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Cavitation occurs in the micro-clearance of liquid-hydrogen-lubricated bearings owing to the pressure drop caused by high-speed shearing. The pressure undulation caused by cavitation collapse results in bearing surface erosion and significantly affects the bearing performance. In this study, a modified Z-G-B cavitation model was used to study the crushing process of a single liquid hydrogen bubble in a shear micro-clearance. Fast Fourier transform (FFT) and wavelet transform (WT) were applied to study the frequency characteristics of the pressure, mass transfer rate, and vapor mass fraction during bubble rupture in shearing micro-clearance. To obtain a deeper insight into the details of the effect of the shear micro-clearance structure on bubble collapse, the relationship between the flow field energy, attenuation rate, and frequency was investigated. The proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) methods were used to analyze the energy of each order mode of the flow field. The analysis results of the bubble vibration intensity with respect to time and frequency provide a theoretical basis for the optimization of the bearing structure.

Abstract Despite the well-established significance of transcription factors (TFs) in pathogenesis, their utilization as pharmacological targets has been limited by the inherent challenges in modulating their protein interactions. The lack of defined small-molecule binding pockets and the nuclear localization of TFs do not favor the use of traditional tools. Aptamers possess large molecular weights, expansive blocking surfaces and efficient cellular internalization, making them compelling tools for modulating TF interactions. Here, we report a structure-guided design strategy called Blocker-SELEX to develop inhibitory aptamers (iAptamers) that selectively block TF interactions. Our approach leads to the discovery of iAptamers that cooperatively disrupt SCAF4/SCAF8-RNAP2 interactions, dysregulating RNAP2-dependent gene expression, which impairs cell proliferation. This approach is further applied to develop iAptamers blocking WDR5-MYC interactions. Overall, our study highlights the potential of iAptamers in disrupting pathogenic TF interactions, implicating their potential utility in studying the biological functions of TF interactions and in nucleic acids drug discovery.

Abstract The dynamic load distribution within in-service axlebox bearings of high-speed trains is crucial for the fatigue reliability assessment and forward design of axlebox bearings. This paper presents an in situ measurement of the dynamic load distribution in the four rows of two axlebox bearings on a bogie wheelset of a high-speed train under polygonal wheel–rail excitation. The measurement employed an improved strain-based method to measure the dynamic radial load distribution of roller bearings. The four rows of two axlebox bearings on a wheelset exhibited different ranges of loaded zones and different means of distributed loads. Besides, the mean value and standard deviation of measured roller–raceway contact loads showed non-monotonic variations with the frequency of wheel–rail excitation. The fatigue life of the four bearing rows under polygonal wheel–rail excitation was quantitatively predicted by compiling the measured roller–raceway contact load spectra of the most loaded position and considering the load spectra as input.

Abstract Machine Learning models trained from real-world data have demonstrated promise in predicting suicide attempts in adolescents. However, their transportability, namely the performance of a model trained on one dataset and applied to different data, is largely unknown, hindering the clinical adoption of these models. Here we developed different machine learning-based suicide prediction models based on real-world data collected in different contexts (inpatient, outpatient, and all encounters) with varying purposes (administrative claims and electronic health records), and compared their cross-data performance. The three datasets used were the All-Payer Claims Database in Connecticut, the Hospital Inpatient Discharge Database in Connecticut, and the Electronic Health Records data provided by the Kansas Health Information Network. We included 285,320 patients among whom we identified 3389 (1.2%) suicide attempters and 66% of the suicide attempters were female. Different machine learning models were evaluated on source datasets where models were trained and then applied to target datasets. More complex models, particularly deep long short-term memory neural network models, did not outperform simpler regularized logistic regression models in terms of both local and transported performance. Transported models exhibited varying performance, showing drops or even improvements compared to their source performance. While they can achieve satisfactory transported performance, they are usually upper-bounded by the best performance of locally developed models, and they can identify additional new cases in target data. Our study uncovers complex transportability patterns and could facilitate the development of suicide prediction models with better performance and generalizability.

Abstract Background SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors. Methods In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests. Results We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7–0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). Conclusions This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.

Abstract Parkinson’s disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals’ phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

Abstract Leukemia stem cells (LSCs) are recognized as the root cause of leukemia initiation, relapse, and drug resistance. Lipid species are highly abundant and essential component of human cells, which often changed in tumor microenvironment. LSCs remodel lipid metabolism to sustain the stemness. However, there is no useful lipid related biomarker has been approved for clinical practice in AML prediction and treatment. Here, we constructed and verified fatty acid metabolism-related risk score (LFMRS) model based on TCGA database via a series of bioinformatics analysis, univariate COX regression analysis, and multivariate COX regression analysis, and found that the LFMRS model could be an independent risk factor and predict the survival time of AML patients combined with age. Moreover, we revealed that Galectin-1 (LGALS1, the key gene of LFMRS) was highly expressed in LSCs and associated with poor prognosis of AML patients, and LGALS1 repression inhibited AML cell and LSC proliferation, enhanced cell apoptosis, and decreased lipid accumulation in vitro. LGALS1 repression curbed AML progression, lipid accumulation, and CD8+ T and NK cell counts in vivo. Our study sheds light on the roles of LFMRS (especially LGALS1) model in AML, and provides information that may help clinicians improve patient prognosis and develop personalized treatment regimens for AML.

Abstract Background Guanosine is a purine nucleoside that is widely used as a raw material for food additives and pharmaceutical products. Microbial fermentation is the main production method of guanosine. However, the guanosine-producing strains possess multiple metabolic pathway interactions and complex regulatory mechanisms. The lack of strains with efficiently producing-guanosine greatly limited industrial application. Results We attempted to efficiently produce guanosine in Escherichia coli using systematic metabolic engineering. First, we overexpressed the purine synthesis pathway from Bacillus subtilis and the prs gene, and deleted three genes involved in guanosine catabolism to increase guanosine accumulation. Subsequently, we attenuated purA expression and eliminated feedback and transcription dual inhibition. Then, we modified the metabolic flux of the glycolysis and Entner-Doudoroff (ED) pathways and performed redox cofactors rebalancing. Finally, transporter engineering and enhancing the guanosine synthesis pathway further increased the guanosine titre to 134.9 mg/L. After 72 h of the fed-batch fermentation in shake-flask, the guanosine titre achieved 289.8 mg/L. Conclusions Our results reveal that the guanosine synthesis pathway was successfully optimized by combinatorial metabolic engineering, which could be applicable to the efficient synthesis of other nucleoside products.

Abstract Background Renal fibrosis is a progressive process associated with chronic kidney disease (CKD), contributing to impaired kidney function. Active constituents in traditional Chinese herbs, such as emodin (EMO) and asiatic acid (AA), exhibit potent anti-fibrotic properties. However, the oral administration of EMO and AA results in low bioavailability and limited kidney accumulation. Additionally, while oral probiotics have been accepted for CKD treatment through gut microbiota modulation, a significant challenge lies in ensuring their viability upon administration. Therefore, our study aims to address both renal fibrosis and gut microbiota imbalance through innovative co-delivery strategies. Results In this study, we developed yeast cell wall particles (YCWPs) encapsulating EMO and AA self-assembled nanoparticles (NPYs) and embedded them, along with Lactobacillus casei Zhang, in chitosan/sodium alginate (CS/SA) microgels. The developed microgels showed significant controlled release properties for the loaded NPYs and prolonged the retention time of Lactobacillus casei Zhang (L. casei Zhang) in the intestine. Furthermore, in vivo biodistribution showed that the microgel-carried NPYs significantly accumulated in the obstructed kidneys of rats, thereby substantially increasing the accumulation of EMO and AA in the impaired kidneys. More importantly, through hitchhiking delivery based on yeast cell wall and positive modulation of gut microbiota, our microgels with this synergistic strategy of therapeutic and modulatory interactions could regulate the TGF-β/Smad signaling pathway and thus effectively ameliorate renal fibrosis in unilateral ureteral obstruction (UUO) rats. Conclusion In conclusion, our work provides a new strategy for the treatment of renal fibrosis based on hitchhiking co-delivery of nanodrugs and probiotics to achieve synergistic effects of disease treatment and targeted gut flora modulation. Graphical Abstract

PurposeRhubarb (Rheum palmatum L.) and astragalus (Radix astragali) find widespread used in clinical formulations for treating chronic kidney disease (CKD). Notably, the key active components, total rhubarb anthraquinone (TRA) and total astragalus saponin (TAS), exhibit superiority over rhubarb and astragalus in terms of their clear composition, stability, quality control, small dosage, and efficacy for disease treatment. Additionally, astragalus polysaccharides (APS) significantly contribute to the treatment of renal fibrosis by modulating the gut microbiota. However, due to differences in the biopharmaceutical properties of these components, achieving synergistic effects remains challenging. This study aims to develop combined pellets (CPs) and evaluate the potential effect on unilateral ureteral obstruction (UUO)-induced renal fibrosis.MethodsThe CPs pellets were obtained by combining TRA/TAS-loaded SNEDDS pellets and APS-loaded pellets, prepared using the fluidized bed coating process. The prepared pellets underwent evaluation for morphology, bulk density, hardness, and flowing property. Moreover, the in vitro release of the payloads was evaluated with the CHP Type I method. Furthermore, the unilateral ureteral obstruction (UUO) model was utilized to investigate the potential effects of CPs pellets on renal fibrosis and their contribution to gut microbiota modulation.ResultsThe ex-vivo study demonstrated that the developed CPs pellets not only improved the dissolution of TRA and TAS but also delivered TRA/TAS and APS spatiotemporally to the appropriate site along the gastrointestinal tract. In an animal model of renal fibrosis (UUO rats), oral administration of the CPs ameliorated kidney histological pathology, reduced collagen deposition, and decreased the levels of inflammatory cytokines. The CPs also restored the disturbed gut microbiota induced by UUO surgery and protected the intestinal barrier.ConclusionThe developed CPs pellets represent a promising strategy for efficiently delivering active components in traditional Chinese medicine formulas, offering an effective approach for treating CKD.

The radial load distribution integral given by Harris integral method always plays a significant role in calculating the radial load distribution of radial bearings. The error of Harris integral method for calculating the radial load distribution is found caused by the inaccurate values of the radial load distribution integral given by Harris. The radial load distribution integral is corrected in three loading stages using a discrete method. The corrected radial load distribution integral is capable of calculating the load distribution of a bearing with a small load zone caused by a light external load or a great radial clearance. The corrected radial load distribution integral shows different phases varying with the number of rolling elements participating in the radial load transfer. Some specific numerical examples show the higher accuracy and superiority of the corrected radial load distribution integral.

Bone diseases such as osteoporosis and osteoarthritis have become important human health problems, requiring a deeper understanding of the pathogenesis of related diseases and the development of more effective treatments. Bone organoids are three-dimensional tissue masses that are useful for drug screening, regenerative medicine, and disease modeling because they may mimic the structure and physiological activities of organs. Here, we describe various potential methods for culturing bone-related organoids from different stem cells, detailing the construction processes and highlighting the main applications of these bone organoid models. The application of bone organoids in different skeletal diseases is highlighted, and current and promising bone organoids for drug screening and regenerative medicine as well as the latest technological advancements in bone organoids are discussed, while the future development of bone organoids is discussed. Looking forward, it will provide a reference for constructing bone organoids with more complete structures and functions and applying them to biomedical research.

Working fluid selection for closed-cycle turbo-refrigerators (CCTRs) for deep freezing, as a more fundamental topic, has not yet received careful consideration, leading to limitations in attempts to optimizing CCTR design in the early stages of cycle design. This paper proposed the working fluid selection criteria that to select the one leading to the lowest system weight and volume without compromising the system energy efficiency. Design criteria, such as specific speed and Reynolds number, and their dependence on fluid properties are introduced to ensure uncompromising-efficiency design of turbomachinery. Normalized heat transfer area of recuperator correlated with fluid properties is derived as the evaluation criterion for system weight and volume. Applying the proposed criteria, the comparison between potential pure gases shows the normalized heat transfer areas required for nitrogen, neon, and argon are 1, 1.54 and 2.18, respectively. Therefore, nitrogen among all pure gases has the greatest potential to reduce system weight and volume. The comparison among potential binary mixtures highlights the methane-nitrogen mixture with the molar mass of 24.1 g/mol which reduces the required heat transfer area by approximately 20 % compared to pure-nitrogen-based system and may reduce it by nearly up to 30 % for systems with larger cooling capacity levels.

Hematopoiesis represents a meticulously regulated and dynamic biological process. Genetic aberrations affecting blood cells, induced by various factors, frequently give rise to hematological tumors. These instances are often accompanied by a multitude of abnormal post-transcriptional regulatory events, including RNA alternative splicing, RNA localization, RNA degradation, and storage. Notably, post-transcriptional regulation plays a pivotal role in preserving hematopoietic homeostasis. The DEAD-Box RNA helicase genes emerge as crucial post-transcriptional regulatory factors, intricately involved in sustaining normal hematopoiesis through diverse mechanisms such as RNA alternative splicing, RNA modification, and ribosome assembly. This review consolidates the existing knowledge on the role of DEAD-box RNA helicases in regulating normal hematopoiesis and underscores the pathogenicity of mutant DEAD-Box RNA helicases in malignant hematopoiesis. Emphasis is placed on elucidating both the positive and negative contributions of DEAD-box RNA helicases within the hematopoietic system.

The energy consumption of a large-scale industrial hydrogen liquefaction system is primarily determined by the hydrogen turbo-expanders. To estimate the performance of the expander quickly, a one-dimensional preliminary design is conducted. This paper aims to identify dependable one-dimensional design codes for hydrogen turbo-expanders by employing three mean-line design approaches. The precision of the loss models is validated through hydrogen experiments, revealing a maximum deviation of less than 10 %. This study presents a summary of the optimal design parameter ranges for achieving high-efficiency hydrogen turbo-expanders. One common factor among the three methods is the characteristic ratio, which exhibits an optimal value range of 0.67–0.71. Furthermore, the three methods are applied to design hydrogen turbo-expanders of three different sizes, and the compositions of losses are thoroughly analyzed. The PR method exhibits the highest losses related to geometry sizes, while the VC method shows the greatest losses associated with velocities. The SS-CR method with moderate parameters is recommended for hydrogen turbo-expander design due to its superior maximum efficiency design limit and convenience. The two initial design parameters (specific speed and characteristic ratio) of this method play crucial roles in determining the scalability and efficiency of the hydrogen turbo-expander design.

Abstract Non-pharmaceutical interventions (NPI) have great potential to improve cognitive function but limited investigation to discover NPI repurposing for Alzheimer's Disease (AD). This is the first study to develop an innovative framework to extract and represent NPI information from biomedical literature in a knowledge graph (KG), and train link prediction models to repurpose novel NPIs for AD prevention. We constructed a comprehensive KG, called ADInt, by extracting NPI information from biomedical literature. We used the previously-created SuppKG and NPI lexicon to identify NPI entities. Four KG embedding models (i.e., TransE, RotatE, DistMult and ComplEX) and two novel graph convolutional network models (i.e., R-GCN and CompGCN) were trained and compared to learn the representation of ADInt. Models were evaluated and compared on two test sets (time slice and clinical trial ground truth) and the best performing model was used to predict novel NPIs for AD. Discovery patterns were applied to generate mechanistic pathways for high scoring candidates. The ADInt has 162,212 nodes and 1,017,284 edges. R-GCN performed best in time slice (MR = 5.2054, Hits@10 = 0.8496) and clinical trial ground truth (MR = 3.4996, Hits@10 = 0.9192) test sets. After evaluation by domain experts, 10 novel dietary supplements and 10 complementary and integrative health were proposed from the score table calculated by R-GCN. Among proposed novel NPIs, we found plausible mechanistic pathways for photodynamic therapy and Choerospondias axillaris to prevent AD, and validated psychotherapy and manual therapy techniques using real-world data analysis. The proposed framework shows potential for discovering new NPIs for AD prevention and understanding their mechanistic pathways.

Abstract Metal-halide perovskite thin monocrystals featuring efficient carrier collection and transport capabilities are well suited for radiation detectors, yet their growth in a generic, well-controlled manner remains challenging. Here, we reveal that mass transfer is one major limiting factor during solution growth of perovskite thin monocrystals. A general approach is developed to overcome synthetic limitation by using a high solute flux system, in which mass diffusion coefficient is improved from 1.7×10–10 to 5.4×10–10 m2 s–1 by suppressing monomer aggregation. The generality of this approach is validated by the synthesis of 29 types of perovskite thin monocrystals at 40–90 °C with the growth velocity up to 27.2 μm min–1. The as-grown perovskite monocrystals deliver a high X-ray sensitivity of 1.74×105 µC Gy−1 cm−2 without applied bias. The findings regarding limited mass transfer and high-flux crystallization are crucial towards advancing the preparation and application of perovskite thin monocrystals.

Abstract Coat protein complex I (COPI) vesicles mediate the retrograde transfer of cargo between Golgi cisternae and from the Golgi to the endoplasmic reticulum (ER). However, their roles in the cell cycle and proliferation are unclear. This study shows that TANGO6 associates with COPI vesicles via two transmembrane domains. The TANGO6 N- and C-terminal cytoplasmic fragments capture RNA polymerase II subunit B (RPB) 2 in the cis-Golgi during the G1 phase. COPI-docked TANGO6 carries RPB2 to the ER and then to the nucleus. Functional disruption of TANGO6 hinders the nuclear entry of RPB2, which accumulates in the cytoplasm, causing cell cycle arrest in the G1 phase. The conditional depletion or overexpression of TANGO6 in mouse hematopoietic stem cells results in compromised or expanded hematopoiesis. Our study results demonstrate that COPI vesicle-associated TANGO6 plays a role in the regulation of cell cycle progression by directing the nuclear transfer of RPB2, making it a potential target for promoting or arresting cell expansion.

Induced-charge electro-osmosis (ICEO) is a research hotspot in bioengineering and analytical chemistry. Inflow-outflow asymmetry of ICEO was reported in the existing literatures, but systematic study on this phenomenon is insufficient. In this experimental study, we found that in strong electric fields, not only the velocity magnitude but also the vortex positions of ICEO are asymmetrical along the inflow and outflow directions because of the pronounced non-uniform surface electrokinetic transport. On the inflow and outflow directions, the amplitudes of velocities are unequal, ICEO maximum velocity positions change depending on the electric field intensity and sodium chloride (NaCl) concentration. Additionally, the distances between vortex centers are different. At NaCl solution concentration of 0.001 mol·L–1, the outflow velocity almost vanishes. The asymmetry rises with the increasing electric field intensity. The new discoveries can direct the application of microscale devices.

Introduction Postoperative radiotherapy in patients with breast cancer with one to three lymph node metastases, particularly within the pT1–2N1M0 cohort with a low clinical risk of local–regional recurrence (LRR), has incited a discourse surrounding personalised treatment strategies. Multigene testing for Recurrence Index (RecurIndex) model capably differentiates patients based on their level of LRR risk. This research aims to validate whether a more aggressive treatment approach can enhance clinical outcomes in N1 patients who possess a clinically low risk of LRR, yet a high RecurIndex-determined risk of LRR. Specifically, this entails postoperative whole breast irradiation combined with regional lymph node irradiation (RNI) following breast-conserving surgery or chest wall irradiation with RNI after mastectomy.Methods and analysis The RIGAIN (RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1–3 node-positive breast cancer) Study is a multicentre, prospective, randomised, open-label, phase III clinical trial that is being conducted in China. In this study, patients with low clinical LRR risk but high RecurIndex-LRR risk are randomly assigned in a 1:1 ratio to the experimental group or the control group. In the experimental group, RNI is performed and the control group omits RNI. Efficacy and safety analyses will be conducted, enrolling a total of 540 patients (270 per group). The primary endpoint is invasive disease-free survival, and secondary endpoints include any first recurrence, LRR-free survival, distant metastasis-free survival, recurrence-free survival, overall survival, disease-free survival, breast cancer-specific mortality and assessment of patient quality of life. The study began in April 2023 and with a follow-up period of 60 months after the last participant completes radiation therapy.Ethics and dissemination The study was approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University (SYSKY-2022-097-02, V.3.1). It adheres to the Helsinki Declaration and Good Clinical Practice. Research findings will be submitted for publication in peer-reviewed journals.Trial registration number NCT04069884.

Abstract Numerous studies have demonstrated that exposure to cadmium disrupts the diversity and composition of the gut microbiota, resulting in damage to organ tissue. However, there remains a lack of comprehensive understanding regarding the broader ecological reality associated with this phenomenon. In this study, we conducted a thorough evaluation of the effects of different concentrations of Cd (6, 12, 24, and 48 mg/L) over a period of 35 consecutive days on the organ viscera and the gut microbiota of long‐tailed dwarf hamsters, Cricetulus longicaudatus (Rodentia: Cricetidae), using histopathological analysis, 16S rDNA, and metagenome sequencing. Our findings revealed that the results suggest that Cd exposure induced liver, spleen, and kidney damage, potentially leading to increased intestinal permeability and inflammation. These alterations were accompanied by significant perturbations in the gut microbiota composition, particularly affecting potentially pathogenic bacteria such as Prevotella and Treponema within the gut ecosystem. Consequently, host susceptibility to underlying diseases was heightened due to these changes. Notably though, Cd exposure did not significantly impact the overall structure of the gut microbiota itself. Additionally, Cd exposure induced significant changes in the metabolic functions, with the pathways related to disease and environmental information processing notably enhanced, possibly indicating stronger innate defense mechanisms against external injuries among wild mammals exposed to Cd. This study offers a novel approach to comprehensively evaluate the significant impact of Cd pollution on ecosystems by investigating both structural and functional alterations in the digestive system, as well as disruptions in intestinal flora among wild mammals.

The tumor microenvironment (TME) contains cells that regulate medication response and cancer growth in a major way. Tumor immunology research has been rejuvenated and cancer treatment has been changed by immunotherapy, a rapidly developing therapeutic approach. The growth patterns of tumor cells in vivo and the heterogeneity, complexity, and individuality of tumors produced from patients are not reflected in traditional two-dimensional tumor cell profiles. On the other hand, an in vitro three-dimensional (3D) model called the organoid model is gaining popularity. It can replicate the physiological and pathological properties of the original tissues in vivo. Tumor cells are the source of immune organoids. The TME characteristics can be preserved while preserving the variety of tumors by cultivating epithelial tumor cells with various stromal and immunological components. In addition to having genetic and physical similarities to human diseases and the ability to partially reconstruct the complex structure of tumors, these models are now widely used in research fields including cancer, developmental biology, regenerative mechanisms, drug development, disease modeling, and organ transplantation. This study reviews the function of organoids in immunotherapy and the tumor immune milieu. We also discuss current developments and suggest translational uses of tumor organoids in immuno-oncology research, immunotherapy modeling, and precision medicine.

The turbo-expander is the crucial equipment for obtaining refrigeration capacity and power in the system, and the aerodynamic performance is vital for the system. Spontaneous condensation of moist air in a high-speed turbo expander has a significant effect on the efficiency and output power. Based on the model of non-equilibrium spontaneous condensation, the flow of moist air in a high-speed turbo expander was studied, which is verified by the experiments. The meridional surface shape affects the variation of the flow passage cross-sectional area. The impeller with a uniform variation in cross-sectional area has the highest efficiency. Based on the optimal meridional surface shape, the condensation flow of moist air with different impeller blade diversion curvature was compared. The optimal curvature can increase the efficiency of the moist air turbo-expander by 2.83 %, and the optimized impeller has 3.53 % higher output power. The largest curvature of the blade leads to an efficiency reduction by 3.06 %, but it has little droplet condensation in the impeller, which can help to avoid damage of high-speed blades.

Abstract Gut microbiota is a key factor in maintaining the dietary and metabolic homeostasis of small mammals. To explore the effect of diet on the gut microbiota of the long‐tailed dwarf hamster (Cricetulus longicaudatus), 16S rDNA high‐throughput sequencing combined with bioinformatics analysis was used to investigate the succession process of the gut microbiota and effects of different nutrients on the composition and function of the gut microbiota. The results showed that diet structure can significantly influence the composition and function of the gut microbiota, as well as the health of animals. The highest relative abundance of Firmicutes, and the simplest co‐occurrence network occurred in the wild. Whereas the relative abundance of Bacteroidetes is higher and the most complex network structure was observed after 35 days of same feeding. Compared to the other four groups, the relative abundance of Firmicutes in the wheat + peanuts (WP) group was the highest after 35 days of different feeding, and the highest relative abundance of Bacteroidetes occurred in the wheat‐only (WH) group. Bacteroidetes exhibit carbohydrate degradation activity, and Firmicutes are strongly associated with fat uptake. We also found a significant positive correlation between Lactobacillus and body weight, indicating that Lactobacillus plays a crucial role in modulating fat intake and weight management. This study provides empirical evidence to facilitate the understanding of the co‐evolutionary dynamics between C. longicaudatus and their gut microbiota and establishes a theoretical foundation for utilizing gut microbiota in rodent control.

[Objective] During the process of EPB SC (earth pressure balanced shield construction), inevitable soil disturbances occur, causing ground deformation and subsequently impacting the surrounding built environment negatively. Therefore, conducting research on the ground deformation caused by EPB SC holds significant importance. [Method] By integrating various relevant literatures, the research is centered around the connections between each stage of the construction. The working mechanism of EPC SC is clarified, the causes of ground deformation are studied from three aspects: tunnel geometry factors, soil geological conditions, and shield tunneling parameters. The prediction methods for ground deformation caused by EPC SC are discussed, the applicability and pros and cons of each method are analyzed. Based on the causes of deformation and deformation prediction, control measures for ground deformation caused by EPB SC are listed. The shortcomings in the research of EPB SC are pointed out, and the future development direction of EPB SC is discussed. [Result & Conclusion] The causes of ground deformation induced by EPB SC are tunnel geometry factors, soil geological conditions, and shield tunneling parameters. The prediction methods for ground deformation caused by EPC SC include empirical formula method, theoretical analysis method, numerical simulation method of finite elements and finite difference, model test method, and artificial intelligence method. Based on the monitoring of ground deformation, continuously adjusting the shield parameters during construction is an effective method to control ground deformation by EPB shield.

Therapeutic targeting FOXO3A (a forkhead transcription factor) represents a promising strategy to suppress acute myeloid leukemia (AML). However, the effective inhibitors that target FOXO3A are lacking and the adaptive response signaling weakens the cytotoxic effect of FOXO3A depletion on AML cells. Here, we show that FOXO3A deficiency induces a compensatory response involved in the reactive activation of mTOR that leads to signaling rebound and adaptive resistance. Mitochondrial metabolism acts downstream of mTOR to provoke activation of JNK/c-JUN via reactive oxygen species (ROS). At the molecular level, FOXO3A directly binds to the promoter of G protein gamma subunit 7 (GNG7) and preserves its expression, while GNG7 interacts with mTOR and restricts phosphorylated activation of mTOR. Consequently, combinatorial inhibition of FOXO3A and mTOR show a synergistic cytotoxic effect on AML cells and prolongs survival in a mouse model of AML. Through a structure-based virtual screening, we report one potent small-molecule FOXO3A inhibitor (Gardenoside) that exhibits a strong effect of anti-FOXO3A DNA binding. Gardenoside synergizes with rapamycin to substantially reduce tumor burden and extend survival in AML patient-derived xenograft model. These results demonstrate that mTOR can mediate adaptive resistance to FOXO3A inhibition and validate a combinatorial approach for treating AML.

Abstract The high-speed train transmission system, experiencing both the internal excitation originating from gear meshing and the external excitation originating from the wheel–rail interaction, exhibits complex dynamic behavior in the actual service environment. This paper focuses on the gearbox in the high-speed train to carry out the bench test, in which various operating conditions (torques and rotation speeds) were set up and the excitation condition covering both internal and external was created. Acceleration responses on multiple positions of the gearbox were acquired in the test and the vibration behavior of the gearbox was studied. Meanwhile, a stochastic excitation modal test was also carried out on the test bench under different torques, and the modal parameter of the gearbox was identified. Finally, the sweep frequency response of the gearbox under gear meshing excitation was analyzed through dynamic modeling. The results showed that the torque has an attenuating effect on the amplitude of gear meshing frequency on the gearbox, and the effect of external excitation on the gearbox vibration cannot be ignored, especially under the rated operating condition. It was also found that the torque affects the modal parameter of the gearbox significantly. The torque has a great effect on both the gear meshing stiffness and the bearing stiffness in the transmission system, which is the inherent reason for the changed modal characteristics observed in the modal test and affects the vibration behavior of the gearbox consequently.

Based on data from the 2022 Chinese Minors’ Digital Life and Online Protection Survey, this study investigated the status quo of social media use and its influencing mechanism on academic performance among Chinese children and adolescents. The statistical results indicate that the average level of Chinese students’ social media use was generally low, with their academic performance varying across socio-demographic and schooling characteristics. After controlling for other variables, it was found that the frequency of social media use could exert a significant positive impact on students’ academic performance. Moreover, the mechanism analysis revealed that online learning behavior and prosocial behavior served as chain mediators linking social media use to academic performance. Specifically, students could transfer their social media behavioral patterns to the internet-based learning context, and then effectively utilize remote learning resources. Meanwhile, engagement with social media would cultivate individuals’ prosocial personality, thereby stimulating intrinsic motivation for learning and ultimately enhancing academic performance. The heterogeneity analysis further confirmed that the impact of social media use on students’ academic performance was stronger in lower-class families, underscoring the moderating role of family socioeconomic status in the relationship between social media use and academic performance. The findings suggest that if academic performance is regarded as an integral part of individual capacity development, then the rational utilization of social media resources might be a pivotal approach to alleviate the predicament of developmental inequality faced by students from low socioeconomic backgrounds.

Based on the theory of new structural economics, this research aims to explore the dynamic correlation among high-quality development, environmental regulation structures, and property rights structures in China’s construction industry. A panel vector autoregressive model (PVAR) is employed to conduct an empirical study of 30 provinces from 2008 to 2022. To further explore regional heterogeneity, K-means clustering is utilized to categorize the country into three types of regions. The results indicate that strict environmental regulation structures have a beneficial effect on the high-quality growth of the construction sector, which is most pronounced in Region III with a lower degree of construction development. Conversely, state-owned ownership structures are an impediment, and their influence is the greatest in Region I with a higher degree of construction development. Additionally, environmental regulation structures and property rights structures demonstrate a certain interactional effect. The dynamic correlation between these indicators varies in distinct regions. Various regions in China should combine their development characteristics and advantages to reasonably adjust environmental regulation structures and property rights structures. This research provides a direction for structural adjustments for the high-quality development of the construction industry.

BackgroundRemimazolam is a new ultrashort-acting benzodiazepine for sedation and anesthesia. The effects of remimazolam and the mechanism by which it functions in cancer cells have not been determined. This research aimed to explore the mechanism of remimazolam action in colon cancer treatment, using bioinformatics analysis and in vitro experiments.MethodsCell cycle progression, colony formation, self-renewal capacity, and apoptosis detection were performed in HCT8 cells treated with or without remimazolam. Transcriptome sequencing, Gene Ontology, Kyoto Encyclopedia of Genes and Genome, Protein–Protein Interaction, Gene Set Enrichment Analysis, Western blotting, and qPCR were performed to investigate the mechanism of action of remimazolam in HCT8 colon cancer cells.ResultsRemimazolam promoted proliferation and cell-cycle progression of HCT8 cells. After remimazolam treatment, a total of 1,096 differentially expressed genes (DEGs) were identified: 673 genes were downregulated, and 423 genes were upregulated. The DEGs were enriched mainly in “DNA replication“, “cell cycle”, and “G1/S transition” related pathways. There were 15 DEGs verified by qPCR, and representative biomarkers were detected by Western Bloting. The remimazolam-mediated promotion of cell proliferation and cell cycle was reversed by G1T28, a CDK4/6 inhibitor.ConclusionRemimazolam promoted cell-cycle progression and proliferation in HCT8 colon cancer cells, indicating that the long-term use of remimazolam has potential adverse effects in the anesthesia of patients with colon cancer.

Triphenyltin (TPT) is a typical persistent organic pollutant whose occurrence in coral reef ecosystems may threaten the survival of reef fishes. In this study, a brightly colored representative reef fish, Amphiprion ocellaris was used to explore the effects of TPT at environmental levels (1, 10, and 100 ng/L) on skin pigment synthesis. After the fish were exposed to TPT for 60 days, the skin became darker, owing to an increase in the relative area of black stripes, a decrease in orange color values while an increase in brown color values, and an increase in the number of melanocytes in the orange part of the skin tissues. To explore the mechanisms by which TPT induces darker body coloration, the enzymatic activity and gene expression levels of the members of melanocortin system that affect melanin synthesis were evaluated. Leptin levels and lepr expression were found to be increased after TPT exposure, which likely contributed to the increase found in pomc expression and α-melanocyte-stimulating hormone (α-MSH) levels. Then Tyr activity and mc1r, tyr, tyrp1, mitf, and dct were upregulated, ultimately increasing melanin levels. Importantly, RT-qPCR results were consistent with the transcriptome analysis of trends in lepr and pomc expression. Because the orange color values decreased, pterin levels and the pteridine metabolic pathway were also evaluated. The results showed that TPT induced BH4 levels and spr, xdh, and gch1 expression associated with pteridine synthesis decreased, ultimately decreasing the colored pterin content (sepiapterin). We conclude that TPT exposure interferes with the melanocortin system and pteridine metabolic pathway to increase melanin and decrease colored pterin levels, leading to darker body coloration in A. ocellaris. Given the importance of body coloration for the survival and reproduction of reef fishes, studies on the effects of pollutants (others alongside TPT) on body coloration are of high priority.

Background Although aerobic exercise is the primary modality recommended for the treatment of hypertension, it remains unclear whether high-intensity all-out sprint interval training (SIT) can result in greater reductions of blood pressure (BP) and cardiorespiratory health. This systematic review aims to compare the impact of SIT versus Moderate-intensity continuous training (MICT) on improvements in resting systolic blood pressure (SBP), diastolic blood pressure (DBP) and maximal oxygen uptake (VO2 max) among adults. Methods We conducted a systematic search of three online databases (PubMed, Embase, and Web of Science) from January 2000 to July 2023 to identify randomized controlled trials that compared the chronic effects of SIT versus MICT on BP in participants with high or normal blood pressure. We extracted information on participant characteristics, exercise protocols, BP outcomes, and intervention settings. Furthermore, the changes in VO2 max between the two groups were analyzed using a meta-analysis. The pooled results were presented as weighted means with 95% confidence intervals (CI). Results Out of the 1,874 studies initially were found, eight were included in this review, totaling 169 participants. A significant decrease in SBP (MD = −2.82 mmHg, 95% CI [−4.53 to −1.10], p = 0.08, I2 =45%) was observed in the SIT group compared to before the training, but no significant decrease in DBP (MD = −0.75 mmHg, 95% CI [−1.92 to 0.42], p = 0.16, I2 = 33%) was observed. In contrast, both SBP (MD = −3.00 mmHg, 95% CI [−5.31 to −0.69], p = 0.68, I2 = 0%) and DBP (MD = −2.11 mmHg, 95% CI [−3.63 to −0.60], p = 0.72, I2 = 0%) significantly decreased in the MICT group with low heterogeneity. No significant difference was found in resting SBP and DBP between SIT and MICT after the intervention. Both SIT and MICT significantly increased VO2 peak, with SIT resulting in a mean difference (MD) of 1.75 mL/kg/min (95% CI [0.39–3.10], p = 0.02, I2 = 61%), and MICT resulting in a mean difference of 3.10 mL/kg/min (95% CI [1.03–5.18], p = 0.007, I2 = 69%). MICT was more effective in improving VO2 peak (MD = −1.36 mL/kg/min, 95% CI [−2.31 to 0.40], p = 0.56, I2 = 0%). Subgroup analysis of duration and single sprint time showed that SIT was more effective in reducing SBP when the duration was ≥8 weeks or when the sprint time was

The rapid development of industrial and information technology is driving the demand to improve the applicability and hydraulic performance of centrifugal pumps in various applications. Enhancing the rotational speed of pumps can simultaneously increase the head and reduce the impeller diameter, thereby reducing the pump size and weight and also improving pump efficiency. This paper reviews the current application status of high-speed pumps using low-temperature thermosensitive fluids, which have been applied in fields such as novel energy-saving cooling technologies, aerospace, chemical industries, and cryogenic engineering. Due to operational constraints and thermal effects, there are inherent challenges that still need to be addressed for high-speed pumps. Based on numerical simulation and experimental research for different working fluids, the results regarding cavitation within the inducer have been categorized and summarized. Improvements to cavitation models, the mechanism of unsteady cavity shedding, vortex generation and cavitation suppression, and the impact of cavitation on pump performance were examined. Subsequently, the thermal properties and cavitation thermal effects of low-temperature thermosensitive fluids were analyzed. In response to the application requirements of pump-driven two-phase cooling systems in data centers, a high-speed refrigerant pump employing hydrodynamic bearings has been proposed. Experimental results indicate that the prototype achieves a head of 56.5 m and an efficiency of 36.1% at design conditions (n = 7000 rpm, Q = 1.5 m3/h). The prototype features a variable frequency motor, allowing for a wider operational range, and has successfully passed both on/off and continuous operation tests. These findings provide valuable insights for improving the performance of high-speed refrigerant pumps in relevant applications.

Abstract Background Propofol is a common sedative-hypnotic drug used for general anesthesia. Recent studies have drawn attention to the antitumor effects of propofol, but the potential mechanism by which propofol suppresses colon cancer stemness and epithelial-mesenchymal transition (EMT) has not been fully elucidated. Methods For the in vitro experiments, we used propofol to treat LOVO and SW480 cells and Cell Counting Kit-8 (CCK-8) to detect proliferation. Self-renewal capacity, cell invasion and migration, flow cytometry analysis, qPCR and Western blotting were performed to detect the suppression of propofol to colon cancer cells and the underlying mechanism. Tumorigenicity and immunohistochemistry experiments were performed to confirm the role of propofol in vivo. Result We observed that propofol could suppressed stem cell-like characteristics and EMT-related behaviors, including self-renewal capacity, cell invasion and migration in colon cancer cells, and even suppressed tumorigenicity in vivo. Furthermore, investigations of the underlying mechanism revealed that propofol treatment downregulated SIRT1. SIRT1 overexpression or knockdown affected the stemness and EMT of colon cancer cells. Additionally, propofol reversed stemness and EMT in cells with overexpressing SIRT1 and subsequently inhibited the Wnt/β-catenin and PI3K/AKT/mTOR signaling pathways. Wnt/β-catenin pathway inhibitor and PI3K/AKT/mTOR pathway inhibitor blocked the propofol-induced reduction of sphere-formation and cell invasion-migration. Conclusion Propofol inhibits LOVO and SW480 cell stemness and EMT by regulating SIRT1 and the Wnt/β-catenin and PI3K/AKT/mTOR signaling pathways. Our findings indicate that propofol inhibits SIRT1 in cancer and is advantageous in colon cancer surgical treatment of patients with high SIRT1 expression.

Abstract Background Limb-girdle muscular dystrophy R8 (LGMD R8) is a rare autosomal recessive muscle disease caused by TRIM32 gene biallelic defects. The genotype–phenotype correlation of this disease has been reported poorly. Here, we report a Chinese family with two female LGMD R8 patients. Methods We performed whole-genome sequencing (WGS) and Sanger sequencing on the proband. Meanwhile, the function of mutant TRIM32 protein was analyzed by bioinformatics and experimental analysis. In addition, a summary of the reported TRIM32 deletions and point mutations and an investigation of genotype–phenotype correlation were performed through a combined analysis of the two patients and other cases reported in previous literature. Results The two patients displayed typical symptoms of LGMD R8, which worsened during pregnancy. Genetic analysis by whole-genome sequencing (WGS) and Sanger sequencing showed that the patients were compound heterozygotes of a novel deletion (chr9.hg19:g.119431290_119474250del) and a novel missense mutation (TRIM32:c.1700A > G, p.H567R). The deletion encompassed 43 kb and resulted in the removal of the entire TRIM32 gene. The missense mutation altered the structure and further affected function by interfering with the self-association of the TRIM32 protein. Females with LGMD R8 showed less severe symptoms than males, and patients carrying two mutations in NHL repeats of the TRIM32 protein had earlier disease onset and more severe symptoms than other patients. Conclusions This research extended the spectrum of TRIM32 mutations and firstly provided useful data on the genotype–phenotype correlation, which is valuable for the accurate diagnosis and genetic counseling of LGMD R8.

Abstract Thermal Bridges on Building Rooftops (TBBR) is a multi-channel remote sensing dataset. It was recorded during six separate UAV fly-overs of the city center of Karlsruhe, Germany, and comprises a total of 926 high-resolution images with 6927 manually-provided thermal bridge annotations. Each image provides five channels: three color, one thermographic, and one computationally derived height map channel. The data is pre-split into training and test data subsets suitable for object detection and instance segmentation tasks. All data is organized and structured to comply with FAIR principles, i.e. being findable, accessible, interoperable, and reusable. It is publicly available and can be downloaded from the Zenodo data repository. This work provides a comprehensive data descriptor for the TBBR dataset to facilitate broad community uptake.

Phytosterol organic acid esters are important food resources and the components of biomembrane structure. Due to the lack of extraction and synthesis techniques, more research has been focused on phytosterols, and the research on phytosterol acid esters have encountered a bottleneck, but phytosterol acid esters confer substantial benefits to human health. In this study, stigmasteryl vanillate (VAN), stigmasteryl protocatechuate (PRO) and stigmasteryl sinapate (SIN) were prepared through the Steglich reaction. The processes are promotable and the products reach up to 95% purity. In addition, their stability was evaluated by differential scanning calorimetry and thermogravimetric analysis. HPLC analysis revealed an enhancement in water solubility after esterification with phenolic acid. In an in vitro digestion model, the bioaccessibility of stigmasteryl phenolates was significantly higher than that of stigmasterols (STIs). Regarding the anti-inflammatory properties, VAN, PRO, and SIN exhibit superior effects against TNF-α induced pro-inflammatory responses compared to STI. All stigmasteryl phenolates supplementation increased the ATP production, the basal, and maximal oxygen consumption rate in mitochondrial stress test. Overall, we present a synthesis method for stigmasteryl phenolates. It will contribute to the development and research of phytosterol acid ester analysis, functions and utilization in food. Moreover, the nutrient-stigmasterol hybrids tactic we have constructed is practical and can become a targeted mitochondrial delivery strategy with enhanced anti-inflammatory effects.

Summary: Biomedical knowledge graphs (BKGs) provide a new paradigm for managing abundant biomedical knowledge efficiently. Today’s artificial intelligence techniques enable mining BKGs to discover new knowledge. Here, we present a protocol for implementing a computational pipeline for biomedical knowledge discovery (BKD) based on a BKG. We describe steps of the pipeline including data processing, implementing BKD based on knowledge graph embeddings, and prediction result interpretation. We detail how our pipeline can be used for drug repurposing hypothesis generation for Parkinson’s disease.For complete details on the use and execution of this protocol, please refer to Su et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Vascular cognitive impairment not dementia (VCIND) is one of the three subtypes of vascular cognitive impairment (VCI), with cognitive dysfunction and symptoms ranging between normal cognitive function and vascular dementia. The specific mechanisms underlying VCIND are still not fully understood, and there is a lack of specific diagnostic markers in clinical practice. With the rapid development of magnetic resonance imaging (MRI) technology, structural MRI (sMRI) and functional MRI (fMRI) have become effective methods for exploring the neurobiological mechanisms of VCIND and have made continuous progress. This article provides a comprehensive overview of the research progress in VCIND using multimodal MRI, including sMRI, diffusion tensor imaging, resting-state fMRI, and magnetic resonance spectroscopy. By integrating findings from these multiple modalities, this study presents a novel perspective on the neuropathological mechanisms underlying VCIND. It not only highlights the importance of multimodal MRI in unraveling the complex nature of VCIND but also lays the foundation for future research examining the relationship between brain structure, function, and cognitive impairment in VCIND. These new perspectives and strategies ultimately hold the potential to contribute to the development of more effective diagnostic tools and therapeutic interventions for VCIND.

Rapid population growth has led to an increasing demand for food, accompanied by an increase in the resources invested in producing food, and the extensive food production practices have placed a huge burden on the environment. There is an urgent desire of need to find a sustainable model of food production. Therefore, this study attempted to develop a dynamic regional grid-scale crop layout model (ABCAMODP-Crop) combining agent-based model, multi-objective programming, dynamic programming and cellular automata model to promote more sustainable food production from a supply-side perspective. The model can: (1) take into account the planting preferences and practical behaviours of government and farmer as stakeholders in crop layout; (2) further weigh the conflicts among the various objectives that stakeholders are concerned with from resource, environmental, nutritional and economic dimensions; (3) consider the impact of the previous year's crop layout on the next year's crop placement; and (4) obtain grid-scale accurate crop layout solutions by considering the spatial variability of optimization parameters and the neighborhood effects of crop layout cells. The model was applied to the Shiyang River Basin in China to verify its usefulness. Over the entire planning period, crop layout schemes optimized with the objective of integrating irrigation water productivity, environmental impact, nutrient availability and economic benefits have higher comprehensive benefits than the original scheme, with an increase in average irrigation water productivity per unit area of 14.55%, an increase in total yield of 14.45%, an increase in total carbohydrate availability of 7.39%, an increase in total calcium availability of 18.74%, an increase in total net carbon sequestration of 8.05%, an increase in total net benefit of 20.08%. The model developed allows for a holistic view of crop layout and guides decision-makers in a rational distribution of regional crops, thus promoting more sustainable food production. It can equally be extended to other regions as a generic modelling framework.

Accurate numerical prediction of frosting patterns is essential for the efficient layout and timing defrosting of heat exchangers under frosting conditions. In this study, a numerical model is developed to predict the spatio-temporal frosting habits on curved surfaces in combination with the correlations of frost density and thermal conductivity. In the model, frost melting is considered. After verification, the frosting and heat transfer characteristics along the flow path are investigated under various structural and operating conditions. Frost thickness along the path is mainly affected by the cooling surface temperature, while the heat and mass transfer rates are strongly correlated with the humidity ratio. The proportions of latent heat and sensible heat are distributed more unevenly in parallel flow case than in counter flow case. Frost deposition is facilitated by a smaller radius of curvature of the cooling surface. More uniform frosting characteristics along the path and smaller heat transfer obstruction are presented with a smaller length-to-height ratio of the flow path.

Chromium (Cr) contamination, widely present in the environment, poses a significant threat to both ecology and human health. Microbial remediation technology has become a hot topic in the field of heavy metal remediation due to its advantages, such as environmental protection, low cost, and high efficiency. This paper focused on using various characterization and analysis methods to investigate the bioreduction effect and mechanism of microorganisms on Cr(VI) under various influencing factors. The main contents and conclusions were as follows: Shewanella oneidensis MR-1 was selected as the target strain for studying its reduction of Cr(VI) at different inoculation amounts, temperatures, pH values, time intervals, etc. The results indicated that S. oneidensis MR-1 exhibited an optimal reduction effect on Cr(VI) at pH 7 and a temperature of 35 °C. Additionally, electron shuttles (ESs), including humic acid (HA) and 9,10-antraquinone-2,6-disulfonate (AQDS), were introduced into the degradation system to improve the reduction efficiency of S. oneidensis MR-1. Upon adding goethite further, S. oneidensis MR-1 significantly enhanced its reducing ability by converting Fe(III) minerals to Fe(II) and reducing Cr(VI) to Cr(III) during electron transfer.

In high-speed motors, there is a huge amount of heat generation from core and winding losses, which may result in thermal failures or motor performance deterioration. In the prevention of heat accumulation, efficient cooling technology is critical for smooth and reliable motor movement. This paper summarizes the diverse application of high-speed motor and thermal requirements, such as in electrical devices, turbo-machinery, and high-precision machine tools. Three paths of case convection—cooling, internal ventilation cooling and spindle core cooling—are analyzed. Methods for configuring thermal resistance and improving cooling efficiency are summarized. Among them, coolant flow characteristics and flow channel shapes, gas supply ventilation systems, and methods to reduce air resistance, as well as axial cooling and integrated heat pipe structures, are extensively investigated. Finally, the development prospects of high-speed motor cooling are also forecasted. At present, the primary research directions are to reduce the heat generated by the heat source, utilize the latent heat of the coolant, optimize the cooling flow path of the shell, design an axial air-cooling circulation system, and enhance the heat dissipation of the spindle.

Under abiotic stress, plant root exudates can improve plant growth performance. However, studies on the effect of root exudates on the stress resistance of another plant are insufficient. In this study, root exudates (REs) were extracted from Suaeda glauca to explore their effect on alfalfa seedlings under salt stress. The results showed that the plant height and fresh weight of alfalfa significantly increased by 47.72% and 53.39% after 7 days of RE treatment at a 0.4% NaCl concentration. Under 1.2% salt stress, REs reduced the Malondialdehyde content in alfalfa by 30.14% and increased the activity of its antioxidant enzymes (peroxidase and catalase) and the content of its osmotic regulators (soluble sugar and proline) by 60.68%, 52%, 45.67%, and 38.67%, respectively. Soil enzyme activity and the abundance of soil-beneficial bacteria were increased by REs. Spearman analysis showed that urease and neutral phosphatase were related to the richness of beneficial bacteria. Redundancy analysis confirmed that urease affected the composition of the soil bacterial community. The partial least squares structural equation model (PLS-SEM) revealed that REs had a direct positive effect on alfalfa growth under salt stress by regulating the plant’s injury and antioxidant systems, and the soil bacterial community had an indirect positive effect on alfalfa growth through soil enzyme activity.

(1) Background: Colorectal cancer (CRC) is the third most common malignant tumor worldwide and the second most common cause of cancer death. However, effective anti-CRC drugs are still lacking in clinical settings. This article investigated the anti-proliferative effect of involucrasin B on CRC Caco-2 cells. (2) Methods: This study employed a sulforhodamine B (SRB) method, colony formation experiments, flow cytometry, FastFUCCI assay, dual luciferase assay, and Western blot analysis for the investigation. (3) Results: The SRB method and colony formation experiments showed that involucrasin B exhibited an inhibitory effect on the Caco-2 cells cultured in vitro. Subsequently, the flow cytometry, FastFUCCI assay, and Western blotting results showed that involucrasin B induced cell cycle arrest in the G1 phase dose-dependently. Involucrasin B significantly enhanced the TGFβ RII protein level and SMAD3 phosphorylation, thus inhibiting the expression of CDK4 and cyclin D1 and causing G1 cell cycle arrest. (4) Conclusion: This study shows that involucrasin B exerts its anti-proliferative effect by regulating the TGFβ/SMAD2-3-4 pathway to cause G1 cycle arrest in Caco-2 cells.

In this study, fibroblasts were harvested and isolated from a healthy 14-year-old male donor and reprogrammed with four Yamanaka factors containing Oct3/4, Sox2, Klf4 and c-Myc to generate human induced pluripotent stem cell (iPSC) lines. The resulting iPSCs were integration-free, expressed normal karyotype, displayed pluripotency markers, and have been demonstrated to differentiate into cells with three germ layer. And the iPSCs were further differentiated to chondrosphere in vivo. The models could be used to test multiple differentiation protocols and also as a control for screening drugs and studying cartilage related disease.

BackgroundAmnestic mild cognitive impairment (aMCI) is an early stage of Alzheimer’s disease (AD). Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) are employed to explore spontaneous brain function in patients with aMCI. This study applied ALFF and ReHo indicators to analyze the neural mechanism of aMCI by resting-state functional magnetic resonance imaging (rs-fMRI).MethodsTwenty-six patients with aMCI were included and assigned to the aMCI group. The other 26 healthy subjects were included as a healthy control (HC) group. Rs-fMRI was performed for all participants in both groups. Between-group comparisons of demographic data and neuropsychological scores were analyzed using SPSS 25.0. Functional imaging data were analyzed using DPARSF and SPM12 software based on MATLAB 2017a. Gender, age, and years of education were used as covariates to obtain ALFF and ReHo indices.ResultsCompared with HC group, ALFF decreased in the left fusiform gyrus, left superior temporal gyrus, and increased in the left cerebellum 8, left inferior temporal gyrus, left superior frontal gyrus (BA11), and right inferior temporal gyrus (BA20) in the aMCI group (p

IntroductionGrasslands are home to complex bacterial communities whose dynamic interactions play a crucial role in organic matter and nutrient cycling. However, there is limited understanding regarding the impact of changes in rainfall amount and the duration of dry intervals on bacterial interactions.MethodsTo assess the impact of changes in precipitation volume and dry intervals on bacterial co-occurrence networks, we carried out precipitation manipulation experiments in the Eastern Eurasian Steppe of China.Results and DiscussionWe found that alterations in precipitation and dry intervals did not significantly affect bacterial alpha and beta diversity. However, we observed significant changes in the co-occurrence network structure of bacteria in the rhizosphere ecosystem, with the 12-day dry interval showing the most notable reduction in the number of degrees, edges, and clustering coefficient. Additionally, the study identified putative keystone taxa and observed that the moderately prolonged dry intervals between precipitation events had a major effect on the robustness of bacterial networks. The complexity and stability of the network were found to be positively correlated, and were primarily influenced by soil water content, phosphorous, and aboveground biomass, followed by available phosphorus (AP) and total biomass. These findings have the potential to enhance our comprehension of how bacterial co-occurrence pattern react to variations in dry intervals, by regulating their interactions in water-limited ecosystems. This, in turn, could aid in predicting the impact of precipitation regime alterations on ecosystem nutrient cycling, as well as the feedback between ecosystem processes and global climate change.