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The accuracy of landslide susceptibility prediction (LSP) mainly depends on the precision of the landslide spatial position. However, the spatial position error of landslide survey is inevitable, resulting in considerable uncertainties in LSP modeling. To overcome this drawback, this study explores the influence of positional errors of landslide spatial position on LSP uncertainties, and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error. This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example. The 30–110 m error-based multilayer perceptron (MLP) and random forest (RF) models for LSP are established by randomly offsetting the original landslide by 30, 50, 70, 90 and 110 m. The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics. Finally, a semi-supervised model is proposed to relieve the LSP uncertainties. Results show that: (1) The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors, and are lower than those of original data-based models; (2) 70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices, thus original landslides with certain position errors are acceptable for LSP; (3) Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.

Abstract The interplay of topology, magnetism, and correlations gives rise to intriguing phases of matter. In this study, through state-of-the-art angle-resolved photoemission spectroscopy, density functional theory, and dynamical mean-field theory calculations, we visualize a fourfold degenerate Dirac nodal line at the boundary of the bulk Brillouin zone in the antiferromagnet YMn2Ge2. We further demonstrate that this gapless, antiferromagnetic Dirac nodal line is enforced by the combination of magnetism, space-time inversion symmetry, and nonsymmorphic lattice symmetry. The corresponding drumhead surface states traverse the whole surface Brillouin zone. YMn2Ge2 thus serves as a platform to exhibit the interplay of multiple degenerate nodal physics and antiferromagnetism. Interestingly, the magnetic nodal line displays a d-orbital dependent renormalization along its trajectory in momentum space, thereby manifesting Hund’s coupling. Our findings offer insights into the effect of electronic correlations on magnetic Dirac nodal lines, leading to an antiferromagnetic Hund nodal line.

Abstract Purpose This study evaluates the efficacy of intrauterine hCG perfusion for RIF, as defined by ESHRE 2023 guidelines, highlighting hCG as a cost-effective alternative to other immunotherapies, especially suitable for less developed regions. It aims to clarify treatment guidance amidst previous inconsistencies. Methods This meta-analysis, registered with PROSPERO (CRD42024443241) and adhering to PRISMA guidelines, assessed the efficacy and safety of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in RIF. Comprehensive literature searches were conducted through December 2023 in major databases including PubMed, Web of Science, Embase, the Cochrane Library, and key Chinese databases, without language restrictions. Inclusion and exclusion criteria were strictly aligned with the 2023 ESHRE recommendations, with exclusions for studies lacking robust control, clear outcomes, or adequate data integrity. The risk of bias was evaluated using the Newcastle-Ottawa Scale, ROBINS-I, and RoB2 tools. Data analysis was performed in R using the ‘meta’ package, employing both fixed and random effect models to account for study variability. Subgroup analyses by dosage, volume, hCG concentration, timing of administration, and type of embryo transfer were conducted to deepen insights, enhancing the reliability and depth of the meta-analysis in elucidating the role of hCG perfusion in RIF treatments. Results Data from 13 studies, comprising six retrospective and six prospective studies from single centers, along with one multi-center RCT, totaling 2,157 participants, were synthesized to evaluate the effectiveness of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in patients with RIF. Significant improvements were observed in clinical pregnancy and embryo implantation rates across various dosages, timing of administration, and embryo developmental stages, without impacting miscarriage rates. Notably, the most significant efficacy within subgroups occurred with a 500 IU dosage and perfusion parameters of ≤ 500µL volume and ≥ 2 IU/µL concentration. Additionally, a limited number of studies showed no significant increases in ectopic pregnancy or multiple pregnancy rates, and a modest improvement in live birth rates, although the small number of these studies precludes definitive conclusions. Conclusions The analysis suggests that intrauterine hCG perfusion probably enhances embryo implantation, clinical pregnancy, and live birth rates slightly in RIF patients. Benefits are indicated with a dosage of 500 IU and a maximum volume of 500µL at concentrations of at least 2 IU/µL. However, substantial heterogeneity from varying study types and the limited number of studies necessitate cautious interpretation. These findings underscore the need for more rigorously designed RCTs to definitively assess the efficacy and safety.

Abstract Background Chayote is a high economic crop in the Cucurbitaceae family, playing an important role in food production, disease treatment and the production of degradable materials in industries. Due to the harsh environment, such as high temperature, drought and frost, some chayote resources are gradually disappearing. It is crucial to collect, characterize, and conserve chayote resources. However, the genetic diversity of chayote resources in China has not been studied so far. Results In this study, we collected 35 individuals of chayote from 14 provinces in China. Subsequently, we found 363,156 SSR motifs from the chayote genome and designed 57 pairs of SSR primers for validation. Out of these, 48 primer pairs successfully amplified bands, with 42 of them showing polymorphism. These 42 primer pairs detected a total of 153 alleles, averaging 3.64 alleles per locus. The polymorphic information content ranged from 0.03 to 0.78, with an average value of 0.41, indicating a high level of polymorphism. Based on the analysis using STRUCTURE, PCoA, and UPGMA methods, the 35 chayote individuals were divided into two major clusters. Through further association analysis, 7 significantly associated SSR markers were identified, including four related to peel color and three related to spine. Conclusions These molecular markers will contribute to the analysis of genetic diversity and genetic breeding improvement of chayote in the future.

Abstract Targeting ferroptosis-related pathway is a potential strategy for treatment of lung cancer (LC). Consequently, exploration of ferroptosis-related markers is important for treating LC. We collected LC clinical data and mRNA expression profiles from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained through FerrDB database. Expression analysis was performed to obtain differentially expressed FRGs. Diagnostic and prognostic models were constructed based on FRGs by LASSO regression, univariate, and multivariate Cox regression analysis, respectively. External verification cohorts GSE72094 and GSE157011 were used for validation. The interrelationship between prognostic risk scores based on FRGs and the tumor immune microenvironment was analyzed. Immunocytochemistry, Western blotting, and RT-qPCR detected the FRGs level. Eighteen FRGs were used for diagnostic models, 8 FRGs were used for prognostic models. The diagnostic model distinguished well between LC and normal samples in training and validation cohorts of TCGA. The prognostic models for TCGA, GSE72094, and GSE157011 cohorts significantly confirmed lower overall survival (OS) in high-risk group, which demonstrated excellent predictive properties of the survival model. Multivariate Cox regression analysis further confirmed risk score was an independent risk factor related with OS. Immunoassays revealed that in high-risk group, a significantly higher proportion of Macrophages_M0, Neutrophils, resting Natural killer cells and activated Mast cells and the level of B7H3, CD112, CD155, B7H5, and ICOSL were increased. In conclusion, diagnostic and prognostic models provided superior diagnostic and predictive power for LC and revealed a potential link between ferroptosis and TIME.

Abstract Autophagy is a conserved, catabolic process essential for maintaining cellular homeostasis. Malfunctional autophagy contributes to neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we report a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and brain LC3-interactome reveals roles of neuronal autophagy in targeting proteins of multiple cellular organelles/pathways, including endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) for degradation. By combining phosphoproteomics and functional analysis in human and mouse neurons, we uncovered a function of neuronal autophagy in controlling cAMP-PKA and c-FOS-mediated neuronal activity through selective degradation of the protein kinase A - cAMP-binding regulatory (R)-subunit I (PKA-RI) complex. Lack of AKAP11 causes accumulation of the PKA-RI complex in the soma and neurites, demonstrating a constant clearance of PKA-RI complex through AKAP11-mediated degradation in neurons. Our study thus reveals the landscape of autophagy degradation in human neurons and identifies a physiological function of autophagy in controlling homeostasis of PKA-RI complex and specific PKA activity in neurons.

Abstract Objective IR emerges as a feature in the pathophysiology of PCOS, precipitating ovulatory anomalies and endometrial dysfunctions that contribute to the infertility challenges characteristic of this condition. Despite its clinical significance, a consensus on the precise mechanisms by which IR exacerbates PCOS is still lacking. This study aims to harness bioinformatics tools to unearth key IR-associated genes in PCOS patients, providing a platform for future therapeutic research and potential intervention strategies. Methods We retrieved 4 datasets detailing PCOS from the GEO, and sourced IRGs from the MSigDB. We applied WGCNA to identify gene modules linked to insulin resistance, utilizing IR scores as a phenotypic marker. Gene refinement was executed through the LASSO, SVM, and Boruta feature selection algorithms. qPCR was carried out on selected samples to confirm findings. We predicted both miRNA and lncRNA targets using the ENCORI database, which facilitated the construction of a ceRNA network. Lastly, a drug-target network was derived from the CTD. Results Thirteen genes related to insulin resistance in PCOS were identified via WGCNA analysis. LASSO, SVM, and Boruta algorithms further isolated CAPN2 as a notably upregulated gene, corroborated by biological verification. The ceRNA network involving lncRNA XIST and hsa-miR-433-3p indicated a possible regulatory link with CAPN2, supported by ENCORI database. Drug prediction analysis uncovered seven pharmacological agents, most being significant regulators of the endocrine system, as potential candidates for addressing insulin resistance in PCOS. Conclusions This study highlights the pivotal role of CAPN2 in insulin resistance within the context of PCOS, emphasizing its importance as both a critical biomarker and a potential therapeutic target. By identifying CAPN2, our research contributes to the expanding evidence surrounding the CAPN family, particularly CAPN10, in insulin resistance studies beyond PCOS. This work enriches our understanding of the mechanisms underlying insulin resistance, offering insights that bridge gaps in the current scientific landscape.

CO2 emissions prediction plays a key role in atmospheric environment management and regional sustainable development. Taking the Four Provinces of Mountains and Rivers (Henan, Hebei, Shandong, and Shanxi) in China as an example, the Autoregressive Integrated Moving Average Model (ARIMA) and random forest importance analysis were used to calculate the future trend of the CO2 emission–influencing factors and obtain the main influencing factors. Based on the above, BP neural network (BPNN), support vector machine (SVR), and random forest (RF) models were used to predict the future apparent CO2 emissions of the four provinces. The results show that, in general, population, coal consumption, and per capita GDP are the main factors influencing CO2 emissions. The RF model has the best prediction performance; for instance, RMSE (81.86), R2 (0.905), and MAE (64.69). The prediction results show that the total apparent CO2 emissions of the Four Provinces of Mountains and Rivers will peak in 2028 (with a peak of about 4500 Mt). The apparent CO2 emissions of Henan, Hebei, and Shandong Province peaked in 2011 (with a peak of about 654 Mt), 2013 (with a peak of about 657 Mt), and 2020 (with a peak of about 1273 Mt), respectively. Shanxi is forecast to reach its peak (with a peak of about 2486 Mt) in 2029. The apparent CO2 emissions of all provinces showed an obvious downward trend after reaching their peak. Henan, Hebei Shandong, and Shanxi showed a significant downward trend in 2018, 2023, and 2032, respectively.

Impatiens walleriana is of great ornamental value, but it may suffer growth inhibition when it is exposed to sub-low temperatures for a long time. Although there are many studies on the positive effect of arbuscular mycorrhizal fungi (AMF) on cold tolerance, whether AMF could alleviate the sub-low temperature injury of Impatiens walleriana is unknown. In this experiment, two kinds of Impatiens walleriana were inoculated with AMF and treated with sub-low temperature to evaluate the physiological and biochemical characteristics of Impatiens walleriana seedlings. The results showed that the plant height of ‘Super Elf (Rose red)’ under stress and inoculated with 50 g and 100 g AMF compared to sub-low temperature treatment increased by 4.94% and 19.01%, and the plant height of ‘Super Elf (red)’ under stress and inoculated with 50 g and 100 g AMF increased by 3.11% and 17.03%, respectively. Compared to sub-low temperature treatment, the stem diameter of ‘Super Elf (Rose red)’ under stress and inoculated with 50 g and 100g AMF increased by 47.17% and 50.94%, respectively. The same mitigation effect was observed in ‘Super Elf (red)’. Compared with sub-low temperature treatment, Fv’/Fm’, Y(II) and qP of ‘Super Elf (Rose red)’ inoculated with 50 g AMF significantly increased by 75.76%, 52.17%, and 43.48%, while NPQ significantly decreased by 2.96 times, whereas the corresponding values for ‘Super Elf (Rose red)’ inoculated with 100 g AMF increased by 87.88%, 82.61%, and 65.22%, while NPQ significantly increased by 1.47 times. Compared with sub-low temperature treatment, Fv’/Fm’, Y(II) and qP of ‘Super Elf (red)’ inoculated with 50 g AMF significantly increased by 53.49%, 28.95%, and 29.31%, while NPQ significantly decreased by 0.84 times, whereas the corresponding values for ‘Super Elf (red)’ inoculated with 100 g AMF increased by 53.49%, 23.68%, and 22.41%, while NPQ significantly increased by 3.48 times. Meanwhile, ‘Super Elf (Rose red)’ and ‘Super Elf (red)’ vaccination with AMF reduced the levels of O2− and H2O2 accumulation in leaves at sub-low temperatures and mitigated the extent of damage to cell membrane lipid peroxidation. Therefore, AMF inoculation can improve the tolerance of plants to sub-low temperatures.

Abstract Background Chayote is an underutilized species of Cucurbitaceae. It is rich in nutrients such as protein, minerals, phenols and its extracts have anti-cardiovascular and anti-cancer effects, making it a versatile plant for both medicinal and culinary purposes. Although research on its root tuber is limited, they are rich in starch and have a structure similar to that of potatoes, cassava, and sweet potatoes. Therefore, they can serve as potential substitutes for potatoes and offer promising prospects as agricultural and industrial resources. However, the physiological and cellular mechanisms of chayote root tuber formation and development are still unclear. Results In this study, we observed the growth habit of ‘Tuershao’ (high yield of root tuber). The results revealed that the tuber enlargement period of ‘Tuershao’ lasts approximately 120 days, with the early enlargement phase occurring during 0–30 days, rapid enlargement phase during 30–90 days, and maturation phase during 90–120 days. Physiological indicators demonstrated a gradual increase in starch content as the tuber developed. The activities of sucrose synthase (SUS) and invertase (VIN) showed a consistent trend, reaching the highest level in the rapid expansion period, which was the key enzyme affecting tuber expansion. Moreover, the special petal like structure formed by the secondary phloem and secondary xylem of the tuber resulted in its enlargement, facilitating the accumulation of abundant starch within the thin-walled cells of this structure. Principal component analysis further confirmed that starch content, SUS and VIN activities, as well as the concentrations of calcium (Ca), iron (Fe), and selenium (Se), were the major factors influencing tuber development. Moreover, the low temperature environment not only promoted the growth of ‘Tuershao’ tubers but also enhanced the accumulation of nutritional substances. Conclusions These findings contribute to a deeper understanding of the formation and developmental mechanisms of ‘Tuershao’ tubers, providing valuable guidance for cultivation practices aimed at improving crop yield.

A rational landslide susceptibility mapping (LSM) can minimize the losses caused by landslides and enhance the efficiency of disaster prevention and reduction. At present, frequency ratio (FR), information value (IV), and certainty factor (CF) are widely used to quantify the relationships between landslides and their causative factors; however, it remains unclear which method is the most effective. Moreover, existing landslide susceptibility zoning methods lack full automation; thus, the results are full of uncertainties. To address this, the FR, IV, and CF were used to analyze the relationship between landslides and causative factors. Subsequently, three distinct sets of models were developed, namely random forest models (RF_FR, RF_IV, and RF_CF), support vector machine models (SVM_FR, SVM_IV, and SVM_CF), and logistic regression models (LR_FR, LR_IV, and LR_CF) using the analysis results as inputs. A Gaussian mixture model (GMM) was introduced as a new method for landslide susceptibility zoning, classifying the LSM into five distinct levels. An accuracy evaluation of the models and a rationality analysis of the LSM indicated that the FR is superior to the IV and CF in quantifying the relationship between landslides and causative factors. Additionally, the quantile method was employed as a comparative approach to the GMM, further validating the effectiveness of the GMM. This research contributes to more effective and efficient LSM, ultimately enhancing landslide prevention measures.

Light is one of the important environmental factors affecting the growth and development of facility vegetables. In this experiment, we investigated the effects of different light intensities on the growth, nutritional quality and flavonoid accumulation of celery under hydroponic and full LED light conditions. Four light intensities of 40, 100, 200, or 300 µmol·m-2·s-1 were set up in the experiment, and three harvest periods were set up on the basis of different light intensities, which were 15, 30, and 45 d after treatment (labeled as S1, S2, and S3, respectively). The results showed that the plant height and aboveground biomass of celery increased with the increase of light intensity, and the light intensity of 200 μmol·m-2·s-1 was beneficial to increase the contents of chlorophyll, carotenoids, total phenols, vitamin C, cellulose, total flavones and apigenin in celery. During the S1-S3 period, the activities of PAL, CHS, CHI and ANS increased gradually under 200 and 300 μmol·m-2·s-1 light intensity treatments, and the activities of FNS and CHS enzymes were the highest under 200 μmol·m-2·s-1 light intensity treatment. The expression and ANS activity of Ag3GT, a key gene for anthocyanin synthesis, reached the maximum value at 300 μmol·m-2·s-1, and the expression level and FNS activity of AgFNS, a key gene for apigenin synthesis, reached a maximum value at 200 μmol·m-2·s-1. In general, the anthocyanin content was the highest at 300 μmol·m-2·s-1, and the apigenin content was the highest at 200 μmol·m-2·s-1. In conclusion, light intensity of 200 µmol·m-2·s-1 treatment was more favorable for celery growth and nutrient synthesis.

Immune cell membrane coated nanomedicine was developed to neutralize cytokines via receptor-ligand interaction, which showed potential for the treatment of inflammatory bowel disease (IBD). However, cell membrane isolation and re-assembly process involved protein loss and spatial disorder, which reduced the sequestration efficiency towards cytokines. In addition, oral administration of probiotics was accepted for IBD treatment via gut microbiota modulation, but most probiotics showed weak adhesion to intestine mucosa and were quickly expelled from gastrointestinal tract. Herein, an intracellular hydrogelation technology was proposed to construct gelated peritoneal macrophage (GPM) with intact membrane structure, resulting from the avoidance of membrane isolation and re-assembly process. GPM efficiently neutralized multiple cytokines in vitro and in vivo to ameliorate inflammatory Caco-2 ​cells and colitis rats by regulating oxidative stress, inflammation level and intestinal barrier repair. Moreover, the probiotics (Nissle1917, EcN) were easily attached on GPM surface through specific recognition, to construct GPM-EcN conjugate for GPM hitchhiking delivery to colitis tissue. Conjugation process of GPM and EcN showed no damage on bacterial physiological function. Due to the chemical attachment on inflammatory cells, GPM carried the attached EcN hand-in-hand to accumulate in the colitis tissue of IBD rat, and enhanced intestine retention time of EcN in comparison to free EcN, which improved bacterial diversity, and shifted the microbiota community and acid metabolites to an anti-inflammatory phenotype. This study transferred the hydrogel synthesis from in vitro to intracellular cytoplasm, and came to a new insight of conjugating strategy of GPM and probiotics for hitchhiking delivery and combined anti-IBD treatment.

Purpose: To evaluate the effect of extralesional triamcinolone acetonide (TA) injection in the treatment of small chalazion (diameter ≤ 5 mm). Methods: Prospective interventional clinal study that included patients diagnosed as chalazion of small size not responding to conservative management for at least 2 weeks. All patients were treated with extralesional TA injection (4 mg). Successful resolution of a chalazion was defined as a decrease in size to 1 mm or smaller. Results: Thirty-eight patients were included in the study. The resolution was achieved in 33 (87%) patients. Nineteen (50%) patients had complete resolution after the first injection, and 13 (34.2%) patients had complete resolution after the second injection. Chalazion near the lower punctum needed more times of injections than those elsewhere (P = 0.02). Conclusions: Extralesional TA injection is effective in the treatment of both primary and recurred small chalazia. It is a simple and cost-saving procedure and can be considered an alternative first-line treatment for small chalazion.

Abstract To better implement the Strategy of Rural Revitalization, it is essential to characterize the rural settlements and understand their roles in the socio-environmental interactive system. This paper is hence aimed at achieving such a study using different spatial analysis such as kernel density and spatial autocorrelation (SA) and modeling approaches, e.g., simple and multiple linear regression analyses taking Jiangxi, a province in China as an example. Remote sensing, topographic and socioeconomic data were employed for this purpose. Through these analyses, it is found that the rural settlements in the study area appear to have a spatial distribution pattern of “dense north and sparse south” as an “F” type, and are quantitatively characterized as low elevations, flat terrain, high river and road densities, rich cultivated land resources and susceptible to the impact of urban radiation with a R2 of 0.520–0.748. Based on this understanding, a new inequality evaluation indicator of rural development, i.e., socio-environmental evaluation index (SEI), was developed. Areas with SEI lower than 0.40 should be given a priority to implement the revitalization strategy in the province. This index can also be extended to study of the imbalance of rural development in other regions and countries.

Three different photoperiod treatments (8 h/16 h, 12 h/12 h, and 16 h/8 h of light/dark) were implemented to investigate the impact of growth, biomass, and phytochemical accumulation in two celery cultivars, namely ‘Zhangqiubaoqin’ (BQ) and ‘Hongchenghongqin’ (HQ), within a plant factory setting. The findings demonstrated that the 12 h/12 h photoperiod stimulated the growth of both celery varieties, while the 16 h/8 h photoperiod hindered their growth. Notably, the root length, shoot fresh and dry weight, plant height, chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid content of both celery cultivars exhibited the highest values under the 12 h/12 h light and dark photoperiod. Furthermore, the effective quantum yields of the electron transfer ratio (ETR) and the photochemical quenching coefficient (qP) displayed superior value under the 12 h/12 h light and dark photoperiod. With the exception of cellulose, the levels of soluble sugar, soluble protein, total phenol, and vitamin C were also highest under the 12 h/12 h photoperiod for both cultivars. BQ demonstrated the highest total apigenin content under the 12 h/12 h (light and dark) photoperiod, whereas HQ exhibited the highest content under the 16 h/8 h (light and dark) photoperiod. In summary, celery plants exhibited optimal performance and biomass production when subjected to the 12 h/12 h (light and dark) photoperiod treatment.

Alzheimer's disease (AD) is a prevalent and deleterious neurodegenerative disorder characterized by an irreversible and progressive impairment of cognitive abilities as well as the formation of amyloid β (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. By far, the precise mechanisms of AD are not fully understood and no interventions are available to effectively slow down progression of the disease. Autophagy is a conserved degradation pathway that is crucial to maintain cellular homeostasis by targeting damaged organelles, pathogens, and disease-prone protein aggregates to lysosome for degradation. Emerging evidence suggests dysfunctional autophagy clearance pathway as a potential cellular mechanism underlying the pathogenesis of AD in affected neurons. Here we summarize the current evidence for autophagy dysfunction in the pathophysiology of AD and discuss the role of autophagy in the regulation of AD-related protein degradation and neuroinflammation in neurons and glial cells. Finally, we review the autophagy modulators reported in the treatment of AD models and discuss the obstacles and opportunities for potential clinical application of the novel autophagy activators for AD therapy.

As geographic environment is an expression of the geological settings, it is the objective of this research to explore the roles of geological background in society development, in particular, city development. Based on field trips, geological and tectonic maps, digital elevation model (DEM) and Google Earth images were utilized for this study. Simple linear and binary logistic regression (BLR) and a set of spatial analysis were applied to explore the impacts of environmental factors on city distribution and its relationship with the geological factors taking Jiangxi, China as an example. Here we show that distribution of all level of cities is surprisingly consistent with the lithospheric faults, deep-and-large faults which constitute the fundamental framework for developing the open valleys, rivers and plains that host in turn cities. This finding may provide scientists with deeper understanding and rethinking on the human-environmental interaction and decision-makers an idea where to urbanize in future.

Ovarian cancer is the most lethal gynecologic tumor, with the highest mortality rate. Numerous studies have been conducted on the treatment of ovarian cancer in the hopes of improving therapeutic outcomes. Immune cells have been revealed to play a dual function in the development of ovarian cancer, acting as both tumor promoters and tumor suppressors. Increasingly, the tumor immune microenvironment (TIME) has been proposed and confirmed to play a unique role in tumor development and treatment by altering immunosuppressive and cytotoxic responses in the vicinity of tumor cells through metabolic reprogramming. Furthermore, studies of immunometabolism have provided new insights into the understanding of the TIME. Targeting or activating metabolic processes of the TIME has the potential to be an antitumor therapy modality. In this review, we summarize the composition of the TIME of ovarian cancer and its metabolic reprogramming, its relationship with drug resistance in ovarian cancer, and recent research advances in immunotherapy.

Immune checkpoint blockade (ICB) has rapidly transformed the treatment paradigm for various cancer types. Multiple single or combinations of ICB treatments have been approved by the US Food and Drug Administration, providing more options for patients with advanced cancer. However, most patients could not benefit from these immunotherapies due to primary and acquired drug resistance. Thus, a better understanding of the mechanisms of ICB resistance is urgently needed to improve clinical outcomes. Here, we focused on the changes in the biological functions of CD8+ T cells to elucidate the underlying resistance mechanisms of ICB therapies and summarized the advanced coping strategies to increase ICB efficacy. Combinational ICB approaches and individualized immunotherapies require further in-depth investigation to facilitate longer-lasting efficacy and a more excellent safety of ICB in a broader range of patients.

Despite numerous studies indicating an imperative role of vitamin D for reproduction, the importance of vitamin D supplementation on in vitro fertilization (IVF) outcomes remains controversial. We therefore performed this meta-analysis to investigate the IVF outcomes of vitamin D supplementation in infertile women with vitamin D deficiency. We systematically searched PubMed, Embase and the Cochrane library for identifying all relevant studies published before August 2021. Pregnancy rate was defined as the primary outcome while good quality embryo, fertilization rate, ongoing pregnancy, and miscarriage were secondary outcomes. We used Review Manager 5.3 (RevMan) to conduct meta-analysis and examined the robustness of the primary outcome by trial sequential analysis. Five studies were included in the final analysis and it suggested that vitamin D supplementation was associated with improved chemical pregnancy rate (risk ratio [RR] = 1.53, 95% confidence interval [CI] = 1.06 to 2.20, p = 0.02) but not benefited in improving clinical pregnancy rate (RR = 1.34, 95% CI = 0.81 to 2.24, p = 0.25) and all secondary outcomes. Trial sequential analysis suggested further studies are needed to confirm this conclusion. We concluded that vitamin D supplementation should be prescribed to improve chemical pregnancy in infertile women with vitamin D deficiency and more studies are required to further confirm this finding.

For crop growth monitoring and agricultural management, it is important to use hyperspectral remote sensing techniques to estimate canopy nitrogen content in a timely and accurate manner. The traditional nadir method has limited ability to assess the nitrogen trophic state of cotton shoots, which is not conducive to high-precision nitrogen inversion, whereas the multi-angle remote sensing monitoring method can effectively extract the canopy’s physicochemical information. However, multi-angle spectral information is affected by a variety of factors, which frequently causes shifts in the band associated with nitrogen uptake, and lowers the estimation accuracy. The capacity of the spectral index to estimate aerial nitrogen concentration (ANC) in cotton was therefore investigated in this work under various observation zenith angles (VZAs), and the Relief−F method was employed to select the best spectral band with weight for ANC that is insensitive to VZA. Therefore, in this study, the ability of the spectral index to estimate ANC in cotton was explored under different VZAs, and the Relief-F algorithm was used to optimize the optimal spectral band with weight for ANC that is insensitive to VZA. The angle insensitive nitrogen index (AINI) for various VZAs was calculated using the expression (R530 − R704)/(R1412 + R704). The results show that the correlation between the spectral index and the ANC chosen in this study is stronger than the correlation between off-nadir observations, and the correlation coefficients between Photochemical Reflectance Index (PRI), AINI, and ANC are highest when VZA is −20° and −50° (r = 0.866 and 0.893, respectively). Compared with the traditional vegetation index, AINI had the best correlation with ANC under different VZAs (r > 0.84), and the performance of ANC in the backscatter direction was estimated to be better than that in the forward-scatter direction. At the same time, the ANC estimation model of the optimal indices AINI and PRI was combined with the machine learning method to achieve better accuracy, and the prediction accuracy of the random forest (RF) model was R2 = 0.98 and RMSE = 0.590. This study shows that the AINI index can estimate cotton ANC under different VZAs. Simultaneously, the backscattered direction is revealed to be more conducive to cotton ANC estimation. The findings encourage the use of multi-angle observations in crop nutrient estimation, which will also help to improve the use of ground-based and satellite sensors.

Nitrate accumulation is a major factor for the secondary salinization of greenhouse soil in China. Our previous study pointed out that a low ratio of red:far-red light (R:FR) can improve salt tolerance in pakchoi under excessive nitrate stress. However, the nitrogen metabolism mechanism is still unclear. To detect the effect of a low R:FR ratio on nitrogen metabolism of pakchoi under excessive nitrate stress, two extra additions of nitrogen of 80 mmol·L−1 NO3− (H80) and 160 mmol·L−1 NO3− (H160) with/without a low R:FR ratio (R:FR = 0.7) were set, and the growth index, chlorophyll content, key enzymes in nitrogen metabolism, nitrate and glutamic acid content and NRT gene expression level of pakchoi leaves were examined. The results indicated that a low ratio of R:FR could alleviate the reduction in growth and chlorophyll content in pakchoi under high-level nitrogen stress (H80 and H160). The activity of nitrate reductase (NR), glutamine synthetase (GS) and glutamine synthetase (GOGAT) decreased under H80 and H160 conditions, except of NR with the H80 treatment. The activity of glutamate dehydrogenase (GDH) increased under H80 treatment, but decreased under H160 treatment. However, the activity of GDH decreased further by reducing the ratio of R:FR. Excessive nitrate stress increased the nitrate content, and a low R:FR ratio could inhibit nitrate accumulation. However, the change in glutamic acid content was significantly increased under a low R:FR ratio without stress. Under the high-nitrogen level treatment (H160), the use of a low ratio of R:FR increased NRT gene expression. Therefore, a low R:FR ratio (R:FR = 0.7) could effectively promote the growth of pakchoi and improve its nitrogen metabolism, thus alleviating the stress effect of a high level of nitrogen in pakchoi.

Early diagnosis of cotton verticillium wilt (VW) and accurate assessment of the disease degree are important prerequisites for preventing the large-scale development of cotton VW. Hyperspectral techniques have been widely used for monitoring the extent of plant diseases, but early detection of VW disease in cotton remains a challenge. In this study, the Boruta algorithm was used to select the key physiological characteristics (leaf temperature, chlorophyll a content, and equivalent water thickness) of cotton leaves at the early stage of VW disease, and then the Relief-F algorithm was used to select the spectral features indicating multiple “symptoms” of cotton VW disease at the early stage. In addition, a new cotton VW early monitoring indicator (CVWEI) was constructed by combining the weights of the new index and related bands using a hierarchical analysis (AHP) and entropy weighting method (EWM). The study showed that the physiological indices constructed under VW stress were better indicators of VW disease than traditional vegetation indices; CVEWI achieved a high accuracy of 95% in the test set, with a Kappa coefficient of 0.89; and the test set R2 was 0.73 and RMSE was 3.15% for monitoring disease severity, compared to the optimal classification constructed using a single spectral index. The results may provide new ideas and methods for early and accurate monitoring of VW and other fungal diseases.

Conventional treatments for ovarian cancer, including debulking cytoreductive surgery combined with carboplatin/paclitaxel-based chemotherapy, are insufficient, as evidenced by the high mortality rate, which ranks first among gynecological tumors. Therefore, there is an urgent need to develop new and effective treatment strategies. Recent evidence has shown that metabolic processes and cell behaviors in ovarian cancer are regulated by intracellular factors as well as metabolites in the tumor microenvironment (TME), which determine occurrence, proliferation, and metastasis. In this review, we describe the comprehensive landscape of metabolic cross-talk between ovarian cancer and its TME with a focus on the following four aspects: (1) intracellular metabolism based on the Warburg effect, (2) metabolism in non-tumor cells in the ovarian TME, (3) metabolic communication between tumor cells and non-tumor cells in the TME, and (4) metabolism-related therapeutic targets and agents for ovarian cancer. The metabolic cross-talk between ovarian cancer and its microenvironment involves a complex network of interactions, and interrupting these interactions by metabolic interventions is a promising therapeutic strategy.

The first successful sand-control was achieved in the Mu Us Desert by local people in the 1950–1960s, and their experience and approach have been extended to the whole Ordos and Northern China since then. The objective of this paper is to assess comprehensively the effectiveness of sand-control in 15 counties in and around Mu Us using multitemporal satellite images and socioeconomic data. After atmospheric correction, Landsat TM and OLI images were harnessed for land cover classification based on the ground-truth data and for derivation of the GDVI (generalized difference vegetation index) to extract the biophysical changes of the managed desert and desertification. Climatic, socioeconomic, environmental and spatial factors were selected for coupling analysis by multiple linear and logistic regression models to reveal the driving forces of desertification and their spatial determinants. The results show that from 1991 to 2020, 8712 km2 or 63% of the desert has been converted into pastures and shrublands with a greenness increase of 0.3509 in GDVI; the effectiveness of sand-control is favored by the rational agropastoral activities and policies; though desertification occurs locally, it is associated with both climatic and socioeconomic factors, such as wind speed, precipitation, water availability, distance to roads and animal husbandry.

Nitrate accumulation is one of the main factors of secondary soil salinization in protected horticulture in China. Previous studies have shown that a low red(R)/far-red (FR) ratio can improve the salt tolerance of plants under NaCl stress. However, the effect of a low R/FR ratio on plant growth under nitrate stress is not clear. In order to explore the effect of a low R/FR ratio on the adaptability of pakchoi under high nitrogen stress, the growth index, soluble protein content, soluble sugar content, nitrate content, nitrate reductase activity and Nia2 gene expression of pakchoi’s leaves were measured. The results showed that a high level of nitrogen (the addition of 80 mmol · L−1 NO3− (N80) and 160 mmol · L−1 NO3− (N160)) inhibited the growth of pakchoi and promoted the accumulation of osmoregulation substances and nitrate content, respectively. The reduction of the R/FR ratio under high nitrogen stress (L80) increased the fresh weight of the plants under it by 19.0%, reduced the nitrate content in the leaves by 22.7%, increased the NR activity by 29.9%, and made the Nia2 gene expression more significant, compared with N80. There was a similar mitigation effect of a low R/FR ratio under 160 mmol · L−1 excessive NO3− stress. Therefore, the reduction of the R/FR ratio can effectively control the nitrate content and improve the adaptability of pakchoi under high nitrogen stress. Thus, there is a practical application prospect for a low R/FR ratio for the production of pakchoi under a high level of nitrogen.

Star anise, rich in effective active constituents, is extensively employed in the pharmaceutical and food industries. The drying temperature can irreversibly damage these constituents. To enhance the drying quality and efficiency, this study undertook experiments using three drying methods on star anise including microwave vacuum drying, hot air drying, and a combination of microwave vacuum and hot air drying. The research examined the impacts of varying drying conditions on the drying characteristics of star anise, the moisture diffusion coefficient, and the primary component contents (anethole and shikimic acid). Models were separately established for microwave vacuum and hot air thin-layer drying kinetics including Lewis, Weibull distribution, two-term exponential, Wang, and Singh models, and a Weibull distribution model for combined microwave vacuum-hot air drying. The results indicated that drying with microwave vacuum and hot air primarily proceeded in a falling rate drying phase, whereas combined microwave vacuum and hot air drying encompassed both falling rate and constant rate stages. The effective moisture diffusion coefficients (Deff) for microwave vacuum drying and hot air drying of star anise ranged from 3.4423E-07 to 8.8239E-07 m²/s and 2.0386E-08 to 8.8239E-07 m²/s, respectively, while the Deff for combined microwave and hot air drying ranged from 2.8683E-07 to 4.8014E-07 m²/s and 7.9516E-8 to 2.0964E-7 m²/s, respectively. Evidently, segmented combined drying facilitated more convenient moisture diffusion, and both coefficients increased with microwave power and hot air temperature. During the microwave vacuum and hot air drying processes, both the Wang and Singh models and the Weibull distribution models showed good fitting effects. The Weibull distribution model could effectively predict the drying behavior of segmented microwave vacuum and hot air drying of star anise. In comparison with hot air drying time, combined microwave vacuum and hot air drying shortened the drying time by 30% to 92%. Considering quality and energy consumption, a microwave power of 2,000 W, a conversion moisture content of 30%, and a hot air drying temperature of 45°C were selected as the optimal drying parameters. Employing the combined microwave vacuum and hot air drying technique, this study, with a focus on drying efficiency and high quality, provided a scientific and theoretical foundation for the drying production of star anise, which represented a significant breakthrough in the traditional drying methods of star anise as a medicinal herb. [ABSTRACT FROM AUTHOR]