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Abstract Sleep disorders significantly impact the quality of life for many individuals, which remain largely unrecognized. It is widely believed that dietary nutrient intake plays a crucial role in promoting healthy sleep patterns. However, there is lack of research focusing on cancer survivors. This study utilized the National Health and Nutrition Examination Survey (NHANES) database to investigate the correlation between dietary nutrient intake and sleep disorders in cancer survivors. Analyzing data from 2882 cancer survivors in NHANES spanning from 2005 to 2018. Dietary nutrient intake was evaluated through two 24-h dietary recalls. Weighted multivariable logistic regression model was employed to further applied to explore the association between dietary fiber intake and sleep disorders while controlling for relevant confounding factors. Additionally, the nonlinear and dose–response relationships were explored using restricted cubic spline (RCS) regression along with smooth curve fitting and threshold effect analysis. Stratified analysis and interaction analysis were conducted to assess the consistency of the results. Univariable and multivariable analysis demonstrated that dietary fiber intake showed negative correlation with sleep disorders (P 0.05). Notably, no statistically significant interactions were observed in all subgroup analyses except poverty income ratio (PIR) (P for interaction

Abstract For a long time, the decline in lung function has been regarded as a potential factor associated with the risk of osteoporosis (OP). Although several observational studies have investigated the relationship between lung function and OP, their conclusions have been inconsistent. Given that Mendelian randomization (MR) studies can help reduce the interference of confounding factors on outcomes, we adopted this approach to explore the causal relationship between lung function and OP at the genetic level. To investigate the potential causality between lung function (FVC, FEV1, FEV1/FVC, PEF) and OP, we conducted a MR analysis employing three approaches: inverse variance weighted (IVW), MR-Egger, and weighted median. We used Cochran’s Q test to detect potential heterogeneity, MR-Egger regression to evaluate directional pleiotropy, and the MR-PRESSO method to evaluate horizontal pleiotropy. In addition, we used MR-PRESSO and MR radial methods to exclude SNPs exhibiting pleiotropic outliers. Upon identification of potential outliers, we removed them and subsequently ran MR analysis again to assess the reliability of our findings. The MR analysis suggested that there was no causal effect of lung function (FVC, PEF, FEV1/FVC, FEV1) on OP, which is consistent with the. results after excluding potential outliers using MR-PRESSO and MR radial. methods. Sensitivity analysis confirmed the reliability and consistency of these. results. The study concluded that there is no causal link between lung function and OP. The association found in observational studies might be attributable to shared risk factors.

Abstract Autophagy-mediated chemoresistance is the core mechanism for therapeutic failure and poor prognosis in breast cancer. Breast cancer chemotherapy resistance is believed to be influenced by tumor-associated macrophages (TAMs), by which C-X-C motif chemokine ligand 1 (CXCL1) is the most abundant cytokine secreted. Yet, its role in mediating autophagy-related chemoresistance is still unknown. This study aimed to explore the molecular mechanisms by which TAMs/CXCL1 induced autophagy-mediated chemoresistance in breast cancer. It was found that TAMs/CXCL1 promoted chemoresistance of breast cancer cells through autophagy activation in vitro, and CXCL1 silence could enhance the chemosensitivity of paclitaxel-resistant breast cancer cells via autophagy inhibition. A high-throughput quantitative PCR chip and subsequent target validation showed that CXCL1 induced autophagy-mediated chemoresistance by inhibiting VHL-mediated IGF1R ubiquitination. The elevated IGF1R then promoted STAT3/HMGB1 signaling to facilitate autophagy. Additionally, TAMs/CXCL1 silence improved paclitaxel chemosensitivity by suppressing autophagy in breast cancer mice xenografts, and clinical studies further linked CXCL1 to IGF1R/HMGB1 signaling, as well as shorter free survival of recurrence. Taken together, these results not only uncover the crucial role of TAMs/CXCL1 signaling in mediating breast cancer chemoresistance through enhancing autophagy, but also shed novel light on the molecular mechanism of IGF1R/STAT3/HMGB1 pathway in regulating autophagy and its impact on cancer prognosis.

Introduction The association of air pollution with bone mineral density (BMD) has attracted increasing attention. However, establishing a causal relationship remains uncertain. Methods We conducted a Mendelian randomization (MR) study employing PM 2.5 , PM 2.5-10 , PM 10 , nitrogen dioxide, and nitrogen oxides as exposures and BMD as the outcome to explore the causality between air pollution and the occurrence of decreased BMD. Results By employing the IVW method, we identified a negative causality between air pollution (PM 2.5 , PM 10 , and nitrogen oxides) and BMD. Conclusions Our findings demonstrate that PM 2.5 , PM 10 and nitrogen oxides exposure may contribute to decreased BMD.

Abstract Immunotherapy exhibits considerable promise for sustained tumor reduction. However, current cancer immunotherapy methods elicit limited responses due to the inadequate immunogenicity exhibited by cancer cells. This obstacle may be addressed using nanoplatforms that can activate synergistic therapies (photodynamic therapy and ferroptosis) in response to the acidic pH of the tumor microenvironment. We previously developed an amphiphilic photosensitizer, SR780, which displays satisfactory photodynamic effects. This photosensitizer is inactivated when bound to Fe3+ (SR780Fe) but is activated upon release in mildly acidic conditions. In this study, M1 macrophage-derived extracellular vesicles (EVs) were fused with REV and SR780Fe–loaded liposomes (REV@SR780Fe@Lip) to form REV@SR780Fe@LEV hybrid nanovesicles. Further modification with the RS17 peptide for tumor targeting enabled a combination of photodynamic therapy, ferroptosis, and cGAS-STING pathway activation, resulting in enhanced antitumor efficacy through a synergistic effect. Upon laser irradiation, REV@SR780Fe@LEV-RS17 demonstrated antitumor effects in 4T1 breast cancer models, including the inhibition of lung and liver metastasis, as well as prevention of tumor recurrence. Graphical Abstract

Abstract Background Flowering time has an important effect on regional adaptation and yields for crops. The tyrosine kinase-like (TKL) gene family is widely existed and participates in many biological processes in plants. Furthermore, only few TKLs have been characterized functions in controlling flowering time in wheat. Results Here, we report that TaCTR1, a tyrosine kinase-like (TKL) gene, regulates flowering time in wheat. Based on identification and evolutionary analysis of TKL_CTR1-DRK-2 subfamily in 15 plants, we proposed an evolutionary model for TaCTR1, suggesting that occurrence of some exon fusion events during evolution. The overexpression of TaCTR1 caused early flowering time in transgenic lines. Transcriptomics analysis enabled identification of mass differential expression genes including plant hormone (ET, ABA, IAA, BR) signaling, flavonoid biosynthesis, phenolamides and antioxidant, and flowering-related genes in TaCTR1 overexpression transgenic lines compared with WT plants. qRT–PCR results showed that the expression levels of ethylene (ET) signal-related genes (ETR, EIN, ERF) and flowering-related genes (FT, PPD1, CO, PRR, PHY) were altered in TaCTR1-overexpressing wheat compared with WT plants. Metabonomics analysis showed that flavonoid contents were altered. Conclusions Thus, the results show that TaCTR1 plays a positive role in controlling flowering time by activating various signaling pathways and regulating flowering-related genes, and will provide new insights on the mechanisms of wheat flowering regulation.

Abstract Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Abstract Background Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and chemotherapy still serves as the cornerstone treatment functioning by inducing cytotoxic cell death. Notably, emerging evidence suggests that dying cell-released signals may induce cancer progression and metastasis by modulating the surrounding microenvironment. However, the underlying molecular mechanisms and targeting strategies are yet to be explored. Methods Apoptotic TNBC cells induced by paclitaxel or adriamycin treatment were sorted and their released extracellular vesicles (EV-dead) were isolated from the cell supernatants. Chemokine array analysis was conducted to identify the crucial molecules in EV-dead. Zebrafish and mouse xenograft models were used to investigate the effect of EV-dead on TNBC progression in vivo. Results It was demonstrated that EV-dead were phagocytized by macrophages and induced TNBC metastasis by promoting the infiltration of immunosuppressive PD-L1+ TAMs. Chemokine array identified CXCL1 as a crucial component in EV-dead to activate TAM/PD-L1 signaling. CXCL1 knockdown in EV-dead or macrophage depletion significantly inhibited EV-dead-induced TNBC growth and metastasis. Mechanistic investigations revealed that CXCL1EV-dead enhanced TAM/PD-L1 signaling by transcriptionally activating EED-mediated PD-L1 promoter activity. More importantly, TPCA-1 (2-[(aminocarbonyl) amino]-5-(4-fluorophenyl)-3-thiophenecarboxamide) was screened as a promising inhibitor targeting CXCL1 signals in EVs to enhance paclitaxel chemosensitivity and limit TNBC metastasis without noticeable toxicities. Conclusions Our results highlight CXCL1EV-dead as a novel dying cell-released signal and provide TPCA-1 as a targeting candidate to improve TNBC prognosis. Graphical abstract

Abstract Endocrine therapy is standard for hormone receptor–positive (HR+) breast cancer treatment. However, current strategies targeting estrogen signaling pay little attention to estradiol metabolism in the liver and is usually challenged by treatment failure. In a previous study, we demonstrated that the natural compound naringenin (NAR) inhibited HR+ breast cancer growth by activating estrogen sulfotransferase (EST) expression in the liver. Nevertheless, the poor water solubility, low bio-barrier permeability, and non-specific distribution limited its clinical application, particularly for oral administration. Here, a novel nano endocrine drug NAR-cell penetrating peptide-galactose nanoparticles (NCG) is reported. We demonstrated that NCG presented specific liver targeting and increased intestinal barrier permeability in both cell and zebrafish xenotransplantation models. Furthermore, NCG showed liver targeting and enterohepatic circulation in mouse breast cancer xenografts following oral administration. Notably, the cancer inhibition efficacy of NCG was superior to that of both NAR and the positive control tamoxifen, and was accompanied by increased hepatic EST expression and reduced estradiol levels in the liver, blood, and tumor tissue. Moreover, few side effects were observed after NCG treatment. Our findings reveal NCG as a promising candidate for endocrine therapy and highlight hepatic EST targeting as a novel therapeutic strategy for HR+ breast cancer. Graphical Abstract

The inhibition of autophagy is a potential therapeutic strategy to improve the chemosensitivity of triple-negative breast cancer (TNBC). In this study, we demonstrated that a natural terpenoid tanshinone I (TAN) enhanced the effectiveness of paclitaxel (PTX), at least in part, through an autophagy-dependent mechanism against TNBC. In vitro validation demonstrated that the combined therapy resulted in a synergistic decrease in the growth of TNBC cells. The chemosensitizing impact of TAN might be attributed to its inhibition of PTX-induced autophagy in the late phase by obstructing the fusion of autophagosomes and lysosomes, rather than by inhibiting lysosomal function. The findings from KEGG pathway analysis and molecular docking suggested that TAN might impact breast cancer chemoresistance primarily through the PI3K-Akt and MAPK signaling pathways. The non-canonical AKT/p38 MAPK signaling was further validated as the primary mechanism responsible for the inhibition of autophagy by TAN. In vivo study showed that the combined administration of TAN and PTX demonstrated a more significant suppression of tumor growth and autophagic activity compared to PTX monotherapy in the MDA-MB-231 xenograft nude mouse model. The safety evaluation of TAN in a zebrafish model, along with in vitro and in vivo validation, provided experimental and pre-clinical data supporting its potential as a natural adjunctive therapy in TNBC. Overall, this study suggests that the combination of TAN with PTX could provide an effective treatment option for advanced breast cancer, and targeting the AKT/p38 MAPK/late-autophagy signaling axis may be a promising approach for developing therapeutic interventions against TNBC.

Abstract Triple‐negative breast cancer (TNBC) is the most aggressive breast cancer subtype and chemotherapy is the cornerstone treatment for TNBC. Regrettably, emerging findings suggest that chemotherapy facilitates pro‐metastatic changes in the tumour microenvironment. Extracellular vesicles (EVs) have been highly implicated in cancer drug resistance and metastasis. However, the effects of the EVs released from dying cancer cells on TNBC prognosis and corresponding therapeutic strategies have been poorly investigated. This study demonstrated that paclitaxel chemotherapy elicited CXCL1‐enriched EVs from apoptotic TNBC cells (EV‐Apo). EV‐Apo promoted the chemoresistance and invasion of co‐cultured TNBC cells by polarizing M2 macrophages through activating PD‐L1 signalling. However, baohuoside I (BHS) remarkably sensitized the co‐cultured TNBC cells to paclitaxel chemotherapy via modulating EV‐Apo signalling. Mechanistically, BHS remarkably decreased C‐X‐C motif chemokine ligand 1 (CXCL1) cargo within EV‐Apo and therefore attenuated macrophage M2 polarization by suppressing PD‐L1 activation. Additionally, BHS decreased EV‐Apo release by diminishing the biogenesis of intraluminal vesicles (ILVs) within multivesicular bodies (MVBs) of TNBC cells. Furthermore, BHS bound to the LEU104 residue of flotillin 2 (FLOT2) and interrupted its interaction with RAS oncogene family member 31 (RAB31), leading to the blockage of RAB31‐FLOT2 complex‐driven ILV biogenesis. Importantly, BHS remarkably chemosensitised paclitaxel to inhibit TNBC metastasis in vivo by suppressing EV‐ApoCXCL1‐induced PD‐L1 activation and M2 polarization of tumour‐associated macrophages (TAMs). This pioneering study sheds light on EV‐ApoCXCL1 as a novel therapeutic target to chemosensitise TNBC, and presents BHS as a promising chemotherapy adjuvant to improve TNBC chemosensitivity and prognosis by disturbing EV‐ApoCXCL1 biogenesis.

Oxidative stress and inflammation are crucial factors contributing to the occurrence and development of vascular dementia (VD). In a previous study, we demonstrated that brozopine (BZP) is an anti-ischemic drug. In this study, a model of VD in rats with modified permanent bilateral common carotid artery occlusion (2-VO) was established in vivo, a model of cellular excitotoxicity/oxidative stress was established via L-glutamate-induced PC12 cell injury, a model of neuroinflammation was established in LPS-induced BV2 cells in vitro, and the ameliorative effect of BZP on cognitive impairment was assessed. BZP treatment improved memory deficit in VD rats through inhibiting Ca2+overload and the levels of oxidative stress, ferroptosis, and inflammatory markers (IL-1β, IL-6, and COX-2) in different brain regions. Additionally, we found that the levels of inflammatory markers in the plasma were also reduced in the VD rats. BZP was further found to have antioxidative stress, antiferroptosis (ferroptosis markers: GPX4, P53, and ACSL4), and antineuroinflammatory effects in PC12 and BV2 cells. Its mechanisms of action were found to be related to the activation of the Nrf2/TLR4/NF-κB pathway; the protective effect of BZP was partially inhibited after using Nrf2-specific inhibitors. Thus, BZP has therapeutic properties for the potential mitigation of cognitive impairment.

In an arid region, water shortage limits agricultural development, and worse, soil salinization is accompanied by soil moisture drought. In this region, hydraulic lift occurs due to the drying upper layer caused by high precipitation and the wet lower layer. Hydraulic lift is defined as water redistribution from wetter, deeper soil layers to drier, shallower soil layers near the soil surface through the plant roots. To examine the effects of water and salt stresses on tomato yield and fruit quality under the condition of hydraulic lift, a 2year experiment was conducted. Different water and salt treatments were designed, including three water levels (W1, W2 and W3 indicating soil moisture contents of 60%–70%, 50%–60% and 40%–50% of the field capacity, respectively) and four salt levels (S0, S1, S2 and S3 indicating NaCl addition of 0%, 0.2%, 0.4% and 0.6% of the dry soil weight, respectively) of the upper pot, and water and salt levels of control treatment (CK) were W1 and S0, respectively. The yield under other treatments significantly decreased by 4.59%–58.39% and 5.12%–62.96% in 2018 and 2019, respectively, compared with that under CK, and the yield under W1S1 treatment had no significance with that under CK in 2018. The firmest fruit quality was observed in the plant under W3S1 treatment, and the percentage increases were 28.67% and 28.89% in both years compared with that under CK. Water, salt stress and their interactions had significant effects on tomato taste quality and vitamin C. Tomato taste quality and vitamin C decreased under the W3 and S3 treatments. In both years, the total magnitudes of hydraulic lift during the entire growth period were higher under the W1S2 treatment (65.20% and 76.06%, respectively) than that under CK. Whereas yield and total magnitudes of hydraulic lift were significantly both correlated with single fruit weight, single fruit volume, fruit shape index and taste qualities, no correlations were observed between hydraulic lift and yield. Mild waterdeficit and salt stresses could improve tomato quality with negligible yield loss, and hydraulic lift had positive effects on fruit quality. Principal component analysis revealed that the combination of W1 and S1 treatments increased fruit quality and total hydraulic lift magnitudes with an acceptable yield decline. These results are important for tomato production in arid saline-alkali region where hydraulic lift is positively corelated with fruit quality and famers may consider this trait to resist drought and soil salinization. Future studies focusing on the effects of the internal mechanisms of hydraulic lift caused by changes in sap flow on tomato quality and yield are warranted.

Multiband synthetic aperture radar (SAR) image fusion combines the scattering characteristics of targets from different bands to provide a comprehensive and informative output. However, the conventional SAR denoise and fusion separation framework often encounters the loss of fine details. This problem arises due to the inherent conflict between noise filtering and edge preservation. To address this issue, this article proposes the joint tensor-based low-rank total variation (TLRTV) dual-band SAR image denoise–fusion strategy. The proposed strategy formulates the denoise–fusion problem by integrating the LR and TV models. Furthermore, this problem is extended to a high-dimensional form using tensor representation. To effectively solve the TLRTV problem, an optimization method is developed based on the alternating direction method of multipliers. This method decomposes the TLRTV problem into a series of subproblems, allowing for an efficient and accurate solution. To evaluate the performance of the proposed TLRTV method, the real measurement dual-band SAR images obtained from our developed airborne multiband SAR system are utilized to compare with other existing denoise and fusion separation methods. The extensive experimental results demonstrate the superiority of the TLRTV approach achieving better fusion results, particularly in the presence of noise interference.

Abstract Real‐time and accurate short‐term traffic flow prediction can provide a scientific basis for decision making by travellers and traffic management, and alleviate traffic congestion to a certain extent. The existing traffic flow prediction methods often encounter limitations in real‐time performance and accuracy due to the post‐processing required to rectify anomaly detection results during data pre‐processing. This paper presents a novel traffic flow prediction model, termed the With‐Anomaly Detection Probability (ADP) Attention‐Bidirectional Long‐Short Term Memory (BiLSTM) model. This model takes the probability of anomaly detection into consideration, integrating the anomaly detection outcomes as an inherent parameter into the traffic flow prediction framework. Additionally, the model incorporates an attention mechanism within the long‐short term memory network. Through a comprehensive simulation study utilizing actual measured traffic flow data from the Shanghai‐Chongqing Expressway, the effectiveness of the proposed model is rigorously evaluated. The prediction results show that the model proposed in this paper is a real‐time and accurate short‐time traffic flow prediction model compared with the basic models.

Pipeline pullback load is a crucial basis for drill rig selection and pipeline strength design. This paper presents a new pullback load calculation model from the perspective of pipe–borehole wall contact. The pipe–borehole wall contact analysis includes the distribution of contact pressure and the relationship between the external load and compressive displacement. The friction force between the pipe and the borehole wall was calculated based on the pipe–borehole wall contact analysis and adhesion theory without depending on the empirical friction coefficient. The effects of the eccentricity were also considered when calculating the fluid drag force. Through case studies, we verified the applicability of the model and discussed the possible reasons for the errors between the theoretical and field-measured results. This study can provide a helpful tool for analyzing the pipe–borehole wall contact and pullback loads for horizontal directional drilling.

Background: Primary tumor resection is associated with survival benefits in patients with metastatic lung adenocarcinoma (mLUAD). However, there are no established methods to determine which individuals would benefit from surgery. Therefore, we developed a model to predict the patients who are likely to benefit from surgery in terms of survival. Methods: Data on patients with mLUAD were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether surgery was performed on the primary tumor, patients were categorized into two groups: cancer-directed surgery (CDS) and no-cancer-directed surgery (No-CDS). Propensity Score Matching (PSM) was utilized to address bias between the CDS and No-CDS groups. The prognostic impact of CDS was assessed using Kaplan-Meier analysis and Cox proportional hazard models. Subsequently, we constructed a nomogram to predict the potential for surgical benefits based on multivariable logistic regression analysis using preoperative factors. Results: A total of 89,039 eligible patients were identified, including 6.4% (5705) who underwent surgery. Following PSM, the CDS group demonstrated a significantly longer median overall survival (mOS) compared with the No-CDS group (23 [21–25] vs. 7 [7–8] months; P

In response to the problems of the traditional punishment-based coal mine safety management model, the active safety-guided management model, which is based on rewards and a combination of rewards and punishments, was proposed. The model has established a more rigid management system by organizing a wide range of high-frequency advanced safety selection and rewards, establishing a special reward system for production and operation management, and implementing a series of active guidance measures such as safety veto by one vote, public announcement of rewards, exposure of penalties, hearings on unsafe behavior, and rewards for violation investigation and handling, while strictly enforcing the rigidity of the system, strengthening safety management, and cashing in safety penalties. The results show that the implementation of this management model is effective, with a 57.69% reduction in the number of unsafe act outputs in Shangyuquan Mine; after strengthening management, the number of unsafe behavior investigations and punishments in Mindong No.1 Mine increased by about four times, and then rapidly decreased by 72.31%. This management model has greatly reduced all kinds of violations and safety hazards of coal mine units, and greatly improved the enthusiasm of employees and grass-roots managers to take the initiative to safety and act proactively.

Based on a constant volume combustion chamber, the initial ambient pressure effect on gasoline combustion performance and flame propagation of the active and passive pre-chamber ignition systems were studied. Compared with the passive pre-chamber, the active pre-chamber can significantly expand the lean combustion limit from 1.2 to 1.5, enhance the ignition and combustion performance, and speed up the combustion of the main combustion chamber. At slightly lean combustion conditions, the heat release performance has a positive correlation with the initial ambient pressure. As the premixed λ increases, the heat release performance and the initial ambient pressure begin to become negatively correlated. Ignition delay can be decreased by approximately 50% at an initial pressure of 0.75 MPa, premixed lambda of 1.2 with APC compared with PPC. The high ambient pressure (1.0 MPa) in the constant volume chamber greatly reduces the mixture entrainment ability of the jet flame at lean combustion conditions, thereby reducing the combustion speed and peak heat release rate.

This paper investigates the role of chaotic analysis and deep learning models in combustion instability predictions. To detect the precursors of impending thermoacoustic instability (TAI) in a swirled combustor with various fuel injection strategies, a data-driven framework is proposed in this study. Based on chaotic analysis, a recurrence matrix derived from combustion system is used in deep learning models, which are able to detect precursors of TAI. More specifically, the ResNet-18 network model is trained to predict the proximity of unstable operation conditions when the combustion system is still stable. The proposed framework achieved state-of-the-art 91.06% accuracy in prediction performance. The framework has potential for practical applications to avoid an unstable operation domain in active combustion control systems and, thus, can offer on-line information on the margin of the combustion instability.

Waste cooking oil’s (WCO’s) potential as a rejuvenator of aged asphalt has received attention in recent years, with the acid value of WCO affecting its rejuvenation effect. This study explored the rejuvenation effect of WCO with a high acid value on aged asphalt by using molecular dynamics simulation. First, the representative molecules of WCO with a high acid value and asphalt were determined. The rejuvenation effect of WCO on aged asphalt was analyzed by adding different contents of WCO to an aged asphalt model. The effect of WCO on the thermodynamic properties of the aged asphalt was analyzed. The results show that WCO can restore the thermodynamic properties of aged asphalt binder to a certain extent. Regarding the microstructure of rejuvenated asphalt, WCO molecules dispersed around asphaltenes weakened the latter’s aggregation and improved the colloidal structure of the aged asphalt. In terms of interface adhesion properties, WCO can improve the adhesion properties between asphalt binder and SiO2, but it has limited influence on water sensitivity. The results allowed us to comprehensively evaluate the rejuvenation effect of WCO with a high acid value on aged asphalt and to explore its rejuvenation mechanism.

Abstract Transportation stress is one of the most serious issues in the management of yak. Previous studies have demonstrated that transport stress is caused by a pro-oxidant state in the animal resulting from an imbalance between pro-oxidant and antioxidant status. In this context, vitamin C has the ability to regulate reactive oxygen species (ROS) synthesis and alleviate oxidative stress. Although this effect of vitamin C is useful in pigs, goats and cattle, the effect of vitamin C on the mitigation of transport stress in yaks is still unclear. The purpose of this study was to better assess the metabolic changes induced by the action of vitamin C in yaks under transportation stress, and whether these changes can influence antioxidant status. After the yaks arrived at the farm, control or baseline blood samples were collected immediately through the jugular vein (VC_CON). Then, 100 mg/kg VC was injected intramuscularly, and blood samples were collected on the 10th day before feeding in the morning (VC). Relative to the control group, the VC injection group had higher levels of VC. Compared with VC_CON, VC injection significantly (P 0.05) in GGT, ALP, TBA, TP, ALBII, GLO, A/G, TC, TG, HDL-C, LDL-C, GLU and l-lactate between VC_CON and VC. The injection of VC led to greater (P 0.05) the serum concentrations of LPO and ROS. The injection of VC led to greater (P 0.05) in GSH, GSH-ST and GR was observed between VC_CON and VC. Compared with the control group, metabolomics using liquid chromatography tandem–mass spectrometry identified 156 differential metabolites with P 1.5 in the VC injection group. The injection of VC resulted in significant changes to the intracellular amino acid metabolism of glutathione, glutamate, cysteine, methionine, glycine, phenylalanine, tyrosine, tryptophan, alanine and aspartate. Overall, our study indicated that VC injections were able to modulate antioxidant levels by affecting metabolism to resist oxidative stress generated during transport.

AimChronic kidney disease (CKD) is a major complication of diabetes and a significant disease burden on the healthcare system. The aim of this work was to apply a predictive model to identify high-risk patients in the early stages of CKD as a means to provide early intervention to avert or delay kidney function deterioration.Materials and methodsUsing the data from the National Diabetes Database in Singapore, we applied a machine-learning algorithm to develop a predictive model for CKD progression in diabetic patients and to deploy the model nationwide.ResultsOur model was rigorously validated. It outperformed existing models and clinician predictions. The area under the receiver operating characteristic curve (AUC) of our model is 0.88, with the 95% confidence interval being 0.87 to 0.89. In recognition of its higher and consistent accuracy and clinical usefulness, our CKD model became the first clinical model deployed nationwide in Singapore and has been incorporated into a national program to engage patients in long-term care plans in battling chronic diseases. The risk score generated by the model stratifies patients into three risk levels, which are embedded into the Diabetes Patient Dashboard for clinicians and care managers who can then allocate healthcare resources accordingly.ConclusionThis project provided a successful example of how an artificial intelligence (AI)-based model can be adopted to support clinical decision-making nationwide.

Disulfidptosis, a newly revealed form of cell death, regulated by numerous genes that has been recently identified. The exact role of disulfidptosis in lung adenocarcinoma (LUAD) still uncertain. Objective of this study was to explore potential prognostic markers among disulfidptosis genes in LUAD. By combining transcriptomic information from Gene Expression Omnibus databases and The Cancer Genome Atlas, we identified differentially expressed and prognostic disulfidptosis genes. By conducting least absolute shrinkage and selection operator with multivariate Cox regression, four disulfidptosis genes were selected to create the prognostic signature. The implementation of the signature separated the training and validation cohorts into groups with high- and low-risk. Subsequently, the model was verified by conducting an independent analysis of receiver operating characteristic (ROC) curves. Further comparisons were made between the two risk-divided groups with regards the tumor microenvironment, immune cell infiltration, immunotherapy response, and drug sensitivity. The signature was constructed using four disulfidptosis-related genes: SLC7A11, SLC3A2, NCKAP1, and GYS1. According to ROC curves, the signature was effective for predicting LUAD prognosis. In addition, the prognostic signature correlated with sensitivity to chemotherapeutic agents and the efficacy of immunotherapy in LUAD. Finally, through external validation, we showed that NCKAP1 are correlated with tumor migration, proliferation, and invasion of LUAD cells. GYS1 affects immune cell, especially M2 macrophage infiltration in the tumor microenvironment. The disulfidptosis four-gene model can reliably predict the prognosis of patients diagnosed with LUAD, thereby providing valuable information for clinical applications and immunotherapy.

Abstract Metal halide crystals are bright but hygroscopic scintillator materials that are widely used in X‐ray imaging and detectors. Precipitating them in situ in glass to form glass ceramics (GCs) scintillator offers an efficient avenue for large‐scale preparation, high spatial resolution, and excellent stability. However, precipitating a high fraction of metal halide nanocrystals in glass to maintain high light yield remains a challenge. Herein, an ionic‐covalent hybrid network strategy for constructing GCs scintillator with high crystallinity (up to ≈37%) of BaCl2: Eu2+ nanocrystals is presented. Experimental data and simulations of glass structure reveal that the Ba2+‐Cl− clustering promotes the high crystallization of BaCl2 nanocrystals. The ultralow phonon energy (≈200 cm−1) of BaCl2 nanocrystals and good Eu reduction effect enable high photoluminescence inter quantum efficiency (≈80.41%) in GC. GCs with varied crystallinity of BaCl2: Eu2+ nanocrystals demonstrate efficient radioluminescence and tunable scintillator performance. They either outperform Bi4Ge3O14 single crystal by over 132% steady‐state light yield or provide impressive X‐ray imaging resolutions of 20 lp mm−1. These findings provide a new design strategy for developing bright transparent GCs scintillators with a high fraction of metal halide nanocrystals for X‐ray high‐resolution imaging applications.

To prepare molecularly imprinted polymers (MIPs) with specific selectivity for steranes, the prepolyme-rization system was screened by UV spectroscopy to determine the type, proportion and mode of action of functional monomers. In this study, the interaction intensities between three template molecules (cholesterol, β-sitosterol, deoxycholic acid) and four functional monomers (acrylic acid (AA), methacrylic acid (MAA), methyl methacrylate (MMA), and acrylamide (AM)) are compared respectively. The results show that the functional monomer AA can interact strongly with the three template molecules and form a stable prepolymerization system, so AA is selected as the functional monomer of MIPs. In addition, the UV spectral absorbance change and differential UV spectral analysis of different proportions of AA show that the optimal concentration ratios of the three template molecules to functional monomer AA are all 1:4, and the stable complex configurations formed are cholesterol-1AA, β-sitosterol-1AA and deoxycholic acid-3AA, respectively. The MIPs are successfully synthesized by precipitation polymerization using EDGMA as dispersant and AIBN as initiator, and the results of FTIR show that MIPs are well prepared. Therefore, this method can be used for the screening and preparation of MIPs functional monomers with specific selectivity for steranes, and provide technical support for the study of oil-source correlation between deep and ultra-deep source rocks.

Abstract Background To investigate the association between clinical periodontal parameters of periodontitis, serum lipid metabolism markers and adipokines’ levels in patients with obesity and periodontitis. Methods A total of 112 patients admitted to Hospital of Xi’an Jiaotong University were included in this study. They were divided into normal body weight group (18.5

Abstract Background Emerging studies have identified chronic psychological stress as an independent risk factor influencing breast cancer growth and metastasis. However, the effects of chronic psychological stress on pre-metastatic niche (PMN) formation and the underlying immunological mechanisms remain largely unknown. Methods The effects and molecular mechanisms of chronic unpredictable mild stress (CUMS) on modulating tumor-associated macrophages (TAMs) and PMN formation were clarified by multiplex immunofluorescence technique, cytokine array, chromatin immunoprecipitation, the dual-luciferase reporter assay, and breast cancer xenografts. Transwell and CD8+ T cytotoxicity detection were used to analyze the mobilization and function of myeloid-derived suppressor cells (MDSCs). mCherry-labeled tracing strategy and bone marrow transplantation were applied to explore the crucial role of splenic CXCR2+/+ MDSCs facilitating PMN formation under CUMS. Results CUMS significantly promoted breast cancer growth and metastasis, accompanied by TAMs accumulation in the microenvironment. CXCL1 was identified as a crucial chemokine in TAMs facilitating PMN formation in a glucocorticoid receptor (GR)-dependent manner. Interestingly, the spleen index was significantly reduced under CUMS, and splenic MDSCs were validated as a key factor mediating CXCL1-induced PMN formation. The molecular mechanism study revealed that TAM-derived CXCL1 enhanced the proliferation, migration, and anti-CD8+ T cell functions of MDSCs via CXCR2. Moreover, CXCR2 knockout and CXCR2−/−MDSCs transplantation significantly impaired CUMS-mediated MDSC elevation, PMN formation, and breast cancer metastasis. Conclusion Our findings shed new light on the association between chronic psychological stress and splenic MDSC mobilization, and suggest that stress-related glucocorticoid elevation can enhance TAM/CXCL1 signaling and subsequently recruit splenic MDSCs to promote PMN formation via CXCR2. Graphical Abstract

Introduction: Chronic psychological stress is a well-established risk factor for breast cancer development. Si-Ni-San (SNS) is a classical traditional Chinese medicine formula prescribed to psychological disorder patients. However, its action effects, molecular mechanisms, and bioactive phytochemicals against breast cancer are not yet clear. Objectives: This study aimed to explore the modulatory mechanism and bioactive compound of SNS in regulating estrogen metabolism during breast cancer development induced by chronic psychological stress. Methods: Mouse breast cancer xenograft was used to determine the effect of SNS on breast cancer growth and metastasis. Metabolomics analysis was conducted to discover the impact of SNS on metabolic profile changes in vivo. Multiple molecular biology experiments and breast cancer xenografts were applied to verify the anti-metastatic potentials of the screened bioactive compound. Results: SNS remarkably inhibited chronic psychological stress-induced breast cancer growth and metastasis in the mouse breast cancer xenograft. Meanwhile, chronic psychological stress increased the level of cholic acid, accompanied by the elevation of estradiol. Mechanistic investigation demonstrated that cholic acid activated farnesoid X receptor (FXR) expression, which inhibited hepatocyte nuclear factor 4α (HNF4α)-mediated estrogen sulfotransferase (EST) transcription in hepatocytes, and finally resulting in estradiol elevation. Notably, SNS inhibited breast cancer growth by suppressing estradiol level via modulating FXR/EST signaling. Furthermore, luciferase-reporting gene assay screened naringenin as the most bioactive compound in SNS for triggering EST activity in hepatocytes. Interestingly, pharmacokinetic study revealed that naringenin had the highest absorption in the liver tissue. Following in vivo and in vitro studies demonstrated that naringenin inhibited stress-induced breast cancer growth and metastasis by promoting estradiol metabolism via FXR/EST signaling. Conclusion: This study not only highlights FXR/EST signaling as a crucial target in mediating stress-induced breast cancer development, but also provides naringenin as a potential candidate for breast cancer endocrine therapy via promoting estradiol metabolism.

Zinc calcine with high Fe content is leached with a large amount of Fe at the same time, which affects the subsequent operation. In order to solve this problem, the high iron zinc calcine of a company in Shaanxi was taken as the research object. The influence factors of Zn and Fe leaching rate were analyzed by studying the initial acidity, leaching temperature and solid-liquid ratio. The leaching process was optimized to improve the leaching rate of Zn and reduce the leaching rate of Fe. The results show that the effect of temperature on leaching rate of Zn and Fe is different in different sulfuric acid concentration leaching system. When the sulfuric acid dosage is insufficient, the temperature has no obvious effect on the leaching of Zn and Fe. When the sulfuric acid is excessive, the temperature will affect the leaching of Zn and Fe, especially for Fe. Initial acidity 90 g/L, leaching temperature 60 ℃, solid-liquid ratio 10:1, stirring speed 600 r/min are ideal leaching conditions.

Recently there has been interest in exploring the coupling between magnons for use in information processing, however, this is hampered by the fact that such coupling is forbidden due to the different parity of the acoustic and optical magnons. Here, Comstock et al show that the interlayer Dzyaloshinskii–Moriya-Interaction in a layered hybrid antiferromagnet can allow for strong coupling between the acoustic and optical magnons, offering a pathway for magnon coherent information processing.

This study focuses on exploring the indication and importance of selenium (Se) and tellurium (Te) in distinguishing different genetic types of ore deposits. Traditional views suggest that dispersed elements are unable to form independent deposits, but are hosted within deposits of other elements as associated elements. Based on this, the study collected trace elemental data of pyrite, sphalerite, and chalcopyrite in various types of Se-Te bearing deposits. The optimal end-elements for distinguishing different genetic type deposits were recognized by principal component analysis (PCA) and the silhouette coefficient method, and discriminant diagrams were drawn. However, support vector machine (SVM) calculation of the decision boundary shows low accuracy, revealing the limitations in binary discriminant visualization for ore deposit type discrimination. Consequently, two machine learning algorithms, random forest (RF) and SVM, were used to construct ore genetic type classification models on the basis of trace elemental data for the three types of metal sulfides. The results indicate that the RF classification model for pyrite exhibits the best performance, achieving an accuracy of 94.5% and avoiding overfitting errors. In detail, according to the feature importance analysis, Se exhibits higher Shapley Additive Explanations (SHAP) values in volcanogenic massive sulfide (VMS) and epithermal deposits, especially the latter, where Se is the most crucial distinguishing element. By comparison, Te shows a significant contribution to distinguishing Carlin-type deposits. Conversely, in porphyry- and skarn-type deposits, the contributions of Se and Te were relatively lower. In conclusion, the application of machine learning methods provides a novel approach for ore genetic type classification and discrimination research, enabling more accurate identification of ore genetic types and contributing to the exploration and development of mineral resources.

Primary colorectal squamous cell carcinoma (CSCC) is a rare pathological subtype. Currently, clinical data with regards to its prognosis and treatment is limited, and there is no optimal treatment method. The case presented involves a proficient mismatch repair (pMMR) and microsatellite-stable (MSS) Colorectal cancer (CRC) patient with squamous cell carcinoma (SCC) located transversely in the colon. Based on the imaging assessment, the tumor infiltration depth is classified as T4. After receiving 4 cycles of neoadjuvant treatment with oxaliplatin and capecitabine (XELOX), the patients were evaluated for partial response (PR) in 2 cycles and stable disease (SD) in 4 cycles. The patient underwent a right hemicolectomy and received postoperative paclitaxel/cisplatin (TC) adjuvant chemotherapy. After 23 months, a systemic examination revealed abdominal metastasis. A needle biopsy was conducted on the detected abdominal metastases, with the resulting pathology indicating the presence of metastatic SCC. The individual exhibited expression of programmed cell death ligand 1 (PD-L1) and a mutation in the TP53 gene. Considering the patient’s disease recurrence based on medical history, a treatment plan was formulated. This involved Sintilimab plus Cetuximab and the combination of leucovorin, fluorouracil, and irinotecan (FOLFIRI) regimen. The patient received four cycles of treatment with an efficacy evaluation of SD- and seven cycles of treatment with an efficacy evaluation of SD+, which resulted in a progression-free survival (PFS) duration of 7 months. This case study presents the conventional XELOX chemotherapy protocol, which has shown limited effectiveness, and highlights the favorable results achieved by implementing the TC adjuvant chemotherapy regimen in individuals diagnosed with primary colonic SCC. Furthermore, combining immune checkpoint blockade (ICB) with other therapies for patients with advanced disease is anticipated to provide an extended duration of survival.

BackgroundDepression increases the risk of breast cancer recurrence and metastasis. However, there lacks potential biomarkers for predicting prognosis in breast cancer. 5-hydroxytryptamine (5-HT) plays a key role in the pathogenesis and treatment of depression. In this study, we developed a prognostic signature based on 5-HT receptors (5-HTRs) and elucidated its potential immune regulatory mechanisms for breast cancer prognosis.MethodsOncomine, GEPIA, UALCAN, cBioPortal, Kaplan-Meier plotter, and TIMER were used to analyze differential expression, prognostic value, genetic alteration, and immune cell infiltration of HTRs in breast cancer patients. The model training and validation assays were based on the analyses of GSE1456 and GSE86166. A risk signature was established by univariate and multivariate Cox regression analyses. The transwell assay was utilized to verify the effect of the 5-HTRs expression on breast cancer invasion. Effects of HTR2A/2B inhibitor on CD8+ T cell proliferation and infiltration as well as apoptosis of 4T1 cells in the tumor microenvironment were detected by flow cytometry and TUNEL assay. Zebrafish and mouse breast cancer xenografts were used to determine the effect of HTR2A/2B inhibitor on breast cancer metastasis.ResultsThe expression levels of HTR1A, HTR1B, HTR2A, HTR2B, HTR2C, HTR4, and HTR7 were significantly downregulated in highly malignant breast cancer types. 5-HTRs were significantly associated with recurrence-free survival (RFS) in breast cancer patients. The genetic alteration of HTR1D, HTR3A, HTR3B, and HTR6 in breast cancer patients was significantly associated with shorter overall survival (OS). Finally, HTR2A and HTR2B were determined to construct the risk signature. The expression of HTR2A/2B was positively correlated with the infiltration of immune cells such as CD8+ T cells and macrophages. Furthermore, inhibition of HTR2A expression could suppress CD8+ T cell proliferation and enhance invasion and metastasis of breast cancer cells in both zebrafish and mice model.ConclusionsThe HTR2A/2B risk signature not only highlights the significance of HTRs in breast cancer prognosis by modulating cancer immune microenvironment, but also provides a novel gene-testing tool for early prevention of depression in breast cancer patients and lead to an improved prognosis and quality of life.

This manuscript compares deterministic artificial intelligence to a model-following control applied to DC motor control, including an evaluation of the threshold computation rate to let unmanned underwater vehicles correctly follow the challenging discontinuous square wave command signal. The approaches presented in the main text are validated by simulations in MATLAB®, where the motor process is discretized at multiple step sizes, which is inversely proportional to the computation rate. Performance is compared to canonical benchmarks that are evaluated by the error mean and standard deviation. With a large step size, discrete deterministic artificial intelligence shows a larger error mean than the model-following self-turning regulator approach (the selected benchmark). However, the performance improves with a decreasing step size. The error mean is close to the continuous deterministic artificial intelligence when the step size is reduced to 0.2 s, which means that the computation rate and the sampling period restrict discrete deterministic artificial intelligence. In that case, continuous deterministic artificial intelligence is the most feasible and reliable selection for future applications on unmanned underwater vehicles, since it is superior to all the approaches investigated at multiple computation rates.

The amplitude and phase imbalances of the in-phase (I) and quadrature (Q) branches inherent in the direct conversion receiver structure cause the generation of image frequency interference signals. In this paper, a frequency-domain I/Q imbalance calibration algorithm is proposed for wideband direct conversion receivers. The I/Q imbalance model is rebuilt by applying the infinitesimal method and FFT algorithm. The mathematical expressions for the exact computation of the I/Q imbalance parameters are derived based on the frequency-domain statistical properties of the baseband signal. The two phase parameters, frequency-dependent I/Q imbalance (FD-IQI) and frequency-independent I/Q imbalance (FI-IQI), are separated according to the parity properties of the imbalance parameter. To avoid the interference from the transmitter, the receiver impairment estimation is performed using a frequency offset (FO) DC training signal, and a low-cost real-valued compensation (RVC) filter is introduced to correct the impairments of the received signal. The performances of the proposed calibration model are evaluated through simulations and experiments. The simulation results show that the image rejection ratio (IRR) is improved to 80-120 dBc and can also exceed 40 dBc at high noise levels. The experimental results based on the CX9261A evaluation board show that the average IRR of the multi-tone signal is increased by 24.99 dB, and the IRR of the wideband signal is increased by 19.08 dB.

Abstract Background Peutz-Jeghers syndrome (PJS) is a rare, autosomal dominant disorder caused by germline mutations of STK11/LKB1, with an increased risk of tumors at multiple sites. Intraductal oncocytic papillary neoplasm (IOPN) is a unique subtype of intraductal papillary neoplasm of the bile duct (IPNB) defined by a premalignant neoplasm with intraductal papillary or villous growth of biliary-type epithelium. IOPN has a distinct mutation profile compared with both IPNB and intraductal papillary mucinous neoplasm (IPMN). Case presentation We herein describe the case of a 44-year-old woman who presented as polyps in the intestinal lumen of sigmoid colon and a 3.1 × 2.1 cm mass in the left lobe of liver. Gross feature revealed a cystic papillary mass and the neoplasm had a clear boundary with the surrounding liver tissue. Histology revealed complex papillary structures, a small amount of fine fibrovascular cores and immunohistochemistry showed extensive positive for MUC5AC, MUC6, CD117. Therefore, histological and immunohistochemical examination of the liver tumor suggested the diagnosis of IOPN. Next-generation sequencing (NGS) revealed other than STK11 germline mutation, the tumor also harbors GNAS somatic mutation at codon 478 and EGFR amplification. Conclusion To our knowledge, this is the first report of IOPN arising in PJS. This case enlarges the spectrum of PJS related tumors and genetic rearrangements in IOPN.

Abstract Global climate change has threatened world crop production and food security. Decoding the adaptive genetic basis of wild relatives provides an invaluable genomic resource for climate‐smart crop breedinG. Here, we performed whole‐genome sequencing of 185 diverse wild soybean (Glycine soja) accessions collected from three major agro‐ecological zones in China to parse the genomic basis of local adaptation in wild soybean. The population genomic diversity pattern exhibited clear agro‐ecological zone‐based population structure, and multiple environmental factors were observed to contribute to the genetic divergence. Demographic analysis shows that wild soybeans from the three ecological zones diverged about 1 × 105 years ago, and then the effective population sizes have undergone different degrees of expansions. Genome‐environment association identified multiple genes involved in the local adaptation, such as flowering time and temperature‐related genes. A locus containing two adjacent MADS‐box transcription factors on chromosome 19 was identified for multiple environmental factors, and it experienced positive selection that enables the adaptation to high‐latitude environment. This study provides insights into the genetic mechanism of ecological adaptation in wild soybean that may facilitate climate‐resilient soybean breeding.

Interfacial ferroelectricity may emerge in moiré superlattices. Here, the authors find that the polarized charge is much larger than the capacity of the moiré miniband and the associated anomalous screening exists outside the band.

Abstract The structural properties of octahedral sites (BOh) in spinel oxides (AB2O4) play vital roles in the electrochemical performance of oxygen‐related reactions. However, the precise manipulation of AB2O4 remains challenging due to the complexity of their crystal structure. Here, a simple and versatile molten‐salt‐mediated strategy is reported to introduce Ni2+ in Boh sites intentionally on the surface of zinc ferrite (ZnFe2O4, ZFO) to promote the active sites for photoelectrochemical (PEC) water splitting. The as‐created photoanode (ZFO‐MSNi) shows a remarkable cathodic shift of ≈ 450 mV (turn‐on voltage of ≈ 0.6 VRHE) as well as three times the 1‐sun photocurrent density at 1.23 VRHE for PEC water oxidation in comparison with bare ZFO. A comprehensive structural characterization clearly reveals the local structure of the introduced Ni2+ in ZFO‐MSNi. Fewer surface trapping states are observed while the precisely introduced Ni2+ and associated neighboring Fe(3‐σ)+ (0

This paper presents an experimental study on the box girder of a low-tower cable-stayed railway bridge with a W-shaped section that consists of prestressed concrete diagonal braces. A 1:6 scale test model was designed and constructed for the experiment. The mechanical behavior of the test model was investigated under two loading conditions: a double-track train symmetrical load and a single-track train unsymmetrical load. The experimental results were validated against a finite element model. Furthermore, the torsional performance of the box girder section was analyzed and discussed.

Dry topsoil and relatively moist subsoil can occur in specific areas and times, limiting plant growth but creating conditions for hydraulic lift (HL). There is a lack of a rational water and nitrogen (N) strategy to improve cotton growth and maintain HL. This study investigated the effects of three topsoil water conditions (W0.6: 60–70%, W0.5: 50–60%, and W0.4: 40–50% of field capacity) and three N rates (N120-120, N240-240, and N360-360 kg N ha−1) plus one control treatment on cotton growth and HL under dry topsoil conditions in 2020 and 2021. The results showed that plant height and leaf area increased with increasing N rate, but the differences among topsoil water conditions were relatively small, except for leaf area in 2021. The HL water amount of all treatments increased gradually and then continued to decline during the observation period. There was a trend that the drier the topsoil or the more N applied, the greater the amount of HL water. Additionally, topsoil water conditions and N rate significantly affected the total HL water amount and root morphological characteristics (root length, surface area, and volume). Seed and lint cotton yield tended to decrease with increasing topsoil dryness at N240 or N360, except for lint yield in 2021, or with decreasing N rate, especially under W0.6. As topsoil became drier, the total evapotranspiration (ET) decreased, while with the increase in N rate, ET showed small differences. Water use efficiency increased with a higher N rate, while N partial factor productivity (PFPN) did the opposite. Furthermore, the PFPN under W0.4 was significantly lower than that under W0.6 at N240 or N120. These findings could be useful for promoting the utilization of deep water and achieving sustainable agricultural development.

To improve the resilience of power distribution systems to fight natural disasters caused by extreme weather, A framework for enhancing disaster resilience at the full time scale is proposed. First, the influence of extreme weather events on power system components is analyzed, the failure probability of system components during extreme weather is evaluated. Then the vulnerability model of the components is established and the multi-stage performance response curve is used to quantify the resilience level of the network in each period. On this basis, framework of disaster resilience enhancement at full time scale before, during and after the occurrence of disasters is proposed. In the pre-failure phase, preventive strategies can be used to avert serious losses. Planning model of distributed power supply and tie line in distribution network based on active resilience lifting strategy during disaster. This paper presents the problem of flexible distribution system planning with resource redistribution and minimizing the cost of post-failure operation and load reduction as objective functions. After a fault occurs, maintenance measures for the faulty components could be optimized to restore the resilience of the distribution network as effectively as possible. Finally, the proposed strategy was applied to an ice and snow disaster in northern China in 2008 to study the effectiveness of the strategy in practical application.

The development of anode-free batteries requires investigations at the electrode and electrolyte levels. Here, the authors report a high-energy quasi-solid-state anode-free pouch cell with a Li2S-based cathode that demonstrates enhanced safety features.

The glass-ceramics were prepared by sintering method from an iron tailings in Shangluo area. The optimum process parameters of melting base glass were optimized. The effects of the crystallization temperature on the compressive strength, density and thermal expansivity of glass-ceramics were investigated. The results show that optimal performance of the base glass melted can be obtained at the melting temperature of 1400℃ and melting time of 2 h. Moreover the best properties of the glass-ceramics such as compressive strength of 158.32 MPa, density of 2.74 g/cm3, thermal expansivity of 6.8×10-6K-1 could be obtained at the crystallization temperature of 900℃ and holding time of 2 h.

ObjectivesTo understand the different characteristics and growth corridors of knosp grade 4 pituitary adenomas (Knosp4PA) with cavernous sinus (CS) compartments penetration and intracranial extension, aiming to improve the safety, effectiveness, and total resection rate of surgery.MethodsA case series of 120 Knosp4PA patients with 187 invaded compartments were retrospectively reviewed. A novel surgery-relevant grading system was proposed according to the CS penetrating features. The details of approach drafting, risk prediction, and complication avoidance were analyzed and integrated through illustrated cases.ResultsAll enrolled tumor was Knosp4PA which was derived from Knosp subgrades 3A(62.5%) and 3B(37.5%). Based on the tumor growth pathway and its relevant features, five subclassifications of intracranial extension(n=98,81.7%) were classified, which derived from the superior (Dolenc’s and Oculomotor subtype, 5% and 24.2%), lateral (Parkinson’s subtype,18.3%), and posterior (cerebral peduncle and Dorello’s subtype, 5.8% and 1.7%) CS compartment penetration. The size of intracranial extension is assessed by Lou’s scale proposed here based on preoperative MRI characteristics. Under Lou’s scale, the gross total rate (GTR) decreased (82%, 53%, 22%, and 19%) with grades increased (grade 0,1,2,3, respectively), and presents significant difference between the four groups (p=0.000), as well as between single and multiple compartments involved (p=0.001). Preoperative cranial nerve deficits included the optic nerve (53%), oculomotor nerve (24.2%), and abducent nerve (4.2%), with an overall rate of visual function improvement in 68.1%. Postoperative complications of transient diabetes insipidus, cerebrospinal fluid (CSF) leakage, and cranial nerve deficits were 6.7%, 0.8%, and 0%. No new cranial nerve deficits occurred. The mortality rate was 0.8%.ConclusionThe concept of “penetration” refines the extracavernous growth pattern, and the five intracranial subclassifications help to understand the potential extension corridors, enhancing adequate exposure and targeted resection of Knosp4PA. This grading system may benefit from its predictive and prognostic value, from which a higher GTR rate can be achieved.

The ubiquitous and continuous natural processes of water absorption and evaporation have stimulated interest in generating electricity through the creation of a flow of electrical charge, which can then be collected and stored. However, the resultant low output power density as well as the complicated fabrication and operation processes have hindered the practical applications of this technology. Herein, we demonstrate a highly efficient self-operating hydroelectric nanogenerator (HENG) that produces electricity through the absorption and evaporation of seawater. The single HENG consists of a hydrophilic wool cloth stripe functionalized with ketjen black powders and equipped with two electrodes affixed at its ends. The continuous absorption and evaporation of seawater results in the generation of electricity that can be stored in a capacitor. A series of 16 HENGs, each consisting of 10 stacked wool cloth stripes, can generate sufficient power to charge a supercapacitor to 1.6 V within 5 h 30 min under ambient conditions, outperforming most comparable devices reported. The superior performance observed for the HENG is attributable to the hydrophilicity and porosity of wool cloth which can continuously absorb seawater at a desired rate as well as the 2D structure of ketjen black and its high conductivity. This work paves the way to facilitate the development of HENGs for practical applications.

Electrolysis of inexhaustible seawater offers a promising way for harvesting practically infinite hydrogen energy without worsening freshwater shortage. Complicated ionic environment of saline seawater, however, places a great burden on catalyst performance for hydrogen evolution. Herein, tailoring the electronic structure of transitional metal phosphide by rare‐earth doping for effectively propelling hydrogen evolution in a wide pH range and natural seawater is reported. The rare‐earth doping leads to not only a nearly zero Gibbs free energy of H* adsorption and lower work function but also faster OH* desorption for rapid release of the active sites, thereby accelerating the hydrogen evolution reaction (HER) kinetics under nonacidic conditions. On this basis, highly conductive and hydrophilic MXene is introduced to further boost the adsorption of hydrogen carriers and charge transfer across the catalyst. Together, they allow the activity, kinetics, and durability of the electrocatalyst for HER to be improved overall. The obtained electrocatalyst shows superior activity to commercial Pt/C in terms of specific surface area and active mass and turnover frequency, as well as 400 times longer lifetime than Pt/C with high Faradaic efficiency in natural seawater. This study presents new insight into the development of viable electrocatalysts for harvesting hydrogen energy from abundant‐reserve seawater.