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Polycystic ovarian syndrome (PCOS) is the major cause of anovulatory infertility. Since women with PCOS are often accompanied by increased body weight and hyper response to controlled ovarian stimulation, individualized gonadotropin (Gn) dose is required to achieve a therapeutic effect while minimizing the risk of ovarian hyperstimulation simultaneously. We aimed to investigate the essential role of body weight in optimizing initial Gn dosage for PCOS patients during in vitro fertilization (IVF). We retrospectively included 409 infertile PCOS patients who used gonadotropin-releasing hormone (GnRH)-antagonist fixed protocol and underwent their first cycle of IVF in West China Second University Hospital from January 2019 to June 2021. Baseline characteristics controlled ovarian stimulation parameters, and reproductive outcomes were compared between patients with different body weights and different ovarian responses. Multivariable linear regression analyses were adopted to investigate the relationship between body weight and initial Gn dosage. Receiver operating characteristic (ROC) curves were drawn to find the optimal cut-off value of body weight in predicting the starting Gn dosage so as to prevent high ovarian response (HOR). We found that luteinizing hormone (LH) level and Anti-Mullerian hormone (AMH) level were lowest in the group with body weight over 70 kg and was highest in the group with body weight less than 50 kg. Increased body weight was significantly correlated to the rise of initial Gn dosage (Beta = 0.399, t = 8.921, p < 0.001). Normal ovarian response (NOR) patients had significantly less fresh cycle cancel rate and ovarian hyperstimulation syndrome (OHSS) rate which outweighed the fewer embryos compared with HOR patients. Using ROC curves, 53.25 kg (sensitivity, 84.2%; specificity, 53.8%) and 70.5 kg (sensitivity, 58.8%; specificity, 93.0%) were identified as the optimal cut-off values to predict the initial Gn dosage of no more than 150 IU and 225 IU, respectively. In conclusion, adjusting the initial Gn dosage based on body weight is crucial to preventing ovarian hyperstimulation while not influencing reproductive outcomes for PCOS patients during IVF.

PurposeTo explore another choice for a controlled ovarian stimulation (COS) protocol that does not increase severe ovarian hyperstimulation syndrome (OHSS) risk among polycystic ovarian syndrome (PCOS) patients with specific clinical features.MethodsA retrospective study was performed. Two hundred and fifty-nine participants were divided into two groups, group 1 (fixed GnRH antagonist protocol, n = 295) and group 2 (follicular-phase GnRH agonist protocol, n = 69) according to COS protocols. The basic characteristics and laboratory indicators between these two groups were compared. The severe OHSS rate and clinical pregnancy rate were selected as indicators to evaluate the risks and benefits of the two COS protocols. Subgroup analyses for the severe OHSS rate and clinical pregnancy rate were performed based on baseline luteinizing hormone/follicle-stimulating hormone (bLH/FSH) and anti-Mullerian hormone (AMH) levels.ResultsThe severe OHSS rate was statistically higher in group 2 than in group 1 (11.6% vs. 3.7%, p = 0.008), but the biochemical pregnancy rate and clinical pregnancy rate showed no statistical difference between the groups (71.9% vs. 60.3% and 62.5% vs. 54.3%). In the higher bLH/FSH subgroup (≥1.33) and the higher serum AMH level subgroup (>3.4 ng/ml), severe OHSS incidence was statistically higher in group 2 compared to group 1, but this incidence was lower in the bLH/FSH subgroup (

In recent years, many studies have indicated that vitamin C might be negatively associated with the risk of cancer, but the actual relationship between vitamin C and cancer remains ambivalent. Therefore, we utilized a two-sample Mendelian randomization (MR) study to explore the causal associations of genetically predicted vitamin C with the risk of a variety of cancers. Single-nucleotide polymorphisms (SNPs) associated with vitamin C at a significance level of p < 5 × 10–8 and with a low level of linkage disequilibrium (LD) (r2 < 0.01) were selected from a genome-wide association study (GWAS) meta-analysis of plasmid concentration of vitamin C consisting of 52,018 individuals. The data of the GWAS outcomes were obtained from United Kingdom Biobank, FinnGen Biobank and the datasets of corresponding consortia. In the inverse-variance weight (IVW) method, our results did not support the causal association of genetically predicted vitamin C with the risk of overall cancer and 14 specific types of cancer. Similar results were observed in sensitivity analyses where the weighted median and MR-Egger methods were adopted, and heterogeneity and pleiotropy were not observed in statistical models. Therefore, our study suggested that vitamin C was not causally associated with the risk of cancer. Further studies are warranted to discover the potential protective and therapeutic effects of vitamin C on cancer, and its underlying mechanisms.

Creating an enhanced-security-level label that carries entirely distinct information in different optical states has proven challenging. Here, the authors design geminate labels by programming fluorescent cholesteric liquid crystal microdroplets to encrypt fluorescent security information behind colorful reflective patterns.

Abstract Background Unexplained recurrent spontaneous abortion (URSA) is defined as two or more consecutive pregnancy losses, generally of unknown cause; it is related to a failure of fetal–maternal immunological tolerance. Regulatory T cells (Tregs) exert immunosuppressive effects, which are essential to maintain fetal–maternal immunological tolerance and regulate immune balance. In this study, we used the specific cell-surface phenotype of CD4+CD25highCD127low/− Tregs to investigate the number and suppressive function of Tregs isolated from the peripheral blood of patients with URSA with the aim of expanding our understanding of their role in URSA. Methods We isolated a relatively pure population of peripheral CD4+CD25highCD127low/− Tregs and CD4+CD25− responder T cells (Tresps) from the patients with URSA and normal fertile nonpregnant control women via fluorescence-activated cell sorting. We compared the frequency, suppressive capacity, and forkhead box transcription factor P3 (FOXP3) expression of Tregs in the peripheral blood between patients with URSA and normal controls. Results The frequency of CD4+CD25highCD127low/− Tregs in the peripheral blood was lower in URSA patients than in the controls (P

While single-atom catalysts exhibit intriguing catalytic performances and electronic structures, syntheses are often tailored to a particular system. Here, authors report electrochemical deposition as a universal approach for the fabrication of single-atom catalysts over range of metals and supports.

Introduction: In the past two decades, urbanization in many Asian countries has led to sedentary lifestyle and overnutrition, which has set the stage for the epidemic of obesity. Those who have obesity during adolescence usually have obesity into adulthood, which causes many medical and psychological issues that can result in premature death. Recent data suggest that short sleep duration may contribute to the risk of obesity, opening a new avenue for potential intervention. The aim of this study was to describe the prevalence of sleeping time, body mass index (BMI), and fat mass in Chinese freshmen and to indicate the relationship among them. Methods: We conducted a cross-sectional study consisting of 1,938 freshmen aged from 18 to 24 years, including 684 (35.3%) men and 1,254 (64.7%) women. BMI, sleeping time, and other potential related variables were collected by questionnaire. Obesity and overweight were defined as BMI ≥28.0 and ≥24.0, respectively. All students were divided into three groups according to the tertiles of body fat percentage (Fat%), which were measured by bioelectrical impedance analysis. Sleeping time was divided into 3 categories based on the duration, 8 h per day. Results: Participants who slept longer had lower BMI and Fat%. Sex, diet control, and maternal obesity were all significantly associated with BMI or Fat% after adjustment. There were significant differences between sleeping time 8 h in both overweight group and Fat% tertiles independent of adjustment used. The significant difference between sleeping time 6–8 and >8 h only existed in overweight group, while irrelevant relation was observed in both models of obesity group. Conclusion: Longer sleeping time was associated with a lower BMI in Chinese freshmen, even after adjustment for multiple confounders. The overweight stage is a critical period of weight management intervention by changing sleeping time. If adolescents have entered the obesity stage, the effect size of lifestyle intervention might be significantly limited.

With the continuous expansion of urban cable scale and the increase in service time, the fire accident risk of cable tunnels also increases. Defects in the configuration of fire prevention measures lead to many fire accidents and seriously affect the reliability of power supply. First, the detection data of a typical tunnel fire accident are analyzed in this study. The results show that the main problems are the unreasonable installation position of fire extinguishers, the lack of fire prevention measures between intermediate joints, and the insufficient fire prevention performance of interlayer fire barriers. Then, the field test of cable tunnel fire is carried out in a cable tunnel to be put into operation. The test data show that the high-temperature area is mainly concentrated on the top of the tunnel, and the insufficient suspension height of the fire extinguisher will affect the trigger time. The energy of a short circuit accident is large, the cable burns and spreads rapidly, and the delayed triggering may lead to large fire to extinguish effectively. Comparing the simulation and test results of abnormal characteristic parameters in fire, the temperature error is less than 4%. The fire power development curve is obtained through simulation, and the burner power is set to test the fire prevention and extinguishing devices. Finally, the optimal configuration scheme of the fire anomaly data detection equipment and fire-extinguishing products is proposed. The temperature drop rate increases by 135%.

PurposeNo non-invasive method can accurately determine the presence of central cervical lymph node (CCLN) metastasis in papillary thyroid cancer (PTC) until now. This study aimed to investigate factors significantly associated with CCLN metastasis and then develop a model to preoperatively predict CCLN metastasis in fine-needle aspiration (FNA) reporting suspicious papillary thyroid cancer (PTC) or PTC without lateral neck metastasis.Patients and MethodsConsecutive inpatients who were diagnosed as suspicious PTC or PTC in FNA and underwent partial or total thyroidectomy and CCLN dissection between May 1st, 2016 and June 30th, 2018 were included. The total eligible patients were randomly divided into a training set and an internal validation set with the ratio of 7:3. Univariate analysis and multivariate analysis were conducted in the training set to investigate factors associated with CCLN metastasis. The predicting model was built with factors significantly correlated with CCLN metastasis and validated in the validation set.ResultsA total of 770 patients were eligible in this study. Among them, 268 patients had histologically confirmed CCLN metastasis, while the remaining patients did not. Factors including age, BRAF mutation, multifocality, size, and capsule involvement were found to be significantly correlated with the CCLN metastasis in univariate and multivariate analysis. A model used to predict the presence CCLN metastasis based on these factors and US CCLN status yielded AUC, sensitivity, specificity and accuracy of 0.933 (95%CI: 0.905-0.960, p < 0.001), 0.816, 0.966 and 0.914 in the training set and 0.967 (95%CI: 0.943-0.991, p < 0.001), 0.897, 0.959 and 0.936 in the internal validation set.ConclusionAge, BRAF mutation, multifocality, size, and capsule involvement were independent predictors of CCLN metastasis in FNA reporting suspicious PTC or PTC without lateral neck metastasis. A simple model was successfully built and showed excellent discrimination to distinguish patients with or without CCLN metastasis.

The association between polycystic ovary syndrome (PCOS) and endometrial cancer remains unclear. We aimed to investigate the causal association between genetically predicted PCOS and endometrial cancer risk in two ethnic groups through a two-sample Mendelian randomization (MR) approach. Our study includes 13 single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) for PCOS in Europeans, and another 13 SNPs are used as IVs for PCOS in Asians. Outcome data were obtained from the largest published meta-GWAS of European ancestry to date, as well as from the BioBank Japan Project of Asian ancestry. Our study demonstrates that genetically predicted PCOS is not causally associated with the risk of overall endometrial cancer in either Europeans or Asians (odds ratio (OR) = 0.93, 95% confidence interval (CI) = 0.85–1.01, p = 0.09 and OR = 0.98, 95% CI 0.84–1.13, p = 0.75, respectively). Subgroup analyses according to histotype further illustrate that PCOS might not be associated with the risk of either endometrioid endometrial cancer or non-endometrioid endometrial cancer in European ancestry. No pleiotropy is found in our study, and a sensitivity analysis shows similar results. Our results indicate that genetically predicted PCOS might not be associated with the risk of endometrial cancer.

This work introduces a one-step method for the preparation of layered oxide cathode materials utilizing pure Ni and Co mixed solution obtained from the waste hydrodesulfurization (HDS) catalyst. An efficient non-separation strategy with pyrometallurgical-hydrometallurgical (pyro-hydrometallurgical) process consisting of roasting and leaching is proposed. Most of the impurity metal elements such as Mo and V were removed by simple water leaching after the waste HDS catalyst was roasted with Na2CO3 at 650 °C for 2.5 h. Additionally, 93.9% Ni and 100.0% Co were recovered by H2SO4 leaching at 90 °C for 2.5 h. Then, LiNi0.533Co0.193Mn0.260V0.003Fe0.007Al0.004O2 (C–NCM) was successfully synthesized by hydroxide co-precipitation and high temperature solid phase methods using the above Ni and Co mixed solution. The final C–NCM material exhibits excellent electrochemical performance with a discharge specific capacity of 199.1 mAh g−1 at 0.1 C and a cycle retention rate of 79.7% after 200 cycles at 1 C. This novel process for the synthesis of cathode material can significantly improve production efficiency and realize the high added-value utilization of metal resources in a waste catalyst.

Epilepsy is one of the most challenging neurologic diseases confronted by human society. Approximately 30–40% of the worldwide epilepsy patients are diagnosed with drug-resistant epilepsy and require pre-surgery evaluation. Magnetoencephalography (MEG) is a unique technology that provides optimal spatial-temporal resolution and has become a powerful non-invasive imaging modality that can localize the interictal spikes and guide the implantation of intracranial electrodes. Currently, the most widely used MEG source estimation method for clinical applications is equivalent current dipoles (ECD). However, ECD has difficulties in precisely locating deep sources such as insular lobe. In contrast to ECD, another MEG source estimation method named spatio-temporal unifying tomography (STOUT) with spatial sparsity has particular advantages in locating deep sources. In this case study, we recruited a 5 year-old female patient with insular lobe epilepsy and her seizure recurred in 1 year after receiving the radiofrequency thermocoagulation (RF-TC) therapy. The STOUT method was adopted to locate deep sources for identifying the epileptic foci in epilepsy evaluation. MEG STOUT method strongly supported a stereo-electroencephalographic (SEEG)-guided RF-TC operation, and the patient reported a satisfactory therapeutic effect. This case raises the possibility that STOUT method can be used particularly for the localization of deep sources, and successfully conducted RF-TC under the guidance of MEG STOUT results.

Abstract High‐capacity layered oxide Ni‐rich cathodes are attractive to enhance the driving‐range of electric vehicles because of its preferential costs. Nevertheless, in Ni‐rich cathodes, there are still many issues such as microcracks generation along grain boundaries and interface side reaction between active substance and electrolyte, resulting in the rapidly deterioration of electrochemical property. Herein, improving the performance of Ni‐based cathodes by structural regulation is summarized. The remaining challenges and outlook are discussed as well.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic diseases among women of reproductive age. Inflammation may be involved in the pathogenesis of PCOS, but its exact relationship with PCOS remains unclear. Herein, we investigate the causal association between systemic inflammatory regulators and PCOS risk through a two-sample Mendelian randomization (MR) approach based on the latest and largest genome-wide association study (GWAS) of 41 systemic inflammatory regulators in 8293 Finnish participants and a GWAS meta-analysis consisting of 10,074 PCOS cases and 103,164 controls of European ancestry. Our results suggest that higher levels of IL-17 and SDF1a, as well as lower levels of SCGFb and IL-4, are associated with an increased risk of PCOS (OR = 1.794, 95% CI = 1.150 – 2.801, P = 0.010; OR = 1.563, 95% CI = 1.055 – 2.315, P = 0.026; OR = 0.838, 95% CI = 0.712 – 0.986, P = 0.034; and OR = 0.637, 95% CI = 0.413 – 0.983, P = 0.042, respectively). In addition, genetically predicted PCOS is related to increased levels of IL-2 and VEGF (OR = 1.257, 95% CI = 1.022 – 1.546, P = 0.030 and OR = 1.112, 95% CI = 1.006 – 1.229, P = 0.038, respectively). Our results indicate the essential role of cytokines in the pathogenesis of PCOS. Further studies are warranted to assess the possibility of these biomarkers as targets for PCOS prevention and treatment.

The growth in the global energy consumption demands an increasing use of the renewable energy sources. Nevertheless, fossil fuels are projected to remain as the dominating backbone of petrochemical and consumer industry in the coming decades. As a bridge from the fossil fuel-based to renewable fuel-based economy, chemical looping technology has been developed to achieve sustainable applications by generating highly efficient energy and products through economically viable processes. This article discusses the advances in chemical looping with a focus on the fundamentals of formulation concepts on chemical looping carriers, rationale for reactor configurations, and design consideration from the process analysis. Particularly, the carriers utilized for different chemical looping applications ranging from syngas generation to ammonia synthesis are elaborated. The reactor configurations applied for different chemical looping systems are discussed along with the essentials of the process simulation approach to system optimization. The article also describes the prospects of the future development in the chemical looping technology, and its viability and readiness for industrial deployment.

Introduction: The association between systemic sclerosis (SSc) and sexual dysfunction was controversial. Aim: To explore the impacts of SSc on sexual function, the prevalence of sexual dysfunction in patients with SSc and associated risk factors. Methods: A systematic review of all published studies was performed. Studies exploring the association between SSc and sexual function were retrieved from PubMed, Web of Science, and EBSCO. All retrieved papers were selected according to the inclusion and exclusion criteria. Main Outcome Measure: The impacts of SSc on sexual function, the prevalence of sexual dysfunction in males and females with SSc and associated risk factors. Results: A total 12 studies were included in this study. The prevalence of sexual dysfunction in SSc males and SSc females were 76.9–81.4% and 46.7–86.6%, respectively. But the direct impacts of SSc on sexual function were controversial. EULAR SSc activity score ≥3, the number of complications ≥2, and the presence of anticardiolipin antibody and anti U1 ribonucleoprotein antibody in males and resistive index (RI) and the systolic/diastolic (S/D) ratio of clitoral blood in females have potential to be SSc-specific risk factors for sexual dysfunction. Clinical Implications: Clinicians need to pay more attention to the impacts of SSc on sexual function of patients especially in those with risk factors. Strengths & Limitations: Systematically explored the prevalence of sexual dysfunction in SSc males and females, and the risk factors of sexual dysfunction for SSc were explored innovatively. However, there were some limitations in included studies prevented exploring the impacts of SSc on sexual function deeply. Conclusion: Sexual dysfunction may be an important symptom of SSc, many risk factors may be associated with sexual dysfunction in males and females with SSc.Gao R, Qing P, Sun X, et al. Prevalence of Sexual Dysfunction in People With Systemic Sclerosis and the Associated Risk Factors: A Systematic Review. Sex Med 2021;9:100392.

Chemical looping methane partial oxidation is an effective technology to produce syngas with a minimal energy penalty. Here, the authors design and develop a mesoporous silica supported nanoparticle oxygen carrier that enables a near 100% CO generation with high recyclability and substantially lower operating temperature.

Abstract Background Cultivated peanut (Arachis hypogaea L.) is an important oil and protein crop, but it has low disease resistance; therefore, it is important to reveal the number, sequence features, function, and evolution of genes that confer resistance. Nucleotide-binding site–leucine-rich repeats (NBS–LRRs) are resistance genes that are involved in response to various pathogens. Results We identified 713 full-length NBS–LRRs in A. hypogaea cv. Tifrunner. Genetic exchange events occurred on NBS–LRRs in A. hypogaea cv. Tifrunner, which were detected in the same subgenomes and also found in different subgenomes. Relaxed selection acted on NBS–LRR proteins and LRR domains in A. hypogaea cv. Tifrunner. Using quantitative trait loci (QTL), we found that NBS–LRRs were involved in response to late leaf spot, tomato spotted wilt virus, and bacterial wilt in A. duranensis (2 NBS–LRRs), A. ipaensis (39 NBS–LRRs), and A. hypogaea cv. Tifrunner (113 NBS–LRRs). In A. hypogaea cv. Tifrunner, 113 NBS–LRRs were classified as 75 young and 38 old NBS–LRRs, indicating that young NBS–LRRs were involved in response to disease after tetraploidization. However, compared to A. duranensis and A. ipaensis, fewer LRR domains were found in A. hypogaea cv. Tifrunner NBS–LRR proteins, partly explaining the lower disease resistance of the cultivated peanut. Conclusions Although relaxed selection acted on NBS–LRR proteins and LRR domains, LRR domains were preferentially lost in A. hypogaea cv. Tifrunner compared to A. duranensis and A. ipaensis. The QTL results suggested that young NBS–LRRs were important for resistance against diseases in A. hypogaea cv. Tifrunner. Our results provid insight into the greater susceptibility of A. hypogaea cv. Tifrunner to disease compared to A. duranensis and A. ipaensis.

Turnip mosaic virus (TuMV), an important pathogen that causes mosaic diseases in vegetable crops worldwide, belongs to the genus Potyvirus of the family Potyviridae. Previously, the areas of genetic variation, population structure, timescale, and migration of TuMV have been well studied. However, the codon usage pattern and host adaptation analysis of TuMV is unclear. Here, compositional bias and codon usage of TuMV were performed using 184 non-recombinant sequences. We found a relatively stable change existed in genomic composition and a slightly lower codon usage choice displayed in TuMV protein-coding sequences. Statistical analysis presented that the codon usage patterns of TuMV protein-coding sequences were mainly affected by natural selection and mutation pressure, and natural selection was the key influencing factor. The codon adaptation index (CAI) and relative codon deoptimization index (RCDI) revealed that TuMV genes were strongly adapted to Brassica oleracea from the present data. Similarity index (SiD) analysis also indicated that B. oleracea is potentially the preferred host of TuMV. Our study provides the first insights for assessing the codon usage bias of TuMV based on complete genomes and will provide better advice for future research on TuMV origins and evolution patterns.

The sugarcane streak mosaic virus (SCSMV) is the most important disease in sugarcane produced in southern China. The SCSMV encoded protein 1 (P1SCSMV) is important in disease development, but little is known about its detailed functions in plant–virus interactions. Here, the differential accumulated proteins (DAPs) were identified in the heterologous expression of P1SCSMV via a potato virus X (PVX)-based expression system, using a newly developed four-dimensional proteomics approach. The data were evaluated for credibility and reliability using qRT-RCR and Western blot analyses. The physiological response caused by host factors that directly interacted with the PVX-encoded proteins was more pronounced for enhancing the PVX accumulation and pathogenesis in Nicotiana benthamiana. P1SCSMV reduced photosynthesis by damaging the photosystem II (PSII). Overall, P1SCSMV promotes changes in the physiological status of its host by up- or downregulating the expression of host factors that directly interact with the viral proteins. This creates optimal conditions for PVX replication and movement, thereby enhancing its accumulation levels and pathogenesis. Our investigation is the first to supply detailed evidence of the pathogenesis-enhancing role of P1SCSMV, which provides a deeper understanding of the mechanisms behind virus–host interactions.

The remediation of uranium (U) through phosphate-solubilizing bacteria (PSB) is an emerging technique as well as an interesting phenomenon for transforming mobile U into stable minerals in the environment. While studies are well needed for in-depth understanding of the mechanism of U(VI) immobilization by PSB. In this study, two PSB were isolated from a U-tailing repository site. These bacterial strains (ZJ-1 and ZJ-3) were identified as Bacillus spp. by the sequence analysis of 16S ribosomal RNA (rRNA) genes. Incubation of PSB in liquid medium showed that the isolate ZJ-3 could solubilize more than 230 mg L–1 P from glycerol-3-phosphate and simultaneously removed over 70% of 50 mg L–1 U(VI) within 1 h. During this process, the rapid appearance of yellow precipitates was observed. The microscopic and spectroscopic analysis demonstrated that the precipitates were associated with U-phosphate compound in the form of saleeite-like substances. Besides, scanning electron microscopy coupled with energy-dispersive X-ray (SEM-EDS) and Fourier transform infrared spectroscopy (FTIR) analysis of the precipitates confirmed that the extracellular polymeric substances (EPS) might also play a key role in U sequestration. Furthermore, SEM and FTIR analysis revealed that part of U(VI) was adsorbed on the bacterial surface through cellular phosphate, hydroxy, carboxyl, and amide groups. This study provides new insights into the synergistic strategies enhancing U immobilization rates by Bacillus spp. that uses glycerol-3-phosphate as the phosphorus source, the process of which contributes to harmful pollutant biodegradation.

Magnesian suite (Mg-suite) rocks represent plutonic materials from the lunar crust, and their global distribution can provide critical information for the early magmatic differentiation and crustal asymmetries of the Moon. Visible and near-infrared (VNIR) spectrometers mounted on orbiters and rovers have been proven to be powerful approaches for planetary mineral mapping, which are instrumental in diagnosing Mg-suite rocks. However, due to the scarcity and diversity of Mg-suite samples, laboratory measurements with variable proportions of minerals are imperative for spectral characterization. In this study, spectroscopic investigation and petrographic study were conducted on lunar Mg-suite meteorite Northwest Africa 8687. We classify the sample as a pink spinel-bearing anorthositic norite through spectral and petrographic characteristics. The ground-truth information of the Mg-suite rock is provided for future exploration. Meanwhile, the results imply that the VNIR technique has the potential to identify highland rock types by mineral modal abundance and could further be applied in extraterrestrial samples for primary examination due to its advantage of being fast and non-destructive.

Food is the core of urban daily life and socio-economic activities but is rarely the focus of urban planning. The spatial layout of food retail outlets is important for optimizing the urban food system, improving land resource allocation, and encouraging healthy food consumption. Based on food retail POI data, this study employed kernel density estimation, road network centrality, spatial autocorrelation analysis, and locational entropy to analyze the spatial characteristics of supermarkets, produce markets, and small stores in an urban center in Beijing, and explored street coupling and supply-demand matching. The results indicated that within the study area: (1) supermarkets had an obvious “core-periphery” distribution, produce markets had a polycentric distribution, and small stores had a relatively uniform distribution; (2) road network centrality indices revealed a differentiated multi-core-edge distribution; (3) streets with high locational entropy values for supermarkets and produce markets were mostly concentrated in the central area, whereas the matching distribution of small stores was relatively balanced. From the perspective of urban planning, policy implications are proposed based on spatial and social equity, urban-rural differences, population structure and distribution status, and a resilient supply chain. The study findings have practical significance for guiding the development of urban food systems in a healthy, just, and sustainable direction, as well as rational urban land planning.

Coronavirus disease 2019 (COVID-19) is highly contagious and has affected the whole world. We seek to investigate the clinical and laboratory characteristics of COVID-19 patients in the high altitude areas of Sichuan, China. In this retrospective cohort study, a total of 67 patients with laboratory-confirmed SARS-CoV-2 infections in Sichuan's Ngawa Tibetan and Qiang Autonomous Prefecture were included from February 1, 2020, to March 2, 2020. Their clinical characteristics, as well as radiological and laboratory features, were extracted. Four (6.0%) patients were categorized as severe cases; 39 (58.2%) were non-severe cases, and 24 (35.8%) were asymptomatic cases. A total of 46 (68.7%) patients were associated with cluster infection events in this study. The most common symptoms were cough, sputum production, dyspnea, fatigue or myalgia, and headache. Seven (10.4%) patients showed leucopenia, and 20 (29.9%) patients showed lymphopenia. Lymphocyte counts and neutrophil-to-lymphocyte ratios (NPR) were different between the three groups. In total, 14 (20.9%) patients had thrombocytopenia, and prothrombin times (PT) and fibrinogen levels differed between groups. We also found significant differences in sodium, chloride and calcium levels between the three groups. Antiviral therapy did not lead to obvious adverse events or shortened durations from initial positive to subsequent negative nuclei acid tests. Advanced age, hypertension, high neutrophil count, the neutrophil-to-lymphocyte ratio, fibrinogen and lactate dehydrogenase levels were identified as independent risk factors for symptomatic cases of COVID-19. In conclusion, the symptoms of patients in high altitude areas were mild, and about one third were asymptomatic. We also identified several independent risk factors for symptomatic cases of COVID-19.

PurposeThe positivity of sentinel lymph node (SLN) metastasis is relatively low in ductal carcinoma in situ (DCIS) patients. The aim of this study was to investigate factors associated with SLN metastasis and build a model to predict the potential risk of SLN metastasis in patients with a preoperative diagnosis of DCIS.Patients and MethodsCore needle biopsy-proved DCIS patients who underwent SLN biopsy and breast surgery were retrospectively reviewed and selected. Univariate analysis was used to identify the variables correlated with SLN metastasis. A model to predict SLN metastasis was developed using a multivariate logistic regression in the training set and then validated in an internal set.ResultsA total of 407 patients with a preoperative diagnosis of DCIS were included. Upstaging to invasive/microinvasive cancer occurred in 225 patients after surgery. SLN metastasis was found in 42 patients, including 32 patients upstaging to invasive disease, 8 to microinvasive disease, and 2 pure DCIS. Tumor size based on US examination, axillary ultrasound finding, multifocality, surgery, upstaging, and Ki-67 expression were significantly related to SLN metastasis. The model incorporating tumor size, axillary ultrasound finding and multifocality yielded an AUC of 0.805 (95% CI: 0.715–0.895, p

Manipulating small water droplets on an intelligent surface with tunable superhydrophobic adhesion has attracted considerable interests because of potential applications ranging from no-loss transfer to surface chemistry but remains challenging. Herein, we present a strategy to manipulate the small water droplet on a photo-switchable mat, which is fabricated by a fluorinated linear liquid crystal polymer via electrospinning. The electrospun mat with hierarchical microstructures exhibits fast and reversible superhydrophobic adhesion change, and still remains the superhydrophobicity after pinning and removing of the water droplets for several times. Diverse erasable and rewritable arrays on the vertically placed mat are formed by pinning the small water droplets to any high adhesive position after localized light irradiation. Moreover, after evaporation of the water droplets containing aggregation-induced emission materials, the mat exhibits bright fluorescence upon faint UV irradiation to indicate the trace with the same pattern as the original droplets. Such photo-switchable superhydrophobic mats would provide an open tunable surface for microdroplets manipulation.

Narcissus degeneration virus (NDV), narcissus late season yellows virus (NLSYV) and narcissus yellow stripe virus (NYSV), which belong to the genus Potyvirus of the family Potyviridae, cause significant losses in the ornamental value and quality of narcissus. Several previous studies have explored the genetic diversity and evolution rate of narcissus viruses, but the analysis of the synonymous codons of the narcissus viruses is still unclear. Herein, the coat protein (CP) of three viruses is used to analyze the viruses’ phylogeny and codon usage pattern. Phylogenetic analysis showed that NYSV, NDV and NLSYV isolates were divided into five, three and five clusters, respectively, and these clusters seemed to reflect the geographic distribution. The effective number of codon (ENC) values indicated a weak codon usage bias in the CP coding region of the three narcissus viruses. ENC-plot and neutrality analysis showed that the codon usage bias of the three narcissus viruses is all mainly influenced by natural selection compared with the mutation pressure. The three narcissus viruses shared the same best optimal codon (CCA) and the synonymous codon prefers to use codons ending with A/U, compared to C/G. Our study shows the codon analysis of different viruses on the same host for the first time, which indicates the importance of the evolutionary-based design to control these viruses.

Chemical looping combustion (CLC) and chemical looping reforming (CLR) are innovative technologies for clean and efficient hydrocarbon conversion into power, fuels, and chemicals through cyclic redox reactions. Metal oxide materials play an essential role in the chemical looping redox processes. During reduction, the oxygen carriers donate the required amount of oxygen ions for hydrocarbon conversion and product synthesis. In the oxidation step, the depleted metal oxide oxygen carriers are replenished with molecular oxygen from the air while heat is released. In recent years, there have been significant advances in oxygen carrier materials for various chemical looping applications. Among these metal oxide materials, iron-based oxygen carriers are attractive due to their high oxygen-carrying capacity, cost benefits, and versatility in applications for chemical looping reactions. Their reactivity can also be enhanced via structural design and modification. This review discusses recent advances in the development of oxygen carrier materials and the mechanisms of hydrocarbon conversion over these materials. These advances will facilitate the development of oxygen carrier materials for more efficient chemical looping technology applications. Keywords: Chemical looping, Oxygen carrier, Hydrocarbon conversion, Ionic diffusion, Mechanism

Introduction: The purpose of the study was to describe lipid profile and explore pathogenetic role of LDL-c on hypertension in patients with Cushing’s disease (CD). Hypertension is a common feature in patients with CD. Previous study found low-density lipoprotein cholesterol (LDL-c) uptake in vascular cells might be involved in vascular remodeling in patients with CD. Therefore, we evaluated the relationship between lipid profile and the blood pressure in patients with CD. Methods: This retrospective study included 84 patients referred to Huashan Hospital for the evaluation and diagnosis of CD from January 2012 to December 2013. All subjects had detailed clinical evaluation by the same group of endocrinology specialists to avoid subjective influences. Results: We found that high LDL-c patients had significant higher body mass index (BMI), systolic blood pressure (SBP), cholesterol (CHO), triglyceride (TG), and apolipoproteinB (apoB) (P < 0.05). An association was detected between SBP values and lipids profile including CHO, TG, LDL-c, apolipoproteinA (apoA), apoB and lipoprotein(a) (LP(a)). After adjustment for all covariates, the LDL-c remained positively associated with SBP. In patients with or without taking statins, patients with LDL-c ≥3.37 mmol/L had higher SBP than patients with LDL-c

Geospatial data sharing is an inevitable requirement for scientific and technological innovation and economic and social development decisions in the era of big data. With the development of modern information technology, especially Web 2.0, a large number of geospatial data sharing websites (GDSW) have been developed on the Internet. GDSW is a point of access to geospatial data, which is able to provide a geospatial data inventory. How to precisely identify these data websites is the foundation and prerequisite of sharing and utilizing web geospatial data and is also the main challenge of data sharing at this stage. GDSW identification can be regarded as a binary website classification problem, which can be solved by the current popular machine learning method. However, the websites obtained from the Internet contain a large number of blogs, companies, institutions, etc. If GDSW is directly used as the sample data of machine learning, it will greatly affect the classification precision. For this reason, this paper proposes a method to precisely identify GDSW by combining multi-source semantic information and machine learning. Firstly, based on the keyword set, we used the Baidu search engine to find the websites that may be related to geospatial data in the open web environment. Then, we used the multi-source semantic information of geospatial data content, morphology, sources, and shared websites to filter out a large number of websites that contained geospatial keywords but were not related to geospatial data in the search results through the calculation of comprehensive similarity. Finally, the filtered geospatial data websites were used as the sample data of machine learning, and the GDSWs were identified and evaluated. In this paper, training sets are extracted from the original search data and the data filtered by multi-source semantics, the two datasets are trained by machine learning classification algorithms (KNN, LR, RF, and SVM), and the same test datasets are predicted. The results show that: (1) compared with the four classification algorithms, the classification precision of RF and SVM on the original data is higher than that of the other two algorithms. (2) Taking the data filtered by multi-source semantic information as the sample data for machine learning, the precision of all classification algorithms has been greatly improved. The SVM algorithm has the highest precision among the four classification algorithms. (3) In order to verify the robustness of this method, different initial sample data mentioned above are selected for classification using the same method. The results show that, among the four classification algorithms, the classification precision of SVM is still the highest, which shows that the proposed method is robust and scalable. Therefore, taking the data filtered by multi-source semantic information as the sample data to train through machine learning can effectively improve the classification precision of GDSW, and comparing the four classification algorithms, SVM has the best classification effect. In addition, this method has good robustness, which is of great significance to promote and facilitate the sharing and utilization of open geospatial data.

The subjective inner experience of mental imagery is among the most ubiquitous human experiences in daily life. Elucidating the neural implementation underpinning the dynamic construction of mental imagery is critical to understanding high-order cognitive function in the human brain. Here, we applied a frequency-tagging method to isolate the top-down process of speech mental imagery from bottom-up sensory-driven activities and concurrently tracked the neural processing time scales corresponding to the two processes in human subjects. Notably, by estimating the source of the magnetoencephalography (MEG) signals, we identified isolated brain networks activated at the imagery-rate frequency. In contrast, more extensive brain regions in the auditory temporal cortex were activated at the stimulus-rate frequency. Furthermore, intracranial stereotactic electroencephalogram (sEEG) evidence confirmed the participation of the inferior frontal gyrus in generating speech mental imagery. Our results indicate that a disassociated neural network underlies the dynamic construction of speech mental imagery independent of auditory perception.

In order to understand how these studies are evolving to respond to COVID-19 and to facilitate the containment of COVID-19, this paper accurately extracted the spatial and topic information from the metadata of papers related to COVID-19 using text mining techniques, and with the extracted information, the research evolution was analyzed from the temporal, spatial, and topic perspectives. From a temporal view, in the three months after the emergence of COVID-19, the number of published papers showed an obvious growth trend, and it showed a relatively stable cyclical trend in the later period, which is basically consistent with the development of COVID-19. Spatially, most of the authors who participated in related research are concentrated in the United States, China, Italy, the United Kingdom, Spain, India, and France. At the same time, with the continuous spread of COVID-19 in the world, the distribution of the number of authors has gradually expanded, showing to be correlated with the severity of COVID-19 at a spatial scale. From the perspective of topic, the early stage of COVID-19 emergence, the related research mainly focused on the origin and gene identification of the virus. After the emergence of the pandemic, studies related to the diagnosis and analysis of psychological health, personal security, and violent conflict are added. Meanwhile, some categories are most closely related to the control and prevention of the epidemic, such as pathology analysis, diagnosis, and treatment; epidemic situation and coping strategies; and prediction and assessment of epidemic situation. In most time periods, the majority of studies focused on these three categories.

Broad bean wilt virus 2 (BBWV-2), which belongs to the genus Fabavirus of the family Secoviridae, is an important pathogen that causes damage to broad bean, pepper, yam, spinach and other economically important ornamental and horticultural crops worldwide. Previously, only limited reports have shown the genetic variation of BBWV2. Meanwhile, the detailed evolutionary changes, synonymous codon usage bias and host adaptation of this virus are largely unclear. Here, we performed comprehensive analyses of the phylodynamics, reassortment, composition bias and codon usage pattern of BBWV2 using forty-two complete genome sequences of BBWV-2 isolates together with two other full-length RNA1 sequences and six full-length RNA2 sequences. Both recombination and reassortment had a significant influence on the genomic evolution of BBWV2. Through phylogenetic analysis we detected three and four lineages based on the ORF1 and ORF2 nonrecombinant sequences, respectively. The evolutionary rates of the two BBWV2 ORF coding sequences were 8.895 × 10−4 and 4.560 × 10−4 subs/site/year, respectively. We found a relatively conserved and stable genomic composition with a lower codon usage choice in the two BBWV2 protein coding sequences. ENC-plot and neutrality plot analyses showed that natural selection is the key factor shaping the codon usage pattern of BBWV2. Strong correlations between BBWV2 and broad bean and pepper were observed from similarity index (SiD), codon adaptation index (CAI) and relative codon deoptimization index (RCDI) analyses. Our study is the first to evaluate the phylodynamics, codon usage patterns and adaptive evolution of a fabavirus, and our results may be useful for the understanding of the origin of this virus.

In order to improve the diagnosis accuracy of chlorophyll content in maize canopy, the remote sensing image of maize canopy with multiple growth stages was acquired by using an unmanned aerial vehicle (UAV) equipped with a spectral camera. The dynamic influencing factors of the canopy multispectral images of maize were removed by using different image segmentation methods. The chlorophyll content of maize in the field was diagnosed. The crop canopy spectral reflectance, coverage, and texture information are combined to discuss the different segmentation methods. A full-grown maize canopy chlorophyll content diagnostic model was created on the basis of the different segmentation methods. Results showed that different segmentation methods have variations in the extraction of maize canopy parameters. The wavelet segmentation method demonstrated better advantages than threshold and ExG index segmentation methods. This method segments the soil background, reduces the texture complexity of the image, and achieves satisfactory results. The maize canopy multispectral band reflectance and vegetation index were extracted on the basis of the different segmentation methods. A partial least square regression algorithm was used to construct a full-grown maize canopy chlorophyll content diagnostic model. The result showed that the model accuracy was low when the image background was not removed (Rc2 (the determination coefficient of calibration set) = 0.5431, RMSEF (the root mean squared error of forecast) = 4.2184, MAE (the mean absolute error) = 3.24; Rv2 (the determination coefficient of validation set) = 0.5894, RMSEP (the root mean squared error of prediction) = 4.6947, and MAE = 3.36). The diagnostic accuracy of the chlorophyll content could be improved by extracting the maize canopy through the segmentation method, which was based on the wavelet segmentation method. The maize canopy chlorophyll content diagnostic model had the highest accuracy (Rc2 = 0.6638, RMSEF = 3.6211, MAE = 2.89; Rv2 = 0.6923, RMSEP = 3.9067, and MAE = 3.19). The research can provide a feasible method for crop growth and nutrition monitoring on the basis of the UAV platform and has a guiding significance for crop cultivation management.

The content of chlorophyll, an important substance for photosynthesis in plants, is an important index used to characterize the photosynthetic rate and nutrient grade of plants. The real-time rapid acquisition of crop chlorophyll content is of great significance for guiding fine management and differentiated fertilization in the field. This study used the method of continuous wavelet transform (CWT) to process the collected visible and near-infrared spectra of a corn canopy. This task was conducted to extract the valuable information in the spectral data and improve the sensitivity of chlorophyll content assessment. First, a Savitzky–Golay filter and standard normal variable processing were applied to the spectral data to eliminate the influence of random noise and limit drift on spectral reflectance. Second, CWT was performed on the spectral reflection curve with 10 frequency scales to obtain the wavelet energy coefficient of the spectral data. The characteristic bands related to chlorophyll content in the spectral data and the wavelet energy coefficients were screened using the maximum correlation coefficient and the local correlation coefficient extrema, respectively. A partial least-square regression model was established. Results showed that the characteristic bands selected via local correlation coefficient extrema in a wavelet energy coefficient created a detection model with optimal accuracy. The determination coefficient (Rc2) of the calibration set was 0.7856, and the root-mean-square error (RMSE) of the calibration set (RMSEC) was 3.0408. The determination coefficient (Rv2) of the validation set is was 0.7364, and the RMSE of the validation set (RMSEV) was 3.3032. Continuous wavelet transform is a process of data dimension enhancement which can effectively extract the sensitive variables from spectral datasets and improve the detection accuracy of models.

The analysis of chlorophyll concentration based on spectroscopy has great importance for monitoring the growth state and guiding the precision nitrogen management of potato crops in the field. A suitable data processing and modeling method could improve the stability and accuracy of chlorophyll analysis. To develop such a method, we collected the modelling data by conducting field experiments at the tillering, tuber-formation, tuber-bulking, and tuber-maturity stages in 2018. A chlorophyll analysis model was established using the partial least-square (PLS) algorithm based on original reflectance, standard normal variate reflectance, and wavelet features (WFs) under different decomposition scales (21–210, Scales 1–10), which were optimized by the competitive adaptive reweighted sampling (CARS) algorithm. The performances of various models were compared. The WFs under Scale 3 had the strongest correlation with chlorophyll concentration with a correlation coefficient of −0.82. In the model calibration process, the optimal model was the Scale3-CARS-PLS, which was established based on the sensitive WFs under Scale 3 selected by CARS, with the largest coefficient of determination of calibration set (Rc2) of 0.93 and the smallest Rc2−Rcv2 value of 0.14. In the model validation process, the Scale3-CARS-PLS model had the largest coefficient of determination of validation set (Rv2) of 0.85 and the smallest root–mean–square error of cross-validation (RMSEV) value of 2.77 mg/L, demonstrating good prediction capability of chlorophyll concentration. Finally, the analysis performance of the Scale3-CARS-PLS model was measured using the testing data collected in 2020; the R2 and RMSE values were 0.69 and 3.36 mg/L, showing excellent applicability. Therefore, the Scale3-CARS-PLS model could be used to analyze chlorophyll concentration. This study indicated the best decomposition scale of continuous wavelet transform and provided an important support method for chlorophyll analysis in the potato crops.

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

Austronesian languages such as Sasak and Javanese have a pattern of morphological nasal substitution, where nasals alternate with homorganic oral obstruents—except that [s] is described as alternating with [ɲ], not with [n]. This appears to be an abstract morphophonological relation between [s] and [ɲ] where other parts of the paradigm have a concrete homorganic relation. Articulatory ultrasound data were collected of productions of [t, n, ʨ, ɲ], along with [s] and its nasal counterpart from two languages, from 10 Sasak and 8 Javanese speakers. Comparisons of lingual contours using a root mean square analysis were evaluated with linear mixed-effects regression models, a method that proves reliable for testing questions of phonological neutralization. In both languages, [t, n, s] exhibit a high degree of articulatory similarity, whereas postalveolar [ʨ] and its nasal counterpart [ɲ] exhibited less similarity. The nasal counterpart of [s] was identical in articulation to [ɲ]. This indicates an abstract, rather than concrete, relationship between [s] and its morphophonological nasal counterpart, with the two sounds not sharing articulatory place in either Sasak or Javanese.

The large high-power solid lasers, such as the National Ignition Facility (NIF) of America and the Shenguang-III (SG-III) laser facility of China, can output over 2.1 MJ laser pulse for the inertial confinement fusion (ICF) experiments. Because of the enhancement of operating flux and the expansion of laser driver scale, the problem of contamination seriously influences their construction period and operation life. During irradiation by intense laser beams, the contaminants on the metallic surface of beam tubes can be transmitted to the optical surfaces and lead to damage of optical components. For the high-power solid-state laser facilities, contamination control focuses on the slab amplifiers, spatial filters, and final-optical assemblies. In this paper, an effective solution to control contaminations including the whole process of the laser driver is put forward to provide the safe operation of laser facilities, and the detailed technical methods of contamination control such as washing, cleanliness metrology, and cleanliness protecting are also introduced to reduce the probability of laser-induced damage of optics. The experimental results show that the cleanliness level of SG-III laser facility is much better to ensure that the laser facility can safely operate at high energy flux.