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Abstract With the increasing depletion of shallow mineral resources, deep mining has become important; however, basic research on deep resource development remains insufficient, and basic laws are unclear. In particular, comprehensive research on the pore structure characteristics of deep coal bodies at different scales is needed, and how burial depth affects pore structure characteristics should be investigated. Herein, this study performed mercury intrusion porosimetry, liquid nitrogen method, and low-temperature carbon dioxide adsorption method to systematically determine the pore structure characteristics of deep coal and comprehensively analyze coal pore complexity based on the Menger Sponge, Frenkel–Halsey–Hill (FHH), and density function models. The influence of depth on coal pore structure was also discussed. In the study zone, the stage pore volume was mainly concentrated in the macroporous (43.6–83.4%) and mesoporous Sect. (16.3–54.7%) and sparsely distributed in the microporous Sect. (0.3–2.1%). The accumulated pore volume decreased with an increase in coal sample burial depth, with a gentle curve in the micropore section and obvious fluctuations in the mesopore and macropore sections. The main distribution of stage surface area was in the mesoporous Sect. (79.5–91.8%), followed by the microporous (7.8–19.8%) and macroporous Sect. (0.3–0.6%). The accumulated surface area curve fluctuated greatly in the mesoporous and microporous sections, and that in the macroporous section was relatively flat with limited distribution. According to the Menger Sponge model, the fractal dimensions of the macroporous (Dmac) and mesoporous (Dmes) sections ranged from 2.4 to 2.8 and 3.7–3.9, respectively, with obvious fractal characteristics; Dmes was higher than Dmac, indicating that the structure of small and medium-sized micropores is more complex and irregular. The fractal dimension in the high-pressure zone of the FHH model (DHP) ranged from 2.8 to 2.9, and that in the low-pressure zone (DLP) ranged from 2.1 to 2.4, indicating that coal pore structure under low-pressure conditions is relatively simple. The fractal dimension of the density functional model ranged from 2.5 to 3.0, closer to 3, indicating that the pores are relatively complex and rough. A single-variable analysis revealed a strong correlation between burial depth and aperture parameters. This is the first study to reveal the relationship between burial depth and aperture parameters. Moreover, characterization of critical depth based on aperture structure was performed, providing a feasible method for quantifying “critical depth.” Our results enrich our understanding of the structure of deep coal bodies and serve as a reference for deep mining engineering.

To study the pore structure and fractal characteristics of deep medium-rank coal, combined characterization using mercury intrusion and liquid nitrogen adsorption methods was conducted on coal samples from the main coal seams in typical deep mining areas, including Shenyang Hongyang Third Mine, Kailuan Linxi Mine, Huainan Xinji Second Mine, and Pingdingshan Pingmei Sixth Mine. Parameters such as pore size, pore volume, and specific surface area were obtained, and the pore fractal characteristics were studied based on the Menger sponge model and the FHH model. The results showed that: (1) Among the pore structure parameters tested with mercury intrusion method, the average pore size ranged from 31.10 to 34.70 nm, pore volume from 0.048 3 to 0.059 4 mL/g, and specific surface area from 5.590 9 to 7.652 8 m2/g. The pore development in the main coal seams of typical deep mining areas was relatively similar. The pore volume distribution was dominated by macropores, with micropores and transition pores contributing roughly equally, and mesopores having a relatively small distribution. This indicated that macropores had better connectivity and mesopores were more closed. Micropores accounted for more than 70% of the total specific surface area, while the proportions of mesopores and macropores were minimal, indicating that micropores had the strongest adsorption capacity, which was negatively affected gas management in deep coal seams. The fractal dimensions based on the Menger sponge model ranged from 2.6 to 3.0, indicating irregular pore shapes, complex pore structures, and generally rough pore surfaces. (2) The effective pore size tested using liquid nitrogen adsorption method ranged from 3 to 177 nm with significant differences in total pore volume and specific surface area among the mining areas. Pore volume distribution was dominated by transition pores and mesopores, with a lower distribution of micropores and no macropores. This indicated that liquid nitrogen adsorption was effective for characterizing mesopores and transition pores but struggled to characterize macropore structures. Moreover, the connectivity of micropores was relatively poor. The specific surface area was mainly composed of transition pores, micropores, and mesopores, with no macropores. Among them, transition pores were mostly dominant and had relatively strong adsorption capacity. The fractal dimensions based on the FHH model ranged from 2.0 to 2.7, indicating a relatively simple and regular structure. (3) The differences in pore structures of deep medium-rank coal were discussed. The pore structure parameters (specific surface area and pore volume) determined by mercury intrusion and liquid nitrogen adsorption methods showed a non-linear concave curve variation with increasing burial depth. The fractal dimensions derived from the Menger sponge model and the FHH model showed a convex curve trend with increasing burial depth.

Currently, the detection technology for road surface potholes, primarily focuses on the identification and segmentation, lacking the ability to quantitatively analyze the damage inflicted by road potholes. Therefore, this pa per proposes a method based on three-dimensional point clouds for the identification, segmentation, and reconstruction of road potholes, ultimately leading to the quantification of the damage volume. An RGB-D depth sensor is employed to collect point cloud data of road potholes. Voxel filtering and voxelization downsampling are used for denoising, filtering, and enhancing data processing efficiency. Surface segmentation is achieved through RANSAC (Random Sample Consensus) and Euclidean clustering, while the Alpha Shapes algorithm is utilized for three-dimensional volume reconstruction, facilitating the volumetric quantification of potholes. For evaluation, comparative experiments were conducted under different lighting conditions and shooting distances. The experimental results demonstrate that the proposed algorithm achieves an accuracy of 96.4% in volumetric damage measurement of road potholes, accurately determining the damage volume of pothole.

Abstract The recent discovery of the persistence of long-range magnetic order when van der Waals magnets are thinned towards monolayers provides a tunable platform for engineering of novel magnetic structures and devices. Here, we study the evolution of the electronic structure of CrGeTe3 as a function of surface electron doping. From angle-resolved photoemission, we observe spectroscopic fingerprints that this electron doping drives a marked increase in T C, reaching values more than double that of the undoped material, in agreement with recent studies using electrostatic gating. Together with density functional theory calculations and Monte Carlo simulations, we show that, surprisingly, the increased T C is mediated by the population of spin-minority Cr t 2g states, forming a half-metallic 2D electron gas. This promotes a novel variant of double exchange, and unlocks a significant influence of Ge – which was previously thought to be electronically inert in this system – in mediating Cr-Cr exchange.

Abstract Background Over the past few years, the development of telerehabilitation has advanced rapidly. Patients with Parkinson's disease (PwPD) often have difficulty with mobility, making it challenging for them to perform centre-based exercise.This study aims to compare the effectiveness and adherence of home physical therapy (HPT) and telerehabilitation (TR) in mitigating motor symptoms and improving the quality of life in patients with mild to moderate Parkinson’s disease. Methods This randomized controlled trial included a total of 190 patients who underwent in-person eligibility assessment, with 100 allocated to the HPT group and 90 to the TR group. Both interventions consisted of home-based training sessions lasting 40–60 min and were conducted five times a week for 4 weeks. The primary outcome was the Unified Parkinson’s Disease Rating Scale motor section (UPDRS3) score. Secondary outcomes included balance function, assessed using the Berg Balance Scale (BBS); risk of fall, evaluated through the Timed Up-and-Go test (TUG) and the Five Times Sit-to-Stand test (FTSST); gait, measured using the Freezing of Gait Questionnaire (FOGQ) and IDEEA activity monitor; muscle strength, evaluated using the isokinetic dynamometry; motor aspects of experiences of daily living (UPDRS2); and quality of life, assessed by Parkinson's Disease Questionnaire-39 (PDQ-39). Results There was a significant difference in the UPDRS3, BBS, TUG, FTSST, FOGQ,step length, step velocity,preswing angle, UPDRS2 and PDQ-39 between baseline and 4 weeks in both groups. The decrease in the UPDRS3 score was significantly greater in the HPT group (-3.38 points) than in the RE group (-1.45 points) in the older age group (P = 0.021), but there was no significant between-group difference in the younger age group (P = 0.416). Similar changes favouring the HPT group were observed in the BBS, TUG, step velocity, and extension average torque. 7 (7%) patients in the HPT group and 12 (13%) patients in the TR group did not complete their daily exercise plan. Conclusions Both HPT and TR have demonstrated effectiveness, safety, and feasibility in PwPD. However, the HPT program exhibited greater effectiveness among older patients and higher patient compliance compared to TR. Trial registration Chictr.org.cn, ChiCTR2300071648. Registered on 22 May 2023—retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=196313 .

This study investigates two extraction methods—ultrasound-assisted extraction (UAE) and compound enzyme extraction (CE)—for the isolation of Lonicera macranthoides polysaccharides (LMP) and evaluates their physicochemical properties, bioactivity, and therapeutic potential. The optimization of extraction conditions was performed using single-factor experiments and response surface methodology. The yield of LMP from UAE was optimized to 8.02 % ± 0.12 %, while the yield from CE was 10.03 % ± 0.32 %. Both polysaccharide extracts were characterized in terms of chemical composition, monosaccharide composition, molecular weight, thermal stability, and functional group analysis. Notably, UAE-LMP exhibited superior antioxidant, hypolipidemic, nitrite scavenging, and anti-tumor activities compared to CE-LMP. The ultrasound-assisted method enhanced the stability and bioactivity of LMP, with improved water- and oil-holding capacities and the integrity of the active groups. Our findings demonstrate that the extraction method significantly influences the structural and functional properties of LMP, suggesting that UAE may be a more effective approach for extracting bioactive polysaccharides with potential applications in medicine and nutrition.

Multidrug resistance significantly impedes the efficacy of cancer chemotherapy. Resistance often arises from the reduced cellular uptake of chemotherapeutic drugs, a process crucial for their cytotoxic effects. This reduction is frequently due to transmembrane efflux pumps powered by ATP from mitochondria and the cytoplasmic matrix, leading to lower intracellular concentrations of these drugs. This study introduces an amphiphilic molecule, bis(zinc-dipicolylamine) farnesol (Bis-ZnDPA), which targets phosphatidylserine (PS) – a negatively charged phospholipid prominently displayed on the outer leaflet of cancer cell plasma membranes. Integrating the hydrophobic segment of Bis-ZnDPA into the plasma membrane disrupts its integrity, potentially leading to hole formation and facilitating the uptake of chemotherapeutic drugs. Furthermore, the binding of Bis-ZnDPA to phosphatidylserine inhibits ATP production caused by Ca2+ influx and deregulation of the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) signaling pathway, reducing the efflux of drugs from cells. The results indicate the potent synergistic effect of Bis-ZnDPA with chemotherapeutic agents, suggesting that targeting PS is a viable strategy for overcoming multidrug resistance in cancer chemotherapy.

BackgroundPlatelets can dynamically regulate tumor development and progression. Nevertheless, research on the predictive value and specific roles of platelets in gastric cancer (GC) is limited. This research aims to establish a predictive platelets-related gene signature in GC with prognostic and therapeutic implications.MethodsWe downloaded the transcriptome data and clinical materials of GC patients (n=378) from The Cancer Genome Atlas (TCGA) database. Prognostic platelets-related genes screened by univariate Cox regression were included in Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk model. Kaplan-Meier curves and receiver operating characteristic curves (ROCs) were performed in the TCGA cohort and three independent validation cohorts. A nomogram integrating the risk score and clinicopathological features was constructed. Functional enrichment and tumor microenvironment (TME) analyses were performed. Drug sensitivity prediction was conducted through The Cancer Therapeutics Response Portal (CTRP) database. Finally, the expression of ten signature genes was validated by quantitative real-time PCR (qRT-PCR).ResultsA ten-gene (SERPINE1, ANXA5, DGKQ, PTPN6, F5, DGKB, PCDH7, GNG11, APOA1, and TF) predictive risk model was finally constructed. Patients were categorized as high- or low-risk using median risk score as the threshold. The area under the ROC curve (AUC) values for the 1-, 2-, and 3-year overall survival (OS) in the training cohort were 0.670, 0.695, and 0.707, respectively. Survival analysis showed a better OS in low-risk patients in the training and validation cohorts. The AUCs of the nomogram for predicting 1-, 2-, and 3-year OS were 0.708, 0.763, and 0.742, respectively. TME analyses revealed a higher M2 macrophage infiltration and an immunosuppressive TME in the high-risk group. Furthermore, High-risk patients tended to be more sensitive to thalidomide, MK-0752, and BRD-K17060750.ConclusionThe novel platelets-related genes signature we identified could be used for prognosis and treatment prediction in GC.

Selenium nanoparticles (SeNPs) have been used as a potential alternative to other forms of selenium in nutritional supplements for the treatment and prevention of inflammatory and oxidative stress-related diseases. Zearalenone (ZEA) is a foodborne mycotoxin present in grains that poses a health threat. Here, we investigated the adverse impacts of ZEA on intestinal homeostasis and explored the protective effects of probiotic-synthesized SeNPs against its damage. Results showed that ZEA reduced mucin and tight junction proteins expression in jejunum, induced inflammatory process and oxidative stress which in turn increased intestinal permeability in mice. ZEA-induced intestinal toxicity was further verified in vitro. Intracellular redox imbalance triggered endoplasmic reticulum (ER) stress in intestinal epithelial cells, which caused structural damage to the ER. Remarkably, SeNPs exhibited a counteractive effect by inducing a decrease in intracellular levels of Inositol 1,4,5-trisphosphate (IP3) and Ca2+, along with a reduction in the expression level of IP3 receptor. SeNPs effectively mitigated ZEA-induced ER stress was related to the increased activity of selenium-dependent antioxidant enzymes and the expression of ER-resident selenoproteins. Furthermore, SeNPs significantly inhibited the activation of PERK/eIF2α/ATF4/CHOP pathway in vitro and in vivo. In addition, SeNPs effectively reversed ZEA-induced gut microbiota dysbiosis and increased the abundance of short-chain fatty acid-producing beneficial bacteria (Alloprevotella and Muribaculaceae). The Spearman correlation analysis suggested that the structure of gut microbiota was closely related to the SeNPs attenuation of ZEA-induced intestinal toxicity. This study provides new insights into ZEA-induced intestinal toxicity and identifies a novel potential nutrient SeNPs to overcome adverse effects.

With the rapid development of infrared detection technology, the importance and urgency of air-craft infrared stealth are becoming increasingly prominent. The engine exhaust system is one of the main infrared radiation sources of fighter aircraft, and it is of great significance to effectively suppress the infrared radiation of the engine exhaust system and tail jet. In this paper, based on the Reverse Monte Carlo Method, a program is developed to calculate the infrared radiation characteristics of an aeroengine exhaust system and evaluate the infrared suppression effect. The Ray Tracing Method is created to search the control body that passes through the ray transmission path, and the computing efficiency is greatly improved. Based on the program, the effect of the lobe mixer on the infrared characteristics of the engine exhaust system is analyzed. The results show that the use of the lobe mixer can not only effectively suppress the gas radiation but also reduce the solid radiation intensity of the high temperature wall and play a good infrared suppression effect on all detection directions of the exhaust system.

Abstract Background Bergeyella porcorum is a newly identified bacterium that has an ambiguous relationship with pneumonia in pigs. However, few studies have adequately characterized this species. Results In this study, we analyzed the morphological, physiological, and genomic characteristics of the newly identified B. porcorum sp. nov. strain QD2021 isolated from pigs. The complete genome sequence of the B. porcorum QD2021 strain consists of a single circular chromosome (2,271,736 bp, 38.51% G + C content), which encodes 2,578 genes. One plasmid with a size of 70,040 bp was detected. A total of 121 scattered repeat sequences, 319 tandem repeat sequences, 4 genomic islands, 5 prophages, 3 CRISPR sequences, and 51 ncRNAs were predicted. The coding genes of the B. porcorum genome were successfully annotated across eight databases (NR, GO, KEGG, COG, TCDB, Pfam, Swiss-Prot and CAZy) and four pathogenicity-related databases (PHI, CARD, VFDB and ARDB). In addition, a comparative genome analysis was performed to explore the evolutionary relationships of B. porcorum QD2021. Conclusions To our knowledge, this is the first study to provide fundamental phenotypic and whole-genome sequences for B. porcorum. Our results extensively expand the current knowledge and could serve as a valuable genomic resource for future research on B. porcorum.

Abstract Background Hepatitis B virus (HBV) integrates into human chromosomes and can lead to genomic instability and hepatocarcinogenesis. Current tools for HBV integration site detection lack accuracy and stability. Results This study proposes a deep learning-based method, named ViroISDC, for detecting integration sites. ViroISDC generates corresponding grammar rules and encodes the characteristics of the language data to predict integration sites accurately. Compared with Lumpy, Pindel, Seeksv, and SurVirus, ViroISDC exhibits better overall performance and is less sensitive to sequencing depth and integration sequence length, displaying good reliability, stability, and generality. Further downstream analysis of integrated sites detected by ViroISDC reveals the integration patterns and features of HBV. It is observed that HBV integration exhibits specific chromosomal preferences and tends to integrate into cancerous tissue. Moreover, HBV integration frequency was higher in males than females, and high-frequency integration sites were more likely to be present on hepatocarcinogenesis- and anti-cancer-related genes, validating the reliability of the ViroISDC. Conclusions ViroISDC pipeline exhibits superior precision, stability, and reliability across various datasets when compared to similar software. It is invaluable in exploring HBV infection in the human body, holding significant implications for the diagnosis, treatment, and prognosis assessment of HCC.

Abstract Background Serum uric acid (SUA) is an important pathogenetic and prognostic factor for heart failure (HF). Gender differences are apparent in HF. Furthermore, gender differences also exist in the association between SUA and prognosis in various cardiovascular diseases. However, the gender difference for SUA in the prediction of long-term prognosis in HF is still ambiguous. Methods A total of 1593 HF patients (897 men, 696 women) from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 cycle were enrolled in our final analysis. Participants were categorized according to gender-specific SUA tertile. We assessed the association between SUA and long-term prognosis of HF patients, defined as all-cause mortality and cardiovascular mortality, in different genders via Kaplan–Meier curve analysis, Cox proportional hazard model, and Fine-Gray competing risk model. The restricted cubic spline (RCS) was performed to investigate the dose-response relationship between SUA and outcomes. Results Gender differences exist in demographic characteristics, clinical parameters, laboratory tests, and medication of HF patients. After a median follow-up of 127 months (95% CI 120–134 months), there were 853 all-cause deaths (493 events in men, 360 events in women) and 361 cardiovascular deaths (206 events in men, 155 events in women). Kaplan-Meier analysis showed that SUA had gender difference in the prediction of cardiovascular mortality (Log-rank p

Abstract Objective The purpose of this study is to investigate the connection of pre-competition anxiety with gut microbiota and metabolites in wrestlers with different sports performances. Methods One week prior to a national competition, 12 wrestlers completed anxiety questionnaires. Faecal and urine samples were collected for the analysis of gut microbiota and metabolites through the high-throughput sequencing of the 16 S rRNA gene in conjunction with untargeted metabolomics technology. The subjects were divided into two groups, namely, achievement (CP) and no-achievement (CnP) wrestlers, on the basis of whether or not their performances placed them in the top 16 at the competition. The relationship amongst the variations in gut microbiota, metabolites, and anxiety indicators was analyzed. Results (1) The CP group exhibited significantly higher levels of “state self-confidence,” “self-confidence,” and “somatic state anxiety” than the CnP group. Conversely, the CP group displayed lower levels of “individual failure anxiety” and “sports competition anxiety” than the CnP group. (2) The gut microbiota in the CP group was more diverse and abundant than that in the CnP group. Pre-competition anxiety was linked to Oscillospiraceae UCG_005, Paraprevotella, Ruminococcaceae and TM7x. (3) The functions of differential metabolites in faeces and urine of the CP/CnP group were mainly enriched in caffeine metabolism, lipopolysaccharide biosynthesis and VEGF and mTOR signaling pathways. Common differential metabolites in feces and urine were significantly associated with multiple anxiety indicators. Conclusions Wrestlers with different sports performance have different pre-competition anxiety states, gut microbiota distribution and abundance and differential metabolites in faeces and urine. A certain correlation exists between these psychological and physiological indicators.

The current investigation aims to study the bio route preparation of chitosan capped-silver nanoparticles using aqueous flower extract of the Achillea ptarmica plant. The biosynthesized silver nanoparticles/chitosan (Ag NPs@CHI) were characterized by various spectroscopic techniques. The creation of Ag nanoparticles over the chitosan was initially determined by the presence of a single broad peak at 545 nm that was recorded by the UV–Vis spectrum. The presence of poly-dispersity, spherical shape and nanosizes in the Ag NPs@CHI were verified by the TEM and SEM pictures. The purity and crystalline nature of the prepared Ag NPs@CHI were confirmed by XRD analysis. In vivo, Ag NPs@CHI decreased the inflammatory cells presence in the colon and ileum, lowered the levels of IL-17A, IL-1β, IL-6, and TNF-α, raised the levels of IL-10 and IL-4 in colon tissues, enhanced acetate and propionate production. The findings revealed that Ag NPs@CHI have the potential to boost intestinal structure restoration, decrease levels of inflammatory cytokines and enhance short-chain fatty acid (SCFA) levels. Our research demonstrated that Ag NPs@CHI can safeguard the intestinal barrier by upregulating the expression of Claudin-1 and Occludin. Furthermore, silver nanoparticles suppressed the MAPK signaling pathway to ameliorate the inflammatory condition. Following the completion of clinical trials, these novel nanoparticles could serve as a promising new treatment for diarrhea in humans.

Objective Hepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC is imperative for improving patient prognosis.Design In this study, to systematically investigate the characteristics of cancer-associated fibroblast (CAF) subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by CAF subsets, we generated an HCC atlas by compiling single-cell RNA sequencing (scRNA-seq) datasets on 220 samples from six datasets. We combined spatial transcriptomics with scRNA-seq and multiplexed immunofluorescence to identify the specific CAF subsets in the TME that determine the efficacy of immunotherapy in HCC patients.Results Our findings highlight the pivotal role of POSTN+ CAFs as potent immune response barriers at specific tumor locations, as they hinder effective T-cell infiltration and decrease the efficacy of immunotherapy. Additionally, we elucidated the interplay between POSTN+ CAFs and SPP1+ macrophages, whereby the former recruits the latter and triggers increased SPP1 expression via the IL-6/STAT3 signaling pathway. Moreover, we demonstrated a spatial correlation between POSTN+ CAFs and SPP1+ macrophages, revealing an immunosuppressive microenvironment that limits the immunotherapy response. Notably, we found that patients with elevated expression levels of both POSTN+ CAFs and SPP1+ macrophages achieved less therapeutic benefit in an immunotherapy cohort.Conclusion Our research elucidates light on the role of a particular subset of CAFs in immunotherapy resistance, emphasizing the potential benefits of targeting specific CAF subpopulations to improve clinical responses to immunotherapy.

TC4/DP780 dissimilar metals were laser welded with different thicknesses of the H62 interlayer. Joints with good forming and mechanical properties were obtained. The corrosive behaviors of TC4/DP780 joints in 3.5 wt% NaCl solution were investigated by micro-area scanning vibrating electrode technique (SVET). Results showed that TC4/DP780 joints effectively hindered the brittle intermetallic compounds of Ti–Fe through mutual diffusion and the solid solution between the H62 layer metal and TC4 alloy. Cu–Ti intermetallic compounds and H62 Cu-based solid solution formed at the H62/TC4 interface. The intermetallic compounds layer grew dendritically from the dependent TC4 alloy toward the weld. With increased Ti element content and interlayer temperature, the microstructure morphology changed from fine dendrites to coarse dendrites. Corrosion experiments further revealed that with increased thickness of the H62 interlayer, the corrosion resistance of joints initially increased and then decreased. The joints added with a 0.4 mm H62 interlayer had the highest self-corrosion potential and the lowest self-corrosion current density. The corrosion rate of joints was the slowest. DP780 steel formed loose porous Fe2O3, accelerating the metal-corrosion dissolution. The H62 primarily formed due to the corrosion susceptibility of ZnO, leaving the porous structure of the Cu layer and the enabling the formation of CuO. TC4 had the highest corrosion potential and was protected as the cathode. TC4 underwent galvanic coupling corrosion with the DP780 steel and the H62 interlayer metal. Meanwhile, TC4 was oxidized in air to form a dense TiO2 and Al2O3 protective film, which had good restoration and passivation effects.

Objective: To improve the film heating process. Methods: In this experiment, edible protein-polysaccharide films were prepared by using the method of chain dissociation at 35, 40, 45, 50, 55 ℃ at one stage and denaturing and heating whey protein isolation at 85 ℃ at the second stage. The structure, hydrophobicity, barrier properties and mechanical properties of the films were compared, and the optimum film forming process conditions were determined. Results: The oxygen resistance, tensile strength （TS） and elongation at break （EAB） of the film increased by 25.0%~58.7%, 54.8%~89.9% and 40.2%~59.2%, respectively, when the film was heated at 25 ℃ and 85 ℃ respectively. Water vapor barrier performance improved by 20.0%~52.6%. The infrared map of the film shows that temperature does not cause the change of the valence bond of the film. It was found that 45 ℃/85 ℃ two-stage step heating process had the most significant effect on improving the properties of the film. Conclusion: After the process optimization, the film's barrier properties and mechanical properties have been improved, which has the potential for food packaging applications.

Due to the rapid development of unmanned aerial vehicles (UAVs) communication technology, UAVs are gradually competing with primary users (PUs) for spectrum resources. Cognitive radio (CR) technology is a promising solution to meet the spectrum requirements of UAVs. Cooperative spectrum sensing (CSS) is considered as an effective paradigm to detect the PU signal and identify available spectrum resources for UAVs in a cognitive UAV network (CUAVN). However, the cooperative mode among multiple UAVs may incur a high communication overhead, resulting in a significant performance degradation. Therefore, we propose a differential sequential 1 (DS1), which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance the cooperative performance and efficiency of the PU detection. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multi-slot cooperative mode within a single UAV to realize cooperative gain. Further, only the information change about the PU status is sequentially calculated in DS1, and combined with a sequential idea, the efficiency of the voting rule is greatly improved. Moreover, the application of support vector machine (SVM) in dynamic selection enables the selection of the optimal voting rule based on diverse sensing parameters. This dynamic selection process follows the characteristic of the different PU scenarios to ensure the performance and efficiency. Finally, simulation results demonstrate that the superiority of the proposed DS1 and SVM dynamic selection with respect to the detection performance, sample size and the energy efficiency is evident, which proves the high performance of the proposed policy.

The drainage pipeline network constitutes a critical component of municipal infrastructure. Effective inspection of drainage pipelines is crucial for maintaining urban functions. However, manual inspection methods are inefficient and prone to error. To address this, an intelligent system for detecting, tracking and managing defects in drainage pipelines using YOLO-DeepSort (YOLO-DS) is proposed for automated defect information collection. Initially, YOLOv7 is employed to train the defect detection model, achieving a mean Average Presion (mAP) of 91.1% and processing at 172 frames per second (FPS). Subsequently, the YOLO-DS detection-based tracking algorithm is utilized to track defects in the pipeline video. Moreover, within the tracking framework, an innovative fusion module combining detection and ReID features enhances cross-frame matching robustness. Under conditions of lens rotation, jitter, and blur, the system achieves confidence levels exceeding 87% for potholes, 78% for misalignments, and 80% for obstructions, respectively, demonstrating strong robustness. Lastly, the detection and tracking algorithms are integrated into the information management platform. The management platform facilitates intelligent identification and counting of pipeline defects, and includes a professional communication module for automatic generation drainage pipeline health assessment reports, thereby streamlining manual inspection processes and saving assessment time.

A FeCrMoNiCuBSiC metallic glass coating was designed and then deposited by the high-velocity oxygen fuel (HVOF) spraying technique. X-ray diffraction, a scanning electron microscope, and a microhardness tester were applied to characterize the phase, microstructure, and mechanical properties of the coating. The amorphous phase was the main phase in the coating, and crystal phases were almost undetectable in the XRD results. The coating had a dense structure (the porosity was 1.47 ± 0.32%) and high Vickers microhardness (848 ± 22 HV0.3). The wear behavior of the coatings sliding against WC-Co was studied with a pin-on-disc wear test system and was compared with that of 316L stainless steel. The coating improved the wear resistance of the steel by around 7–9 times at different sliding speeds. As the sliding speed was increased, the wear loss rate of the steel obviously increased, yet the loss rate of the coating decreased first and then increased. This happened because the contact flash temperature induced by friction increases with the sliding speed, which results in oxidative behavior and crystallization events in the coating. The dominating wear mechanism of the coating is fatigue wear combined with oxidative wear.

Selenium nanoparticles (SeNPs) are proposed as a safer and more effective selenium delivery system than sodium selenite (Na2SeO3). Here, we investigated the effects of replacing dietary Na2SeO3 with SeNPs synthesized by Lactobacillus casei ATCC 393 on the growth performance and gut health of early-weaned piglets. Seventy-two piglets (Duroc × Landrace × Large Yorkshire) weaned at 21 d of age were divided into the control group (basal diet containing 0.3 mg Se/kg from Na2SeO3) and SeNPs group (basal diet containing 0.3 mg Se/kg from SeNPs) during a 14-d feeding period. The results revealed that SeNPs supplementation increased the average daily gain (P = 0.022) and average daily feed intake (P = 0.033), reduced (P = 0.056) the diarrhea incidence, and improved (P = 0.013) the feed conversion ratio compared with Na2SeO3. Additionally, SeNPs increased jejunal microvilli height (P = 0.006) and alleviated the intestinal barrier dysfunction by upregulating (P

Post-weaning diarrhea (PWD) in piglets poses a significant challenge and presents a grave threat to the global swine industry, resulting in considerable financial losses and compromising the welfare of animals. PWD is commonly associated with gut homeostatic imbalance, including oxidative stress, excessive inflammation, and microbiota dysbiosis. Antibiotic use has historically been a common initiative to combat PWD, but concerns about the development of antibiotic resistance have led to increased interest in alternative strategies. Mitochondria are key players in maintaining cellular homeostasis, and their dysfunction is intricately linked to the onset and progression of PWD. Accumulating evidence suggests that targeting mitochondrial function using antioxidant nutrients, such as vitamins, minerals and polyphenolic compounds, may represent a promising approach for preventing and treating PWD. Moreover, nutrients based on antioxidant strategies have been shown to improve mitochondrial function, restore intestinal redox balance, and reduce oxidative damage, which is a key driver of PWD. The present review begins with an overview of the potential interplay between mitochondria and gut homeostasis in the pathogenesis of PWD in piglets. Subsequently, alternative strategies to prevent and treat PWD using antioxidant nutrients to target mitochondria are described and discussed. Ultimately, we delve into potential limitations and suggest future research directions in this field for further advancement. Overall, targeting mitochondria using antioxidant nutrients may be a promising approach to combat PWD and provides a potential nutrition intervention strategy for regulating gut homeostasis of weaned piglets.

Pinus is an economically and ecologically important genus whose members are dominant components globally in low-latitude mountainous and mid-latitude temperate forests. Pinus species richness is currently concentrated in subtropical mid-low latitudes of the Northern Hemisphere, differing from the latitudinal diversity gradient mostly recognized in woody angiosperms. How the present pattern was developing in Earth's past is still poorly studied, particularly in eastern Asia. Here, a new fossil species, Pinus shengxianica sp. nov. is described based on a fossil seed cone from the Late Miocene Shengxian Formation in Zhejiang, southeast China. A co-occurring cone is recognized as a known fossil species, Pinus speciosa Li. Extensive comparison of extant and fossil members of Pinus suggests P. shengxianica shares a striking cone similarity to Pinus merkusii and Pinus latteri (subsection Pinus) from tropical Southeast Asia in having annular bulges around the umbo on the apophysis. The morphological resemblance indicates these two extant low-latitude pines probably possess a close affinity with the present newly-discovered P. shengxianica and originated from East Asian mid-low latitude ancestors during this generic re-diversification in the Miocene. This scenario is consistent with the evolutionary trajectory reflected by the pine fossil history and molecular data, marking the Miocene as a key period for the origin and evolution of most extant pines globally. The co-occurrences of diverse conifers and broadleaved angiosperms preferring diverse niches demonstrate Late Miocene eastern Zhejiang was one of the hot spots for coniferophyte diversity and hosted a needled-broadleaved mixed forest with complex vegetation structure and an altitudinal zonation.

The mortality of hepatocellular carcinoma (HCC) is on the rise globally, particularly in the Western world, with etiology gradually shifting from virus-related liver diseases to metabolic disorders such as non-alcoholic fatty liver disease. Early detection of HCC is challenging, and effective prognostic indicators are currently lacking, urgently necessitating reliable markers to assist in treatment planning and clinical management. Here, we introduce hepatocellular carcinoma senescence genes (HSG) to assess cellular senescence in HCC and devise a hepatocellular carcinoma senescence score (HSS) for prognostic prediction. Higher HSS levels signify poorer prognosis and increased tumor proliferation activity. Additionally, we observe alterations in the tumor immune microenvironment with higher HSS levels, such as increased infiltration of Treg, potentially providing a basis for immunotherapy. Furthermore, we identify key genes, such as PTTG1, within the senescence gene set and demonstrate their regulatory roles in HCC cells and Treg through experimentation. In summary, we establish a scoring system based on hepatocellular carcinoma senescence genes for prognostic prediction in HCC, potentially offering guidance for clinical treatment planning.

Abstract Background The current standard of care for locally advanced gastric cancer (GC) involves neoadjuvant chemotherapy followed by radical surgery. Recently, neoadjuvant treatment for this condition has involved the exploration of immunotherapy plus chemotherapy as a potential approach. However, the efficacy remains uncertain. Methods A single‐arm, phase 2 study was conducted to evaluate the efficacy and tolerability of neoadjuvant camrelizumab combined with mFOLFOX6 and identify potential biomarkers of response through multi‐omics analysis in patients with resectable locally advanced GC. The primary endpoint was the pathological complete response (pCR) rate. Secondary endpoints included the R0 rate, near pCR rate, progression‐free survival (PFS), disease‐free survival (DFS), and overall survival (OS). Multi‐omics analysis was assessed by whole‐exome sequencing, transcriptome sequencing, and multiplex immunofluorescence (mIF) using biopsies pre‐ and post‐neoadjuvant therapy. Results This study involved 60 patients, of which 55 underwent gastrectomy. Among these, five (9.1%) attained a pathological complete response (pCR), and 11 (20.0%) reached near pCR. No unexpected treatment‐emergent adverse events or perioperative mortality were observed, and the regimen presented a manageable safety profile. Molecular changes identified through multi‐omics analysis correlated with treatment response, highlighting associations between HER2‐positive and CTNNB1 mutations with treatment sensitivity and a favourable prognosis. This finding was further supported by immune cell infiltration analysis and mIF. Expression data uncovered a risk model with four genes (RALYL, SCGN, CCKBR, NTS) linked to poor response. Additionally, post‐treatment infiltration of CD8+ T lymphocytes positively correlates with pathological response. Conclusion The findings suggest the combination of PD‐1‐inhibitor and mFOLFOX6 showed efficacy and acceptable toxicity for locally advanced GC. Extended follow‐up is required to determine the duration of the response. This study lays essential groundwork for developing precise neoadjuvant regimens.

Although Mollisols are renowned for their fertility and high-productivity, high carbon (C) losses pose a substantial challenge to the sustainable provision of ecosystem services, including food security and climate regulation. Protecting these soils with a specific focus on revitalizing their C sequestration potential emerges as a crucial measure to address various threats associated with climate change. In this study, we employed a modeling approach to assess the impact of different fertilization strategies on crop yield, soil organic carbon (SOC) stock, and C sequestration efficiency (CSE) under various climate change scenarios (baseline, RCP 2.6, RCP 4.5, and RCP 8.5). The process-based SPACSYS model was calibrated and validated using data from two representative Mollisol long-term experiments in Northeast China, including three crops (wheat, maize and soyabean) and four fertilizations (no-fertilizer (CK), mineral nitrogen, phosphorus and potassium (NPK), manure only (M), and chemical fertilizers plus M (NPKM or NM)). SPACSYS effectively simulated crop yields and the dynamics of SOC stock. According to SPACSYS projections, climate change, especially the increased temperature, is anticipated to reduce maize yield by an average of 14.5% in Harbin and 13.3% in Gongzhuling, and soybean yield by an average of 10.6%, across all the treatments and climatic scenarios. Conversely, a slight but not statistically significant average yield increase of 2.5% was predicted for spring wheat. SOC stock showed a decrease of 8.2% for Harbin and 7.6% for Gonghzuling by 2,100 under the RCP scenarios. Future climates also led to a reduction in CSE by an average of 6.0% in Harbin (except NPK) and 13.4% in Gongzhuling. In addition, the higher average crop yields, annual SOC stocks, and annual CSE (10.15–15.16%) were found when manure amendments were performed under all climate scenarios compared with the chemical fertilization. Soil CSE displayed an exponential decrease with the C accumulated input, asymptotically approaching a constant. Importantly, the CSE asymptote associated with manure application was higher than that of other treatments. Our findings emphasize the consequences of climate change on crop yields, SOC stock, and CSE in the Mollisol regions, identifying manure application as a targeted fertilizer practice for effective climate change mitigation.

This paper discusses the successful welding of AZ31 Mg alloy to 22MnB5 high-strength steel using pinless friction stir welding (P-FSSW) to join dissimilar metals and reduce vehicle weight while maintaining strength and stiffness. P-FSSW eliminates fusion welding defects, ensuring good performance of Mg/steel welds. An orthogonal experimental design was adopted to comprehensively analyze welding parameters for determining the optimum P-FSSW process conditions. The study provides an in-depth examination of the interfacial layer formation between AZ31 Mg alloy and 22MnB5 steel, emphasizing the importance of Al for effective bonding in Mg alloys. Numerical simulation of the welding process's temperature field is verified by thermocouple measurements, confirming result accuracy. The study aims to optimize bonding of dissimilar materials and facilitate interfacial reactions for achieving high-performance welded joints. This comprehensive understanding of the P-FSSW process and interfacial layer formation holds great significance for lightweight construction in the automotive industry, contributing to reduced emissions and improved fuel efficiency.

In order to enhance the microstructure and mechanical properties of additively manufactured metal parts, the application of ultrasonic impact treatment (UIT) after the additive manufacturing process is introduced as a means to modulate and optimize the material's microstructure and properties. This study systematically investigates the effect of UIT on the distribution of residual stresses in CrCoNi medium entropy alloy (CrCoNi-MEA) through numerical simulation. A suitable finite element model and boundary conditions are established to simulate the UIT assisted laser DED process. The reliability of the finite element model is verified by XRD residual test results and EBSD observation results. The numerical simulation results shows that the specimen's surface exhibited predominantly compressive stress within a specific depth range, with the maximum compressive stress in the vertical direction. Furthermore, it is observed that UIT amplitude, frequency, and impact needle diameter also significantly influenced the residual stresses. By appropriately adjusting the UIT parameters, the magnitude and distribution of residual stresses could be further controlled and regulated. In addition, it is found that multiple UITs at different surface locations exhibited no significant mutual influence between each other.

Abstract Background Many long noncoding RNAs (lncRNAs) are the key regulators for cancer progression, including breast cancer (BC). RUSC1 antisense 1 (RUSC1‐AS1) has been found to be highly expressed in BC, but its role and potential molecular mechanism in BC remain to be further elucidated. Methods Quantitative reverse transcription‐polymerase chain reaction (RT‐PCR) was utilized to measure RUSC1‐AS1, microRNA (miR)‐326 and X‐ray repair cross‐complementing group 5 (XRCC5) expression. Cell proliferation, metastasis, cell cycle, apoptosis and angiogenesis were determined by cell counting kit‐8, colony formation, transwell, flow cytometry and tube formation assays. Protein expression was detected by western blot analysis. The targeted relationship between miR‐326 and RUSC1‐AS1 or XRCC5 was validated using dual‐luciferase reporter assay and RIP assay. Xenograft models were constructed to uncover the effect of RUSC1‐AS1 on BC tumorigenesis. Results RUSC1‐AS1 was upregulated in BC, and its downregulation suppressed BC proliferation, metastasis, cell cycle, angiogenesis, and tumor growth. MiR‐326 was confirmed to be sponged by RUSC1‐AS1, and its inhibitor reversed the regulation of RUSC1‐AS1 silencing on BC progression. XRCC5 could be targeted by miR‐326. Overexpression of XRCC5 reversed the inhibitory impacts of miR‐326 on BC progression. Conclusion RUSC1‐AS1 could serve as a sponge of miR‐326 to promote BC progression by targeting XRCC5, suggesting that RUSC1‐AS1 might be a target for BC treatment.

The pore fracture structure of deep coal reservoirs is crucial for evaluating the potential of deep coalbed methane resources, conducting exploration and development, and controlling coal mine gas disasters. Mercury intrusion porosimetry, the liquid nitrogen method, and the low-temperature carbon dioxide adsorption method were used to study the full pore size structure and pore fractal characteristics of different coal grades in deep coal and comprehensively characterize the pore structure of kilometer-level coal mining. The sponge, Frenkel–Halsey–Hill (FHH), and density function models were applied to comprehensively analyze the pore complexity of coal, and the influence of metamorphic degree on pore size structure was evaluated. The distribution relationship of pore volume in different stages of coal samples was macropore→mesopore→micropore, and macropores had the best connectivity. Micropores and mesopores had the largest specific surface area, and the development of micropores and microcracks controlled the deep gas adsorption performance. The micropore volume and specific surface area both revealed a nonlinear decreasing trend with the increase in volatile matter, and coal metamorphism promoted the development of micropores. The pore volume and specific surface area of mesopores and macropores decreased first and then increased in a “U” shape with increasing volatile matter. In contrast, the fractal dimension D1 revealed an inverted U shape with increasing volatile matter, followed by a decrease. The D2 value decreased nonlinearly with increasing volatile matter, whereas the D3 value increased nonlinearly with increasing volatile matter. The degree of metamorphism increased, and the microporous structure became more regular.

In this study, the extraction, purification and metabolic enzyme inhibition potential of Selaginella doederleinii were investigated. In order to extract the total biflavonoids from S. doederleinii (SDTBs), the optimum extraction process was obtained by optimizing the ultrasonic extraction parameters using response-surface methodology. This resulted in a total biflavonoid content of 22.26 ± 0.35 mg/g. Purification of the S. doederleinii extract was carried out using octadecylsilane (ODS), and the transfer rate of the SDTBs was 82.12 ± 3.48% under the optimum purification conditions. We determined the effect of the SDTBs on α-glucosidase (AG), α-amylase and xanthine oxidase (XOD) and found that the SDTBs had an extremely potent inhibitory effect on AG, with an IC50 value of 57.46 μg/mL, which was much lower than that of the positive control. Meanwhile, they also showed significant inhibition of XOD and α-amylase, with IC50 values of 289.67 μg/mL and 50.85 μg/mL, respectively. In addition, molecular docking studies were carried out to understand the nature of the action of the biflavonoids on AG and XOD. The results showed that robustaflavone had the lowest binding energy to AG (−11.33 kcal/mol) and XOD (−10.21 kcal/mol), while, on the other hand, amentoflavone showed a good binding affinity to AG (−10.40 kcal/mol) and XOD (−9.962 kcal/mol). Moreover, molecular dynamics simulations verified the above results.

Rice (Oryza sativa L.) is grown nearly worldwide and is a staple food for more than half of the world’s population. With the rise in extreme weather and climate events, there is an urgent need to decode the complex mechanisms of rice’s response to environmental stress and to breed high-yield, high-quality and stress-resistant varieties. Over the past few decades, significant advancements in molecular biology have led to the widespread use of several omics methodologies to study all aspects of plant growth, development and environmental adaptation. Transcriptomics and proteomics have become the most popular techniques used to investigate plants’ stress-responsive mechanisms despite the complexity of the underlying molecular landscapes. This review offers a comprehensive and current summary of how transcriptomics and proteomics together reveal the molecular details of rice’s response to environmental stresses. It also provides a catalog of the current applications of omics in comprehending this imperative crop in relation to stress tolerance improvement and breeding. The evaluation of recent advances in CRISPR/Cas-based genome editing and the application of synthetic biology technologies highlights the possibility of expediting the development of rice cultivars that are resistant to stress and suited to various agroecological environments.

Boundary layer transition prediction has always been a hot and difficult research topic in the field of fluid mechanics. Among them, the crossflow induced transition plays a crucial role in the transition phenomenon on the surface of the aircraft, which is affected by the freestream disturbance, wall surface roughness, wall pressure gradient, local sweep angle, crossflow characteristic Reynolds number, Mach number, wall curvature and temperature. All those factors make the prediction of the cross-flow transition very complicated and difficult. In recent years, many research institutions have proposed various prediction methods for this problem, which are basically divided into two categories: one is to establish the critical transition Reynolds number criterion, and to determine whether transition occurs; the other type is the modeled linear stability theory, which calculates the cross-flow disturbance amplification factor and compares it with the transition threshold to determine whether transition occurs. Several typical prediction models of crossflow dominated transition based on local variables of low-speed boundary layer and high-speed boundary will be systematically reviewed and summarized, and the future research directions will be prospected.

Abstract Cycle slip detection and repair is one of the key factors of Global Navigation Satellite System carrier phase high precision positioning. Although various methods have been proposed to detect and repair the cycle slip, they are still limited by kinds of factors and the effect is not ideal, especially in real‐time triple‐frequency high precise positioning applications for BeiDou Systems (BDSs). Traditional methods only improve the algorithm from the detection level, but the observation level and the threshold of detection always be ignored. Research indicates that the noise of observation seriously affects the success rate of cycle slip detection, and the threshold of detection largely depends on the satellite type and data sampling rate. A new triple‐frequency cycle slip detection and repair method, based on wavelet packet transform and adaptive threshold strategy, is proposed to detect and repair the cycle slip for real‐time BDS triple‐frequency positioning applications. The key idea of the proposed method is the use of both the wavelet packet transform and elevation model to mitigate random noise and the satellite‐induced code bias from the observation level, and the adaptive threshold strategy to adjust the threshold of detection based on satellite type and data sampling rate in the detection level. Real datasets are collected to evaluate the performance of the proposed method. Experimental results indicated that the proposed method can effectively detect and repair all types of cycle slips, such as single‐frequency small cycle slip, large cycle slip, and particular cycle slip, improve the success rate and reliability, and lay a solid foundation for BDS high‐precision positioning.

The freeze-thaw (F-T) properties of ordinary concrete have been extensively studied and related models were well-established. However, these models cannot be used to accurately assess the F-T damage of dune sand and fiber reinforced concrete (DSFC), which is essential for performing targeted repairs. This study established an interpretable machine learning (ML) model to predict the F-T damage indicator D of DSFC through systematic comparisons of eight ML models (four classical models and four ensemble models). As an initial step, a dataset containing 257 samples was created by combining the F-T test results of this study and previous literature. This dataset was utilized to establish the eight models, which were then benchmarked against the polynomial models to select the optimal model. Subsequently, the selected model was interpreted using importance analysis, which included permutation feature importance (PFI) and partial dependency plots (PDP), to dissect the predictive mechanism of this model. Comparisons of eight models revealed that the four ensemble learning models generally outperforms the four classical learning models. Among the four ensemble learning models, XGBoost was verified to have optimal performance, with an R2 of 0.965 and RMSE of 0.019 on the test set. The importance analysis of XGBoost further demonstrated the inhibitory effect of dune sand and basalt fiber on F-T damage revealed in the experimental results. In summary, the proposed XGBoost along with importance analysis, is a practical methodology to predict and interpret the F-T damage of DSFC.

Geophysical logging plays a very important role in reservoir evaluation. In the actual production process, some logging data are often missing due to well wall collapse and instrument failure. Therefore, this paper proposes a logging reconstruction method based on improved sand cat swarm optimization (ISCSO) and a temporal convolutional network (TCN) and bidirectional gated recurrent unit network with attention mechanism (BiGRU-AM). The ISCSO-TCN-BiGRU-AM can process both past and future states efficiently, thereby extracting valuable deterioration information from logging data. Firstly, the sand cat swarm optimization (SCSO) improved by the variable spiral strategy and sparrow warning mechanism is introduced. Secondly, the ISCSO’s performance is evaluated using the CEC–2022 functions and the Wilcoxon test, and the findings demonstrate that the ISCSO outperforms the rival algorithms. Finally, the logging reconstruction method based on the ISCSO-TCN-BiGRU-AM is obtained. The results are compared with the competing models, including the back propagation neural network (BPNN), GRU, and BiGRU-AM. The results show that the ISCSO-TCN-BiGRU-AM has the best performance, which verifies its high accuracy and feasibility for the missing logging reconstruction.

Rice (Oryza sativa L.) production is highly susceptible to temperature fluctuations, which can significantly reduce plant growth and development at different developmental stages, resulting in a dramatic loss of grain yield. Over the past century, substantial efforts have been undertaken to investigate the physiological, biochemical, and molecular mechanisms of cold stress tolerance in rice. This review aims to provide a comprehensive overview of the recent developments and trends in this field. We summarized the previous advancements and methodologies used for identifying cold-responsive genes and the molecular mechanisms of cold tolerance in rice. Integration of new technologies has significantly improved studies in this era, facilitating the identification of essential genes, QTLs, and molecular modules in rice. These findings have accelerated the molecular breeding of cold-resistant rice varieties. In addition, functional genomics, including the investigation of natural variations in alleles and artificially developed mutants, is emerging as an exciting new approach to investigating cold tolerance. Looking ahead, it is imperative for scientists to evaluate the collective impacts of these novel genes to develop rice cultivars resilient to global climate change.

The air-supported membrane coal shed is widely used in bulk cargo terminals. It not only effectively protects goods from adverse weather conditions but also helps reduce coal dust and harmful gas emissions, promoting the green and sustainable development of ports. However, in practical engineering, the design parameters of the coal shed are often based on experience, making it difficult to accurately assess the quality of the structural design. The flexibility of the membrane material also makes the structure susceptible to deformation or tearing. This paper mainly focuses on modeling and solving the optimization design issues of air-supported membrane coal shed structures. According to the evaluation criteria for the form of air-supported membrane coal sheds, a multi-objective structural optimization model is established to minimize the maximum stress on the membrane surface, ensure uniform stress distribution, maximize structural stiffness, and minimize costs. The study utilizes a combined optimization approach using ANSYS 19.0 and MATLAB 2016a, incorporating an improved NSGA-II algorithm program developed in MATLAB into ANSYS for structural form analysis and load calculation. The research results indicate that the optimal solution reduces the maximum stress on the loaded membrane surface by 5.36%, shortens the maximum displacement by 30.3%, and saves on economic costs by 9.85%. Compared to traditional empirical design methods, the joint use of MATLAB and ANSYS for optimization design can provide more superior solutions, helping ports to achieve environmental protection and economic efficiency goals.

Publicly available ionograms are often in the form of pictures. This paper proposes a novel algorithm for extracting and repairing the F layer traces from pictorial ionograms. Extensive efforts have been invested in ionogram autoscaling and critical parameter identification to improve the efficiency of scaling algorithms. To obtain the parameters of the F layer automatically, it is necessary to accurately extract the F layer trace. However, research on F layer trace extraction with repair is relatively limited. The method employed in this study makes full use of the characteristics of different types of echoes on the ionograms, and the procedure includes noise preprocessing, coupling noise processing, and trace repair. To enhance the applicability of the repair, two different automatic filling algorithms are adopted to repair the F layer trace. The aim of this paper is to present an adaptive algorithm to automatically extract and repair F layer traces from different pictorial ionograms. The results of Hainan Fuke ionograms illustrate the reliability of the F layer trace extraction and trace repair.

In many cases, it is difficult to obtain precise distributional information on multivariate sequences. Therefore, there is a need to propose nonparametric methods for monitoring multivariate sequences. This article discusses the multivariate change detection problem and utilizes the kernel function as the statistic to construct the nonparametric Multivariate Cumulative Sum multi-chart, under the assumption that there is prior information about the abrupt changes. Through theoretical and numerical analysis, we show that the proposed control chart is more effective compared to other existing control charts. The good monitoring effect of this method demonstrates a strong potential for application.

In this study, the deep eutectic solvent based ultrasound-assisted extraction (DES-UAE) was investigated for the efficient and environmentally friendly extraction of Selaginella chaetoloma total biflavonoids (SCTB). As an extractant for optimization, tetrapropylaminium bromide-1,4-butanediol (Tpr-But) was employed for the first time. 36 DESs were created, with Tpr-But producing the most effective results. Based on response surface methodology (RSM), the greatest extraction rate of SCTB was determined to be 21.68 ± 0.78 mg/g, the molar ratio of HBD to HBA was 3.70:1, the extraction temperature was 57 °C, and the water content of DES was 22 %. In accordance with Fick's second rule, a kinetic model for the extraction of SCTB by DES-UAE has been derived. With correlation coefficients 0.91, the kinetic model of the extraction process was significantly correlated with the general and exponential equations of kinetics, and some important kinetic parameters such as rate constants, energy of activation and raffinate rate were determined. In addition, molecular dynamics simulations were used to study the extraction mechanisms generated by different solvents. Comparing the effect of several extraction methods on S.chaetoloma using ultrasound-assisted extraction and conventional methods, together with SEM examination, revealed that DES-UAE not only saved time but also enhanced SCTB extraction rate by 1.5–3 folds. SCTB demonstrated superior antioxidant activity in three studies in vitro. Furthermore, the extract could suppress the growth of A549, HCT-116, HepG2, and HT-29 cancer cells. Alpha-Glucosidase (AG) inhibition experiment and molecular docking studies suggested that SCTB exhibited strong inhibitory activity against AG and potential hypoglycemic effects. The results of this study indicated that a Tpr-But-based UAE method was suitable for the efficient and environmentally friendly extraction of SCTB, and also shed light on the mechanisms responsible for the increased extraction efficiency, which could aid in the application of S.chaetoloma and provide insight into the extraction mechanism of DES.

Root system architecture is influenced by gravity. How the root senses gravity and directs its orientation, so-called gravitropism, is not only a fundamental question in plant biology but also theoretically important for genetic improvement of crop root architecture. However, the mechanism has not been elucidated in most crops. We characterized a rice agravitropism allele, wavy root 1 (war1), a loss-of-function allele in OsPIN2, which encodes an auxin efflux transporter. With loss of OsPIN2 function, war1 leads to altered root system architecture including wavy root, larger root distribution angle, and shallower root system due to the loss of gravitropic perception in root tips. In the war1 mutant, polar auxin transport was disrupted in the root tip, leading to abnormal auxin levels and disturbed auxin transport and distribution in columella cells. Amyloplast sedimentation, an important process in gravitropic sensing, was also decreased in root tip columella cells. The results indicated that OsPIN2 controls gravitropism by finely regulating auxin transport, distribution and levels, and amyloplast sedimentation in root tips. We identified a novel role of OsPIN2 in regulating ABA biosynthesis and response pathways. Loss of OsPIN2 function in the war1 resulted in increased sensitivity to ABA in seed germination, increased ABA level, changes in ABA-associated genes in roots, and decreased drought tolerance in the seedlings. These results suggest that the auxin transporter OsPIN2 not only modulates auxin transport to control root gravitropism, but also functions in ABA signaling to affect seed germination and root development, probably by mediating crosstalk between auxin and ABA pathways.

To accurately predict reservoir porosity, a method based on bi-directional long short-term memory with attention mechanism (BiLSTM-AM) optimized by the improved pelican optimization algorithm (IPOA) is proposed. Firstly, the nonlinear inertia weight factor, Cauchy mutation, and sparrow warning mechanism are introduced to improve the pelican optimization algorithm (POA). Secondly, the superiority of IPOA is verified by using the CEC–2022 benchmark test functions. In addition, the Wilcoxon test is applied to evaluate the experimental results, which proves the superiority of IPOA against other popular algorithms. Finally, BiLSTM-AM is optimized by IPOA, and IPOA-BiLSTM-AM is used for porosity prediction in the Midlands basin. The results show that IPOA-BiLSTM-AM has the smallest prediction error for the verification set samples (RMSE and MAE were 0.5736 and 0.4313, respectively), which verifies its excellent performance.

To solve the problems of high computational cost and the long time required by the simulation and calculation of aeroengines’ exhaust systems, a method of predicting the characteristics of infrared radiation based on the hybrid kernel extreme learning machine (HKELM) optimized by the improved dung beetle optimizer (IDBO) was proposed. Firstly, the Levy flight strategy and variable spiral strategy were introduced to improve the optimization performance of the dung beetle optimizer (DBO) algorithm. Secondly, the superiority of IDBO algorithm was verified by using 23 benchmark functions. In addition, the Wilcoxon signed-rank test was applied to evaluate the experimental results, which proved the superiority of the IDBO algorithm over other current prominent metaheuristic algorithms. Finally, the hyperparameters of HKELM were optimized by the IDBO algorithm, and the IDBO-HKELM model was applied to the prediction of characteristics of infrared radiation of a typical axisymmetric nozzle. The results showed that the RMSE and MAE of the IDBO-HKELM model were 20.64 and 8.83, respectively, which verified the high accuracy and feasibility of the proposed method for predictions of aeroengines’ infrared radiation characteristics.

Tolerance to submergence-induced hypoxia is an important agronomic trait especially for crops in lowland and flooding-affected areas. Although rice (Oryza sativa) is considered a flood-tolerant crop, only limited cultivars display strong tolerance to prolonged submergence and/or hypoxic stress. Therefore, characterization of hypoxic resistant genes and/or germplasms have important theoretical and practical significance for rice breeding and sustained improvements. Previous investigations have demonstrated that loss-of-function of OsPIN2, a gene encoding an auxin efflux transporter, results in the loss of root gravitropism due to disrupted auxin transport in the root tip. In this study, we revealed a novel connection between OsPIN2 and reactive oxygen species (ROS) in modulating root gravitropism and hypoxia tolerance in rice. It is shown that the OsPIN2 mutant had decreased accumulation of ROS in root tip, due to the downregulation of glycolate oxidase encoding gene OsGOX6, one of the main H2O2 sources. The morphological defects of root including waved rooting and agravitropism in OsPIN2 mutant may be rescued partly by exogenous application of H2O2. The OsPIN2 mutant exhibited increased resistance to ROS toxicity in roots due to treatment with H2O2. Furthermore, it is shown that the OsPIN2 mutant had increased tolerance to hypoxic stress accompanied by lower ROS accumulation in roots, because the hypoxia stress led to over production of ROS in the roots of the wild type but not in that of OsPIN2 mutant. Accordingly, the anoxic resistance-related gene SUB1B showed differential expression in the root of the WT and OsPIN2 mutant in response to hypoxic conditions. Notably, compared with the wild type, the OsPIN2 mutant displayed a different pattern of auxin distribution in the root under hypoxia stress. It was shown that hypoxia stress caused a significant increase in auxin distribution in the root tip of the WT but not in that of the war1 mutant. In summary, these results suggested that OsPIN2 may play a role in regulating ROS accumulation probably via mediating auxin transport and distribution in the root tip, affecting root gravitropism and hypoxic tolerance in rice seedlings. These findings may contribute to the genetic improvement and identification of potential hypoxic tolerant lines in rice.

Abstract Selenium (Se) is an essential micronutrient that promotes body health. Endemic Se deficiency is a major nutritional challenge worldwide. The low toxicity, high bioavailability, and unique properties of biogenic Se nanoparticles (SeNPs) allow them to be used as a therapeutic drug and Se nutritional supplement. This study was conducted to investigate the regulatory effects of dietary SeNPs supplementation on the oxidative stress-induced intestinal barrier dysfunction and its association with mitochondrial function and gut microbiota in mice. The effects of dietary SeNPs on intestinal barrier function and antioxidant capacity and its correlation with gut microbiota were further evaluated by a fecal microbiota transplantation experiment. The results showed that Se deficiency caused a redox imbalance, increased the levels of pro-inflammatory cytokines, altered the composition of the gut microbiota, and impaired mitochondrial structure and function, and intestinal barrier injury. Exogenous supplementation with biogenic SeNPs effectively alleviated diquat-induced intestinal barrier dysfunction by enhancing the antioxidant capacity, inhibiting the overproduction of reactive oxygen species (ROS), preventing the impairment of mitochondrial structure and function, regulating the immune response, maintaining intestinal microbiota homeostasis by regulating nuclear factor (erythroid-derived-2)-like 2 (Nrf2)-mediated NLR family pyrin domain containing 3 (NLRP3) signaling pathway. In addition, Se deficiency resulted in a gut microbiota phenotype that is more susceptible to diquat-induced intestinal barrier dysfunction. Supranutritional SeNPs intake can optimize the gut microbiota to protect against intestinal dysfunctions. This study demonstrates that dietary supplementation of SeNPs can prevent oxidative stress-induced intestinal barrier dysfunction through its regulation of mitochondria and gut microbiota.

Abstract Background To analyze the level changes of 28 cytokines in aqueous humor of patients with proliferative diabetic retinopathy (PDR) coexisting neovascular glaucoma (NVG) after intravitreal injection of conbercept (IVC), and to investigate whether these cytokines are associated with intraoperative bleeding (IOB). Methods Totally 34 eyes with NVG secondary to PDR were enrolled. Patients were randomized into two groups, and all of them underwent 25-gauge pars plana vitrectomy (PPV) combined with trabeculectomy. Group I, 18 eyes received IVC 3 days before PPV, and 100 µL aqueous humor was collected at the time of IVC pretreatment and 3 days later at the beginning of PPV respectively. Group II, 16 eyes received IVC after PPV, and 100 µL aqueous humor was collected only at the beginning of PPV. Aqueous humor from 19 eyes with age-matched cataract patients served as controls. Luminex bead-based multiplex array was used to measure the levels of 28 cytokines in aqueous humor. The baseline cytokine levels were compared among the three groups. All NVG patients were divided into IOB and non-bleeding (INB) groups. The cytokine levels of aqueous humor at the beginning of PPV were compared between group I and II, also between IOB and INB groups. IOB in NVG patients was graded according to vitreous bleeding amount. The correlation between cytokine levels and the grades of IOB were analyzed. Results Compared with controls, the baseline levels of 18 cytokines associated with inflammation and angiogenesis showed significantly increased in group I and group II (all, P 0.4, P