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Fluoride-salt-cooled High-temperature Reactor (FHR) is a promising nuclear reactor technology. Among many challenges presented by the molten fluoride salts is the corrosion of salt-facing structural components. Higher moisture contents, in the FLiNaK (LiF-NaF-KF, 46.5–11.5-42 mol%) salt, aggravate intergranular corrosion and pitting for the given alloys. Therefore, several thermal dehydration tests of FLiNaK salt were performed with a batch size suitable for thermal-hydraulic experiments. Thermogravimetric Analysis (TGA) was performed for the three constituent fluoride salts individually. Preliminary thermal dehydration plans were then proposed for NaF and KF salts based on the TGA curves. However, the dehydration process may not be required for LiF since its low mass loss (500 °C) were necessary to remove a significant amount of moisture (>1 wt%) from NaF salt, while relatively low temperatures (around 300 °C) with a long holding time (>10 h) were sufficient to remove most of the moisture from KF salt.

In order to reduce costs and environmental hazards, this article explores a new synthesis method for preparing NaY zeolite using water quenching residue as the raw material. The effects of the crystallisation time, crystallisation temperature, n(SiO₂)/n(Al₂O₃) ratio and n(Na₂O)/n(Al₂O₃) ratio on the crystallisation of NaY zeolite were investigated, and an ideal synthetic route was obtained. The physical and chemical properties of the prepared NaY zeolite were characterised by XRD, SEM, STEM, FTIR and other methods. In order to understand the adsorption performance of the prepared Y zeolite, different adsorption isotherm models were studied at 30 °C, 60 °C, 90 °C and 0 to 1 bar. At these three temperatures, NaY zeolite has a much higher adsorption capacity for CO₂ than N₂. The Toth equation fits well the CO₂ adsorption of NaY zeolite. The BET test calculates that the micropore specific surface area of NaY zeolite is 838.88m²/g. The range of the zeolite micropores is mainly between 0.35∼0.45nm. The NaY zeolite obtained by the technical route reported in this study has high crystallinity, a uniform particle size, high thermal stability, and excellent CO₂ adsorption performance under flue gas conditions, and will have potential applications in the CO₂ capture in steel plant flue gas prospect

In recent years, with the increasing consumption of resources around the world, motors in various industries are also urgently added to the ranks of energy saving and emission reduction. High-speed permanent magnet air compressor is widely used in various new energy vehicles. The study on its loss can provide reference for motor manufacturing industry. In this paper, the 27 kW, 90000 r/min high-speed permanent magnet air compressor is studied and analyzed. Taking 0.1 mm thick silicon steel sheet as an example, two different kinds of silicon steel sheet materials were compared and analyzed through the study of stator core loss. At the beginning of the design of the motor, the material was tested, and the good performance, low carbon and environmentally friendly material was used in the design and manufacture of the motor, which played a good role in the stable operation of energy saving and emission reduction and the motor. The high-speed motor uses frequency converter for power supply, and its characteristics of large harmonic content and high frequency lead to the increase of rotor eddy current loss. Therefore, the analytical calculation method of rotor eddy current loss is derived. This method establishes the physical model in polar coordinate system, and considers the sub domains such as air gap, sheath and permanent magnet. A prototype and an experimental platform were made to study the influence of harmonics on the motor. In this paper, the actual output current harmonics with IGBT and SIC as controllers are studied by comparative method. The actual output current is collected and applied as excitation to the 2D finite element model of motor for analysis and calculation. Finally, the influence of motor loss is analyzed comprehensively, which has reference value for each motor manufacturing enterprise.

Phycobilisomes and chlorophyll-a (Chla) play important roles in the photosynthetic physiology of red macroalgae and serve as the primary light-harvesting antennae and reaction center for photosystem II. Neopyropia is an economically important red macroalga widely cultivated in East Asian countries. The contents and ratios of 3 main phycobiliproteins and Chla are visible traits to evaluate its commercial quality. The traditional analytical methods used for measuring these components have several limitations. Therefore, a high-throughput, nondestructive, optical method based on hyperspectral imaging technology was developed for phenotyping the pigments phycoerythrin (PE), phycocyanin (PC), allophycocyanin (APC), and Chla in Neopyropia thalli in this study. The average spectra from the region of interest were collected at wavelengths ranging from 400 to 1000 nm using a hyperspectral camera. Following different preprocessing methods, 2 machine learning methods, partial least squares regression (PLSR) and support vector machine regression (SVR), were performed to establish the best prediction models for PE, PC, APC, and Chla contents. The prediction results showed that the PLSR model performed the best for PE (RTest2 = 0.96, MAPE = 8.31%, RPD = 5.21) and the SVR model performed the best for PC (RTest2 = 0.94, MAPE = 7.18%, RPD = 4.16) and APC (RTest2 = 0.84, MAPE = 18.25%, RPD = 2.53). Two models (PLSR and SVR) performed almost the same for Chla (PLSR: RTest2 = 0.92, MAPE = 12.77%, RPD = 3.61; SVR: RTest2 = 0.93, MAPE = 13.51%, RPD =3.60). Further validation of the optimal models was performed using field-collected samples, and the result demonstrated satisfactory robustness and accuracy. The distribution of PE, PC, APC, and Chla contents within a thallus was visualized according to the optimal prediction models. The results showed that hyperspectral imaging technology was effective for fast, accurate, and noninvasive phenotyping of the PE, PC, APC, and Chla contents of Neopyropia in situ. This could benefit the efficiency of macroalgae breeding, phenomics research, and other related applications.

The ultra-high speed permanent magnet motor (UHSPM) for hydrogen fuel cell air compressor is characterized by high speed, high motor power density, small size, and high reliability. Compared to the conventional motor, the loss per unit volume is increased and therefore the calculation of the temperature field is more important than that of conventional motors. In this paper, a UHSPM with a rated speed of 90000 r/min is designed. Firstly, a finite element (FE) model of the UHSPM is established and the losses of each part of the high-speed motor are calculated, and the calculated losses are introduced into the fluid field in the form of a heat source for motor temperature analysis. The calculated losses were introduced into the fluid field in the form of a heat source and used in the motor temperature analysis. The temperature rise was then calculated for the unidirectional and bidirectional magneto-thermal coupling (MTC) respectively. The results show that the bidirectional magneto- thermal coupling (BMTC) simulation results are about 2-3°C smaller than the experimental measured values, which can more accurately predict the motor temperature. The measurement results verify the accuracy of BMTC, and provide basic theoretical support for the subsequent cooling optimization scheme of high-speed motor.

Abstract Background Pyropia is an economically advantageous genus of red macroalgae, which has been cultivated in the coastal areas of East Asia for over 300 years. Realizing estimation of macroalgae biomass in a high-throughput way would great benefit their cultivation management and research on breeding and phenomics. However, the conventional method is labour-intensive, time-consuming, manually destructive, and prone to human error. Nowadays, high-throughput phenotyping using unmanned aerial vehicle (UAV)-based spectral imaging is widely used for terrestrial crops, grassland, and forest, but no such application in marine aquaculture has been reported. Results In this study, multispectral images of cultivated Pyropia yezoensis were taken using a UAV system in the north of Haizhou Bay in the midwestern coast of Yellow Sea. The exposure period of P. yezoensis was utilized to prevent the significant shielding effect of seawater on the reflectance spectrum. The vegetation indices of normalized difference vegetation index (NDVI), ratio vegetation index (RVI), difference vegetation index (DVI) and normalized difference of red edge (NDRE) were derived and indicated no significant difference between the time that P. yezoensis was completely exposed to the air and 1 h later. The regression models of the vegetation indices and P. yezoensis biomass per unit area were established and validated. The quadratic model of DVI (Biomass = − 5.550DVI2 + 105.410DVI + 7.530) showed more accuracy than the other index or indices combination, with the highest coefficient of determination (R2), root mean square error (RMSE), and relative estimated accuracy (Ac) values of 0.925, 8.06, and 74.93%, respectively. The regression model was further validated by consistently predicting the biomass with a high R2 value of 0.918, RMSE of 8.80, and Ac of 82.25%. Conclusions This study suggests that the biomass of Pyropia can be effectively estimated using UAV-based spectral imaging with high accuracy and consistency. It also implied that multispectral aerial imaging is potential to assist digital management and phenomics research on cultivated macroalgae in a high-throughput way.

In view of the uncertainty and volatility of wind power generation and the inability to provide stable and continuous power, this paper proposes a hydrogen storage wind-gas complementary power generation system, using Matlab/Simulink to simulate and model wind generators and gas turbines. Considering the economy and power supply reliability of the wind-gas complementary power generation system, and taking the economic and environmental cost of the system as the objective function, the capacity optimization model of the wind-gas complementary power generation system is established. The brain storming algorithm (BSO) is used to solve the optimization problem, and the BSO algorithm is used to optimize the BP neural network, which improves the accuracy of the BP neural network for load forecasting. Finally, a simulation is carried out with load data in a certain area, and the simulation verification verifies that BSO-BP can improve the accuracy of load forecasting and reduce the error of load forecasting. Multi-objective optimization of system economic cost and environmental cost through BSO algorithm can make the system cost reach the most reasonable level. Through the analysis of the calculation examples, it is verified that gas-fired power generation can effectively alleviate the volatility of wind power generation, showing the role and advantages of energy complementary power generation. Therefore, the wind-gas complementary system can effectively increase energy utilization and reduce wind curtailment.

The behavior of two-phase flow and corresponding flow regimes in helical tubes significantly differ when compared to two-phase flows in straight tubes due to centrifugal and torsion effects. In order to gain physical insight and gather data for validating computational models, a large number of experiments were performed on a helical coil experimental setup operated with a mixture of water and air. The experimental data were used to assess the predictive capabilities of current two-phase Computational Fluid Dynamics (CFD) models based on the Volume of Fluid (VOF) approach. In the present paper, a comparison of the CFD simulation results with the high-resolution experimental data is discussed, with special emphasis on two-phase pressure drops and void fraction distributions. It is shown that the CFD VOF model is able to correctly capture the occurrence of five flow regimes observed in the experiments, namely bubbly flow, plug flow, slug flow, slug-annular flow, and annular flow. However, a good quantitative agreement for pressure drops and void fraction distributions is found in slug flow and slug-annular flow regimes only. The good agreement found only in a limited range of flow regimes demonstrates that there is not a single set of best-practice guidelines for CFD VOF models that can be applied across a wide range of two-phase flow regimes. Also, there is not a single mesh that can be used to simulate all of the flow regimes and a case-specific mesh and time-step convergence study is needed for each individual flow regime. In the current study, optimal mesh size and time step were obtained for a slug flow test case. Hence, good agreement was obtained only for similar flow regimes, leading to significant disagreement with experimental data for test cases with substantially different flow patterns.

The pre-pressure device of the ultrasonic motor plays a vital role in the design of the entire motor structure, the contact state of the stator and rotor of the motor, dynamic properties of the stator, friction and wear characteristics of the rotor; even the mechanical behaviors of the entire electric machinery have a profound impact. Appropriate pre-pressure is conducive to the smooth operation of the ultrasonic motor, so that the output performance remains excellent, reducing wear and effectively extend the service life of the motor. Therefore, the research on pre-stress is of great significance, as it can better optimize the structure of the three-stator ultrasonic motor and lay the foundation for the stable operation of the motor. First, this paper introduces the construction of the motor as a whole and the pre-pressure device briefly described the working mechanism of the motor, and then introduces the influence of the pre-pressure on the stator and rotor contact models, the position of the constant velocity point, and the modal frequency. Finally, the motor output under different pre-pressures is discussed. The performance experiment has determined the optimal pre-pressure interval, which provides help for its subsequent optimization.

With the development of intelligent and integrated electronic devices, leadless integrated sensors have a broad development. One of the most critical processes in TSV (Through Silicon Via) leadless packaging is Au–Au bonding, which the bond strength determines the success or failure of sensor preparation. In this research, the effect of the bonding temperature on the bonding strength was studied for the designed the temperature and pressure integrated sensor. To further increase the bonding strength, plasma treatment of the metal surface was applied. The influence of various plasma atmospheres and treatment times on the surface morphology, surface hydrophilicity, chemical state and the bonding rate were studied. And bonding interfaces under different bonding conditions were characterized. Finally, after 120 s of O2 plasma treatment and bonding for 1 h at 450 °C and 4000 mbar, the bond strength was increased by 68%, reaching 27 MPa, which enhances the feasibility of the preparation of temperature and pressure integrated sensors.

Abstract Background Metabolic dysfunction-associated fatty liver disease (MAFLD) has become the leading chronic liver disease globally, and there are no approved pharmacotherapies to treat this disease. Ectonucleotide pyrophosphatase/phosphodiesterase 1 (Enpp1) has been found to be related to insulin resistance and lipid accumulation. However, the role and mechanism of Enpp1 in the development of MAFLD remain unknown. Results Here we discovered that Enpp1 is lowly expressed in the liver of MAFLD patients by clinical investigation. Knocking out Enpp1 in the liver of mice aggravated obesity, insulin resistance and hepatic steatosis, and these effects were reversed by liver-specific Enpp1 overexpression. Through transcriptomic data mining and experimental validation, we demonstrated that Enpp1 deficiency inhibited the expression of AMPK (energy receptor) and PPARα (nuclear transcription factor for lipid metabolism), thereby promoting the transcription of lipid synthesis factors and mediating the progression of MAFLD. Mechanistically, Enpp1 enhanced the activity of AMPK by increasing the AMP-to-ATP ratio, which in turn raised PPARα levels and promoted the transcription of its downstream lipid metabolism factors. Pharmacological inhibition of AMPK activity abolished the promoting effect of Enpp1 on PPARα protein expression. Conclusions This study indicate that Enpp1 can effectively ameliorate MAFLD through effects on AMPK/PPARα signaling pathway-mediated lipid metabolism, revealing the significance of Enpp1 as a promising therapeutic target against MAFLD.

The study explores the relationship between subway passenger satisfaction and passenger travel behaviour characteristics from the perspective of subway passengers. This study takes Qingdao as an example and designs a questionnaire that includes the basic personal information and travel behaviour characteristics of passengers and evaluates their subway satisfaction. A total of 6340 valid questionnaires were obtained through the combination of online surveys and on-site random surveys. By using the fuzzy synthetic evaluation, the overall score of passenger satisfaction with the Qingdao subway is determined. According to the relationship between passenger satisfaction and travel behaviour characteristics, the chi-square test is used to select the correlation variables group. The results show that there is no significant correlation among the satisfaction of subway passengers, the main means of transportation and the availability of private cars; the frequency of taking the subway is related to the satisfaction of subway passengers; and the purpose of travelling and the reasons for choosing the subway are significantly related to the satisfaction of subway passengers. Finally, based on the analysis of the differences in satisfaction under different conditions, some suggestions were proposed to improve the satisfaction of subway passengers.

The conventional perception of astrocytes as mere supportive cells within the brain has recently been called into question by empirical evidence, which has revealed their active involvement in regulating brain function and encoding behaviors associated with emotions. Specifically, astrocytes in the basolateral amygdala have been found to play a role in the modulation of anxiety-like behaviors triggered by chronic stress. Nevertheless, the precise molecular mechanisms by which basolateral amygdala astrocytes regulate chronic stress–induced anxiety-like behaviors remain to be fully elucidated. In this study, we found that in a mouse model of anxiety triggered by unpredictable chronic mild stress, the expression of excitatory amino acid transporter 2 was upregulated in the basolateral amygdala. Interestingly, our findings indicate that the targeted knockdown of excitatory amino acid transporter 2 specifically within the basolateral amygdala astrocytes was able to rescue the anxiety-like behavior in mice subjected to stress. Furthermore, we found that the overexpression of excitatory amino acid transporter 2 in the basolateral amygdala, whether achieved through intracranial administration of excitatory amino acid transporter 2 agonists or through injection of excitatory amino acid transporter 2-overexpressing viruses with GfaABC1D promoters, evoked anxiety-like behavior in mice. Our single-nucleus RNA sequencing analysis further confirmed that chronic stress induced an upregulation of excitatory amino acid transporter 2 specifically in astrocytes in the basolateral amygdala. Moreover, through in vivo calcium signal recordings, we found that the frequency of calcium activity in the basolateral amygdala of mice subjected to chronic stress was higher compared with normal mice. After knocking down the expression of excitatory amino acid transporter 2 in the basolateral amygdala, the frequency of calcium activity was not significantly increased, and anxiety-like behavior was obviously mitigated. Additionally, administration of an excitatory amino acid transporter 2 inhibitor in the basolateral amygdala yielded a notable reduction in anxiety level among mice subjected to stress. These results suggest that basolateral amygdala astrocytic excitatory amino acid transporter 2 plays a role in in the regulation of unpredictable chronic mild stress-induced anxiety-like behavior by impacting the activity of local glutamatergic neurons, and targeting excitatory amino acid transporter 2 in the basolateral amygdala holds therapeutic promise for addressing anxiety disorders.

Tendon injury is a common and challenging problem in the motor system that lacks an effective treatment, affecting daily activities and lowering the quality of life. Limited tendon regenerative capability and immune microenvironment dyshomeostasis are considered the leading causes hindering tendon repair. The chirality of biomaterials was proved to dictate immune microenvironment and dramatically affect tissue repair. Herein, chiral hierarchical structure hydroxylapatite (CHAP) nanoplates are innovatively synthesized for immunomodulatory purposes and further coated onto polylactic acid electrospinning membranes to achieve long-term release for tendon regeneration adaption. Notably, levorotatory-chiral HAP (L-CHAP) nanoplates rather than dextral-chiral or racemic-chiral exhibit good biocompatibility and bioactivity. In vitro experiments demonstrate that L-CHAP induces macrophage M2 polarization by enhancing macrophage efferocytosis, which alleviates inflammatory damage to tendon stem cells (TDSCs) through downregulated IL-17-NF-κB signaling. Meanwhile, L-CHAP-mediated macrophage efferocytosis also promotes TDSCs proliferation and tenogenic differentiation. By establishing a rat model of Achilles tendon injury, L-CHAP was demonstrated to comprehensively promoting tendon repair by enhancing macrophage efferocytosis and M2 polarization in vivo, finally leading to improvement of tendon ultrastructural and mechanical properties and motor function. This novel strategy highlights the role of L-CHAP in tendon repair and thus provides a promising therapeutic strategy for tendon injury.

Abstract The COVID-19 pandemic profoundly altered socio-economic activities, human behaviors, and crime patterns. However, less is known about how the pandemic and associated restrictions affected cyber-enabled and traditional fraud. Here, we conducted a retrospective analysis using police-recorded crime data in the UK to examine the impact of COVID-19 restrictions and changes in human activity on fraud. Results indicate that following the onset of the lockdown, the number of recorded fraud cases increased by 28.5%, contrasting with traditional property crimes, which dropped by 28.1%. However, the lockdown did not have a significant impact on the long-term trend of fraud. With the lifting of restrictions, fraud gradually regressed to levels approaching those before the pandemic. By inspecting the effects of different government responses and changes in population mobility on various types of fraud, we found that more stringent restrictions were associated with larger increases in most types of cyber-enabled fraud, except for those that rely on offline activities, whereas the impact on traditional fraud was mixed and contingent upon specific opportunity structures. These findings overall align with the assumptions of routine activity theory and provide clear support for its applicability in fraud and cybercrime.

Abstract Oral squamous cell carcinoma (OSCC) is the most frequent type of oral malignancy with high metastasis and poor prognosis. The deubiquitinating enzyme Ubiquitin Specific Peptidase 44 (USP44) regulates the mitotic checkpoint, and its deficiency leads to aneuploidy and increases tumor incidence. However, the role of USP44 in OSCC is not well understood. Herein, we analyzed mRNA sequencing data of OSCC samples downloaded from the TCGA and GEO databases and found that USP44 was decreased in human OSCC tissues and was positively correlated to the survival of OSCC patients. To investigate the biological impact of USP44, we used recombinant lentiviruses to overexpress or knockdown USP44 expression in OSCC cell lines, which were also injected subcutaneously or into the lateral tail vein of Male BALB/c nude mice to model tumorigenesis or lung metastasis in vivo, respectively. The results showed that overexpression of USP44 inhibited malignant cell phenotypes in vitro and suppressed tumor growth and lung metastasis in vivo, while its downregulation had the opposite effects. Comprehensive proteomic analyses through Co-IP mass spectrometry and label-free quantitative LC-MS/MS methods identified 112 differentially expressed proteins positively regulated by USP44, among which 13 were involved in cancer-related pathways including apoptotic signaling and cell cycle regulation. PPI analysis identified Hexamethylene Bis-Acetamide-Inducible Protein 1 (HEXIM1) as the hub protein. Upregulation of USP44 enhanced HEXIM1 protein stability, leading to its higher expression in OSCC cells. Silencing of HEXIM1 further enhanced the malignant phenotype of OSCC cells. At the same time, HEXIM1 knockdown reversed the antitumor effects of USP44. These findings demonstrated that USP44 acted as a critical tumor suppressor in OSCC by inhibiting cell proliferation and metastasis through the stabilization of HEXIM1 protein, suggesting that USP44-HEXIM1 axis is a promising target for OSCC therapy. Graphical Abstract

In this study, ultrafine-grained LaB6–ZrB2 composite ceramics were successfully synthesized by sintering a mixture of self-produced LaB6 nanopowder and commercial ZrB2 nanopowder under high pressure. Compared with their coarse-grained counterparts, ultrafine-grained ceramics exhibit improved mechanical properties. Notably, the ultrafine-grained LaB6–ZrB2 composite ceramic sintered at 4 GPa and 1673 K, with an average grain size of 286 nm, shows optimal mechanical performance characterized by a Vickers hardness of 25.6 GPa, a fracture toughness of 4.1 MPa·m1/2, and an elastic modulus of 338 GPa. Furthermore, the ultrafine-grained LaB6–ZrB2 composite ceramics displayed strong thermal emission, reaching a maximum current density of 27.5 A∙cm−2 at 1773 K. The structural and functional advantages of ultrafine-grained LaB6–ZrB2 composite ceramics render them suitable for potential use in thermionic emission cathodes.

Abstract T cell receptors (TCR) and gene expression provide two complementary and essential aspects in T cell understanding, yet their diversity presents challenges in integrative analysis. We introduce TCRclub, a novel method integrating single-cell RNA sequencing data and single-cell TCR sequencing data using local harmony to identify functionally similar T cell groups, termed ‘clubs’. We applied TCRclub to 298,106 T cells across seven datasets encompassing various diseases. First, TCRclub outperforms the state-of-the-art methods in clustering T cells on a dataset with over 400 verified peptide-major histocompatibility complex categories. Second, TCRclub reveals a transition from activated to exhausted T cells in cholangiocarcinoma patients. Third, TCRclub discovered the pathways that could intervene in response to anti-PD-1 therapy for patients with basal cell carcinoma by analyzing the pre-treatment and post-treatment samples. Furthermore, TCRclub unveiled different T-cell responses and gene patterns at different severity levels in patients with COVID-19. Hence, TCRclub aids in developing more effective immunotherapeutic strategies for cancer and infectious diseases.

Abstract Background Chronic apical periodontitis (CAP) has been linked to the development of atherosclerosis, although the underlying mechanisms remain unclear. This study aimed to investigate the role of gut microbiota disruption in CAP-induced atherosclerosis development, focusing on trimethylamine N-oxide (TMAO)-related metabolites. Methods The study utilized fecal microbiota transplantation (FMT) to transfer gut microbiota from mice with CAP to healthy mice. Atherosclerosis development was assessed by analyzing lesions in the aortic arch and aortic root. Serum lipid and inflammatory factor levels were measured. Composition and diversity of gut microbiota were analyzed using targeted metabolomics, with a focus on the ratio of Firmicutes to Bacteroidetes. The expression of hepatic flavin-containing monooxygenase 3 (FMO3) and serum TMAO levels were also evaluated. Results Mice receiving gut microbiota from CAP mice showed increased atherosclerotic lesions compared to controls, without significant differences in serum lipid or inflammatory factor levels. Alterations in gut microbiota composition were observed, characterized by an increase in the Firmicutes to Bacteroidetes ratio. Peptostreptococcaceae abundance positively correlated with atherosclerosis severity, while Odoribacteraceae showed a negative correlation. No significant differences were found in hepatic FMO3 expression or serum TMAO levels. Conclusions The study confirms the role of gut microbiota disruption in CAP-mediated atherosclerosis development, independent of serum lipid or TMAO levels. Alterations in gut microbiota composition, particularly increased Firmicutes to Bacteroidetes ratio and specific bacterial families, were associated with atherosclerosis severity. These findings highlight the intricate interplay between gut microbiota and cardiovascular health in the context of CAP.

Abstract Current stress and soft switching range are important performance indexes of dual active bridge DC–DC converter. Based on three‐phase shift control, Karush–Kuhn–Tucker (KKT) algorithm is used to solve the optimal control strategy of current stress under soft switching conditions, and the interval construction method that KKT cannot solve is given. Aiming at the problem that all or most of the switching devices lose the zero voltage switching (ZVS) soft switching characteristics when the current dual active bridge (DAB) modulation strategy is seriously mismatched in voltage gain or when the output power is relatively small, an optimized modulation strategy is proposed here, which not only realizes the minimum current stress within the full power range, but also ensures that at least six switching tubes can achieve ZVS on–off. The on‐state and switching losses of the system are further reduced, and the transmission efficiency of the converter is improved.

Abstract Background MicroRNAs (miRNAs) are critical regulators of cancer progression, prompting our investigation into the specific function of miR-630 in pancreatic cancer stem cells (PCSCs). Analysis of miRNA and mRNA expression data in PCSCs revealed downregulation of miR-630 and upregulation of PRKCI, implying a potential role for miR-630 in PCSC function and tumorigenicity. Results Functional assays confirmed that miR-630 directly targets PRKCI, leading to the suppression of the Hedgehog signaling pathway and consequent inhibition of PCSC self-renewal and tumorigenicity in murine models. This study unveiled the modulation of the PRKCI-Hedgehog signaling axis by miR-630, highlighting its promising therapeutic potential for pancreatic cancer (PC) treatment. Conclusions MiR-630 emerges as a pivotal regulator in PCSC biology, opening up new avenues for targeted interventions in PC. The inhibitory effect of miR-630 on PCSC behavior underscores its potential as a valuable therapeutic target, offering insights into innovative treatment strategies for this challenging disease.

Abstract Cybercrime is a complex human behavior and social phenomenon. The COVID-19 pandemic has significantly altered socioeconomic activities, potentially causing changes in crime patterns. However, there has been limited research on how the interaction between the pandemic and socioeconomic factors affects cybercrime. Here we explore the spatiotemporal patterns of police-recorded cybercrime, including fraud and cyber-dependent crime, and employ a machine learning approach to assess the correlation of various factors on cybercrimes at the level of internal regions and police areas within the United Kingdom. Our results show that fraud and cyber-dependent crime are mainly concentrated in London and the southeast region of England. Moreover, following the implementation of the third national lockdown, these areas experienced a noticeable increase, while changes in other regions were not as pronounced. The spatial autocorrelation analysis further suggests that there are significant spatial heterogeneities among regions, with spatiotemporal hotspots centered around London and cold spots mainly concentrated in the northeast of England. Additionally, we found that the identified patterns of fraud and cyber-dependent crime are primarily associated with socioeconomic factors, followed by government containment measures and mobility factors. These findings can help law enforcement and regulatory agencies better understand the social-environmental factors contributing to the prevalence of cybercrime within those areas.

Abstract Head and neck squamous cell carcinoma (HNSCC) is notorious for poor prognoses, and effective biomarkers are urgently needed for early diagnosis of HNSCC patients. We investigate the role of alkaline ceramidase 1 (ACER1) and its relationship with immune infiltration in HNSCC. The differential expression and clinical prognostic significance of ACER1 in HNSCC patients are explored using bioinformatics methods and verified in human HNSCC samples. Genetic mutation, DNA methylation and drug sensitivity linked with ACER1 are examined. The potential biological function of ACER1 co-expression genes is assessed, and a series of functional assays are performed on ACER1in vitro. The results comprehensively reveal a relationship between ACER1 and immune infiltration in HNSCC patients. ACER1 expression is significantly downregulated in HNSCC tissues and closely correlated with better prognoses for HNSCC patients, and this prognostic significance is determined by distinct clinical characteristics. Genetic alteration and promoter hypomethylation of ACER1 are involved in progression of HNSCC, and ACER1 expression is significantly related to several drug sensitivities. Functional analysis shows that ACER1 co-expression genes are mainly enriched in the sphingolipid signaling pathway associated with inhibition of tumorigenesis, leading to better prognoses for HNSCC patients. In vitro, ACER1 overexpression inhibits proliferation and migration, induces apoptosis, and promotes adhesion of Fadu and SCC9 cells. In addition, high ACER1 expression is closely linked with infiltration levels of immune cells, and strongly associated with biomarkers of immune cells in HNSCC, suggesting the important role of ACER1 in regulating tumor immunity in HNSCC patients. In summary, ACER1 may be a useful indicator for diagnosis and prognosis, and may regulate immune infiltration in HNSCC patients, thus promising targeted immunotherapy for HNSCC.

Abstract The obese heart undergoes metabolic remodeling and exhibits impaired calcium (Ca2+) homeostasis, which are two critical assaults leading to cardiac dysfunction. The molecular mechanisms underlying these alterations in obese heart are not well understood. Here, we show that the Rab-GTPase activating protein AS160 is a lipid-responsive regulator of Ca2+ homeostasis through governing lysophosphatidylinositol metabolism and signaling. Palmitic acid/high fat diet inhibits AS160 activity through phosphorylation by NEK6, which consequently activates its downstream target Rab8a. Inactivation of AS160 in cardiomyocytes elevates cytosolic Ca2+ that subsequently impairs cardiac contractility. Mechanistically, Rab8a downstream of AS160 interacts with DDHD1 to increase lysophosphatidylinositol metabolism and signaling that leads to Ca2+ release from sarcoplasmic reticulum. Inactivation of NEK6 prevents inhibition of AS160 by palmitic acid/high fat diet, and alleviates cardiac dysfunction in high fat diet-fed mice. Together, our findings reveal a regulatory mechanism governing metabolic remodeling and Ca2+ homeostasis in obese heart, and have therapeutic implications to combat obesity cardiomyopathy.

Abstract The oviduct epithelium is the initial maternal contact site for embryos after fertilization, offering the microenvironment before implantation. This early gestation period is particularly sensitive to stress, which can cause reduced fertility and reproductive disorders in mammals. Nevertheless, the local impact of elevated stress hormones on the oviduct epithelium has received limited attention to date, except for a few reports on polyovulatory species like mice and pigs. In this study, we focused on the effects of chronic maternal stress on cattle, given its association with infertility issues in this monoovulatory species. Bovine oviduct epithelial cells (BOEC) differentiated at the air–liquid interface (ALI) were stimulated with 250 nmol/L cortisol for 1 or 3 weeks. Subsequently, they were assessed for morphology, bioelectrical properties, and gene expression related to oviduct function, glucocorticoid pathway, cortisol metabolism, inflammation, and apoptosis. Results revealed adverse effects of cortisol on epithelium structure, featured by deciliation, vacuole formation, and multilayering. Additionally, cortisol exposure led to an increase in transepithelial potential difference, downregulated mRNA expression of the major glucocorticoid receptor (NR3C1), upregulated the expression of cortisol-responsive genes (FKBP5, TSC22D3), and significant downregulation of oviductal glycoprotein 1 (OVGP1) and steroid receptors PGR and ESR1. The systematic comparison to a similar experiment previously performed by us in porcine oviduct epithelial cells, indicated that bovine cultures were more susceptible to elevated cortisol levels than porcine. The distinct responses between both species are likely linked to their divergence in the cortisol-induced expression changes of HSD11B2, an enzyme controlling the cellular capacity to metabolise cortisol. These findings provide insights into the species-specific reactions and reproductive consequences triggered by maternal stress.

The climate-conflict linkage is a topic of intense debate within the context of security implications. Previous quantitative studies exploring the causal link between climate variability and conflict risk present divergent findings due to the differences in modeling scale or strategies, such as the non-unified definition of conflict risk and the different settings of independent variables. Here we comprehensively assess the impacts of climate variability on conflict risk in conflict-prone countries worldwide at a unified grid-year level (0.5° × 0.5°) covering 2000–2019. Our analysis indicates that the impacts of climate variability on conflict risk exhibit the heterogeneity across conflict-prone countries. The meta-analysis shows that one standard positive temperature deviation (1σ), increased extreme precipitation, and decreased precipitation induce 0.81 %, 2.53 %, and 1.04 % increment respectively in the risk of conflict incidence, as well as 1.12 %, 2.55 %, and 1.15 % decrement respectively in the risk of conflict onset. Our results contribute to a better understanding of climate-conflict linkages in conflict-prone countries, which may partly explain the divergent findings of current research and highlight the importance of speeding up the work of adaption for global warming.

BackgroundConstipation is a prevalent and recurrent gastrointestinal disorder causing significant discomfort. However, current treatments often prove ineffective. Previous research indicates that the postbiotic derived from a combination of hawthorn and probiotics can alleviate constipation. This study aimed to investigate its mechanisms using loperamide-induced constipation in aged KM mice.MethodsConstipated mice were divided into groups receiving 10% lactulose (Y), hawthorn extract (S), probiotics (F), and the postbiotic of hawthorn-probiotic (FS). UPLC–MS metabolomics identified constituents of F, S, and FS. Network pharmacological analysis identified targets affected by FS. RT-qPCR assessed target expression in mouse colons, along with IL-6 and IL-17A levels. Molecular docking with AutoDock Tools1.5.6 evaluated interactions between FS components and targets. ex vivo colonic organ culture and RT-qPCR assessed target changes. Molecular dynamics analysis further scrutinized interactions. Targeted metabolomics measured short-chain fatty acid levels in mouse stool.ResultsUPLC–MS metabolomics revealed distinct profiles for F, S, and FS, with FS showing decreased toxic substances and increased beneficial ones compared to S. Network pharmacology identified 20 cross-targets of FS in constipation. RT-qPCR showed decreased NR1I2 and SULT1A1 and increased GLP-2r in FS-treated mice. Inflammatory cytokines IL-6 and IL-17A were also reduced. ex vivo colonic organ culture and molecular docking identified effective combinations such as TNF-Baicalin and AQP3-Quinacridone. RMSD, RMSF, and RG analyses indicated favorable interactions between small molecules and targets. Targeted metabolomics revealed differing short-chain fatty acid contents in feces among groups.ConclusionThe postbiotic of hawthorn-probiotic alleviates constipation by regulating intestinal water and sodium metabolism, maintaining the intestinal barrier and gut flora, promoting epithelial cell proliferation, reducing inflammatory responses, and improving short-chain fatty acid metabolism.

Autonomous driving technology has garnered significant attention due to its potential to revolutionize transportation through advanced robotic systems. Despite optimistic projections for commercial deployment, the development of sophisticated autonomous driving systems remains largely experimental, with the effectiveness of neurorobotics-based decision-making and planning algorithms being crucial for success. This paper delivers a comprehensive review of decision-making and planning algorithms in autonomous driving, covering both knowledge-driven and data-driven approaches. For knowledge-driven methods, this paper explores independent decision-making systems, including rule based, state transition based, game-theory based methods and independent planing systems including search based, sampling based, and optimization based methods. For data-driven methods, it provides a detailed analysis of machine learning paradigms such as imitation learning, reinforcement learning, and inverse reinforcement learning. Furthermore, the paper discusses hybrid models that amalgamate the strengths of both data-driven and knowledge-driven approaches, offering insights into their implementation and challenges. By evaluating experimental platforms, this paper guides the selection of appropriate testing and validation strategies. Through comparative analysis, this paper elucidates the advantages and disadvantages of each method, facilitating the design of more robust autonomous driving systems. Finally, this paper addresses current challenges and offers a perspective on future developments in this rapidly evolving field.

Electroacupuncture (EA) has shown promise as a treatment for Functional constipation (FC), with growing evidence suggesting it may enhance gut motility. MicroRNAs (miRNAs) serve as key regulatory molecules mediating host-microbiota interactions. However, the specific fecal miRNAs regulating microbiota composition and metabolism in EA-treated constipated mice, along with their key targets, remain unidentified. We examined fecal microbiome composition, metabolism, and colonic miRNA expression in loperamide-induced constipated mice and EA-treated mice to identify differentially expressed miRNAs and assess their relationships with microbial abundance, metabolism, and gut motility. An antibiotic cocktail and adeno-associated virus were employed to interfere with the gut microbiota and target miRNA in vivo, thereby validating the proposed mechanism. Our results indicate that miR-205-5p, significantly upregulated in fecal and colonic tissues of EA-treated constipated mice, promotes intestinal motility in a microbiome-dependent manner. Specifically, EA promoted the growth of Lactobacillus reuteri, enriched in the feces of constipation-recovered mice, through host-derived miR-205-5p regulation. Furthermore, Lactobacillus reuteri and its tryptophan metabolites (indole-3-acetamide, indole-3-acetic acid, and indole-3-carboxaldehyde) alleviated loperamide-induced constipation. These findings underscore the pivotal role of host-derived miR-205-5p in modulating microbial composition and tryptophan metabolites to enhance intestinal motility through EA.

Epidemiological evidence connecting cooking fuel use to metabolic syndrome (MetS) is lacking. Solid cooking fuel usage and MetS prevalence were prospectively investigated in this study. We included participants in 2011 and 2015 from the China Health and Retirement Longitudinal Study (CHARLS) data. Through cross-sectional and longitudinal studies, we found that the use of solid fuels reduced the risk of MetS in participants compared with clean fuels (cross-sectional study: 2011: Odds ratio (OR): 0.819, 95 %confidence interval (CI): 0.747–0.897, P

Abstract Electrochemical C−N coupling presents a promising strategy for converting abundant small molecules like CO2 and NO3− to produce low‐carbon‐intensity chemicals in a potentially more sustainable route. A prominent challenge is the limited product scope, particularly for organonitrogen chemicals featuring a variety of functional groups, alongside the limited understanding of plausible reaction mechanisms leading up to these products. In light of this, the total electrosynthesis method is reported for producing N, N‐dimethylformamide (DMF), a widespread solvent and commodity chemical, from NO3− and CO2. This method enabled a notable production rate of 1.24 mmol h−1 gcat−1 for DMF employing a hybrid Ag/Cu catalyst. Additionally, an impressive Faradaic efficiency (FE) of 28.6% is attained for DMF through oxidative coupling of dimethylamine using Ag/Cu catalyst. Through a distinctive retrosynthetic experimental analysis, the DMF synthesis pathway is systematically deconstructed, tracing its origins from dimethylamine to methylamine, and ultimately to CO2 and NO3−. The investigation revealed that the hydrogenation of coupled intermediates proves to be the limiting step, rather than the C−N coupling steps in the synthetic pathway. Finally, using a combination of in situ measurements and retrosynthetic analysis, the possible mechanism is elucidated underlying DMF synthesis and identified subsequent routes for system improvement.

Rock abrasiveness is an important factor affecting the tool's lifetime and efficiency in breaking a rock. Characterizing rock abrasiveness helps in the design, optimization, and mean-life prediction of tools. X-ray diffraction, cast thin section analysis, and CERCHAR abrasiveness tests were performed on 18 different sandstones to characterize rock abrasiveness and explore new methods for characterization. The relationship between the mineral composition and microstructure of sandstone and abrasiveness was investigated. The results show that different structural maturities have varying effects on abrasiveness. In addition, the higher the structural maturity, the more the abrasiveness. Furthermore, in sandstones of the same structural maturity, the abrasiveness increases with equivalent quartz content (EQC). The texture coefficient (TC) and CERCHAR abrasiveness index (CAI) of sandstones with the same structural maturity showed a good linear relationship. Moreover, the correlation coefficients considering the combined parameters are above 0.85. Therefore, obtaining the microstructure and mineral composition of sandstone can effectively characterize rock abrasiveness. It also provides a new method for predicting the abrasiveness of the rock in the well.

Abstract Astrocytes, the predominant glial cells in the central nervous system, play essential roles in maintaining brain function. Reprogramming induced pluripotent stem cells (iPSCs) to become astrocytes through overexpression of the transcription factors, NFIB and SOX9, is a rapid and efficient approach for studying human neurological diseases and identifying therapeutic targets. However, the precise differentiation path and molecular signatures of induced astrocytes remain incompletely understood. Accordingly, we performed single-cell RNA sequencing analysis on 64,736 cells to establish a comprehensive atlas of NFIB/SOX9-directed astrocyte differentiation from human iPSCs. Our dataset provides detailed information about the path of astrocyte differentiation, highlighting the stepwise molecular changes that occur throughout the differentiation process. This dataset serves as a valuable reference for dissecting uncharacterized transcriptomic features of NFIB/SOX9-induced astrocytes and investigating lineage progression during astrocyte differentiation. Moreover, these findings pave the way for future studies on neurological diseases using the NFIB/SOX9-induced astrocyte model.

Abstract Angular random walk (ARW), rate random walk (RRW), and bias instability (BI) are the main noise types in inertial measurement units (IMUs) and thus determine the navigation performance of IMUs. BI is the flicker noise, which determines the noise level of an inertial sensor. The traditional error modeling approach involves modeling the ARW and BI processes as RRW or Gauss–Markov (GM) processes, and this approach is applied as a suboptimal filter in the global navigation satellite system (GNSS)/inertial navigation system (INS) extended Kalman filter (EKF). In this paper, the random error identification processes for white noise and colored noise for inertial sensors are separated using the Allan variance and power spectral density methods and the equivalence of the stochastic process differential equations of bias instability and a combination of multiple first-order GM processes are derived. A colored noise compensation method is proposed based on the enhanced EKF model. Experimental results demonstrate that, compared to traditional error models, our proposed model reduces positional drift error in dynamic testing from 195 to 49 m, enhancing positional accuracy by 40.2%. These findings confirm the potential and superiority of our method in complex navigation environments.

Abstract Metabolic dysfunction-associated steatohepatitis (MASH) is a rising global disease signaling the urgent need for non-invasive tests (NITs). Recent work demonstrated that dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) imaging can identify MASH by measuring liver glucose transport rate, K1, and liver CT attenuation. By combining dynamic PET/CT with the serum-based fibrosis-4 (FIB-4) test, we were able to better distinguish clinical MASH from fibrotic subtypes, enabling determination of the core tenets of MASH: steatosis, inflammation, and fibrosis. Future studies using FDG-PET technology can further enable concomitant prediction of MASH severity and extrahepatic comorbidities such as cardiovascular disease.

Abstract Zingiber striolatum Diels is a unique medicine food homology plant native to China. In recent years, due to severe habitat destruction, studying the impact of climate change on the distribution of wild resources is of great significance for the ecological conservation and artificial cultivation of Z. striolatum. This study collected 141 valid species distribution records, and 37 environmental variables, and projected two future climate scenarios (SSP126 and SSP585) for two periods (2050s and 2090s). By employing Pearson analysis, Maximum Entropy Model (MaxEnt), and Geographic Information System (ArcGIS), we predicted the potential suitable habitats for Z. striolatum under present and future climates, as well as identified the dominant environmental variables influencing its distribution. The results indicated that the MaxEnt model performed well (AUC > 0.9) with high accuracy and reliability. The dominant environmental factors included Precipitation of driest quarter (39.0 ~ 473.8 mm), Precipitation of wettest quarter (593.2 ~ 1269.4 mm), Temperature annual range (9.8 ~ 28.6℃), and Mean diurnal range (6.5 ~ 9.6℃). The highly suitable areas for Z. striolatum were mainly distributed in western and southern Yunnan, northern and western Guangxi, Guangdong, Fujian, and central Hainan. Under future climate change, the centroid of the total suitable area for Z. striolatum is projected to shift towards the southwest (Yungui Plateau) at higher elevations.

Abstract Background CD74 is ectopically expressed in many tumors and can regulate tumor immunity. However, there are many gaps in the study of the prognostic value of CD74 expression and immune infiltration in hepatocellular carcinoma (HCC). Methods An online tumor database was searched to obtain data on gene/protein expression. Immune infiltration analysis was performed using the Tumor Immune Estimation Resource and Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer databases. Single-cell data were obtained from the Tissue-specific Gene Expression and Regulation, Single-cell Transcriptomes of Tumor Immune Microenvironment and Tumor Immune Single-cell Hub 2 databases. Results CD74 was highly expressed in HCC patients. HCC patients with high CD74 expression who consumed alcohol or were negative for hepatitis virus had a better prognosis than patients with low CD74 expression. CD74 was mainly enriched in immune response regulation pathways. Both copy number variations in CD74 and CD74 expression patterns affected the infiltration levels of immune cells. Interestingly, CD74 regulated the differentiation of myeloid cells. CD74 in macrophages and dendritic cells (DCs) forms complex networks with malignant cells and hepatic progenitor cell (HPC)-like cells, respectively. High CD74 expression in HPC-like cells and malignant cells significantly decreased the fraction of C-type lectin domain family 9 A (CLEC9A)-cDC1+ DCs and IL-1B+ macrophages, respectively. Their crosstalk subsequently shaped the tumor microenvironment of HCC, possibly through the CD74-MIF axis. Importantly, patients with high CD74 expression presented higher immune scores and achieved good outcomes after receiving immunotherapy. Conclusion High CD74 expression is associated with the abundance of a variety of immune cell types, mediating interactions among tumor and immune cells and shaping the malignant behavior of HCC. In summary, CD74 may be a hallmark for determining the prognosis and immune cell infiltration levels of HCC patients.

Abstract The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (−0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

Abstract Artificial wrinkles, especially those with responsive erasure/regeneration behaviors have gained extensive interest due to their potential in smart applications. However, current wrinkle modulation methods primarily rely on network rearrangement, causing bottlenecks in in situ wrinkle regeneration. Herein, we report a dually cross-linked network wherein [2]rotaxane cross-link can dissipate stress within the wrinkles through its sliding motion without disrupting the network, and quadruple H-bonding cross-link comparatively highlight the advantages of [2]rotaxane modulation. Acid stimulation dissociates quadruple H-bonding and destructs network, swiftly eliminating the wrinkles. However, the regeneration process necessitates network rearrangement, making in situ recovery unfeasible. By contrast, alkaline stimulation disrupts host–guest recognition, and subsequent intramolecular motion of [2]rotaxane dissipate energy to eliminate wrinkles gradually. The always intact network allows for the in situ recovery of surface microstructures. The responsive behaviors of quadruple H-bonding and mechanical bond are orthogonal, and their combination leads to wrinkles with multiple but accurate responsiveness.

Light quality is a common environmental factor which influences the metabolism of biochemical substances in algae and leads to the response of algal growth and development. Pyropia yezoensis is a kind of economic macroalgae that naturally grows in the intertidal zone where the light environment changes dramatically. In the present study, P. yezoensis thalli were treated under white light (control) and monochromatic lights with primary colors (blue, green, and red) for 14 days to explore their physiological response to light quality. During the first 3 days of treatment, P. yezoensis grew faster under blue light than other light qualities. In the next 11 days, it showed better adaptation to green light, with higher growth rate and photosynthetic capacity (reflected by a higher rETRmax = 61.58 and Ek = 237.78). A higher nonphotochemical quenching was observed in the treatment of red light than others for 14 days. Furthermore, the response of P. yezoensis to light quality also results in the difference of photosynthetic pigment contents. The monochromatic light could reduce the synthesis of all pigments, but the reduction degree was different, which may relate to the spectral absorption characteristics of pigments. It was speculated that P. yezoensis adapted to a specific or changing light environments by regulating the synthesis of pigments to achieve the best use of light energy in photosynthesis and premium growth and metabolism. [ABSTRACT FROM AUTHOR]

The rare gastrointestinal tract epithelial polyp known as a pyloric gland adenoma (PGA) is more common in elderly women and uncommon in the duodenum. There are reports of two PGA cases involving high-grade intraepithelial neoplasia. A 75-year-old man was admitted to the hospital as Patient 1 due to “epigastric distension and pain for more than 10 days”. The mucous membrane around the stomach fundus and body was thin, and an electron gastroscopy revealed a large, thick protrusion in the stomach fundus that measured about 6 cm in circumference. High-grade intraepithelial neoplasia and stomach pyloric adenoma are the pathological diagnoses. An outside hospital provided consultation for Patient 2, a 68-year-old male. Pyloric adenoma at duodenal bulb with high-grade intraepithelial neoplasia is the pathological diagnosis. The single layer of cuboidal to low columnar epithelial cells with rounded nuclei and eosinophilic cytoplasm was surrounded by densely packed glands with sporadic cystic dilatation that made up the tumor tissue. The diagnosis of PGA required the immunohistochemical labeling of MUC6. In both cases, simple surgical resection was carried out, and followed up for half a year, no recurrence.

Abstract Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversity inherent in cell‐cell interactions (CCIs). This study introduces STAGUE, an innovative framework that concurrently learns a cell graph structure and a low‐dimensional embedding from ST data. STAGUE employs graph structure learning to parameterize and refine a cell graph adjacency matrix, enabling the generation of learnable graph views for effective contrastive learning. The derived embeddings and cell graph improve spatial clustering accuracy and facilitate the discovery of novel CCIs. Experimental benchmarks across 86 real and simulated ST datasets show that STAGUE outperforms 15 comparison methods in clustering performance. Additionally, STAGUE delineates the heterogeneity in human breast cancer tissues, revealing the activation of epithelial‐to‐mesenchymal transition and PI3K/AKT signaling in specific sub‐regions. Furthermore, STAGUE identifies CCIs with greater alignment to established biological knowledge than those ascertained by existing graph autoencoder‐based methods. STAGUE also reveals the regulatory genes that participate in these CCIs, including those enriched in neuropeptide signaling and receptor tyrosine kinase signaling pathways, thereby providing insights into the underlying biological processes.

Heart disease is a common human disease with high morbidity and mortality. Timely and effective prevention and treatment is an urgent clinical problem. The pathogenesis of heart disease is complex and diverse, involving hypertension, diabetes, atherosclerosis, drug toxicity, thrombosis, infection and other aspects. LL-37, an endogenous peptide, is well known for its antimicrobial properties. In recent years, LL-37 has been found to have a variety of biological functions, including its role in the regulation of atherosclerosis, thrombosis, inflammatory responses, and cardiac hypertrophy. Engineered LL-37-related peptides were developed and proved to regulate the development of disease, which revealed its potential clinical application. A comprehensive review and summary of LL-37 is presented to clarify its role in heart disease and to provide a reference and direction for future research.

Streptococcus mutans (S. mutans) is one of the major etiological agents of dental caries. Interfering with the expression of genes associated with cariogenicity of S. mutans is an effective ecological approach for caries prevention. Thus, understanding the role of genes related to cariogenicity in S. mutans is important. dltD is a conserved gene in Gram-positive bacteria, which is involved in D-alanylation of lipoteichoic acid to modify cell surface charge. In vivo caries experiments have shown significant decreases in the caries severity in rats infected with S. mutans dltD-deficient strain. Although the impact of dltD on bacterial surface charge and division in other Gram-positive bacteria is known, its role in S. mutans biological functions remains unclear. This study aimed to investigate the biological functions of dltD in S. mutans. We examined growth curves, morphology, autolysis, biofilm formation, and cell membrane properties of S. mutans wild strain and dltD-deficient strain. Our results revealed that dltD plays a key role in the growth and autolysis of S. mutans. dltD deletion increased biofilm autolysis, thereby reducing the number of viable bacteria within the biofilm. Furthermore, dltD may have an epistatic effect on cell division and surface charge. Its regulatory network needs to be further elucidated. This study shed light on therole of dltD in the growth of S. mutans, thereby enhancing our understanding of its function.

ABSTRACTThe gut microbiota (GM) and its metabolites affect the host nervous system and are involved in the pathogeneses of various neurological diseases. However, the specific GM alterations under pathogenetic pressure and their contributions to the “microbiota – metabolite – brain axis” in Alzheimer’s disease (AD) remain unclear. Here, we investigated the GM and the fecal, serum, cortical metabolomes in APP/PS1 and wild-type (WT) mice, revealing distinct hub bacteria in AD mice within scale-free GM networks shared by both groups. Moreover, we identified diverse peripheral – central metabolic landscapes between AD and WT mice that featured bile acids (e.g. deoxycholic and isodeoxycholic acid) and unsaturated fatty acids (e.g. 11Z-eicosenoic and palmitoleic acid). Machine-learning models revealed the relationships between the differential/hub bacteria and these metabolic signatures from the periphery to the brain. Notably, AD-enriched Dubosiella affected AD occurrence via cortical palmitoleic acid and vice versa. Considering the transgenic background of the AD mice, we propose that Dubosiella enrichment impedes AD progression via the synthesis of palmitoleic acid, which has protective properties against inflammation and metabolic disorders. We identified another association involving fecal deoxycholic acid-mediated interactions between the AD hub bacteria Erysipelatoclostridium and AD occurrence, which was corroborated by the correlation between deoxycholate levels and cognitive scores in humans. Overall, this study elucidated the GM network alterations, contributions of the GM to peripheral – central metabolic landscapes, and mediatory roles of metabolites between the GM and AD occurrence, thus revealing the critical roles of bacteria in AD pathogenesis and gut – brain communications under pathogenetic pressure.

ABSTRACTMelatonin has various physiological effects, such as the maintenance of circadian rhythms, anti-inflammatory functions, and regulation of intestinal barriers. The regulatory functions of melatonin in gut microbiota remodeling have also been well clarified; however, the role of gut microbiota in regulating host melatonin production remains poorly understood. To address this, we studied the contribution of gut microbiota to host melatonin production using gut microbiota-perturbed models. We demonstrated that antibiotic-treated and germ-free mice possessed diminished melatonin levels in the serum and elevated melatonin levels in the colon. The influence of the intestinal microbiota on host melatonin production was further confirmed by fecal microbiota transplantation. Notably, Lactobacillus reuteri (L. R) and Escherichia coli (E. coli) recapitulated the effects of gut microbiota on host melatonin production. Mechanistically, L. R and E. coli activated the TLR2/4/MyD88/NF-κB signaling pathway to promote expression of arylalkylamine N-acetyltransferase (AANAT, a rate-limiting enzyme for melatonin production), and MyD88 deficiency in colonic epithelial cells abolished the influence of intestinal microbiota on colonic melatonin production. Collectively, we revealed a specific underlying mechanism of gut microbiota to modulate host melatonin production, which might provide novel therapeutic ideas for melatonin-related diseases.

A landslide inventory is essential for numerous applications, including disaster prevention and mitigation. The emergence of advanced satellite technologies and the proliferation of extensive satellite imagery have greatly enhanced the role of deep learning-based semantic segmentation networks in the development of comprehensive landslide inventories. In deep learning, especially in semantic segmentation tasks, the loss function is crucial to guide the training of neural networks. However, typical loss functions have several challenges and shortcomings, including difficulty in handling objects of different scales and neglecting spatial correlation. These drawbacks hinder semantic segmentation networks from solely concentrating on accurately predicting landslide categories with rich semantic information. The spatial details (e.g. small landslides and precise landslide boundary information) in the segmentation results may be lost, reducing the accuracy of landslide extraction. Most studies only focus on training and detection in the local region. Consequently, detecting new unexplored region and detrimental to emergency response is challenging. This study presents a level set loss-guided semantic segmentation network, which can be integrated with different semantic segmentation networks, to address these issues. Three out of five study areas (e.g. Bijie, Jiuzhaigou, and Taitung) are used for model training and accuracy evaluation, while the rest, which are newly unexplored regions (e.g. Hokkaido and Haiti), are used to test the transferability of the proposed loss function in different regions. The study results validate the effectiveness of the designed level set loss in various semantic segmentation networks and in different study areas for landslide extraction.

Placental development is a multifaceted process critical for a fruitful pregnancy, reinforced by a complex network of molecular pathways that synchronize trophoblast migration, differentiation, and overall placental function. This review provides an in-depth analysis of the key signaling pathways, such as Wnt, Notch, TGF-β, and VEGF, which play fundamental roles in trophoblast proliferation, invasion, and the complicated process of placental vascular development. For instance, the Wnt signaling pathway is essential to balance trophoblast stem cell proliferation and differentiation, while Notch signaling stimulates cell fate decisions and invasive behavior. TGF-β signaling plays a critical role in trophoblast invasion and differentiation, predominantly in response to the low oxygen environment of early pregnancy, regulated by hypoxia-inducible factors (HIFs). These factors promote trophoblast adaptation, ensure proper placental attachment and vascularization, and facilitate adequate fetal-maternal exchange. Further, we explore the epigenetic and post-transcriptional regulatory mechanisms that regulate trophoblast function, including DNA methylation and the contribution of non-coding RNAs, which contribute to the fine-tuning of gene expression during placental development. Dysregulation of these pathways is associated with severe pregnancy complications, such as preeclampsia, intrauterine growth restriction, and recurrent miscarriage, emphasizing the critical need for targeted therapeutic strategies. Finally, emerging technologies like trophoblast organoids, single-cell RNA sequencing, and placenta-on-chip models are discussed as innovative tools that hold promise for advancing our understanding of placental biology and developing novel interventions to improve pregnancy outcomes. This review emphasizes the importance of understanding these molecular mechanisms to better address placental dysfunctions and associated pregnancy disorders.