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Abstract A scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation.

IntroductionWe investigated the efficacy and safety of oral sodium bicarbonate in kidney-transplant recipients and non-transplant patients with chronic kidney disease (CKD), which are currently unclear.MethodsPubMed, Cochrane Library, Embase, and Web of Science were searched for randomized controlled trials investigating the efficacy and safety of sodium bicarbonate versus placebo or standard treatment in kidney-transplant and non-transplant patients with CKD.ResultsSixteen studies of kidney-transplant recipients (two studies, 280 patients) and non-transplant patients with CKD (14 studies, 1,380 patients) were included. With non-transplant patients, sodium bicarbonate slowed kidney-function declines (standardized mean difference [SMD]: 0.49, 95% confidence interval [CI]: 0.14–0.85, p = 0.006) within ≥12 months (SMD: 0.75 [95% CI: 0.12–1.38], p = 0.02), baseline-serum bicarbonate

The potential distribution of crops will be impacted by climate change, but there is limited research on potential wheat distributions under specific global warming targets. This study employed the Maxent model to predict the potential distribution of wheat under the 1.5°C and 2°C warming targets based on data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) multimodel ensemble, and the effect of global warming on wheat planting suitability was analyzed. Our results indicated global warming would significantly change wheat planting suitability. Over half of the areas experienced changes in wheat planting suitability under two warming targets, and the effect became more pronounced with increasing temperatures. Additionally, global warming might promote wheat planting in more regions. The area with an increase in wheat planting suitability was observed to be 9% higher than those experiencing a decrease on average. Moreover, global warming could exacerbate the disparity between global wheat supply and demand in countries/regions. Traditional wheat-producing countries/regions are poised to benefit from the warming effects of climate change, while less developed and wheat import-dependent countries/regions may face greater challenges in achieving wheat self-sufficiency. To address this potential challenge, the promotion and inter-regional exchange of agronomic technologies, and the development of more rational trade standards are urgently needed. Since socioeconomic factors have a significant impact on wheat cultivation, further investigation is required to determine how the wheat planting distribution may change in the future under the combined impact of climate change, supply-demand relationship, and policy.

Abstract Background The pathophysiological mechanisms of diabetic retinopathy (DR), a blinding disease, are intricate. DR was thought to be a microvascular disease previously. However, growing studies have indicated that the retinal microglia-induced inflammation precedes microangiopathy. The binary concept of microglial M1/M2 polarization paradigms during inflammatory activation has been debated. In this study, we confirmed microglia had the most significant changes in early DR using single-cell RNA sequencing. Methods A total of five retinal specimens were collected from donor SD rats. Changes in various cells of the retina at the early stage of DR were analyzed using single-cell sequencing technology. Results We defined three new microglial subtypes at cellular level, including two M1 types (Egr2 + M1 and Egr2 − M1) and one M2 type. We also revealed the anatomical location between these subtypes, the dynamic changes of polarization phenotypes, and the possible activation sequence and mutual activation regulatory mechanism of different cells. Furthermore, we constructed an inflammatory network involving microglia, blood-derived macrophages and other retinal nonneuronal cells. The targeted study of new disease-specific microglial subtypes can shorten the time for drug screening and clinical application, which provided insight for the early control and reversal of DR. Conclusions We found that microglia show the most obvious differential expression changes in early DR and reveal the changes in microglia in a high-glucose microenvironment at the single-cell level. Our comprehensive analysis will help achieve early reversal and control the occurrence and progression of DR.

Abstract In this paper, we propose the fine-grained geospatial knowledge graph (FineGeoKG), which can capture the neighboring relations between geospatial objects. We call such neighboring relations strong geospatial relations (SGRs) and define six types of SGRs. In FineGeoKG, the vertices (or entities) are geospatial objects. The edges (or relations) can have “sgr” labels together with properties, which are used to quantify SGRs in both topological and directional aspects. FineGeoKG is different from WorldKG, Yago2Geo, and other existing geospatial knowledge graphs, since its edges can capture the spatial coherence among geospatial objects. To construct FineGeoKG efficiently, the crucial problem is to find out SGRs. We improve the existing geospatial interlinking algorithm in order to find out SGRs faster. To answer SGR queries efficiently, we design an index to organize the SGR edges and improve the binary join method for subgraph matching. We conduct experiments on the real datasets and the experimental results show that the proposed algorithm is more efficient than the baseline algorithms. We also demonstrate the usefulness of FineGeoKG by presenting the results of complicated spatial queries which focus on structural and semantic information. Such queries can help researchers (for example, ecologists) find groups of objects following specific spatial patterns.

Abstract In this paper, we employ gauge/gravity duality to investigate the string breaking and melting of doubly-heavy tetraquark that includes two heavy quarks and two light antiquarks in a holographic model at finite temperature. Firstly, four different configurations of $${{\textrm{QQ}}}\bar{{\textrm{q}}}\bar{{\textrm{q}}}$$ QQ q ¯ q ¯ are studied at different separation distances of the heavy quarks at finite temperatures. At high temperature, $${{\textrm{QQ}}}\bar{{\textrm{q}}}\bar{{\textrm{q}}}$$ QQ q ¯ q ¯ will melt at certain distances and the screening distance has been given for different temperatures. As the temperature continues to increase, some configurations of doubly-heavy tetraquark can not exist. Furthermore, we investigate three decay modes of $${{\textrm{QQ}}}\bar{{\textrm{q}}}\bar{{\textrm{q}}}$$ QQ q ¯ q ¯ and compare the potential energy of $${{\textrm{QQ}}}\bar{{\textrm{q}}}\bar{{\textrm{q}}}$$ QQ q ¯ q ¯ with that of $${\textrm{QQq}}$$ QQq at finite temperature.

Due to the swift progress of the economy and society and the rapid escalation of urbanization rates, the sustainable examination of individual water or land resources is no longer adequate to satisfy the rational allocation demands of urban development concerning the water and soil resource framework. To enhance the efficiency of utilizing water and land resources comprehensively and the rationality of the joint allocation of these resources, this paper presents a comprehensive analysis of the eco-economic system of water and land resources, encompassing six key aspects: system emergy flow, water resources subsystem, land resources subsystem, economic subsystem, ecological subsystem, and social subsystem. By considering three types of land use (construction land, agricultural land, and unused land), we constructed a sustainable evaluation index system for the eco-economic system of water and land resources based on the emergy theory. We employ the emergy theory analysis method to provide a comprehensive assessment of the sustainable development status and development trend of the Luoyang City from 2011 to 2020. The results show that Luoyang belongs to the consumer economy and the development of water and soil resources of the ecological economic system in Luoyang is in a critical state of unsustainable and mild sustainability from 2011 to 2020. HIGHLIGHTS This paper constructs the sustainability evaluation index system of water and soil resources of an eco-economic system.; This paper evaluates the sustainability of eco-economic system of water and soil resources by using emergy theory and analysis method.;

Abstract Prostate cancer (PCa) is a significant health concern affecting men worldwide. Previous studies have shown that nimotuzumab, a drug targeting the epidermal growth factor receptor (EGFR), can effectively inhibit cancer progression. Here, we aimed to explore the role of miR‐199a/214 cluster in mediating the inhibitory effect of nimotuzumab on the development of PCa. In this study, we conducted an MTT assay to assess cell proliferation and utilized flow cytometry to evaluate cell apoptosis and cell cycle arrest. To investigate the molecular mechanisms underlying the effects of nimotuzumab on prostate cancer development, we focused on the miR‐199a‐5p and miR‐214‐3p miRNA clusters. The TargetScan Human database was used to predict the binding sites between miR‐199a‐5p or miR‐214‐3p and the 3'‐UTR of the transducin (β)‐like 1 X‐linked receptor 1 (TBL1XR1) mRNA. To confirm the direct interaction and binding between miR‐199a‐5p or miR‐214‐3p and the 3'‐UTR of TBL1XR1 mRNA, we performed luciferase reporter assays. Our findings demonstrated that nimotuzumab exerted a significant dosage‐dependent suppression of PCa cell proliferation and facilitated PCa cell apoptosis and cell cycle arrest. Concurrently, nimotuzumab obviously impeded the activity of Wnt/β‐catenin and EGFR signaling pathways in PCa cells. We also observed downregulation of miR‐199a‐5p and miR‐214‐3p in PCa cells. Overexpression of miR‐199a/214 cluster inhibited PCa cell viability and enhanced cell apoptosis. Furthermore, we found that miR‐199a/214 cluster augmented the inhibitory effect of nimotuzumab on PCa cell proliferation and promoted its ability to induce apoptosis and cell cycle arrest. This effect was reversed upon TBL1XR1 overexpression, indicating that TBL1XR1 is involved in the regulatory pathway of miR‐199a/214 and nimotuzumab in PCa cells. We further revealed that TBL1XR1 was overexpressed in PCa and was identified as a downstream target of the miR‐199a/214 cluster. In nimotuzumab‐treated PCa cells, the overexpression of miR‐199a/214 markedly inhibited Wnt/β‐catenin and EGFR signaling, and this effect was also rescued by TBL1XR1 overexpression. In summary, our data indicated that miR‐199a/214 cluster play a crucial role in enhancing the inhibitory effect of nimotuzumab on PCa development by downregulating TBL1XR1 and modulating Wnt/β‐catenin and EGFR signaling pathways. These findings offer a novel therapeutic approach for the treatment of prostate cancer.

Despite progress in land protection, agricultural land in China faces threats from urban expansion and unsustainable practices, necessitating urgent efforts to protect and enhance cultivated land quality. This study quantifies cultivated land quality as a composite indicator through an evaluation model, which reduces the heterogeneity and diversity of cultivated land quality among fields to some extent. This study introduced the concept of geodiversity and constructed a new framework for measuring cultivated land quality type (CLQT) and explored the CLQT in different geomorphic regions of Jiangxi, China. Using landscape metrics, spatial autocorrelation and structural equation modeling, this study analyzed the spatial clustering types and drivers of CLQT diversity. The results showed that 1) the framework of CLQT composed of nine indicators arranged by topographic conditions, soil conditions, ecological conditions, and anthropogenic management conditions yielded 2,565 CLQTs in the research area. 2) The landscape metrics showed a high degree of overlap, with the main overlapping areas distributed in the plains, hills, and mountainous regions in the central and southern parts of the country. SHDI, SHEI, PR, and PD showed low-low cluster in the central plains, while SHDI, SHEI, PR, LSI, PAFRAC, and DIVISION showed high-high cluster in the southern hills.3) The main influencing factors in the plains were natural factors (mean annual temperature and mean annual precipitation) and in the hills were a combination of natural factors (MAT and MAP) and socio-economic factors (Ninput and GDP). The highest diversity of CLQT was observed in the mountainous regions, where the influencing factors include both natural (MAT) and socio-economic factors (POP and GDP). Therefore, it is recommended that in the plains, large-scale operators should adopt diversified planting strategies to enhance CLQT diversity and the stability of cropland ecosystems. In hills and mountainous regions with high CLQT diversity, the government should formulate policies to stimulate farmers’ planting motivation and increase inputs to support agricultural production. This study provides a new perspective on the study of cultivated land quality and provides a reference for improving agroecosystem stability and food production in regions with similar landscapes around the world.

Plesiomonas shigelloides, a Gram-negative bacillus, is the only member of the Enterobacteriaceae family able to produce polar and lateral flagella and cause gastrointestinal and extraintestinal illnesses in humans. The flagellar transcriptional hierarchy of P. shigelloides is currently unknown. In this study, we identified FlaK, FlaM, FliA, and FliAL as the four regulators responsible for polar and lateral flagellar regulation in P. shigelloides. To determine the flagellar transcription hierarchy of P. shigelloides, the transcriptomes of the WT and ΔflaK, ΔflaM, ΔfliA, and ΔfliAL were carried out for comparison in this study. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and luminescence screening assays were used to validate the RNA-seq results, and the Electrophoretic Mobility Shift Assay (EMSA) results revealed that FlaK can directly bind to the promoters of fliK, fliE, flhA, and cheY, while the FlaM protein can bind directly to the promoters of flgO, flgT, and flgA. Meanwhile, we also observed type VI secretion system (T6SS) and type II secretion system 2 (T2SS-2) genes downregulated in the transcriptome profiles, and the killing assay revealed lower killing abilities for ΔflaK, ΔflaM, ΔfliA, and ΔfliAL compared to the WT, indicating that there was a cross-talk between the flagellar hierarchy system and bacterial secretion system. Invasion assays also showed that ΔflaK, ΔflaM, ΔfliA, and ΔfliAL were less effective in infecting Caco-2 cells than the WT. Additionally, we also found that the loss of flagellar regulators causes the differential expression of some of the physiological metabolic genes of P. shigelloides. Overall, this study aims to reveal the transcriptional hierarchy that controls flagellar gene expression in P. shigelloides, as well as the cross-talk between motility, virulence, and physiological and metabolic activity, laying the groundwork for future research into P. shigelloides’ coordinated survival in the natural environment and the mechanisms that infect the host.

China has been facing a contradiction between its water supply and demand for a long time, and it is urgent that it builds a “water-saving society”. Previous research on water pricing mainly focused on the policy level, only considering the supply and demand sides and ignoring the participation of local governments. Due to the inconsistent approval mechanisms, different times of cost formation, and lack of a scientific pricing relationship between multiple water sources and multiple users, with the current water pricing in China, it is difficult to solve the complex problem of water resource allocation. This study aimed to promote the qualitative supply of water and the reuse of reclaimed water, achieve a high-quality and low-cost water supply, and explore the role of water-pricing mechanisms in the regulation of multi-source water supply configurations. The mechanism of regulation is constructed for the complex, multi-source, multi-user water resource system, and a three-party game model is established among local governments, water supply enterprises, and water users. A reasonable pricing system with a rational price relationship is obtained, and Pinghu City in Zhejiang Province is taken as the research area. The prices of the external water supply to residential users, non-resident users, and special users are 4.48 CNY/m3, 6.28 CNY/m3, and 7.12 CNY/m3. The external supply prices for resident users, non-resident users, and special users are 3.81 CNY/m3, 5.25 CNY/m3, and 6.05 CNY/m3. The external supply price for non-resident users is 2.62 CNY/m3 for reclaimed water. The results of the study showed that when the government’s contribution did not exceed the amount that it would have been without the inclusion of recycled water and the annual payment of water users did not exceed their ability to pay, the income of water suppliers increased by 69%. The three balanced objectives of rational water resource configuration by the local government, reasonable profit for the water supply enterprise, and reasonable payment by water users have been achieved. This study provides theoretical and methodological support for the implementation of water pricing for multi-source and multi-user water supplies in water-scarce areas.

The charging behavior of electric vehicle users is highly stochastic, which makes the short-term prediction of charging load at electric vehicle charging stations difficult. In this paper, a data-driven hybrid model optimized by the improved dung beetle optimization algorithm (IDBO) is proposed to address the problem of the low accuracy of short-term prediction. Firstly, the charging station data are preprocessed to obtain clear and organized load data, and the input feature matrix is constructed using factors such as temperature, date type, and holidays. Secondly, the optimal CNN-BiLSTM model is constructed using convolutional neural network (CNN) and Bi-directional Long Short-Term Memory (BiLSTM), which realizes the feature extraction of the input matrix and better captures the hidden patterns and regularities in it. Then, methods such as Bernoulli mapping are used to improve the DBO algorithm and its hyperparameters; for example, hidden neurons of the hybrid model are tuned to further improve the model prediction accuracy. Finally, a simulation experiment platform is established based on MATLAB R2023a to validate the example calculations on the historical data of EV charging stations in the public dataset of ANN-DATA, and comparative analyses are carried out. The results show that compared with the traditional models such as CNN, BiLSTM and PSO-CNN-BiLSTM, the coefficient of determination of the model exceeds 0.8921 and the root mean square error is maintained at about 4.413 on both the training and test sets, which proves its effectiveness and stability.

Polymer selective laser sintering (SLS) is an additive manufacturing technology that involves the melting of a selected area of particles on the powder bed. A 3D component is then printed using layer-by-layer sintering of the powder bed. SLS is considered one of the most promising technologies applicable to a variety of applications, particularly for manufacturing customized design products with high geometric complexity, such as patient-specific designed implants, surgical tools. Currently, only a small number of polymers are available that are suitable for SLS due to the complex multiple physical phenomena involved. Therefore, it is critical to develop new materials in order to fully realize the potential of SLS technology for manufacturing value-added customized products. For a given material, the quality of powder spreading in SLS plays a key role in printing performance and is a precondition for new material development. The aim of this review is to (1) present flowability characterization methods suitable for SLS, (2) examine the influence of powder properties and flowability on laser–material interaction and the quality of the final part, and (3) discuss the methods adopted in the literature to improve the quality of powder spreading.

In this study, we develop an Atmospheric Motion Vector (AMV)-based method for retrieving wind vectors using 183.31 GHz water-vapor absorption channels. The method involves tracking water-vapor features from image triplets and subsequently deriving wind fields from motion vectors. The height of the derived wind for each channel is determined by calculating the weighing function peak using monthly averaged ERA5 reanalysis data. By utilizing Microwave Humidity Sounder-II (MWHS-II) brightness temperatures from the five channels centered around 183.31 GHz, wind vectors are retrieved within the Arctic region for the entire year of 2022. The retrieval quality is evaluated through comparative analysis with ERA5 reanalysis data and the Visible Infrared Imaging Radiometer Suite (VIIRS) wind product. The resultant vector root mean square errors (RMSEs) are approximately 4.5 m/s for the three lower-height channels and 5.5 m/s for the two upper-height channels. These findings demonstrate a wind retrieval performance comparable to the existing methods, highlighting its potential for augmenting wind availability at lower height levels.

Background: As one of the important components of immunotherapies, mRNA vaccines have displayed promising clinical outcomes in solid tumors. Nonetheless, their efficacy remains unclear in pancreatic adenocarcinoma (PAAD). Given the interaction of pyroptosis with anticancer immunity, our study aims to identify pyroptosis-related antigens for mRNA vaccine development and discern eligible candidates for vaccination. Methods: Utilizing gene expression data from TCGA and ICGC, we integrated RNA-seq data and compared genetic alterations through cBioPortal. Differential gene expressions were integrated using GEPIA. Relationships between immune cell abundance and tumor antigens were analyzed and visualized via TIMER. WGCNA facilitated the clustering of pyroptosis-related genes, identification of hub genes, and pathway enrichment analyses. Pyroptosis landscape was depicted through graph learning-based dimensional reduction. Results: Four overexpressed and mutant pyroptosis-related genes associated with poor prognosis were identified as potential antigens for mRNA vaccines in PAAD, including ANO6, PAK2, CHMP2B, and RAB5A. These genes displayed positive associations with antigen-presenting cells. PAAD patients were stratified into three pyroptosis subtypes. Notably, the PS3 subtype, characterized by a lower mutation count and TMB, exhibited “cold” immunological traits and superior survival compared to other subtypes. The pyroptosis landscape exhibited considerable heterogeneity among individuals. Furthermore, the turquoise module emerged as an independent prognostic indicator and patients with high expressions of hub genes might not be suitable candidates for mRNA vaccination. Conclusions: In PAAD, ANO6, PAK2, CHMP2B, and RAB5A are prospective pyroptosis-related antigens for mRNA vaccine development, which holds potential benefits for patients classified as PS3 and those with diminished hub gene expressions, providing insights into personalized mRNA vaccine strategies.

Abstract Adiponectin, one of the most ubiquitous adipokines found in the blood, plays a major role in glucolipid metabolism and energy metabolism and regulation. In recent years, a growing body of research indicates that adiponectin also plays a significant role in diabetic retinopathy. In the present review, we specifically address the protective effects of adiponectin on the development and progression of diabetic retinopathy through improvement in insulin resistance, alleviation of oxidative stress, limiting of inflammation, and prevention of vascular remodeling, with the aim to explore new potential approaches and targets for the prevention and treatment of diabetic retinopathy.

Background: Studies have shown that vagus nerve-mediated inflammatory reflex could inhibit cytokine production and inflammation in sepsis animals. Objectives: This study aimed to explore the efficacy of transcutaneous auricular vagus nerve stimulation (taVNS) on inflammation and disease severity of sepsis patients. Methods: A randomized, double-blind, sham-controlled pilot study was performed. Twenty sepsis patients were randomly assigned to receive taVNS or sham stimulation for five consecutive days. Stimulation effect was assessed with serum cytokine levels, Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score, and Sequential Organ Failure Assessment (SOFA) score at baseline and on Day 3, Day 5, and Day 7. Results: TaVNS was well tolerated in the study population. Patients receiving taVNS experienced significant reductions in serum TNF-α and IL-1β levels and increases in IL-4 and IL-10 levels. SOFA scores decreased on Day 5 and Day 7 compared with baseline in the taVNS group. However, no changes were found in sham stimulation group. The changes of cytokine from Day 7 to Day 1 were greater with taVNS than sham stimulation. No differences in the APACHE Ⅱ score and SOFA score were observed between the two groups. Conclusions: TaVNS resulted in significantly lower serum pro-inflammatory cytokines and higher serum anti-inflammatory cytokines in sepsis patients.

Deep neural networks (DNNs) are increasingly being used in malware detection and their robustness has been widely discussed. Conventionally, the development of an adversarial example generation scheme for DNNs involves either detailed knowledge concerning the model (i.e., gradient-based methods) or a substantial quantity of data for training a surrogate model. However, under many real-world circumstances, neither of these resources is necessarily available. Our work introduces the concept of the instance-based attack, which is both interpretable and suitable for deployment in a black-box environment. In our approach, a specific binary instance and a malware classifier are utilized as input. By incorporating data augmentation strategies, sufficient data are generated to train a relatively simple and interpretable model. Our methodology involves providing explanations for the detection model, which entails displaying the weights assigned to different components of the specific binary. Through the analysis of these explanations, we discover that the data subsections have a significant impact on the identification of malware. In this study, a novel function preserving transformation algorithm designed specifically for data subsections is introduced. Our approach involves leveraging binary diversification techniques to neutralize the effects of the most heavily-weighted section, thus generating effective adversarial examples. Our algorithm can fool the DNNs in certain cases with a success rate of almost 100%. Instance attack exhibits superior performance compared to the state-of-the-art approach. Notably, our technique can be implemented in a black-box environment and the results can be verified utilizing domain knowledge. The model can help to improve the robustness of malware detectors.

The ground diffusion characteristics of buried oil pipeline after leakage and the laser optical transmission mechanism of surface oil film are the basis of spectral detection technology. Based on the computational fluid dynamics to solve the diffusion equation of multiphase flow in porous media, the leakage law of oil under different soil porosity is analyzed in two dimensions: surface diffusion diameter and oil film thickness. TracePro optical simulation is used to study the absorption and reflection patterns of laser at the oil-gas interface, and validation experiments are carried out based on the tunable diode laser absorption spectroscopy method. The results show that oil is easily accumulated on the ground surface with larger soil porosity and in the depressions of the ground surface. When the oil film thickness is greater than 2 mm, the laser cannot transmit the oil layer and the received light intensity is only provided by the mirror reflection at the oil-gas interface. The mechanism of laser detection of oil leaks is the spectral absorption of volatile alkane gases in the upper layer of the oil film by a laser of a specific wavelength.

Abstract The trip graph, which can model the residents’ taxi demands, consists of vertices used to indicate trips and edges used to indicate the follow-up relationships between trips. A trip $$v_j$$ v j is a tight follow-up trip of another trip $$v_i$$ v i , if a taxi can arrive at the departure location of $$v_j$$ v j within a time threshold $$\delta$$ δ after it finishes $$v_i$$ v i . However, for big cities, there are a large amount of trips every day and it is time consuming to construct a trip graph. In this paper, we propose efficient algorithms to construct trip graphs for big cities. When constructing a trip graph, the most expensive step is to connect the vertices if the tight follow-up relationships exist. To find out the tight follow-up trips fast, we design an index considering both spatial and temporal constraints. To designate appropriate search areas, we propose efficient methods to determine the distance-based search areas and the traffic-based search areas. We conduct experiments on real datasets, i.e., the taxi trajectories of Shanghai in 2015. The experimental results show that our algorithm can construct the trip graph about 40 times faster than the straightforward method. We also demonstrate the usages of the trip graph in green transportation applications, i.e., the minimum fleet analysis and the minimum total “idle” mileage analysis.

Abstract Background Luteinizing hormone (LH) can stimulate mural granulosa cells to produce Amphiregulin (AREG), which can induce the resumption of meiosis in oocytes. Theca cells are present in the outer layer of follicles, providing communication with the pituitary axis through the established vascular system around the follicle. As LH target cells, it is unknown whether theca cells can produce AREG after LH stimulation. Methods Primary cultured human theca cells were treated with LH (with or without the inhibitor of PKA, H89), or agonists of adenylate cyclase (forskolin or db-cAMP). The mRNA and protein levels of AREG were evaluated by RT-qPCR, immunochemistry, immunofluorescence, western blotting, and ELISA. Results Immunohistochemistry of normal ovarian tissue obtained in the early-mid follicle phase showed that AREG expression was absent in both the theca layer and the granulosa cell layer of antral follicles. Double immunofluorescent staining revealed colocalization of AREG and CYP17A1 in human theca cells and colocalization of FSHR and AREG in human granulosa cells isolated from follicular fluid collected during IVF/ICSI after hCG trigger. LH significantly increased the mRNA and protein levels of AREG in human theca cells and the concentration of AREG in the culture medium. Forskolin and db-cAMP, activators of the cAMP/PKA signalling pathway, also significantly increased the mRNA and protein levels of AREG in human theca cells and the concentration of AREG in the culture medium. H89 antagonized the stimulating effect of LH on AREG expression in human theca cells. In addition, the concentration of AREG was lower in polycystic ovarian syndrome (PCOS) follicular fluid than in normal follicular fluid. The mRNA levels of AREG were significantly lower in PCOS granulosa cells and theca cells than in normal granulosa cells and theca cells. Conclusion LH can stimulate the expression of AREG in human theca cells, and the adenylate cyclase/cAMP/PKA cascade may mediate this process. Expression of AREG is decreased in PCOS theca cells compared to normal theca cells, with or without LH stimulation.

The spin Hall effect (SHE), typically emerging in non-magnetic metals with strong spin-orbit couplings, has attracted significant attention for its ability to convert a charge current into a spin current, a key feature in power-efficient spintronic devices. Recently, an enhanced SHE has been detected in the magnetic alloys, where the spin Hall conductivity is strongly modified by the dynamical and thermal spin fluctuations. We find that the spin Hall angle ( ${\theta _{{\text{SH}}}}$ ) in Pt _100− _x Co _x alloys dramatically changes at the Curie temperature, which is positive in the paramagnetic phase akin to Pt, while negative in the ferromagnetic phase. Such intriguing behavior of ${\theta _{{\text{SH}}}}$ stemming from individual and collective fluctuations in the magnetic moments is further substantiated with the full-fledged Monte Carlo simulations. Our work broadens insights into the SHE and highlights the importance of spin fluctuations for the spin-current generation near the ferromagnetic instability point of magnetic alloys.

At present, the new energy industry represented by photovoltaics has become the main force to realize the optimization of China’s energy structure and the goal of “double carbon”; with the absence of land resources, the waterborne bifacial photovoltaic has ushered in a new opportunity. Therefore, in order to address the problem that the maximum power point tracking (MPPT) of photovoltaics (PV) could not take into account, the dynamic economic performance in the control process, an economic model predictive control (EMPC), is proposed in this work to realize the MPPT of the waterborne bifacial PV power generation system. Firstly, the model of the bifacial PV module is constructed by combining the ray-tracing irradiance model and considering the effect of water surface albedo on the irradiance absorbed by the module. Secondly, the EMPC controller is designed based on the state-space model of the system to maximize the power generation as the economic performance index, and to solve the optimal input variables time by time to achieve a rolling optimization with the operational requirements of the system itself as the constraints. Thirdly, the MATLAB/Simulink (R2022a) simulation experimental results verify that the EMPC strategy could be utilized to achieve MPPT of the waterborne bifacial PV power generation system, according to the changes of environment. Finally, it is also demonstrated that the bifacial PV power generation system that employed the EMPC strategy outperformed the traditional MPPT algorithm, with respect to both output power tracking velocity and accuracy, and the power generation could be improved by about 6% to 14.5%, which significantly enhances the system’s dynamic process economics.

Conventional maps of soil parent material (SPM) types obtained by field survey and manual mapping or predictions from other map data have limited accuracy. Digital soil mapping of SPM types necessitates accurate acquisition of SPM distribution information, which is still a challenge in hilly areas. This study developed a high-accuracy method for SPM identification in hilly areas at the county scale. Based on geographic information system technology, seven feature variables were extracted from the geological map, geomorphic map, digital elevation model, and remote sensing image data of Shanggao County, Jiangxi Province, China. Different feature combination schemes were designed to develop SPM identification models based on random forest (RF), support vector machine (SVM), and maximum likelihood classification (MLC) algorithms. The best SPM identification results were obtained from the RF algorithm using the combination of geological type, geomorphic type, elevation, and slope. Confusion matrices were constructed based on a field survey of 586 validation samples, and the results were evaluated in terms of overall accuracy, precision, recall, F1 score, and Kappa coefficient. The overall accuracy and Kappa coefficient of the results from the optimal RF model were 83.11% and 0.79, respectively, which were 26.11% and 0.31 higher than those of the conventional map, respectively. Its precision and recall for various SPM types were greater than 75%. A comprehensive comparison of the accuracy, uncertainty, and plotting performance of the SPM recognition results reveals that the RF algorithm outperforms the SVM algorithm and the MLC algorithm. Geological type was the largest contributor to SPM identification, followed by geomorphic type, elevation, and slope. The importance of different feature variables varied for distinct SPM types. The accuracy of SPM identification was not improved by selecting more feature variables, such as land use type, normalised difference vegetation index, and topographic wetness index. This study demonstrates the feasibility of high-accuracy county-level SPM mapping in hilly areas based on the RF algorithm using geological type, geomorphic type, elevation, and slope as feature variables. As hilly areas have typical topographic features and SPM types, the proposed method of SPM mapping can be useful for application in other similar areas. There are a few limitations in this study with regard to data quality and resolution, feature variable selection, classification algorithm generalisation, and study area representativeness, which may affect the outcomes and need to be solved.

BackgroundWhile adjuvant chemotherapy has been established as standard practice following radical resection of pancreatic ductal adenocarcinoma (PDAC), the role of adjuvant radiation therapy (RT) and which patients may benefit remains unclear.MethodsThis retrospective study included PDAC patients who received pancreatic surgery from April 2012 to December 2019 in Zhongshan Hospital Fudan University. Patients with carcinoma in situ, distant metastasis, and without adjuvant chemotherapy were excluded. Cox proportional hazards modeling of survival were constructed to find potential prognostic factors. Propensity score matching (PSM) and exploratory subgroup analyses were used to create a balanced covariate distribution between groups and to investigate therapeutic effect of radiotherapy in certain subgroups.ResultsA total of 399 patients were finally included, 93 of them receiving adjuvant chemoradiotherapy (C+R+) and 306 of them receiving chemotherapy only. Patients in C+R+ group were more likely to be male patients with T3-4 disease. Lymph node metastases was the only negative prognostic factor associated with overall survival (OS). Additional adjuvant RT was not associated with an OS benefit both before and after PSM. Surprisingly, a trend towards improved OS with RT among patients with either T4, N2 disease or R1 resection becomes significant in patients alive more than 1 year after surgery.ConclusionAdjuvant RT was not associated with an OS benefit across all patients, though did show a possible OS benefit for the subgroup with T4N2 disease or R1 resection at 1 year after surgery.

Change Detection (CD) provides a research basis for environmental monitoring, urban expansion and reconstruction as well as disaster assessment, by identifying the changes of ground objects in different time periods. Traditional CD focused on the Binary Change Detection (BCD), focusing solely on the change and no-change regions. Due to the dynamic progress of earth observation satellite techniques, the spatial resolution of remote sensing images continues to increase, Multi-class Change Detection (MCD) which can reflect more detailed land change has become a hot research direction in the field of CD. Although many scholars have reviewed change detection at present, most of the work still focuses on BCD. This paper focuses on the recent progress in MCD, which includes five major aspects: challenges, datasets, methods, applications and future research direction. Specifically, the background of MCD is first introduced. Then, the major difficulties and challenges in MCD are discussed and delineated. The benchmark datasets for MCD are described, and the available open datasets are listed. Moreover, MCD is further divided into three categories and the specific techniques are described, respectively. Subsequently, the common applications of MCD are described. Finally, the relevant literature in the main journals of remote sensing in the past five years are analyzed and the development and future research direction of MCD are discussed. This review will help researchers understand this field and provide a reference for the subsequent development of MCD. Our collections of MCD benchmark datasets are available at: https://zenodo.org/record/6809804#.YsfvxXZByUk

Landscape and quality attributes are major ecosystem characteristics closely associated with soil conservation service (SCS). However, the intrinsic mechanisms by which these two attributes influence SCS are still unclear. Therefore, this study quantitatively analyzed the landscape pattern, ecological quality, and SCS in the Lianshui River watershed (a typical soil and water loss area of red soil in southern China) and its sub-watersheds in 2019. The boosted regression tree model was used to explore the influence of 15 factors (i.e., landscape and quality attributes) on SCS at the sub-watershed scale. According to the results, compared with the landscape attribute, the quality attribute of the watershed ecosystem could better explain the spatial heterogeneity of SCS across 66 sub-watersheds. The overall degree of influence of five quality factors on SCS reached 57.81%, with the highest being the normalized differential build-up and bare soil index (NDBSI), at 25.11%. Among 10 landscape factors, aggregation had the greatest influence on SCS, at 28.64%. The relationships between key influencing factors and SCS were non-monotonic and non-linear, with threshold effects. For example, NDBSI values of 0.18–0.41 had a positive influence on SCS, while NDBSI values of 0.41–0.65 had a negative influence on SCS. The findings broaden our understanding of the response of SCS to changes in landscape and quality attributes at the sub-watershed scale, and could offer comprehensive support for soil erosion management in the watershed ecosystem.

Economic and social development have worsened the situation of water pollution and even the ecological environment. It is helpful to quantify the water pollution ecological environment losses for decision-makers to formulate reasonable pollution control plans. However, the current quantitative analyses led by economic methods are not comprehensive and systematic. Therefore, based on the emergy theory and method system of eco-economics, this study analyzed the internal energy flow process of the water-polluted ecosystem, discussed the composition of water-polluted ecological environment loss, and proposed a quantitative model of water-polluted ecological environment loss based on the emergy analysis method. It can reasonably quantify the ecological environment loss caused by water pollution and provide a reference for optimizing regional industrial layout, scientifically formulating pollution control planning, and promoting the sustainable development of the ecosystem. Taking Kaifeng City in Henan Province as an example, the rationality of the model is verified. The results show that the annual average total energy value of water pollution ecological environment loss in Kaifeng City is 3.83 × 1020sej, equivalent to 145 million yuan (0.76) of Kaifeng's gross domestic product (GDP) in 2018. HIGHLIGHTS This study analyzed the internal energy flow process of the water-polluted ecosystem.; This study discussed the composition of water-polluted ecological environment loss.; This paper is based on the emergy theory and method system of eco-economics and proposed a quantitative model of water-polluted ecological environment loss based on the emergy analysis method.;

Background and purposeLower-grade gliomas (LGG) exhibit a wide range of metabolic pathway changes, and metabolic reprogramming can be largely seen as a result of oncogenic driving events. Glycolysis, an important pathway of tumor energy source, has been poorly studied in gliomas. The aim of this article is to analyze the relationship between glycolysis and lower-grade glioma development and prognosis in order to explore the heterogeneous relevance of glycolysis in lower-grade gliomas.Methods and resultsOur study searched the TCGA database and identified three glycolytic subtypes with significant prognostic differences by unsupervised clustering analysis of core glycolytic genes, named C1, C2, and C3. By analysis of clinical prognosis, somatic cell variation, and immune infiltration, we found that C3 had the best prognosis with molecular features of IDHmut-codel, followed by C1 with major molecular features of IDHmut-non-codel, G -CIMP high subtype, while C2 had the worst prognosis, mainly exhibiting IDHwt, G-CIMP low and mesenchymal-like subtypes with seven important CNV features, including CDKN2A/B deletion, chr7 gain and chr10 deletion, chr19/20 co-gain, EGFR amplification and PDGFRA/B deletion phenotypes were significantly increased, with the highest level of stemness and significant T-cell depletion features. Finally, to quantify the level of abnormal glycolysis and its impact on prognosis, we developed GlySig to reflect the glycolytic activity of LGG and integrated molecular features to construct nomogram that can be independently assessed to predict prognosis.ConclusionsOur study analyzed the tumor characteristics of different glycolytic states, and our findings explain and describe the heterogeneity of glycolytic metabolism within diffuse LGGs.

Non-infectious chronic diseases, especially inflammatory bowel diseases (IBDs), hypertension, and diabetes mellitus, are characterized by a prolonged and multisystemic course, and their incidence increases annually, usually causing serious economic burden and psychological stress for patients. Therefore, these diseases deserve scientific and consistent disease management. In addition, the lack of a comprehensive “early disease clues tracking—personalized treatment system—follow-up” model in hospitals also exacerbates this dilemma. Based on these facts, we propose an individualized prediction management system for IBDs based on chronic diseases, focusing on the established IBDs-related prediction models and summarizing their advantages and disadvantages. We call on researchers to pay attention to the integration of models with clinical practice and the continuous correction of models to achieve truly individualized medical treatment for chronic diseases, thus providing substantial value for the rapid diagnosis and adequate treatment of chronic diseases such as IBDs, which follow the “relapse-remission” disease model, and realizing long-term drug use and precise disease management for patients. The goal is to achieve a new level of chronic disease management by scientifically improving long-term medication, precise disease management, and individualized medical treatment, effectively prolonging the remission period and reducing morbidity and disability rates.

Sanghuangporus Sanghuang is a fungus species. As a traditional Chinese medicine, it is known for antitumor, antioxidant and anti-inflammatory properties. However, the antiaging effect of S. Sanghuang has not been deeply studied. In this study, the effects of S. Sanghuang extract (SSE) supernatants on the changes of nematode indicators were investigated. The results showed that different concentrations of SSE prolonged the lifespans of nematodes and substantially increased these by 26.41%. In addition, accumulations of lipofuscin were also visibly reduced. The treatment using SSE also played a role in increasing stress resistance, decreasing ROS accumulations and obesity, and enhancing the physique. RT–PCR analysis showed that the SSE treatment upregulated the transcription of daf-16, sir-2.1, daf-2, sod-3 and hsp-16.2, increased the expression of these genes in the insulin/IGF-1 signalling pathway and prolonged the lifespans of nematodes. This study reveals the new role of S. Sanghuang in promoting longevity and inhibiting stress and provides a theoretical basis for the application of S. Sanghuang in anti-ageing treatments.

BackgroundThe time spent with parents is a crucial factor in the growth of children, and children's well-being is an important indicator of their mental health.MethodsTo promote the children's well-being, this study, which is relying on the data from the 2017 China Time Use Survey (CTUS), explores the relationship between parental time and children's well-being and specific influencing factors.ResultsThe more time parents spent with children, the higher their children's well-being will be (coefficient 0.1020, p < 0.01). The life and leisure time parents spent with children promoted children's well-being (coefficient 0.1020, p < 0.01). The life and leisure time the mother spent with children (coefficient 0.1030, p < 0.05) the life and leisure time (coefficient 0.1790, p < 0.05) and the educational interactions time the father spent with children (coefficient 0.3630, p < 0.10) positively affected children's well-being. The influence of the time parents spent with children on children's well-being was heterogeneous based on their children's academic performance.ConclusionsParental accompaniment is an important determinant of children's well-being. Family education, guidance services, and mental health services should be strengthened, and it is necessary to improve the time spent with children and to pay attention to individual differences in children.

The road transportation of explosives is highly concerning due to its substantial impact on social safety. For the safety management of explosive transportation, e.g., transport route planning and emergency rescue, explosion consequence evaluation is of paramount importance. The consequence evaluation of explosion accidents is affected by many factors, especially spatial features, such as the location of transport vehicles, the distribution of buildings, and the presence of individuals around the road, etc. However, there is still a lack of quantification methods for building damage evaluation, human casualty evaluation that considers real-time population density, and efficient interactive damage evaluation methods. In this paper, we formalize three typical scenarios of damage evaluation for explosive road transportation accidents, i.e., explosion point-based, road segment-based, and route-based damage evaluation. For each scenario, we propose a Height-aware Hierarchical Building Damage (HHBD) model and a Shelter-aware Human Casualty (SHC) model for building damage evaluation and human casualty evaluation, respectively. We also develop a GIS-based interactive visualization platform that integrates multi-source geospatial data and that enables efficient geospatial computation. In addition, a case study of liquefied natural gas (LNG) transportation in Wuhan is demonstrated in order to verify the effectiveness and efficiency of the proposed system. The research results can support the decision-making process of explosive transportation safety warnings and emergency rescue.

The O-antigen is one of the outermost surface components of Gram-negative bacteria. Its large structural variation provides the molecular basis for bacterial serological diversity. Here, we established the structure of the O-antigen from an Escherichia coli strain, SD2019180, which appeared to be completely different from the known E. coli serogroups. The O-antigen tetrasaccharide biological repeating unit was identified as → 2)-[β-d-GlcpA-(1 → 4)]-[α-d-Galp-(1 → 3)]-α-l-Fucp-(1 → 3)-α-d-GlcpNAc-(1 →. Furthermore, we analyzed the O-antigen gene cluster of SD2019180 and confirmed its role in O-antigen synthesis by using deletion and complementation experiments. Our findings indicate that SD2019180 is a novel serogroup of Escherichia coli.

Prolonged exposure to high concentrations of suspended particulate matter (SPM), especially aerodynamic fine particulate matter that is ≤2.5 μm in diameter (PM2.5), can cause serious harm to human health and life via the induction of respiratory diseases and lung cancer. Therefore, accurate prediction of PM2.5 concentrations is important for human health management and governmental environmental management decisions. However, the time-series processing of PM2.5 concentration based only on a single region and a special time period is less explanatory, and thus, the spatial-temporal applicability of the model is more restricted. To address this problem, this paper constructs a PM2.5 concentration prediction optimization model based on Convolutional Neural Networks-Long Short-Term Memory (CNN-LSTM). Hourly data of atmospheric pollutants, meteorological parameters, and Precipitable Water Vapor (PWV) of 10 cities in the Beijing-Tianjin-Hebei metropolitan area during the period of 1–30 September 2021/2022 were used as the training set, and the PM2.5 data of 1–7 October 2021/2022 were used for validation. The experimental results show that the CNN-LSTM model optimizes the average root mean square error (RMSE) by 25.52% and 14.30%, the average mean absolute error (MAE) by 26.23% and 15.01%, and the average mean absolute percentage error (MAPE) by 35.64% and 16.98%, as compared to the widely used Back Propagation Neural Network (BPNN) and Long Short-Term Memory (LSTM) models. In summary, the CNN-LSTM model is superior in terms of applicability and has the highest prediction accuracy in the Beijing-Tianjin-Hebei metropolitan area. The results of this study can provide a reference for the relevant departments in the Beijing-Tianjin-Hebei metropolitan area to predict PM2.5 concentration and its trend in specific time periods.

Abstract Solute carrier family 25 (SLC25) encodes transport proteins at the inner mitochondrial membrane and functions as carriers for metabolites. Although SLC25 genetic variants correlate with human metabolic diseases, their roles in colon cancer remain unknown. Cases of colon cancer were retrieved from The Cancer Genome Atlas, and the transcriptionally differentially expressed members (DEMs) of SLC25 were identified. DNA level alterations, clinicopathological characteristics, and clinical survival were also investigated. A risk score model based on the DEMs was constructed to further evaluate their prognostic values in a clinical setting. The results were preliminarily validated using bioinformatic analysis of datasets from the Gene Expression Omnibus, immunohistochemical evaluations in clinical specimens, and functional experiments in colon cancer-derived cell lines. Thirty-seven DEMs were identified among 53 members of SLC25. Eight of 37 DEMs were introduced into a risk score model using integrated LASSO regression and multivariate Cox regression. Validated by GSE395282 and GSE175356, DEMs with high-risk scores were associated with the phenotypes of increasing tumor immune infiltration and decreasing glycolysis and apoptosis contents. SLC25A5 was downregulated in cancer, and its upregulation was related to better overall survival in patients from public datasets and in clinical cases. High SLC25A5 expression was an independent prognostic factor for 79 patients after surgical treatment. A negative correlation between CD8 and SLC25A5 was determined in specimens from 106 patients with advanced colon cancer. SLC25A5 attenuated cell proliferation, upregulated the expression of programmed cell death-related signatures, and exerted its biological function by inhibiting the MAPK signaling pathway. Our study reveals that mitochondrial SLC25 has prognostic value in patients with colon cancer. The bioinformatic analyses by following verification in situ and in vitro provide direction for further functional and mechanistic studies on the identified member of SLC25.

BackgroundLiposarcomas (LPS) are mesenchymal malignancies with four principal subtypes presenting distinct molecular and clinical features. Pleomorphic liposarcoma (PLPS) is one of the rarest and most aggressive subtypes of LPS. Surgical resection is currently a preferred curative approach for localized PLPS. However, the prognosis of unresectable PLPS is extremely poor, and there is no standard treatment.Case presentationA 59-year-old Chinese woman was diagnosed with unresectable PLPS. The case was discussed and managed by specialists from a multidisciplinary team at Fudan Zhongshan Hospital. Preoperative radiotherapy (RT) of intensity-modulated radiation therapy (IMRT) at 50 Gy/25 Fx concurrently with the angiogenesis inhibitor anlotinib (8 mg, days 1–14, every 3 weeks) was prescribed to the patient. The dosage of anlotinib was increased to 10 mg after RT. After 6 months of treatment, the tumor had significantly shrunk and was successfully resected. Examination of the surgical specimens showed a pathological complete response (pCR). Until the latest follow-up (April 2022), no recurrence was observed, and disease-free survival has exceeded 14 months.ConclusionThis case sheds light on the probability that perioperative RT combined with an angiogenesis inhibitor can be effectively used in PLPS, which is resistant to chemotherapy and usually considered to have a poor prognosis. Further studies with randomized controlled clinical trials will improve our knowledge of this preoperative treatment strategy.

BackgroundDepression in chronic disease patients was an important public health problem. However, limited work has been done on how to alleviate the depression of chronic disease patients. This paper attempted to explore the alleviating effect of health insurance and health service quality.MethodsA total of 11,500 middle-aged and elderly people were drawn from four waves (2011, 2013, 2015, and 2018) of the China Health and Retirement Longitudinal Study (CHARLS). We analyzed the effect of chronic disease on depression in middle-aged and elderly people in China, and explored the mechanism of action from health insurance and health service quality.ResultsAfter adjusting for sociodemographic factors, any chronic disease (coefficient 1.471, p < 0.01) and multiple chronic diseases (coefficient 1.733, p < 0.01) could significantly increase the depression score. Any chronic disease increased the depression score (165.3 and 147.4% in non-health insurance group and health insurance group, respectively), the multiple chronic diseases increased the depression score (190.6 and 173.5% in non-health insurance group and health insurance group, respectively). Any chronic disease increased the depression score (161.3 and 139.5% in lower health service quality group and higher health service quality group, respectively), the multiple chronic diseases increased the depression score (228.4 and 162.9% in lower health service quality group and higher health service quality group, respectively). And similar results were obtained after using depression status instead of depression score.ConclusionsChronic disease and multiple chronic diseases were important determinants of depression in middle-aged and elderly people. Health insurance and health service quality were the key factors in relieving the depression of chronic disease patients. Several strategies were urgently needed: paying attention to the mental health of chronic disease patients, increasing the participation rate of health insurance, further improving the quality of health service, and alleviating the psychological harm caused by chronic disease.

At present, malignant tumors are an urgent global threat to human health. Conversion of cancer cells to normal-like or normal cells will open new therapeutic avenues for eradicating cancer. It has been reported that compounds extracted from grains display biological activities, such as antioxidant, antiviral and antitumor activities. In this study, we identified clear changes in a liver tumor cell line (HepG2) after stimulation with zymolytic grain extract (ZGE) supernatants. The expression levels of hepatocyte nuclear factor 1A (HNF1A), hepatocyte nuclear factor 4A (HNF4A) and forkhead box protein A3 (FOXA3) were significantly increased. Eukaryotic transcriptome analyses revealed that trends in the transcriptional changes for genes were similar in HepG2 cells stimulated with ZGE (zHeps) and the normal hepatocyte cell line L02. Changes in the expression levels of genes involved in drug transport, metabolism and the malignant characteristics of cancer cells in nude mice further indicated that ZGE regulated the expression of HNF1A, HNF4A and FOXA3, which altered the expression of a series of hepatocyte-specific genes. It was also confirmed that zHeps acquired some of the characteristics of hepatocyte-like cells. Our results not only provide new ideas for the treatment of liver tumors but also lay a solid foundation for the application of combination therapy.

BackgroundMetabolic reprogramming is a feature of cancer. However, colon cancer subtypes based on the glycolysis‒cholesterol synthesis axis have not been identified, and little is known about connections between metabolic features and the tumor microenvironment.MethodsData for 430 colon cancer cases were extracted from The Cancer Genome Atlas, including transcriptome data, clinical information, and survival outcomes. Glycolysis and cholesterol synthesis-related gene sets were obtained from the Molecular Signatures Database for a gene set variation analysis. The relationship between the genomic landscape and immune landscape were investigated among four metabolic subtypes. Hub genes were determined. The clinical significance of candidate hub gene was evaluated in 264 clinical samples and potential functions were validated in vitro and in vivo.ResultsColon cancer cases were clustered into four metabolic subtypes: quiescent, glycolytic, cholesterogenic, and mixed. The metabolic subtypes differed with respect to the immune score, stromal score, and estimate score using the ESTIMATE algorithm, cancer-immunity cycle, immunomodulator signatures, and signatures of immunotherapy responses. Patients in the cholesterogenic group had better survival outcomes than those for other subtypes, especially glycolytic. The glycolytic subtype was related to unfavorable clinical characteristics, including high mutation rates in TTN, APC, and TP53, high mutation burden, vascular invasion, right colon cancer, and low-frequency microsatellite instability. GGH, CACNG4, MME, SLC30A2, CKMT2, SYN3, and SLC22A31 were identified as differentially expressed both in glycolytic-cholesterogenic subgroups as well as between colon cancers and healthy samples, and were involved in glycolysis‒cholesterol synthesis. GGH was upregulated in colon cancer; its high expression was correlated with CD4+ T cell infiltration and longer overall survival and it was identified as a favorable independent prognostic factor. The overexpression of GGH in colon cancer-derived cell lines (SW48 and SW480) inhibited PKM, GLUT1, and LDHA expression and decreased the extracellular lactate content and intracellular ATP level. The opposite effects were obtained by GGH silencing. The phenotype associated with GGH was also validated in a xenograft nude mouse model.ConclusionsOur results provide insight into the connection between metabolism and the tumor microenvironment in colon cancer and provides preliminary evidence for the role of GGH, providing a basis for subsequent studies.

Scientific identification of the ecological and economic value of water and soil resources and quantitative evaluation are the basis for scientifically guiding the rational allocation of water and soil resources. Various values in previous studies were difficult to measure and compare uniformly, owing to their different manifestations. Based on ecological economics, the energy conversion mechanism of the interaction process of water and soil resources was described, and the ecological and economic values of the water and soil resources generated in the accompanying process were identified in this study. Then, for industrial and mining, residential, and public service land subsystems, the energy analysis method was used to obtain the unified calculation of the ecological and economic value of the water and soil resources. Using Luoyang City, Henan Province, China as the research area, the ecological and economic value of water and soil resources for residential and industrial land from 2015 to 2019 was calculated and according to the results, they were ranked as industrial and mining land > residential land > public service land. This study provides a unified quantitative analysis method for comprehensive decision-making for the rational utilisation of water and soil resources in specific counties, cities, and provinces.

Summary: Background: There are currently limited systemic treatment options for patients with advanced neuroendocrine tumours (NETS) and the efficacy of existing treatments is sub-optimal. We evaluated the efficacy and safety of Tegafur/gimeracil/oteracil/potassium capsules (S-1)/Temozolomide with or without thalidomide for the treatment of NETS (STEM trial). Methods: A randomised, controlled, open-label, phase 2 trial conducted at eight hospitals in China. Adults (≥18 years) with unresectable/metastatic, pancreatic or non-pancreatic NETS, with an Eastern Cooperative Oncology Group (ECOG) PS of 0–1, and progression on ≤2 previous therapies were randomised (1:1, using hierarchical block randomization with block length 4, stratified by pancreatic/non-pancreatic disease to receive S-1 40–60 mg orally twice daily on days 1–14 plus temozolomide 200 mg orally daily on days 10–14 in a 21-day cycle OR S-1 and temozolomide plus thalidomide orally nightly (100 mg on days 1–7, 200 mg on days 8–14, and 300 mg from day 15), until disease progression, death, intolerable toxicity, withdrawal of informed consent or at the investigator's discretion. The primary endpoint was objective response rate (ORR) by RECIST 1.1 in an intention-to-treat population. Safety was assessed in all patients who received treatment. The study was registered at ClinicalTrials.gov: NCT03204019 (pancreatic group) and NCT03204032 (non-pancreatic group). Findings: Between March 23, 2017 and November 16, 2020, 187 patients were screened and 140 were randomly assigned to S-1/temozolomide plus thalidomide (n = 69) or S-1/temozolomide (n =71). After a median follow-up of 12·1 months (IQR: 8·4–16·6), the ORR was comparable in the S-1/temozolomide plus thalidomide and S-1/temozolomide groups 26·1% [95% CI 17·2–37·5] versus 25·4% [95% CI 16·7–36·6]; odds ratio: 1·03 [95% CI 0·48–2·22]; P = 0·9381). In the S-1/temozolomide plus thalidomide group, the most common grade 3–4 treatment-related adverse event was fatigue (2/68, 3%), and in the control group were thrombocytopenia and diarrhea (both 1/71, 2%). There were no treatment-related deaths in either group. Interpretation: S-1/temozolomide with or without thalidomide leads to a comparable treatment response in patients with advanced/metastatic NETS. Funding: This work was supported by CAMS Innovation Fund for Medical Sciences (CIFMS,2021-I2M-1-066, 2017-I2M-4-002, 2021-I2M-1-019, 2017-I2M-1-001), the National Natural Science Foundation of China (81972311, 82141127, 31970794,), the State Key Project on Infection Diseases of China (2017ZX10201021-007-003), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310026), Sanming Project of Medicine in Shenzhen (SZSM202011010), and the State Key Laboratory Special fund from the Ministry of Science (2060204).

OBJECTIVE: This study aimed to assess the effectiveness, feasibility, and security of the Perclose ProGlide device that was used to remove the femoral venous cannulas for the transcatheter closure of atrial septal defect (ASD). METHODS: A total of 145 cases were analyzed retrospectively, who performed transcatheter closure of ASD in our center from March 2019 to March 2021. Based on whether the Perclose ProGlide device was placed or not in the femoral vein, 48 patients were assigned to the Perclose group and 97 ones to the non-Perclose group. The data of general characteristics, femoral venous cannulas, and related puncture complications were compared between the two groups. RESULTS: The data of general characteristics or femoral venous cannulas were not significantly different between the two groups, but the procedure duration of removing venous cannulas was shorter in the Perclose group (0.5 min [0.35, 0.70] vs. 5 min [3.6, 7.4], P < 0.001). The puncture procedure-related blood lose was not significantly different between the two groups (Hemoglobin reduction value: 0.10 [−0.47, 0.30] g/dL vs. 0.10 [−0.50, 0.30] g/dL, P = 0.905). In addition, other complications caused by the removal of venous cannulas, length of stay in the ward, puncture infection, reintervention, and so on were not significantly different between the groups. CONCLUSIONS: The Perclose ProGlide device could simplify the removal of femoral venous cannulas for ASD transcatheter closure by decreasing procedure duration and time in bed. The efficiency, feasibility, and safety of Perclose ProGlide devices, which were used to remove venous cannulas, are good enough for their clinical application.

An 81-year-old male presented to our emergency department for abdominal pain and distension. The patient had previously undergone endovascular aortic repair (EVAR) procedure 9 years ago for infrarenal abdominal aortic aneurysm with regular follow-up in postoperative. Three years ago, computed tomography angiography (CT) revealed Type Ib endoleak with right common iliac artery expansion and Type II endoleak from inferior mesenteric artery (IMA). Then, the patient was successfully treated by relining the iliac stent-graft to cover the common iliac expansion and coil embolism to occlude IMA through the Riolan's arch using endovascular technique. Recently, the following up CTA displayed a new Type IIIa endoleak, which the left iliac limb was disconnected with the main body graft. The patient was ultimately successful to treat by implanting stent-grafts using endovascular therapy. This case emphasizes the necessity of follow-up examination for lifelong stent-grafts surveillance. We debated the current late-related complication of EVAR and stent-graft migration treatment choices.

Abstract The application of ionic liquids in perovskite has attracted wide-spread attention for its astounding performance improvement of perovskite solar cells (PSCs). However, the detailed mechanisms behind the improvement remain mysterious. Herein, a series of imidazolium-based ionic liquids (IILs) with different cations and anions is systematically investigated to elucidate the passivation mechanism of IILs on inorganic perovskites. It is found that IILs display the following advantages: (1) They form ionic bonds with Cs+ and Pb2+ cations on the surface and at the grain boundaries of perovskite films, which could effectively heal/reduce the Cs+/I− vacancies and Pb-related defects; (2) They serve as a bridge between the perovskite and the hole-transport-layer for effective charge extraction and transfer; and (3) They increase the hydrophobicity of the perovskite surface to further improve the stability of the CsPbI2Br PSCs. The combination of the above effects results in suppressed non-radiative recombination loss in CsPbI2Br PSCs and an impressive power conversion efficiency of 17.02%. Additionally, the CsPbI2Br PSCs with IILs surface modification exhibited improved ambient and light illumination stability. Our results provide guidance for an in-depth understanding of the passivation mechanism of IILs in inorganic perovskites.

Ten Candida species strains were isolated from the first known fatal case of rhinofacial and rhino–orbital–cerebral candidiasis. Among them, five strains of Candida parapsilosis complex were isolated during the early stage of hospitalization, while five strains of Candida tropicalis were isolated in the later stages of the disease. Using whole-genome sequencing, we distinguished the five strains of C. parapsilosis complex as four Candida metapsilosis strains and one Candida parapsilosis strain. Antifungal susceptibility testing showed that the five strains of C. parapsilosis complex were susceptible to all antifungal drugs, while five C. tropicalis strains had high minimum inhibitory concentrations to azoles, whereas antifungal-drug resistance gene analysis revealed the causes of azole resistance in such strains. For the first time, we analyzed the microevolutionary characteristics of pathogenic fungi in human hosts and inferred the infection time and parallel evolution of C. tropicalis strains. Molecular clock analysis revealed that azole-resistant C. tropicalis infection occurred during the first round of therapy, followed by divergence via parallel evolution in vivo. The presence/absence variations indicated a potential decrease in the virulence of genomes in strains isolated following antifungal drug treatment, despite the absence of observed clinical improvement in the conditions of the patient. These results suggest that genomic analysis could serve as an auxiliary tool in guiding clinical diagnosis and treatment.

Under the influence of global climate change and urbanization processes, the number of available water resources (AWRs) in basins has become significantly more uncertain, which has restricted the sustainable development of basins. Therefore, it is important for us to understand the relationship between land use (LU) patterns and climate change on AWRs in a basin for sustainable development. To this end, the vector autoregressive (VAR) method was adopted to construct a quantitative model for AWRs in the basin in this study. Taking the Yiluo River Basin (YRB) as an example, the dynamic relationship between the five elements of agricultural land (AD), woodland (WD), grassland (GD), construction land (CD), and annual precipitation (PREP) and AWRs in the basin was studied. The results show the following: (1) The constructed VAR model was stable, indicating that the use of the proposed VAR model to characterize the degree of the effect of LU pattern and PREP on AWRs in the YRB was reasonable and effective. (2) AWRs in the YRB showed a downward trend, and their responses to the change in LU and PREP were delayed. The changes in the AWRs in the YRB tended to occur the year after changes to the LU pattern and PREP occurred. (3) In the long run, the degree of the contribution of each influencing factor to changes to AWRs was 23.76% (AD), 6.09% (PREP), 4.56% (CD), 4.40% (WD), and 4.34% (GD), which meant that the impact of the LU pattern was more than 90%. This study provides new ideas for similar research, water resource allocation, and LU planning in other river basins from a macroscopic perspective.

Phosphatidylethanolamine-binding proteins (PEBP) family plays important roles in regulating plant flowering time and morphogenesis. However, geneme-wide identification and functional analysis of PEBP genes in the rigorous short-day plant Perilla frutescens (PfPEBP) have not been studied. In this study, 10 PfPEBP were identified and divided into three subfamilies based on their phylogenetic relationships: FT-like, TFL1-like and MFT-like. Gene structure analysis showed that all PfPEBP genes contain 4 exons and 3 introns. Motifs DPDxP and GIHR essential for anion-binding activity are highly conserved in PfPEBP. A large number of light-responsive elements were detected in promoter regions of PfPEBP. Gene expression of PfFT1 exhibited a diurnal rhythm. It was highly expressed in leaves under the short-day photoperiod, but higher in flowers and seeds under the long-day photoperiod. Overexpression of PfFT1 in Arabidopsis thaliana not only promoted early flowering of Col-0 or Ler, but also rescued the late flowering phenotype of ft-1 mutant. We concluded that PfFT1 promotes early flowering by regulating the expression of flowering-related genes AtAP1, AtLFY, AtFUL and AtSOC1. In conclusion, our results provided valuable information for elucidating the functions of PfPEBP in P. frutescens and shed light on the promoting effect of PfFT1 on flowering.

Understanding the spatial associations of ecosystem services (ESs) driven by socio-ecological factors is essential for regional ecosystem management and effective resource allocation. Yet previous studies of mechanisms driving ESs have focused mainly on the supply or demand for ESs, rarely consider their threshold effects and supply–demand ratios. Taking the upper reach of Ganjiang watershed (URGW) in southern China as an example, the supply, demand, and supply–demand ratio of ESs (ESDRs) were quantified for grain production (GP), water yield (WY), soil retention (SR), carbon sequestration (CS), and green space recreation (GR). Correlation analysis and random forest models were used to investigate the spatial associations of five ESDRs and the relative importance and marginal effects of 9 socio-ecological factors upon them. At the watershed scale, only SR incurred a supply–demand deficit (ESDR 0). When considered across 188 sub-watersheds, all ESs had different supply–demand deficits. The trade-offs in ESDRs mainly derived from two ESs (GP, SR) and the other three ESs (WY, CS, GR). The supply–demand ratio of SR was mainly determined by topography (i.e., slope gradient), while land use (i.e., proportions of cropland and forest land areas) played a decisive role in the supply–demand ratios of GP and WY. The supply–demand ratios of GR and CS showed similar spatial distribution, driven mainly by the normalized difference vegetation index and human population density. Specific socio-ecological factors (e.g., slope gradient and proportion of forest land area) had significant threshold effects on the ESDRs. Accordingly, research on the mechanisms driving ESs should consider ESs’ supply and demand in tandem, and pay particular attention to the potential threshold effects of socio-ecological factors.