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Land cover change detection and classification, including both inter-class changes (land cover conversion, LCC) and intra-class changes (land cover modification, LCM), is critical for understanding the Earth’s dynamic processes and promoting sustainability. However, previous studies have predominantly focused on LCC, with less emphasis on LCM. Land cover classification remains challenging, and its mapping results are often affected by salt and pepper noise. Here, we propose a hybrid approach for continuous change detection and classification of LCC and LCM using Jinchang City, China, as a case study. Firstly, we combined the Continuous Change Detection and Classification (CCDC) and the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) algorithms to identify LCC and LCM using all available Landsat time series (TS) data from 2000 to 2020. Then, the harmonic regression coefficients and RMSE values derived from CCDC (hereafter called CCDC features) were fed into the DCNN model for LCC classification. Our findings indicate: (1) For LCC and LCM accuracy assessment, the CCDC and BEAST ensemble achieved a spatial F1 score of 82.7% and an average temporal F1 score of 79.7%. (2) In LCC classification, the DCNN model with CCDC features, particularly DeepLabV3+, outperformed the pixel-based XGBoost and other multi-year land cover products, with frequency-weighted intersection over union (FWIoU), overall accuracy, and Kappa scores of 88.7%, 94%, and 0.87, respectively. (3) Seasonal LCM showed a more concentrated distribution than trend LCM. (4) In Jinchang City, LCM larger than LCC in area, and grassland and cultivated land are the most distributed. Our approach can be contributed to wall-to-wall land surface monitoring and enhance land management capabilities.

Abstract We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

The coal industry is the ballast stone and stabilizer that supports the rapid development of China’s economy and society and ensures national energy security. It also undertakes the mission of ensuring energy supply and supporting the stable development of new energy. At present, the high-quality development of China’s coal industry has achieved some staged results, with remarkable achievements in energy supply, the continuous optimization of industrial structure, the significant improvement of scientific and technological innovation capabilities, and the continuous advance of green development and clean and efficient utilization. However, the current development level of the coal industry is far from meeting the national needs of Chinese-style modernization. The sustainable development is restricted by multiple factors. The digital technology and coal development and utilization have not yet been deeply integrated. The intelligent construction is still in the demonstration and cultivation stage. The green development is unbalanced and contradictory and prominent. The transformation and upgrading of the coal industry still has a long way to go. In view of the current development status and challenges of the coal industry, this paper proposes a synergistic development mode of digitalization, intelligentization and greenization (three -izations), clarifies the core connotation of new-quality coal productivity, constructs the overall framework of the synergistic development of new-quality coal productivity, and expounds the technical path for the transformation of the innovative allocation of production factors by digitalization, the breakthrough of key technologies led by intelligentization, and the deep transformation of traditional industries by greenization, i.e., by these three factors to generate new-quality coal productivity. Six major technical systems are proposed: through the research and development of the technical system of efficient data collection and in-depth governance of the whole industry chain, the data barriers among coal production, transportation, storage, marketing and use of the whole process are removed. Through the research and development of the knowledge map and intelligent decision-making and control technological system of the coal industry, the correlation relationship and value of the upstream and downstream business scenarios of the coal industry are deeply explored, so as to lay the foundation for the independent decision-making and intelligent control of the whole process of coal production and utilization. Also, the research should be carried out in terms of the intelligent-green-efficient development technological system of coal resources, the technical system of collaborative guarantee of safety in the coal industry, the technical system of ecological intelligent monitoring-early warning-restoration in mining areas, and the technical system of flexible development and clean and low-carbon utilization of coal, so as to realize the synergistic development of the whole industrial chain and the whole process of coal development and utilization, cultivate and form a new-quality coal productivity, and bring some fundamental changes and improvements to the overall image of the coal industry.

Constitutive activation of GNAQ/11 is the initiative oncogenic event in uveal melanoma (UM). Direct targeting GNAQ/11 has yet to be proven feasible as they are vital for a plethora of cellular functions. In search of genetic vulnerability for UM, we found that inhibition of euchromatic histone lysine methyltransferase 2 (EHMT2) expression or activity significantly reduced the proliferation and migration capacity of cancer cells. Notably, elevated expression of EHMT2 had been validated in UM samples. Furthermore, Kaplan–Meier survival analysis indicated high EHMT2 protein level was related to poor recurrence-free survival and a more advanced T stage. Chromatin immunoprecipitation sequencing analysis and the following mechanistic investigation showed that ARHGAP29 was a downstream target of EHMT2. Its transcription was suppressed by EHMT2 in a methyltransferase-dependent pattern in GNAQ/11-mutant UM cells, leading to elevated RhoA activity. Rescuing constitutively active RhoA in UM cells lacking EHMT2 restored oncogenic phenotypes. Simultaneously blocking EHMT2 and GNAQ/11 signaling in vitro and in vivo showed a synergistic effect on UM growth, suggesting the driver role of these two key molecules. In summary, our study shows evidence for an epigenetic program of EHMT2 regulation that influences UM progression and indicates inhibiting EHMT2 and MEK/ERK simultaneously as a therapeutic strategy in GNAQ/11-mutant UM.

Improving the sustainability and processability of shape memory composites is key to expanding their applications. This work introduces a novel bio-based shape memory composite resin with renewable cellulose nanocrystals, suitable for stereolithography (SLA) printing. We prepared epoxy soybean oil-based composites by incorporating Itaconic acid monomethyl ester (IAME) modified cellulose nanocrystals (CNCs-IAME) into IAME modified epoxy soybean oil (IESO). The CNCs-IAME/IESO composite resin, with a viscosity of 1.01–1.22 Pa•s, is ideal for SLA printing. Adding 0.75 wt% CNCs-IAME particles enhances mechanical properties, yielding a tensile strength of 19.54 MPa and elongation at a break of 34.03%. Demonstrated applications include flexible supports and temperature-responsive sensors. This innovative composite offers excellent sustainability and SLA-printability, showing great potential for new bio-based heat-activated shape memory materials.

Fewer studies related to the durability of multi-source solid waste geopolymer cementitious materials and the massive accumulation of industrial solid waste are urgent problems to be solved in practice in Inner Mongolia, China. In this paper, blast furnace slag (BFS), fly ash (FA), and calcium carbide slag (CCS) are used as the main raw materials to prepare geopolymer cementitious materials (BFCG) with Calcium Carbide Slag as the Ca-source alkali activator and NaOH as the Na-source alkali activator, considering their durability properties. By assessing the indicators of mechanical performance, engineering performance, and the synergistic mechanism of Ca2+ and Na+ in multi-source solid waste geopolymer, four sets of BFCG ratio optimization schemes are selected. XRD, FT-TR, SEM-EDS, and other testing methods are used to analyze its freeze–thaw resistance and acid–alkali-salt corrosion resistance. The following conclusions are drawn: the BFCG prepared under the synergistic excitation of Ca2+ and Na+ has better resistance to freezing and thawing, as well as acid-alkali-salt corrosion, both of which are in accordance with the standard specifications for road construction in China. After the freeze–thaw cycles, BFCG still has more three-dimensional network-like silica-aluminate structures, a compact micromorphology, and small pores. Its strength loss rate is 0.56 %–15.56 %, the mass loss rate is 0.19 %–1.26 %, and the relative dynamic modulus is 79.56 %–100.25 %. In a NaOH environment, the crystal type of BFCG did not change significantly, and the resistivity coefficients are 115.78 %–143.54 %. In a Na2SO4 environment, the decalcification or dealumination of C-A-S-H gel leads to the formation of a gel rich in silicon, magnesium, and aluminum phases, with a corrosion resistance coefficient of 101.8 %–119.96 %. In a HCl environment, HCl erosion inhibits the growth of hydration product crystals, with corrosion resistance coefficients ranging from 73.83 % to 97.24 %. BFCG-D has the best resistance to freezing and thawing as well as acid and alkali corrosion. BFCG-D has the best resistance to freezing and thawing as well as acid and alkali corrosion. These studies show that BFCG offers a promising solution for improving the durability of road base materials and reducing industrial solid waste.

Intercropping of ornamental flowering plants like Lycoris radiata Herb. and Cuphea hookeriana Walp. with tea trees can enhance the visibility and esthetic appeal of tea gardens. However, there has been limited research of the impact of intercropping ornamental flowering plants with tea trees on the soil in tea gardens. During this study, our objective was to analyze the effects of intercropping systems on tea garden soil by examining the physicochemical properties of rhizosphere soil samples from tea gardens intercropped with L. radiata and C. hookeriana. We also performed rhizosphere microbial metagenomic sequencing to assess the microbial community structure. The results revealed significant improvements in soil physicochemical indicators, particularly pH. Although intercropping systems had minor impacts on bacterial diversity and abundance, they had more pronounced effects on the community structure of microorganisms at the phylum and genus levels. Furthermore, an analysis of microbial functions using Functional Annotation of Prokaryotic Taxa (FAPROTAX) revealed enrichment of carbon and nitrogen cycling pathways in the tea garden soil. Our findings indicated that intercropping practices have the potential to enhance the visual appeal of tea gardens while improving soil fertility and modulating the microbial community structure. These results contribute to our understanding of intercropping strategies and the implications of intercropping for tea tree growth and ecosystem functioning.

The acquisition of landslide inventory represents a pivotal challenge in landslide susceptibility mapping. Existing landslide susceptibility maps(LSMs) predominantly rely on manually obtained landslide inventories, leading to an overdependence on expert insights and susceptibilities to topographic and geomorphic influences. In regions characterized by steep terrain, obtaining a landslide inventory can be arduous or even unattainable, subsequently constraining the utility of LSMs. Addressing the limitations of conventional LSMs, this study introduces an innovative method for landslide inventory compilation and LSM creation, utilizing Small Baselines Subset Interferometry Synthetic Aperture Radar(SBAS-InSAR) technology. The study area selected for illustration is the Dongchuan district, notorious for frequent landslide occurrences. The application of SBAS-InSAR facilitated the extraction of surface deformation data, subsequently enabling the selection of landslide deformation points as samples. These samples underwent analysis through a particle swarm optimization-backpropagation neural network(PSO-BPNN) guided by deformation thresholds and the landslide developmental environment. This produced the LSM for the Dongchuan district. Subsequent validation of the LSM employed both qualitative and quantitative measures. Results elucidate that the LSM, as derived from the presented approach, primarily highlights high to very high susceptibility zones in landslide-prone areas, mirroring the spatial distribution of historical landslides. The method also achieved a commendable accuracy(ACC) of 79.59% and an area under the curve(AUC) value of 0.88. Notably, the landslide density exhibited a direct correlation with increasing susceptibility class. Such findings align with previous studies, endorsing the feasibility and reliability of the proposed approach.

Soft clay contamination is an increasingly global issue with significant implications for land development and human health. Electrokinetic remediation (EKR) has demonstrated significant potential for cleaning contaminated soils. It is crucial to develop efficient processes that minimize environmental impact and reduce costs. A series of citric acid (CA)-enhanced EKR tests were conducted using a novel experimental setup, with the electrolyte positioned above the soil surface, to examine the impact of four different electrode arrangements on the effectiveness of EKR. The position of the electrode end had a significant impact on the migration of ions in the anolyte and catholyte, which in turn affected the volume reduction in the anolyte, the magnitude of the current, and the migration of heavy metals. The electrode arrangement mode c (electrodes suspended in the electrolytes) can enhance the migration of the anolyte and reduce the drainage of the soil, making it an effective measure for improving the removal rate of heavy metals. After the heavy metal remediation is complete, the bearing capacity of the soil should be increased. Changing the electrode arrangement to mode d (anode suspended in the anolyte, a very small part of the cathode inserted into the soil) is an effective measure for reducing the soil water content and improving soil strength.

Exploring high-performance carbon anodes that are low-cost and easily accessible is the key to the commercialization of sodium-ion batteries. Producing carbon materials from bio by-products is an intriguing strategy for sodium-ion battery anode manufacture and for high-value utilization of biomass. Herein, a novel hard carbon (PPHC) was prepared via a facile pyrolysis process followed by acid treatment using biowaste pomegranate peel as the precursor. The morphology and structure of the PPHC were influenced by the carbonization temperature, as evidenced by physicochemical characterization. The PPHC pyrolyzed at 1100 °C showed expanded interlayer spacing and appropriate oxygen group content. When used as a sodium ion battery anode, the PPHC-1100 demonstrated a reversible capacity of up to 330 mAh g−1, maintaining 174 mAh g−1 at an increased current rate of 1 C. After 200 cycles at 0.5 C, the capacity delivered by PPHC-1100 was 175 mAh g−1. The electrochemical behavior of PPHC electrodes was investigated, revealing that the PPHC-1100 possessed increased capacitive-controlled energy storage and improved ion transport properties, which explained its excellent electrochemical performance. This work underscores the feasibility of high-performance sodium-ion battery anodes derived from biowaste and provides insights into the sodium storage process in biomass-derived hard carbon.

We attained wurtzite ScxAl1−xN (0.16 ≤ x ≤ 0.37) thin films by varying the Sc and Al fluxes at a fixed active nitrogen flux during plasma-assisted molecular beam epitaxy. Atomic fluxes of Sc and Al sources via measured Sc percentage in as-grown ScxAl1−xN thin films were derived as the feedback for precise determination of the ScxAl1−xN growth diagram. We identified an optimal III/N atomic flux ratio of 0.78 for smooth Sc0.18Al0.82N thin films. Further increasing the III/N ratio led to phase separation under N-rich conditions, validated by the observation of high-Sc-content hillocks with energy-dispersive X-ray spectroscopy mapping. At the fixed III/N ratio of 0.78, we found that phase separation with high-Al-content hillocks occurs for x > 0.37, which is substantially lower than the thermodynamically dictated threshold Sc content of ~0.55 in wurtzite ScxAl1−xN. We postulate that these wurtzite-phase purity degradation scenarios are correlated with adatom diffusion and the competitive incorporation process of Sc and Al. Therefore, the ScxAl1−xN growth window is severely restricted by the adatom kinetics. We obtained single crystalline Sc0.37Al0.63N thin films with X-ray diffraction (002)/(102) ω rocking curve full-width at half-maximums of 2156 arcsec and 209 arcsec and surface roughness of 1.70 nm. Piezoelectric force microscopy probing of the Sc0.37Al0.63N epilayer validates unambiguous polarization flipping by 180°.

Objective: The study analyzed the impact of urbanization on epidemiological characteristics of respiratory infectious disease in Tongzhou District, Beijing during 2014–2022 to provide reference for prevention and control priorities of respiratory infectious diseases during the innovative urbanization process in China. Methods: The incidence data of notifiable respiratory infectious diseases (NRIDs) in Tongzhou Beijing during 2014–2022 were summarized. The trend of incidence rate was analyzed by Joinpoint regression model, and entropy method was performed to construct the comprehensive index of urbanization (CIU) and generalized linear model was used to analyze the influence of CIU on the incidence rate of respiratory infectious diseases. Results: Totally 72616 NRIDs cases were reported in Tongzhou District during 2014–2022, and the incidence rate of NRIDs was higher during 2017–2019 (153/100 000) than during 2014–2016 (930/100 000) and during 2020–2022 (371/100 000), respectively (both P

BackgroundActive surveillance has been an option for patients with low-risk papillary thyroid carcinoma (PTC). However, whether delayed surgery leads to an increased risk of local tumor metastasis remain unclear. We sought to investigate the impact of observation time on central lymph node metastasis (CLNM) and multifocal disease in patients with low-risk PTC.MethodsPatients who were diagnosed with asymptomatic low-risk PTC, and with a pathological maximum tumor size ≤1.5 cm by were included. The patients were classified into observation group and immediate surgery group, and subgroup analyses were conducted by observation time period. The prevalence of CLNM, lymph node (LN) involved >5, multifocal PTC and bilateral multifocal PTC were considered as outcome variables. The changing trend and risk ratio of prevalence over observation time were evaluated by Mann-Kendall trend test and Logistics regression.ResultsOverall, 3,427 and 1,860 patients were classified to the observation group and immediate surgery group, respectively. Trend tests showed that decreasing trends both on the prevalence of CLNM and LN involved >5 over the observation time, but the difference was not statistically significant, and the prevalence of multifocal PTC and bilateral multifocal PTC showed the significant decreasing trends. After adjustment, multivariate analysis showed no statistically significant difference between observed and immediate surgery groups in the four outcome variables.ConclusionIn patients with subclinical asymptomatic low-risk PTC, observation did not result in an increased incidence of local metastatic disease, nor did the increased surgery extent in patients with delayed surgery compared to immediate surgery. These findings can strengthen the confidence in the active surveillance management for both doctors and patients.

To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volumes from and to bus stops was constructed with land use elements between bus stop TAZs and the upstream and downstream collections of bus stop TAZs. Building upon this, the passenger flow volumes from and to 38 bus stops in the Xueyuan Square area of Dalian during weekday morning peak hours were taken as the experimental objects. The basic estimation models of two gravity sets corresponding to passenger flow volumes from and to bus stops were constructed using the bus travel generation based on the aggregation of area-based origin unit method and the bus travel distance impedance based on the probability density method. Finally, the reliability of the estimation method of passenger flow volumes from and to bus stops was verified by regression fitting between the surveyed values of passenger flow volume and the estimated values of the basic models. The results indicate that the fuzzy estimation and transformation of bus travel based on land use elements, which serves as a crucial lever for facilitating strategic alignment in transit-oriented development (TOD), can be effectively achieved by using the area-based origin unit method to aggregate bus travel generation and the probability density method to evaluate the bus travel distance impedance.

In order to effectively address the potential hazards associated with the construction of Phase II of the YE Water Supply Project’s KS tunnel in Xinjiang, this study employs the WBS-RBS (Work Breakdown Structure and Risk Breakdown Structure) method for risk identification. This approach aims to identify various risks that may arise during TBM (Tunnel Boring Machine) construction. To prevent incomplete risk factor identification resulting from subjective judgment, a risk index system is established based on the identification results. Subsequently, a matter-element extension model is utilized to quantify the risk factors within this index system, and comprehensive weights are determined using variable weight theory to assess construction risk levels. Importance analysis of each index is then conducted to identify those with significant impact on risk evaluation outcomes. Finally, by comparing actual engineering cases with other risk evaluation models, this paper verifies the reliability of its constructed risk assessment model and proposes measures for controlling potential risks based on these evaluations. The paper provides a clear definition of safety risks encountered during TBM construction and conducts comprehensive risk assessments as a valuable reference for research related to the tunnel boring machine construction period in tunnel engineering.

Intercropping, a well-established agroecological technique designed to bolster ecological stability, has been shown to have a significant impact on soil health. However, the specific effects of tea/Trachelospermum jasminoides intercropping on the physicochemical properties and functional microbial community structure in practical cultivation have not been thoroughly investigated. In this study, we utilized high-throughput sequencing technology on the 16S/ITS rDNA genes to assess the impact of tea intercropping with T. jasminoides on the composition, diversity, and potential functions of the soil microbial community in tea gardens. The results indicated that the tea/T. jasminoides intercropping system significantly increased pH levels, soil organic matter, available nitrogen, phosphorus, potassium, and enzyme activity, ultimately augmenting soil nutrient levels. Furthermore, an in-depth analysis of the bacterial co-occurrence network and topological structure portrayed a more intricate and interconnected soil bacterial community in tea gardens. Remarkably, the abundance of beneficial genera, including Burkholderia, Mesorhizobium, Penicillium, and Trichoderma, underwent a substantial increase, whereas the relative abundance of pathogenic fungi such as Aspergillus, Fusarium, and Curvularia experienced a marked decline. Functional predictions also indicated a notable enhancement in the abundance of microorganisms associated with nitrogen and carbon cycling processes. In summary, the intercropping of tea and T. jasminoides holds the potential to enrich soil nutrient content, reshape the microbial community structure, bolster the abundance of functional microorganisms, and mitigate the prevalence of pathogenic fungi. Consequently, this intercropping system offers a promising solution for sustainable tea garden management, overcoming the limitations of traditional cultivation methods and providing valuable insights for sustainable agriculture practices.

In the process of intelligent compaction of roadbeds, the water content of the roadbed is one of the important influencing factors of compaction quality. In order to analyze the effect of water content on the compaction quality of roadbeds, this paper is developed by secondary development of Abaqus finite element numerical simulation software. At the same time, the artificial viscous boundary was set to eliminate the influence of boundary conditions on the results in the finite element modeling process, so that the numerical simulation can be refined to model. On this basis, the dynamic response analysis of the roadbed compaction process is performed on the finite element numerical simulation results. This paper established the correlation between compaction degree and intelligent compaction index CMV (Compaction Meter Value) and then analyzed the effect of water content on the compaction quality for the roadbed. The results of this paper show that the amplitude of the vertical acceleration is almost independent of the moisture content, and the vertical displacement mainly occurs in the static compaction stage. The vertical displacement changes sharply in the first 0.5 s when the vibrating wheel is in contact with the roadbed. The main stage of roadbed compaction quality increase is before the end of the first compaction. At the end of the first compaction, the roadbed compaction degree increased rapidly from 80% to 91.68%, 95.34% and 97.41%, respectively. With the increase in water content, the CMV gradually increased. At the end of the second compaction, CMV increased slightly compared with that at the end of the first compaction and stabilized at the end of the second compaction. The water content of the roadbed should be considered to be set slightly higher than the optimal water content of the roadbed by about 1% during the construction of the roadbed within the assumptions of this paper.

Floods in the middle reaches of Yangtze River threaten millions of people and cause casualties and economic losses. Yet, the prediction of floods especially on the sub-seasonal scale in this region is still challenging. To better predict the floods during the flood season (from April to August) in Hunan Province, the models from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) that participated in the sub-seasonal to seasonal (S2S) prediction project were chosen to evaluate their extended-range (the next 11–30 days) prediction skills for heavy precipitation. The original prediction score of single model (original score), the score of single model using optimal threshold of heavy precipitation (adjusted score) and the score of multi-model integration (integrated score) were calculated by the scoring rules for heavy precipitation process. The results show that the integrated score in the extended-range is 75.1, which is 10.3 and 6.9 higher than the average scores of original models and adjusted method, respectively. The false alarm (missing) rate of the integrated method is 5.4% (33.9%), which is 8.6% (4.7%) and 2.9% (3.3%) smaller than the average rates of original models and adjusted method, respectively. HIGHLIGHTS The sub-seasonal to seasonal model data established by the World Meteorological Organization are used.; The method of multi-mode integration is used to effectively improve the prediction score of the heavy precipitation process.; On the basis of multi-mode integration, the empty rate and the missing rate of the heavy precipitation process are effectively reduced by adjusting the threshold of heavy precipitation.;

Objective: Organoids are a powerful tool with broad application prospects in biomedicine. Notably, they provide alternatives to animal models for testing potential drugs before clinical trials. However, the number of passages for which organoids maintain cellular vitality ex vivo remains unclear. Methods: Herein, we constructed 55 gastric organoids from 35 individuals, serially passaged the organoids, and captured microscopic images for phenotypic evaluation. Senescence-associated β-galactosidase (SA-β-Gal), cell diameter in suspension, and gene expression reflecting cell cycle regulation were examined. The YOLOv3 object detection algorithm integrated with a convolutional block attention module (CBAM) was used to evaluate organoid vitality. Results: SA-β-Gal staining intensity; single-cell diameter; and expression of p15, p16, p21, CCNA2, CCNE2, and LMNB1 reflected the progression of aging in organoids during passaging. The CBAM-YOLOv3 algorithm precisely evaluated aging organoids on the basis of organoid average diameter, organoid number, and number × diameter, and the findings positively correlated with SA-β-Gal staining and single-cell diameter. Organoids derived from normal gastric mucosa had limited passaging ability (passages 1–5), before aging, whereas tumor organoids showed unlimited passaging potential for more than 45 passages (511 days) without showing clear senescence. Conclusions: Given the lack of indicators for evaluating organoid growth status, we established a reliable approach for integrated analysis of phenotypic parameters that uses an artificial intelligence algorithm to indicate organoid vitality. This method enables precise evaluation of organoid status in biomedical studies and monitoring of living biobanks.

Miniaturization of supercapacitors offers an attractive route to the fabrication of portable and wearable electronic devices, but still suffers from limited areal capacity. Herein, we utilize a facile stamping approach to fabricate flexible paper-based micro-supercapacitors that are based on the ternary composite containing polyaniline (PANI) as patterned interdigital electrode materials. The ternary composites are composed of PANI, metal-organic frameworks derived from porous carbon (C800) and low-oxidized graphene (LGE). Benefiting from the synergy of C800 and LGE, the electrical conductivity and capacitance retention of PANI composites were enhanced, obviously. The resultant composites displayed high areal capacitance of 162 mF cm−2, remarkable energy density of 24.9 μWh·cm−2, 90 % capacitance over thousands of charge-discharge cycles and excellent stability against bending even at large angles.

Soil stabilizer can improve the physical and chemical properties of clay and improve the bearing capacity of subgrade soil. A kind of liquid polymer soil stabilizer of vinyl acetate-ethylene was used in this paper. First of all, the effects of stabilizer content and curing time on the unconfined compressive strength (UCS) and the water stability were studied to clarify the strength evolution of stabilized soil. Furthermore, the pH test, Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDS), X-Ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR) were performed to study mineralogy, morphology, and chemistry of clay minerals and polymer stabilizer, as well as the potential interaction of the both. The results show that the stabilized soil has a quick strength growth before 14d that reaches about 89% of the final strength, then followed by a decreasing growth rate. Extending the curing time and increasing stabilizer content contribute to the dense agglomeration structure and homogenous skeleton structure. When immersed in the water, the strength has the largest reduction amplitude within the first day. The pore-filling effect, physicochemical bonds, and surface wrapping for clay particles are dominating roles of the polymer stabilizer. The formed fine colloidal particles could fill micro-pores distributed in the matrix. In addition, the polar functional group of carbonyl could create a strong electrostatic attraction and hydrogen bond with the clay minerals, further improving the adhesion, while there are no other new function groups generated. The polymers containing hydrophobic groups are recommended in consideration of water stability.

The emergence of STSW can reduce the amount of materials such as sand and gravel and improve its performance compared to conventional retaining walls. In order to investigate the key influencing factors of STSW, the compression modulus of Scrap tire-soil module (STSM) was obtained by designing a full-scale compression strength test. The shear strength was obtained through a scale-test of shear strength. On this basis, the gravity STSW was established by the finite element numerical simulation software, and the bearing capacity of STSW was analyzed. Further, the key influencing factors of the bearing capacity of STSW were analyzed by designing orthogonal tests, and suggestions for parameter selection for designing STSW were given. The results show that: the friction angle of STSW increases and becomes larger with the increase of area ratio, and the cohesion decreases and decreases with the increase of area ratio; with the increase of compression modulus and internal friction angle, the maximum shear stress inside the retaining wall increases, while the cohesive force has almost no effect on the maximum value of shear stress inside the retaining wall; when constructing retaining walls, it is recommended to use Internal filling material with large compression modulus, small area ratio and its in the range of [0.3–0.5] of STSM.

Nanomaterials, with unique physical, chemical, and biocompatible properties, have attracted significant attention as an emerging active platform in cancer diagnosis and treatment. Amongst them, metal–organic framework (MOF) nanostructures are particularly promising as a nanomedicine due to their exceptional surface functionalities, adsorption properties, and organo-inorganic hybrid characteristics. Furthermore, when bioactive substances are integrated into the structure of MOFs, these materials can be used as anti-tumor agents with superior performance compared to traditional nanomaterials. In this review, we highlight the most recent advances in MOFs-based materials for tumor therapy, including their application in cancer treatment and the underlying mechanisms.

SAR imagery plays a crucial role in geological and environmental monitoring, particularly in highland mountainous regions. However, inherent geometric distortions in SAR images often undermine the precision of remote sensing analyses. Accurately identifying and classifying these distortions is key to analyzing their origins and enhancing the quality and accuracy of monitoring efforts. While the layover and shadow map (LSM) approach is commonly utilized to identify distortions, it falls short in classifying subtle ones. This study introduces a novel LSM ground-range slope (LG) method, tailored for the refined identification of minor distortions to augment the LSM approach. We implemented the LG method on Sentinel-1 SAR imagery from the tri-junction area where the Xiaojiang, Pudu, and Jinsha rivers converge at the Yunnan-Sichuan border. By comparing effective monitoring-point densities, we evaluated and validated traditional methods—LSM, R-Index, and P-NG—against the LG method. The LG method demonstrates superior performance in discriminating subtle distortions within complex terrains through its secondary classification process, which allows for precise and comprehensive recognition of geometric distortions. Furthermore, our research examines the impact of varying slope parameters during the classification process on the accuracy of distortion identification. This study addresses significant gaps in recognizing geometric distortions and lays a foundation for more precise SAR imagery analysis in complex geographic settings.

In order to solve the problem of the poor adaptability of the TBM digging process to changes in geological conditions, a new TBM digging model is proposed. An ensemble learning prediction model based on XGBoost, combined with Optuna for hyperparameter optimization, enables the real-time identification of surrounding rock grades. Firstly, an original dataset was established based on the TBM tunneling parameters under different surrounding rock grades based on the KS tunnel. Subsequently, the RF–RFECV was employed for feature selection and six features were selected as the optimal feature subset according to the importance measure of random forest features and used to construct the XGBoost identification model. Furthermore, the Optuna framework was utilized to optimize the hyperparameters of XGBoost and validated by applying the established TBM dataset of the KS Tunnel. In order to verify the applicability and efficiency of the proposed model in surrounding rock grade identification, the prediction results of five commonly used machine learning models, Optuna–XGBoost, Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Decision Tree (DT), XGBoost, and PSO–XGBoost, were compared and analyzed. The main conclusions are as follows: the feature selection method based on RF–RFECV improved the accuracy by 8.26%. Among the optimal feature subset, T was the most essential feature for the model’s input, while PR was the least important. The Optuna–XGBoost model proposed in this paper had higher accuracy (0.9833), precision (0.9803), recall (0.9813), and F1 score (0.9807) than other models and could be used as an effective means for the lithological identification of surrounding rock grade.

Despite significant advancements in self-supervised anomaly detection, multi-class anomaly detection tasks still pose substantial challenges. Most existing methods require individual network training for each category of objects. This paper presents a novel end-to-end approach for multi-class anomaly detection: self-supervised Mask-pretrained Anomaly Localization Autoencoder (MALA). Firstly, the masked autoencoder (MAE) and Pseudo Label Prediction Module (PLPM) are utilized to recover and perceive normal image patterns. Subsequently, the encoder weights are frozen for further end-to-end network training to predict anomalous maps directly. Token Balance Module(TBM) facilitates anomalous perception and improves anomaly segmentation. By utilizing the Visual Transformer and employing image inpainting as a proxy task, remarkable generalization results are achieved. The proposed method demonstrates its applicability across diverse styles of industrial products. Experiments are conducted on MVTech AD, VisA, KolektorSDD2, and MT datasets, achieving state-of-the-art results in multi-task anomaly detection and segmentation tasks. Specifically, we obtain image AUROC of 98.% and pixel AUROC of 97.1% on the MVTech AD dataset, pixel AUROC of 97.1% on the VisA dataset, and pixel AUROC of 98.7% on the KolektorSDD2 dataset.

In this work, we have described the biogenic synthesized gold nanoparticles being supported over Kaolin mediated by Pomegranate peel extract as natural reducing and stabilizing agent under mild conditions without any toxic reagents. Pomegranate peel extract was used as a green reducing agent and an excellent stabilizer of the synthesized Au NPs. Physicochemical characterization of the as-synthesized Kaolin@extract/Au NPs nanocomposite was carried out through electron microscopy (SEM and TEM), energy dispersive X-ray spectroscopy (EDX), elemental mapping, X-ray diffraction (XRD) and inductively coupled plasma-optical emission spectroscopy (ICP-OES). In the cellular and molecular part of the recent study, the treated cells with Au NPs-Kaolin nanocomposite were assessed by MTT assay for 48 h about the cytotoxicity and anti-human oral squamous cell carcinoma properties on normal (HUVEC) and oral squamous cell carcinoma cell lines i.e. HSC-2, HSC-3, HSC-4 and Ca9-22. It has been observed that the Au NPs with spherical shape and size were dispersed homogeneously on the modified-Kaolin surface. The significance of this study is the novel initiative to combine the gold nanoparticle with inexpensive Kaolin clay and utilization of them as anticancer agent. The IC50 of Kaolin@extract/Au nanocomposite were 277, 367, 250 and 545 µg/mL against HSC-2, HSC-3, HSC-4 and Ca9–22 cell lines, respectively. The viability of malignant human oral cell lines reduced dose-dependently in the presence of Kaolin@extract/Au NPs nanocomposite.

Abstract. Meningiomas are the most common primary intracranial neoplasm with diverse pathological types and complicated clinical manifestations. The fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), published in 2021, introduces major changes that advance the role of molecular diagnostics in meningiomas. To follow the revision of WHO CNS5, this expert consensus statement was formed jointly by the Group of Neuro-Oncology, Society of Neurosurgery, Chinese Medical Association together with neuropathologists and evidence-based experts. The consensus provides reference points to integrate key biomarkers into stratification and clinical decision making for meningioma patients. Registration:. Practice guideline REgistration for transPAREncy (PREPARE), IPGRP-2022CN234

Abstract Deep learning approaches to interactive image segmentation are typically formulated as a binary labeling problem. A model trained to make predictions within a fixed set of labels (i.e., foreground and background labels) cannot be used to directly predict the binary masks of multiple objects of interest, which greatly limits its flexibility and adaptivity. The use of different classes of clicks as input is opted for and the first end‐to‐end learning model for multi‐object segmentation, based on a new designed neural network, is developed. The network consists of a visual feature extractor, a recurrent attention module and a dynamic segmentation head, extracts user click‐adapted appearance embedding features and spatial attention features, and then learns to transform this information into a segmentation of multiple objects. It is also proposed to train the network using a joint loss function, taking the embedding learning into account for segmentation. Comprehensive experiments are conducted on three benchmark datasets to demonstrate the effectiveness of the proposed method. It performs favorably against state‐of‐the‐art approaches on the multiple object segmentation task, for example, with 0.15 s per image, 0.06 s per object and mean IoU & F1 score of 84.90% on Pascal VOC 2012 validation set. It is further shown that the method can be used in numerous vision applications such as image recoloring and colorization.

Abstract Accumulating evidence has demonstrated that carbohydrate response element binding protein (CHREBP) has a crucial function in tumor pathology. In this study, we found CHREBP downregulation in gastric cancer (GC) tissues, and CHREBP was determined to be an independent diagnostic marker of GC. The downregulation of CHREBP promoted cell proliferation and inhibited apoptosis. Moreover, the level of cyclin D1 was significantly correlated with CHREBP expression in GC and paracancerous normal samples. In addition, CHREBP transcriptionally inhibited cyclin D1 expression in GC cells. Tumor suppressor activity of CHREBP could be affected by the upregulation of cyclin D1. In summary, CHREBP was found to be an independent diagnostic marker of GC and to influence GC growth and apoptosis via targeting the cyclin D1-Rb-E2F1 pathway.

E-skins often have poor interfaces that lead to unstable performances. Here, authors report e-skins with a quasi-homogeneous composition and bonded micro-structured interfaces, through which both the sensitivity and stability of the devices are improved.

Abstract Despite the impressive performance of correlation filter-based trackers in terms of robustness and accuracy, the trackers have room for improvement. The majority of existing trackers use a single feature or fixed fusion weights, which makes it possible for tracking to fail in the case of deformation or severe occlusion. In this paper, we propose a multi-feature response map adaptive fusion strategy based on the consistency of individual features and fused feature. It is able to improve the robustness and accuracy by building the better object appearance model. Moreover, since the response map has multiple local peaks when the target is occluded, we propose an anti-occlusion mechanism. Specifically, if the nonmaximal local peak is satisfied with our proposed conditions, we generate a new response map which is obtained by moving the center of the region of interest to the nonmaximal local peak position of the response map and re-extracting features. We then select the response map with the largest response value as the final response map. This proposed anti-occlusion mechanism can effectively cope with the problem of tracking failure caused by occlusion. Finally, by adjusting the learning rate in different scenes, we designed a high-confidence model update strategy to deal with the problem of model pollution. Besides, we conducted experiments on OTB2013, OTB2015, TC128 and UAV123 datasets and compared them with the current state-of-the-art algorithms, and the proposed algorithms have impressive advantages in terms of accuracy and robustness.

Olive leaves are rich in phenolic compounds. This study explored the chemical profiles and contents of free phenolics (FPs) and bound phenolics (BPs) in olive leaves, and further investigated and compared the antioxidant properties of FPs and BPs using chemical assays, cellular antioxidant evaluation systems, and in vivo mouse models. The results showed that FPs and BPs have different phenolic profiles; 24 free and 14 bound phenolics were identified in FPs and BPs, respectively. Higher levels of phenolic acid (i.e., sinapinic acid, 4-coumaric acid, ferulic acid, and caffeic acid) and hydroxytyrosol were detected in the BPs, while flavonoids, triterpenoid acids, and iridoids were more concentrated in the free form. FPs showed a significantly higher total flavonoid content (TFC), total phenolic content (TPC), and chemical antioxidant properties than those of BPs (p < 0.05). Within the range of doses (20–250 μg/mL), both FPs and BPs protected HepG2 cells from H2O2-induced oxidative stress injury, and there was no significant difference in cellular antioxidant activity between FPs and BPs. The in vivo experiments suggested that FP and BP treatment inhibited malondialdehyde (MDA) levels in a D-galactose-induced oxidation model in mice, and significantly increased antioxidant enzyme activity of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and the total antioxidant capacity (T-AOC). Mechanistically, FPs and BPs exert their antioxidant activity in distinct ways; FPs ameliorated D-galactose-induced oxidative stress injury partly via the activation of nuclear factor erythroid-2-related factor 2 (Nrf2) signaling pathway, while the BP mechanisms need further study.

In order to explore the quality differences between Meizhan black tea and Meizhan white tea, Meizhan fresh leaves were used as raw materials to process black tea and white tea, and sensory quality evaluation and physicochemical analysis were carried out. The results showed that the aroma of Meizhan black tea was sweet and flowery, the taste was sweet and mellow. The aroma of Meizhan white tea was floral, the taste was fresh and mellow. The contents of theaflavins, thearubins and theanines in Meizhan black tea were significantly higher than those in Meizhan white tea. The contents of polyphenols and free amino acids in Meizhan white tea were significantly higher than those in Meizhan black tea (P

Complex-valued shift-invariant canonical polyadic decomposition (CPD) under a spatial phase sparsity constraint (pcsCPD) shows excellent separation performance when applied to band-pass filtered complex-valued multi-subject fMRI data. However, some useful information may also be eliminated when using a band-pass filter to suppress unwanted noise. As such, we propose an alternating rank- ${R}$ and rank-1 least squares optimization to relax the CPD model. Based upon this optimization method, we present a novel constrained CPD algorithm with temporal shift-invariance and spatial sparsity and orthonormality constraints. More specifically, four steps are conducted until convergence for each iteration of the proposed algorithm: 1) use rank- ${R}$ least-squares fit under spatial phase sparsity constraint to update shared spatial maps after phase de-ambiguity; 2) use orthonormality constraint to minimize the cross-talk between shared spatial maps; 3) update the aggregating mixing matrix using rank- ${R}$ least-squares fit; 4) utilize shift-invariant rank-1 least-squares on a series of rank-1 matrices reconstructed by each column of the aggregating mixing matrix to update shared time courses, and subject-specific time delays and intensities. The experimental results of simulated and actual complex-valued fMRI data show that the proposed algorithm improves the estimates for task-related sensorimotor and auditory networks, compared to pcsCPD and tensorial spatial ICA. The proposed alternating rank- ${R}$ and rank-1 least squares optimization is also flexible to improve CPD-related algorithm using alternating least squares.

Vegetables from the Brassica species are excellent sources of glucosinolates (GLSs), the precursors of health-promoting isothiocyanates (ITCs). Fermentation enhances the biotransformation of GLSs into potential bioactive ITCs. To explore the biotransformation of GLSs during Brassica fermentation, the changes in GLSs during the fermentation of two Brassica species (i.e., cauliflower and broccoli); the formation of corresponding breakdown products; and the shifts in physicochemical parameters, bacterial communities, and myrosinase activities involved in GLSs degradation were systematically investigated. Nine aliphatic, three indolic, and two benzenic GLSs were identified in fermented cauliflower (FC) and fermented broccoli (FB). Aliphatic glucoiberin and glucoraphanin were the major forms of GLS in FC and FB, respectively; indolic glucobrassicin was also abundant in both FC and FB. The total GLS content decreased by 85.29% and 65.48% after 3 d of fermentation in FC and FB, respectively. After 2 d of fermentation, a significant increase in bioactive GLS degradation products (P

Abstract Recently, object trackers based on Siamese networks have attracted considerable attentions due to their remarkable tracking performance and widespread application. Especially, the anchor-based methods exploit the region proposal subnetwork to get accurate prediction of a target and make great performance improvement. However, those trackers cannot capture the spatial information very well and the pre-defined anchors will hinder robustness. To solve these problems, we propose a Siamese-based anchor-free object tracking algorithm with multiscale spatial attentions in this paper. Firstly, we take ResNet-50 as the backbone network to generate multiscale features of both template patch and search regions. Secondly, we propose the spatial attention extraction (SAE) block to capture the spatial information among all positions in the template and search region feature maps. Thirdly, we put these features into the SAE block to get the multiscale spatial attentions. Finally, an anchor-free classification and regression subnetwork is used for predicting the location of the target. Unlike anchor-based methods, our tracker directly predicts the target position without predefined parameters. Extensive experiments with state-of-the-art trackers are carried out on four challenging visual object tracking benchmarks: OTB100, UAV123, VOT2016 and GOT-10k. Those experimental results confirm the effectiveness of our proposed tracker.

Abstract More than 60% of nonsmall cell lung cancer (NSCLC) patients show a positive response to the first ALK inhibitor, crizotinib, which has been used as the standard treatment for newly diagnosed patients with ALK rearrangement. However, most patients inevitably develop crizotinib resistance due to acquired secondary mutations in the ALK kinase domain, such as the gatekeeper mutation L1196M and the most refractory mutation, G1202R. Here, we develop XMU‐MP‐5 as a new‐generation ALK inhibitor to overcome crizotinib resistance mutations, including L1196M and G1202R. XMU‐MP‐5 blocks ALK signaling pathways and inhibits the proliferation of cells harboring either wild‐type or mutant EML4‐ALK in vitro and suppresses tumor growth in xenograft mouse models in vivo. Structural analysis provides insights into the mode of action of XMU‐MP‐5. In addition, XMU‐MP‐5 induces significant regression of lung tumors in two genetically engineered mouse (GEM) models, further demonstrating its pharmacological efficacy and potential for clinical application. These preclinical data support XMU‐MP‐5 as a novel selective ALK inhibitor with high potency and selectivity. XMU‐MP‐5 holds great promise as a new therapeutic against clinically relevant secondary ALK mutations.

Immune cells play a crucial regulatory role in inflammatory phase and proliferative phase during skin healing. How to programmatically activate sequential immune responses is the key for scarless skin regeneration. In this study, an “Inner-Outer” IL-10-loaded electrospun fiber with cascade release behavior was constructed. During the inflammatory phase, the electrospun fiber released a lower concentration of IL-10 within the wound, inhibiting excessive recruitment of inflammatory cells and polarizing macrophages into anti-inflammatory phenotype “M2c” to suppress excessive inflammation response. During the proliferative phase, a higher concentration of IL-10 released by the fiber and the anti-fibrotic cytokines secreted by polarized “M2c” directly acted on dermal fibroblasts to simultaneously inhibit extracellular matrix overdeposition and promote fibroblast migration. The “Inner-Outer” IL-10-loaded electrospun fiber programmatically activated the sequential immune responses during wound healing and led to scarless skin regeneration, which is a promising immunomodulatory biomaterial with great potential for promoting complete tissue regeneration.

Abstract Background Colorectal cancer (CRC) is one of the most frequent malignancy and a leading cause of cancer-related deaths. Therefore, further researches are required to identify novel and more effective diagnoses and to identify molecular targets in treatment of CRC. Methods C2CD4A expression in CRC tissues and cell lines was detected by qRT-PCR and western blot. The biological functions of C2CD4A were performed both in vitro and in vivo. Western blot, cDNA array, IP-MS, Co-immunoprecipitation assay, and Ubiquitination assay were used to analyze the interaction between C2CD4A and p53. Bioinformatics analysis, FISH, RNA sequencing, luciferase reporter assay, RNA immunoprecipitation, RNA pull-down and rescue experiments, were deployed to detect upstream regulation mechanism of C2CD4A. Results C2CD4A was elevated in CRC tissues compared with adjacent normal colorectal tissues. C2CD4A knockdown significantly promoted cell apoptosis and with inhibited proliferation in vitro, and tumorigenicity in vivo, whereas C2CD4A overexpression led to opposite effects. Moreover, circSLC6A6 was upregulated and shown to positively regulate C2CD4A expression via sponging miR-1265. Fundamentally, C2CD4A inhibited p53 signaling pathway through interacting with p53 and increasing its ubiquitination and degradation. Conclusion Our results identified that circSLC6A6/miR-1265/C2CD4A axis, which was involved in CRC via the p53 signaling pathway, may serve as a therapeutic target for CRC.

Abstract Arecoline, a major alkaloid within areca nut extract, is recognized as the primary active carcinogen promoting oral squamous cell carcinoma (OSCC) pathological development. Dysregulation of N6‐methyladenosine (m6A) methyltransferase components (e.g., Fat mass and obesity‐associated protein [FTO] and methyltransferase‐like 3 [METTL3]) are closely associated with multiple cancer progression, including oral cancer. However, the biological function role of FTO in arecoline‐induced oral cancer is largely unknown. We identified that FTO was significantly upregulated in OSCC tissues from patients with areca nut chewing habits and chronic arecoline‐treated OSCC cell lines. Depletion of FTO attenuated the arecoline‐promoted stemness, chemoresistance, and oncogenicity of OSCC cells. Finally, we revealed that FTO was negatively regulated by a transcription factor forkhead box protein A2 (FOXA2) in OSCC cells. This study, for the first time, demonstrated that FTO plays an oncogenic role in arecoline‐induced OSCC progression. Thus, developing new therapeutic agents targeting FTO may serve as a promising method to treatment OSCC patients, especially those with areca nut chewing habits.

The impact of fermentation by Levilactobacillus brevis YSJ3 on sleep-promoting components (SPCs) of carrot juice was evaluated. The contents of acetic acid, isovaleric acid, butyric acid, and γ-aminobutyric acid (GABA) significantly increased after fermentation. The beneficial effects of fermented carrot juice (FCJ) on sleep were evaluated in animal experiments. Behavioral test reveal SPCs-enriched FCJ could effectively relieve anxiety. The sleep duration in the FCJ group were extended compared to the control (NC) group and the unfermented carrot juice (UCJ) group. Moreover, the relative abundances of Ruminiclostridium and Akkermansia in the FCJ group and PC group, respectively, increased significantly, compared to the NC group the UCJ group. The contents of gut short-chain fatty acids in the FCJ group were significantly higher than that in the NC group and the UCJ group. The levels of GABA and 5-hydroxytryptamine in the brain for the FCJ group also increased significantly, compared to the NC group and the UCJ group. It indicated that SPCs-enriched FCJ effectively improved sleep in mice, which might be related to the fermentation of carrot juice and the compounds produced during the fermentation.

Background: To analyze the polymorphism distribution of low density lipoprotein receptor rs688, AvaII, NcoI gene in ischemic stroke, and explore the linkage disequilibrium among them. The correlation between the linkage disequilibrium and ischemic stroke was further analyzed. Methods: The levels of serum lipid (triglyceride, cholesterol, high density lipoprotein cholesterol, low density lipoprotein cholesterol, apolipoprotein A1, apolipoprotein B) and rs688, AvaII, NcoI polymorphism of low density lipoprotein receptor gene were tested in patients with ischemic stroke (n = 140), healthy control (n = 129) and patients with other cerebrovascular diseases (n = 122). Chi-square test was used to compare the gene frequency and allele frequency of each group. Both the linkage disequilibrium of the three genes and the alleles correlated with ischemic stroke were analyzed. The correlation of linkage disequilibrium gene and ischemic stroke was analyzed with logistic binary regression. Results: In the ischemic stroke group, significant difference was observed in frequencies and allelic frequencies of low density lipoprotein receptor (LDLR) rs688 and AvaII. No difference of NcoI was found. Linkage disequilibrium was found for rs688 and AvaII (D’ = 0.927, R2 = 0.509). Allelic genes correlate with ischemic stroke included T of rs688 (X2 = 46.105, p < 0.001) and C of AvaII (X2 = 20.436, p < 0.001). Conclusions: Linkage disequilibrium existed between LDLR rs688 and AvaII genes. With the wild type gene (WT) (rs688/AvaII: CC/TT) as reference, rs688/AvaII: CT/TC, CT/CC and TT/CC increased the risk of ischemic stroke, which might be a genetic marker used for the screen of high-risk population contributing to the prevention of the disease.

Spikelet number per panicle (SNP) is one of the most important yield components in rice. Rice ENHANCING BIOMASS AND SPIKELET NUMBER (OsEBS), a gene involved in improved SNP and yield, has been cloned from an accession of Dongxiang wild rice. However, the mechanism of OsEBS increasing rice SNP is poorly understood. In this study, the RNA-Seq technology was used to analyze the transcriptome of wildtype Guichao 2 and OsEBS over-expression line B102 at the heading stage, and analysis of the evolution of OsEBS was also conducted. A total of 5369 differentially expressed genes (DEGs) were identified between Guichao2 and B102, most of which were down-regulated in B102. Analysis of the expression of endogenous hormone-related genes revealed that 63 auxin-related genes were significantly down-regulated in B102. Gene Ontogeny (GO) enrichment analysis showed that the 63 DEGs were mainly enriched in eight GO terms, including auxin-activated signaling pathway, auxin polar transport, auxin transport, basipetal auxin transport, and amino acid transmembrane transport, most of which were directly or indirectly related to polar auxin transport. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis further verified that the down-regulated genes related to polar auxin transport had important effects on increased SNP. Analysis of the evolution of OsEBS found that OsEBS was involved in the differentiation of indica and japonica, and the differentiation of OsEBS supported the multi-origin model of rice domestication. Indica (XI) subspecies harbored higher nucleotide diversity than japonica (GJ) subspecies in the OsEBS region, and XI experienced strong balancing selection during evolution, while selection in GJ was neutral. The degree of genetic differentiation between GJ and Bas subspecies was the smallest, while it was the highest between GJ and Aus. Phylogenetic analysis of the Hsp70 family in O. sativa, Brachypodium distachyon, and Arabidopsis thaliana indicated that changes in the sequences of OsEBS were accelerated during evolution. Accelerated evolution and domain loss in OsEBS resulted in neofunctionalization. The results obtained from this study provide an important theoretical basis for high-yield rice breeding.

Rock mass conditions are extremely sensitive to tunnel boring machine (TBM) tunneling. Therefore, establishing a surrounding rock excavatability (SRE) classification system applicable to TBM tunnels. Accurately and intelligently identifying excavatability grades can also facilitate efficient TBM tunneling and intelligent construction. Specific excavation and penetration rates were used to evaluate SRE. Their correlations with geological and tunneling parameters were explored using the field data from two water conveyance tunnels in China with different lithologies. A high-precision empirical SRE classification system was constructed using TOPSIS for multi-objective decision-making, and it was verified using engineering cases. An intelligent identification model for SRE grades in the stable phase of a TBM excavation cycle was established using 12,382 TBM rock-breaking datasets and deep forest models. Ten characteristic parameters, e.g., total thrust, were selected as model input features. Hyperparameter optimization was achieved using the grid search method. Deep forest was compared with decision tree, random forest, support vector classifier, and deep neural network. The contribution of the model’s features was measured using random forest. The main conclusions are as follows: the proposed SRE classification method is feasible and matches well with the actual excavation. In the intelligent identification of SRE classification, the accuracy and F1 scores when using deep forest were 96.33% and 0.9581, respectively. Deep forest exhibited better grade identification performance than the four models. Among the ten input features, penetration is the most important feature for the model’s input, while the top shield cylinder rod’s chamber pressure is the least important. The findings can provide some references for SRE classification and prediction and intelligent TBM control.

Abstract Background Various circular RNAs (circRNAs) are dysregulated in the placenta of fetal growth restriction (FGR) fetuses, but their roles and regulatory mechanisms have not been fully elucidated. Herein, we aimed to elucidate the role of hsa_circ_0081343 in regulating the migration, invasion, and apoptosis of human extravillous trophoblast HTR-8 cells. Methods CircRNA and miRNA levels were examined by quantitative reverse transcription PCR (qRT-PCR). Overexpression plasmid constructs and siRNAs were used to overexpress and knockdown hsa_circ_0081343, respectively. Transwell assays and flow cytometry analyses were performed to evaluate the effects of hsa_circ_0081343 or miR-210-5p on migration, invasion, and apoptosis. Protein levels were analyzed by western blotting. Dual luciferase activity and anti-AGO2 RNA immunoprecipitation (RIP) assays were performed to identify the relationship between miR-210-5p and hsa_circ_0081343. Results Hsa_circ_0081343 expression was significantly downregulated in 37 FGR placental tissues compared to healthy placental control tissues. Hsa_circ_0081343 overexpression may inhibit apoptosis by downregulating the expression of cleaved caspase 3 and caspase 9 and alleviating the migration and invasion of HTR-8 cells by inducing the expression of MMP2 and MMP9. The dual luciferase activity and anti-AGO2 RIP assay results showed that hsa_circ_0081343 binds to miR-210-5p. miR-210-5p overexpression eliminated the effect of hsa_circ_0081343 overexpression in HTR-8 cells. Finally, DLX3 was identified as a direct target of miR-210-5p. Conclusions hsa_circ_0081343 expression levels are significantly downregulated in FGR placental tissues. Hsa_circ_0081343 regulates the migration, invasion, and apoptosis of HTR-8 cells via the hsa-miR-210-5p/DLX3 axis.

Abstract Human gut microbiota modulates normal physiological functions, such as maintenance of barrier homeostasis and modulation of metabolism, as well as various chronic diseases including type 2 diabetes and gastrointestinal cancer. Despite decades of research, the composition of the gut microbiota remains poorly understood. Here, we established an effective extraction method to obtain high quality gut microbiota genomes, and analyzed them with third-generation sequencing technology. We acquired a large quantity of data from each sample and assembled large numbers of reliable contigs. With this approach, we constructed tens of completed bacterial genomes in which there were several new bacteria species. We also identified a new conditional pathogen, Enterococcus tongjius, which is a member of Enterococci. This work provided a novel and reliable approach to recover gut microbiota genomes, facilitating the discovery of new bacteria species and furthering our understanding of the microbiome that underlies human health and diseases.