach. • The over-complete dictionary matrix was proposed to enhance the representation of inter-province spatial diversity. • We used the margin-constraint optimizing formula to eliminate the distraction of unbalanced distributed records. • The proposed new approach reduced the large-scale maize yield estimation error. Accurate and timely maize yield monitoring from satellite imagery is in great demand in developing countries. The spatial heterogeneity deprived of the large territory of China makes it a challenge. In this article, we developed a novel deep learning model for maize yield prediction at the county level based on multiple satellite data. The two-stage feature learning structure integrated data from disparate sources, enhancing feature representation. The discriminative features were optimized from two levels: the dictionary matrix learned the spatial diversity of the provinces, and the improved optimizing formulation fit the distribution of the unbalanced records. The cross-validation results showed that our approach could explain 82 % of the variation in maize yield, achieving state-of-the-art. The model was robust when predicting the future, with the average root-mean-square error of 1006 kg/ha and the mean-absolute-percentage error of 17.1 %. The ability of early maize yield prediction clarifies the tremendous application value, showing the data from the first two months can already explain 75.6 % of yield variation. It was the first effort to improve county-level maize yield prediction in China, providing a potential framework for advancing the use of multi-source datasets for maize yield estimating. [ABSTRACT FROM AUTHOR]

Knowledge of the number of building stories (NoS) is critical for understanding and regulating the urban development process. Existing approaches often transform building heights into numbers of stories using a specific empirical story-height coefficient, e.g., 3 meters for 1 story. However, the story heights of different buildings might differ for various reasons, such as different functional types within a city, differences in urban planning regulations among cities, or the regulations in different construction years. Based on a theoretical analysis and empirical statistics regarding the changes in vertical building information in seasonal composite images, we present a novel method for directly estimating the NoS in individual buildings from optical images. Specifically, four seasonal composite Sentinel-2 images taken within a year are utilized to estimate the NoS of each building with a modified object-detection network to make full use of vertical building information. The proposed method is called the Stories number EstimAtion from Seasonal composite images with an Object detection Network (SEASONet) method. Both theoretical analysis and empirical statistics are used to determine why seasonal composite optical images can effectively provide vertical building information. To validate the performance of the proposed method, we collect data from 61 Chinese cities with various building types, train the model with data from 47 cities (1365 998 buildings) and quantitatively test the model using data from the remaining 14 cities (246 584 buildings). In addition, M 3 Net using ZY-3 multiview images for the pixel-level estimation of building heights is adapted for comparison. The experimental results show that SEASONet achieves lower mean absolute error (MAE) and root mean square error (RMSE) values than M 3 Net over all 14 cities used for testing. Ablation experiments show that the four seasonal composite images are the keys for improving the estimation of the number of stories in high-rise buildings. A comparison with the results of two state-of-the-art methods that use empirical coefficients to convert building height to story number further confirms the superiority of the proposed method, especially its effectiveness in estimating the number of stories in high-rise buildings. • Geometric relationship among the Sun, building height and date of an image. • Empirical statistics on seasonal changes of building shadows in China. • Seasonal composite Sentinel-2 images for building story number estimation. [ABSTRACT FROM AUTHOR]

The southwestern Tarim Basin in western China is one of the most dynamic areas of basin-range coupling in the Cretaceous. This study presents the first attempt to simulate the tectono-sedimentary evolution of the southwestern Tarim Basin during the Cretaceous in three dimensions using a basin and landscape dynamics modeling approach. We have simulated the evolution of the southwestern Tarim Basin and the West Kunlun Orogenic Belt (WKOB) during the Cretaceous over a period of 79 million years. Apart from numerous local fans and streams perpendicular to the mountain front, a major paleo-drainage system paralleling to WKOB was developed within the depression during the Early Cretaceous. It subsequently evolved into two drainage systems by a topographic high within the depression in the Late Cretaceous, forming two river channels flowing to the northwest and southeast, respectively. During the Cretaceous the southwestern Tarim Basin was infilled by sediments of up to 3500 m thick. WKOB contributed the bulk sediments to the basin (75.53%), whereas the Markit Slope to the north contributed 24.23%. The sedimentary centers were located mainly in the areas of the southeastern Wupoer and the northwestern Qibei structural belts. The closure of the Paleo-Tethys Ocean towards the end of Triassic around 200 Ma caused the development of paleouplifts in the region and a subsequent overlapping of the Jurassic by the Cretaceous strata. During the Cretaceous, the tectonic movement was relatively quiescent. Only the topmost sediments were subject to erosion at the end of the Cretaceous, as a result of the subduction of the Neo-Tethys Ocean to the south. Paleoclimate and/or precipitation controlled the denudation rate of the orogenic belts while tectonic subsidence controlled the thickness of sediments within the basin. This finding provides new insights for quantitatively evaluating geomorphic and landscape evolution and source-to-sink systems in the southwestern Tarim Basin. • Using Badlands to provide new insights on tectono-sedimentary evolution. • Paleoclimate and precipitation appear to have controlled the denudation rate of the orogenic belts. • Differential tectonic uplift and subsidence of the orogenic belts and depression controlled the amount of sedimentation. • The sedimentary provenances were sourced from the West Kunlun Orogenic Belt (75%) and the Markit Slope (24%). • Simulation reveals a main paleo-drainage system evolved into a two-channel river system. [ABSTRACT FROM AUTHOR]

The mudrock log-derived compaction curve is a significant tool for investigating the primary migration of hydrocarbon, predicting fluid overpressure, estimating formation erosion thicknesses and restoring the buried history and paleo-structure of a basin. However, the presence of kerogen in organic-rich shales can create typically high logging values of the acoustic transit time. Thus, the abnormally high values of the acoustic transit time for organic-rich rocks may not truly reflect the porosity variations of subsurface rocks, leading to great uncertainties in the understanding of the mudstone compaction and a certain amount of error in the abnormal fluid pressure estimation when using the mudrock log-derived compaction curve. Therefore, it is necessary to recalibrate the mudstone compaction curve by eliminating the increment of the acoustic transit time caused by the kerogen content of organic-rich mudstones. Taking the southwest Ordos Basin as an example, this paper presents a new equivalent volume model based on the composition of organic-rich shale in which the kerogen content is also considered. Based on the quantitative relationship between the rock composition and the acoustic transit time, a quantitative formula for calculating the acoustic transit time increment caused by the kerogen is derived. This formula shows that the increment depends not only on the organic content but also on the occurrence state, pore size, pore fluid composition and other factors. X-ray diffraction (XRD) data were used to determine the main mineral composition of the mudstone and to calculate the acoustic transit time of the rock skeleton. Then, the mudstone compaction curve in the Zhenjing area was calibrated by combining the measured porosity and total organic carbon (TOC) of the mudstone based on the correction formula. The compaction characteristics varied significantly between before and after the calibration. The slope of the normal compaction trend (NCT) line decreased by 30–55%, and the acoustic transit time deviation from the NCT in the undercompaction interval decreased significantly. The overpressure at the maximum burial depth estimated by the equivalent depth method is in better agreement with the results obtained by numerical simulation after the calibration, and the porosity determined from the well log after the calibration is also closer to the true measured value. The method proposed in this paper is of great significance for improving the reliability and accuracy of compaction research on organic-rich mudstones, especially for the accurate estimation of abnormal pressure in the source rock layer. Additionally, it can be used as an effective reference for mudstone compaction studies in similar geological settings areas or basins. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the proportion and clinical characteristics of obstructive sleep apnea (OSA) in Chinese patients with polycystic ovarian syndrome (PCOS) through home sleep apnea test (HSAT) and to evaluate the reproductive endocrine and metabolic characteristics in these patients., Methods: The study was a cross-sectional analysis of infertile PCOS patients who underwent sleep respiratory monitoring between January and December 2019 at Peking University Third Hospital Reproductive Medical Center and respiratory and critical care medicine department. The prevalence of OSA, body mass index (BMI), menstruation, reproductive endocrine, and metabolic characteristics were collected in patients with PCOS. Logistic regression was performed to identify significant relationships among these factors and OSA., Results: Amont 328 patients with PCOS, the prevalence of OSA was 40% (131/328), and six cases (5%) were severe. Univariate analysis showed that BMI and blood pressure were significantly higher in patients with OSA than in those without OSA (P < 0.05), whereas the anti-Mullerian hormone was lower than that in patients without OSA. In terms of glucose and lipid metabolism, the glycosylated hemoglobin (HbA1c), fasting plasma glucose, and fasting insulin levels were significantly higher in patients with PCOS and comorbid OSA than in those without OSA (all P < 0.05). Patients with OSA also had higher triglyceride, low-density lipoprotein cholesterol, and high-sensitivity C-reactive protein levels and lower high-density lipoprotein cholesterol levels (P < 0.05). Logistic regression analysis revealed that higher BMI, elevated serum testosterone, and decreased high-density lipoprotein cholesterol (HDL-C) are correlated with occurrence of OSA (P < 0.05)., Conclusion: OSA in patients with PCOS was associated with multiple alterations in indexes of reproductive endocrine and metabolic disorders., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Purpose: This study aimed to explore the health-related quality of life (HRQoL) and associated variables in children with chronic myeloid leukemia in the chronic phase (CML-CP) receiving tyrosine kinase inhibitors (TKIs)., Methods: A cross-sectional questionnaire was given to children with CML and their parents, who were < 18 years at diagnosis of CML and < 19 years at study. The questionnaire comprised three parts, including demographic information, clinical information, and the Chinese version of Pediatric Quality of Life Inventory ™ (PedsQL ™ ) Cancer Module 3.0 as HRQoL questionnaire., Results: A total of 240 respondents data were analyzed. Multivariate analysis showed that children with symptoms had worse pain (- 10.2; P < 0.001), nausea (- 17.3; P = 0.001), more treatment anxiety (- 7.2; P = 0.005), worse self-assessment appearance (- 7.1; P = 0.001), communication problems (- 6.4; P = 0.001), and worse HRQoL (- 7.0; P < 0.001). Children with mothers having low educational qualifications had worse pain (- 6.0; P = 0.014), more worried about future (- 5.4; P = 0.042), worse cognition problems (- 7.1; P = 0.002), worse communication problems (- 5.5; P = 0.008), and worse HRQoL (- 4.3; P = 0.005). Younger age children at study had more procedural anxiety (2.7; P = 0.001), treatment anxiety (- 1.7; P = 0.014) and cognition problem (3.6; P < 0.001), as well as worse HRQoL (1.8; P = 0.008). However, older age children at diagnosis were more worried about future (- 2.8; P = 0.001), worse self-assessment appearance (- 1.1; P = 0.042) and worse HRQoL (- 1.8; P = 0.007). Other variables significantly associated with worse HRQoL included female gender, rural household registration and their father's low education level. Parents reported more gastrointestinal disorders, were worried about the future and had less concern about appearance than their children., Conclusions: Female gender, older age at diagnosis, younger age at study, lower mother's education level, and TKI-related symptoms are significantly associated with worse HRQoL in Children with CML. Children and their parents have different priorities in the HRQoL., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Exposure to air pollution has been suggested to be associated with an increased risk of women's health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women's exposure to air pollutants using the monitor located nearest to each woman's residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women's exposure to air pollutants (PM 2.5 , CO, O 3 , and SO 2 ) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM 2.5 , CO, O 3 , and SO 2 ) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m -3 increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m -3 , 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m -3 , 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m -3 , and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m -3 . The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women's exposure to air pollutants (PM 2.5 , CO, O 3 , and SO 2 ) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.