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The precise correction of atmospheric zenith tropospheric delay (ZTD) is significant for the Global Navigation Satellite System (GNSS) performance regarding positioning accuracy and convergence time. In the past decades, many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications. But there is no comprehensive evaluation of these models for the whole China region, which features complicated topography and climate. In this study, we completely assess the typical empirical models, the IGGtropSH model (gridded, non-meteorology), the SHAtropE model (scattered, non-meteorology), and the GPT3 model (gridded, meteorology) using the Crustal Movement Observation Network of China (CMONOC) network. In general, the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63, 37.13/2.20, and 38.27/1.34 mm for the GPT3, SHAtropE and IGGtropSH model, respectively. However, the models had a distinct performance regarding geographical distribution, elevation, seasonal variations, and daily variation. In the southeastern region of China, RMSE values are around 50 mm, which are much higher than that in the western region, approximately 20 mm. The SHAtropE model exhibits better performance for areas with large variations in elevation. The GPT3 model and the IGGtropSH model are more stable across different months, and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs.

Abstract Purpose Delirium has a significant impact on millions of people globally and is closely linked to an unfavorable prognosis for complications. Observational studies suggest that plasma metabolites may play significant roles as markers and effectors of delirium, but causal relationships have not yet been elucidated. Based on the most recent genome-wide association study (GWAS) data, our study aims to present novel insights into the genetic relationship between delirium and plasma metabolites. This investigation offers potential clues for utilizing plasma metabolites as predictors of delirium development. Methods We performed a thorough Mendelian randomization (MR) analysis to investigate the causal relationship between 1,091 individual metabolites and 309 metabolite ratios in plasma with respect to delirium. Inverse-variance weighting (IVW) was employed as the primary estimation method, while MR-Egger and weighed median methods were utilized to assess the robustness of the results. Sensitivity analyses encompassing the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test, Cochran Q test, leave-one-out analysis and MR Egger intercept analysis were also undertaken. Additionally, the MR Steiger test was performed to explore any potential reverse causal effect of metabolites on delirium. Results A total of 63 types of plasma metabolites associated with delirium were detected using the IVW method (p < 0.05). Among the known metabolites, our analysis revealed that two specific metabolites (1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and homovanillate) and a metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) demonstrated a consistent and significant causal relationship with delirium across all analysis methods. Finally, no evidence of pleiotropy was detected in our analysis. Conclusions Our study has revealed a causal association between blood metabolites and the risk of delirium. homovanillate is known to be associated with immunity and redox, 1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) may play a role in lipid regulation. These findings may provide fresh insights into the identification of suitable diagnostic markers and potential treatment strategies focused on specific plasma metabolites in patients with delirium. However, further experiments are required to gain a comprehensive understanding of the underlying biological mechanisms involved.

Abstract Background Penicillium oxalicum is an important fungal agent in the composting of cattle manure, but the changes that occur in the microbial community, physicochemical factors, and potential functions of microorganisms at different time points are still unclear. To this end, the dynamic changes occurring in the microbial community and physicochemical factors and their correlations during the composting of cattle manure with Penicillium oxalicum were analysed. Results The results showed that the main phyla observed throughout the study period were Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes, Halanaerobiaeota, Apicomplexa and Ascomycota. Linear discriminant analysis effect size (LEfSe) illustrated that Chitinophagales and Eurotiomycetes were biomarker species of bacteria and eukaryote in samples from Days 40 and 35, respectively. Bacterial community composition was significantly correlated with temperature and pH, and eukaryotic microorganism community composition was significantly correlated with moisture content and NH4 +-N according to redundancy analysis (RDA). The diversity of the microbial communities changed significantly, especially that of the main pathogenic microorganisms, which showed a decreasing trend or even disappeared after composting. Conclusions In conclusion, a combination of high-throughput sequencing and physicochemical analysis was used to identify the drivers of microbial community succession and the composition of functional microbiota during cattle manure composting with Penicillium oxalicum. The results offer a theoretical framework for explaining microecological assembly during cattle manure composting with Penicillium oxalicum.

Abstract The ribosomal DNA (rDNA) constitutes a remarkably conserved DNA sequence within species, located in the area of the nucleolus, and responsible for coding three major types of rRNAs (18S, 5.8S and 28S). While historical investigations into rDNA focused on its structure and coding capabilities, recent research has turned to explore its functional roles in various biological processes. In this review, we summarize the main findings of rDNA methylation with embryonic development, aging and diseases in multiple species, including epigenetic alterations, related biological processes and potential applications of rDNA methylation. We present an overview of current related research and identify gaps in this field.

Abstract Background Walnut anthracnose caused by Colletotrichum gloeosporioides seriously endangers the yield and quality of walnut, and has now become a catastrophic disease in the walnut industry. Therefore, understanding both pathogen invasion mechanisms and host response processes is crucial to defense against C. gloeosporioides infection. Results Here, we investigated the mechanisms of interaction between walnut fruits (anthracnose-resistant F26 fruit bracts and anthracnose-susceptible F423 fruit bracts) and C. gloeosporioides at three infection time points (24hpi, 48hpi, and 72hpi) using a high-resolution time series dual transcriptomic analysis, characterizing the arms race between walnut and C. gloeosporioides. A total of 20,780 and 6670 differentially expressed genes (DEGs) were identified in walnut and C. gloeosporioides against 24hpi, respectively. Generous DEGs in walnut exhibited opposite expression patterns between F26 and F423, which indicated that different resistant materials exhibited different transcriptional responses to C. gloeosporioides during the infection process. KEGG functional enrichment analysis indicated that F26 displayed a broader response to C. gloeosporioides than F423. Meanwhile, the functional analysis of the C. gloeosporioides transcriptome was conducted and found that PHI, SignalP, CAZy, TCDB genes, the Fungal Zn (2)-Cys (6) binuclear cluster domain (PF00172.19) and the Cytochrome P450 (PF00067.23) were largely prominent in F26 fruit. These results suggested that C. gloeosporioides secreted some type of effector proteins in walnut fruit and appeared a different behavior based on the developmental stage of the walnut. Conclusions Our present results shed light on the arms race process by which C. gloeosporioides attacked host and walnut against pathogen infection, laying the foundation for the green prevention of walnut anthracnose.

Abstract This research analyzes the clinical data, whole-exome sequencing results, and in vitro minigene functional experiments of a child with developmental delay and intellectual disability. The male patient, aged 4, began experiencing epileptic seizures at 3 months post-birth and has shown developmental delay. Rehabilitation training was administered between the ages of one and two. There were no other significant family medical histories. Through comprehensive family exome genetic testing, a hemizygous variant in the 11th exon of the OPHN1 gene was identified in the affected child: c.1025 + 1G > A. Family segregation analysis confirmed the presence of this variant in the patient’s mother, which had not been previously reported. According to the ACMG guidelines, this variant was classified as a likely pathogenic variant. In response to this variant, an in vitro minigene functional experiment was designed and conducted, confirming that the mutation affects the normal splicing of the gene’s mRNA, resulting in a 56 bp retention on the left side of Intron 11. It was confirmed that OPHN1: c.1025 + 1G > A is the pathogenic cause of X-linked intellectual disabilities in the child, with clinical phenotypes including developmental delay and seizures.

Objective Numerous surgical techniques for addressing ulnar coronoid process fractures are available; however, a consensus on the optimal approach remains elusive. This study aimed to use the anterior neurovascular interval approach for the surgical management of ulnar coronoid process fractures and to evaluate its clinical outcomes over short‐ to mid‐term follow‐up. Methods This retrospective clinical study included 20 patients with ulnar coronoid process fractures who were treated using the anterior neurovascular interval approach between January 2018 and December 2022. Participants comprised 16 males and four females, aged between 20 and 64 years (mean, 34.3 ± 12.44 years). Clinical and radiological evaluations were based on elbow joint range of motion (ROM), Visual analogue scale (VAS), and Mayo elbow performance score (MEPS). A paired t‐test was used to compare the pre‐operative and final follow‐up VAS and MEPS scores. Results The follow‐up duration for all patients was at least 12 months (average, 12.65 ± 1.60 months). At the final follow‐up, measurements of elbow ROM included a mean extension of 2.85 ± 3.17°, mean flexion of 135 ± 7.25°, mean pronation of 86.4 ± 4.56°, and mean supination of 84.85 ± 5.54°. All participants reached their target MEPS, with an average score of 97.25 ± 4.72 points, and the final mean VAS score was 0.2 ± 0.52 points. The VAS score was significantly lower and MEPS score was higher at the final follow‐up than those before surgery (p

In order to understand the factors leading to rock burst in steeply-inclined coal seams, based on the mining layout and on-site microseismic monitoring data, the distribution of mine microseismic events and previous rock burst events are deeply analyzed from time and space, and the evolution law of disaster factors under different mining depths is studied. The study shows that the rock burst in steeply-inclined coal seams is mainly caused by stress concentration on the working face due to the hanging roof and intermediate rock pillars, as well as the dynamic disturbance induced by the fracture of the coal and rock mass. The daily advance rate, mining depth, and remaining coal pillars are strongly correlated with the occurrence of rock burst events, and are the main factors leading to rock burst in the mine. During shallow mining, the “prying force” effect of the intermediate rock pillars caused by the horizontal tectonic stress and the self-weight stress on the coal-rock mass is the main factor causing instability and failure of the coal-rock mass. After entering deep mining, the “extrusion” effect of the hanging roof is superimposed on the “prying force” effect of the intermediate rock pillars, and the factors leading to rock burst change to the combined “extrusion + prying force” effect of the roof and pillars.

Abstract Due to the increasing power system capacity, the interruption of large fault currents has gradually become a major challenge in power systems. At the moment, such currents are interrupted mainly via circuit breakers based on the method of active current commutation. However, these types of circuit breakers tend to be costly and oversized. One possible alternative—a fuse‐based circuit breaker with current commutation process enhanced by an external transverse magnetic field (ETMF)—is proposed by the authors. Its main advantage lies in the fast current commutation achieved by an ETMF‐enhanced three‐stage increase of the vacuum arc voltage. The study of the current commutation process is mainly represented by the authors, and the influencing factors of the current commutation—contact opening speed and ETMF current—are discussed. At last, the proposed circuit breaker is verified by an experiment, whose results show that a short‐circuit current of 42 kA can be interrupted within just 2 ms.

Abstract Surface coal development activities include mining and ecological restoration, which significantly impact regional carbon sinks. Quantifying the dynamic impacts on carbon sequestration in vegetation (VCS) during coal development activities has been challenging. Here, we provided a novel approach to assess the dynamics of VCS affected by large-scale surface coal mining and subsequent restoration. This approach effectively overcomes the limitations imposed by the lack of finer scale and long-time series data through scale transformation. We found that mining activities directly decreased VCS by 384.63 Gg CO2, while restoration activities directly increased 192.51 Gg CO2 between 2001 and 2022. As of 2022, the deficit in VCS at the mining areas still had 1966.7 Gg CO2. The study highlights that complete restoration requires compensating not only for the loss in the year of destruction but also for the ongoing accumulation of losses throughout the mining lifecycle. The findings deepen insights into the intricate relationship between coal resource development and ecological environmental protection.

Objective Bone marrow mesenchymal stem cells (BMSCs) show significant potential for osteogenic differentiation. However, the underlying mechanisms of osteogenic capability in osteoporosis‐derived BMSCs (OP‐BMSCs) remain unclear. This study aims to explore the impact of YTHDF3 (YTH N6‐methyladenosine RNA binding protein 3) on the osteogenic traits of OP‐BMSCs and identify potential therapeutic targets to boost their bone formation ability. Methods We examined microarray datasets (GSE35956 and GSE35958) from the Gene Expression Omnibus (GEO) to identify potential m6A regulators in osteoporosis (OP). Employing differential, protein interaction, and machine learning analyses, we pinpointed critical hub genes linked to OP. We further probed the relationship between these genes and OP using single‐cell analysis, immune infiltration assessment, and Mendelian randomization. Our in vivo and in vitro experiments validated the expression and functionality of the key hub gene. Results Differential analysis revealed seven key hub genes related to OP, with YTHDF3 as a central player, supported by protein interaction analysis and machine learning methodologies. Subsequent single‐cell, immune infiltration, and Mendelian randomization studies consistently validated YTHDF3's significant link to osteoporosis. YTHDF3 levels are significantly reduced in femoral head tissue from postmenopausal osteoporosis (PMOP) patients and femoral bone tissue from PMOP mice. Additionally, silencing YTHDF3 in OP‐BMSCs substantially impedes their proliferation and differentiation. Conclusion YTHDF3 may be implicated in the pathogenesis of OP by regulating the proliferation and osteogenic differentiation of OP‐BMSCs.

Abstract Sepsis-associated encephalopathy (SAE) is a significant cause of mortality in patients with sepsis. Despite extensive research, its exact cause remains unclear. Our previous research indicated a relationship between non-hepatic hyperammonemia (NHH) and SAE. This study aimed to investigate the relationship between NHH and SAE and the potential mechanisms causing cognitive impairment. In the in vivo experimental results, there were no significant abnormalities in the livers of mice with moderate cecal ligation and perforation (CLP); however, ammonia levels were elevated in the hippocampal tissue and serum. The ELISA study suggest that fecal microbiota transplantation in CLP mice can reduce ammonia levels. Reduction in ammonia levels improved cognitive dysfunction and neurological impairment in CLP mice through behavioral, neuroimaging, and molecular biology studies. Further studies have shown that ammonia enters the brain to regulate the expression of aquaporins-4 (AQP4) in astrocytes, which may be the mechanism underlying brain dysfunction in CLP mice. The results of the in vitro experiments showed that ammonia up-regulated AQP4 expression in astrocytes, resulting in astrocyte damage. The results of this study suggest that ammonia up-regulates astrocyte AQP4 expression through the gut-brain axis, which may be a potential mechanism for the occurrence of SAE.

Abstract Background Observational studies have reported that gut microbiota composition is associated with metabolic syndrome. However, the causal effect of gut microbiota on metabolic syndrome has yet to be confirmed. Methods We performed a bidirectional Mendelian randomization study to investigate the causal effect between gut microbiota and metabolic syndrome in European population. Summary statistics of gut microbiota were from the largest available genome-wide association study meta-analysis (n = 13,266) conducted by the MiBioGen consortium. The summary statistics of outcome were obtained from the most comprehensive genome-wide association studies of metabolic syndrome (n = 291,107). The inverse-variance weighted method was applied as the primary method, and the robustness of the results was assessed by a series of sensitivity analyses. Results In the primary causal estimates, Actinobacteria (OR = 0.935, 95% CI = 0.878–0.996, P = 0.037), Bifidobacteriales (OR = 0.928, 95% CI = 0.868–0.992, P = 0.028), Bifidobacteriaceae (OR = 0.928, 95% CI = 0.868–0.992, P = 0.028), Desulfovibrio (OR = 0.920, 95% CI = 0.869–0.975, P = 0.005), and RuminococcaceaeUCG010 (OR = 0.882, 95% CI = 0.803–0.969, P = 0.009) may be associated with a lower risk of metabolic syndrome, while Lachnospiraceae (OR = 1.130, 95% CI = 1.016–1.257, P = 0.025), Veillonellaceae (OR = 1.055, 95% CI = 1.004–1.108, P = 0.034) and Olsenella (OR = 1.046, 95% CI = 1.009–1.085, P = 0.015) may be linked to a higher risk for metabolic syndrome. Reverse MR analysis demonstrated that abundance of RuminococcaceaeUCG010 (OR = 0.938, 95% CI = 0.886–0.994, P = 0.030) may be downregulated by metabolic syndrome. Sensitivity analyses indicated no heterogeneity or horizontal pleiotropy. Conclusions Our Mendelian randomization study provided causal relationship between specific gut microbiota and metabolic syndrome, which might provide new insights into the potential pathogenic mechanisms of gut microbiota in metabolic syndrome and the assignment of effective therapeutic strategies.

Abstract Background Cancer is the leading cause of death among older adults. Although the integration of immunotherapy has revolutionized the therapeutic landscape of cancer, the complex interactions between age and immunotherapy efficacy remain incompletely defined. Here, we aimed to elucidate the relationship between aging and immunotherapy resistance. Methods Flow cytometry was performed to evaluate the infiltration of immune cells in the tumor microenvironment (TME). In vivo T cell proliferation, cytotoxicity and migration assays were performed to evaluate the antitumor capacity of tumor antigen-specific CD8+ T cells in mice. Real-time quantitative PCR (qPCR) was used to investigate the expression of IFN-γ-associated gene and natural killer (NK)-associated chemokine. Adoptive NK cell transfer was adopted to evaluate the effects of NK cells from young mice in overcoming the immunotherapy resistance of aged mice. Results We found that elderly patients with advanced non-small cell lung cancer (aNSCLC) aged ≥ 75 years exhibited poorer progression-free survival (PFS), overall survival (OS) and a lower clinical response rate after immunotherapy. Mechanistically, we showed that the infiltration of NK cells was significantly reduced in aged mice compared to younger mice. Furthermore, the aged NK cells could also suppress the activation of tumor antigen-specific CD8+ T cells by inhibiting the recruitment and activation of CD103+ dendritic cells (DCs). Adoptive transfer of NK cells from young mice to aged mice promoted TME remodeling, and reversed immunotherapy resistance. Conclusion Our findings revealed the decreased sensitivity of elderly patients to immunotherapy, as well as in aged mice. This may be attributed to the reduction of NK cells in aged mice, which inhibits CD103+ DCs recruitment and its CD86 expression and ultimately leads to immunotherapy resistance.

Herein, we investigate the influence of heat treatment on microstructure and thermo-physical properties of Al-50wt%Si alloy fabricated by selective laser melting (SLM). Microstructure characterizations reveal that SLM and heat-treated Al-50wt%Si alloys are all characterized by the primary Si and eutectic structure consisting of dominant Al matrix and tiny eutectic Si. However, the size of primary Si monotonously increases with increasing the heat treatment holding time at 550 °C. In addition, the SLM Al-50wt%Si alloy displays a highest coefficient of thermal expansion (CTE) among all examined alloys. As the heat treatment holding time increases, the Si precipitates from the Al(Si)-supersaturated solid solution, leading to the formation of a skeleton-like Si phase, which effectively alleviates the thermal expansion. Furthermore, the SLM Al-50wt%Si alloy exhibits a lowest coefficient of thermal conductivity (CTC), since the significantly increased size of primary Si with increasing the heat treatment holding time leads to a substantial reduction in the number of grain boundaries, which severely restricts the scattering of heat transfer phonons. Moreover, theoretical models are employed to calculate the CTE and CTC. Results indicate that the Schapery lower model provides a better prediction of CTE, and the actual CTC values of Al-50wt%Si alloys after heat treatment are closer to theoretical values. These findings can provide new insights into designing Al matrix composites with low CTE and high CTC through microstructural optimization.

【Objective】The digitization of agriculture and rural areas is considered to be a crucial element in promoting rural revitalization and enhancing agricultural construction, significantly contributing to the increase of farmers' income. The study aims to develop an comprehensive framework for evaluating the digitization of agriculture and rural areas, empirically investigating its effectiveness in income increase and clarifying the action mechanisms. Additionally, it provides policyoriented insights to alleviate the challenges of the "digital divide" and to advance the sophisticated development of the digital economy in agricultural and rural areas.【Methods】The panel data from 31 provinces (region) in China from 2011-2020 was selected, and the Entropy-Weighted TOPSIS Method was applied for assessing the level of digitalization in agriculture and rural areas. The fixed and mediation effects were utilized to investigate the influence and mechanisms of digitalization on farmers'income increase. A threshold model was employed to explore the threshold effects between the digitalization and the increase of farmers' income.【Results】(1) Digitalization in agriculture and rural areas significantly enhances farmers' income; with a 1% increase in digitalization level corresponding to an average income increase of 57.4 CNY for farmers. The positive effect is more pronounced in the eastern regions, while it appears to be inhibitory in the central regions and less evident in promoting income in the western regions, indicating the presence of a "digital divide". (2) Digitalization in agriculture and rural areas contributes to farmers' income increase through multiple channels: fostering diversification of farmers' occupations, accelerating land circulation, enhancing the probability of farmers obtaining financing, and promoting the sales of agricultural products. (3) Digital inclusive finance exhibits significant dual threshold effects between digitalization in agriculture and rural areas and farmers' income increase, with the first threshold value at 33.401 and the second at 148.370. As the threshold interval increases, the impact of digitalization on farmers' income increase demonstrates a "positive U-shaped" relationship, showing as initially inhibitory and subsequently promotive.【Conclusion】Digitalization in agriculture and rural areas effectively facilitates income increase for farmers, however, the challenges of the "digital divide" persist. Consequently, it proposes policy implications such as enhancing digital infrastructure, providing training and education in agricultural digitalization, promoting the development of rural digital inclusive finance, and formulating region-specific digital development strategies to further augment farmers' income.

Hybrid Power-line/Visible-light Communication (HPVC) network has been one of the most promising Cooperative Communication (CC) technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency. Current research on HPVC networks focuses on the performance analysis and optimization of the Physical (PHY) layer, where the Power Line Communication (PLC) component only serves as the backbone to provide power to light Emitting Diode (LED) devices. So designing a Media Access Control（MAC) protocol remains a great challenge because it allows both PLC and Visible Light Communication (VLC) components to operate data transmission, i.e., to achieve a true HPVC network CC. To solve this problem, we propose a new HPC network MAC protocol (HPVC MAC) based on Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) by combining IEEE 802.15.7 and IEEE 1901 standards. Firstly, we add an Additional Assistance (AA) layer to provide the channel selection strategies for sensor stations, so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism, respectively. Based on this, we give a detailed working principle of the HPVC MAC, followed by the construction of a joint analytical model for mathematical-mathematical validation of the HPVC MAC. In the modeling process, the impacts of PHY layer settings (including channel fading types and additive noise feature), CSMA/CA mechanisms of 802.15.7 and 1901, and practical configurations (such as traffic rate, transit buffer size) are comprehensively taken into consideration. Moreover, we prove the proposed analytical model has the solvability. Finally, through extensive simulations, we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62% between the simulation and analytical results.

Abstract Meningeal lymphatic vessels (mLVs) play a pivotal role in regulating metabolic waste from cerebrospinal fluid (CSF). However, the current limitations in field of view and resolution of existing imaging techniques impede understanding the stereoscopic morphology and dynamic behavior of mLVs in vivo. Here, we utilized dual-contrast functional photoacoustic microscopy to achieve wide-field intravital imaging of the lymphatic system, including mLVs and glymphatic pathways. The stereoscopic photoacoustic microscopy based on opto-acoustic confocal features has a depth imaging capability of 3.75 mm, facilitating differentiation between mLVs on the meninges and glymphatic pathways within the brain parenchyma. Subsequently, using this imaging technique, we were able to visualize the dynamic drainage of mLVs and identify a peak drainage period occurring around 20–40 min after injection, along with determining the flow direction from CSF to lymph nodes. Inspiringly, in the Alzheimer’s disease (AD) mouse model, we observed that AD mice exhibit a ~ 70% reduction in drainage volume of mLVs compared to wild-type mice. With the development of AD, there is be continued decline in mLVs drainage volume. This finding clearly demonstrates that the AD mouse model has impaired CSF drainage. Our study opens up a horizon for understanding the brain’s drainage mechanism and dissecting mLVs-associated neurological disorders.

In this research, we delved into the predictive potential of three key markers – the neutrophil-to-lymphocyte ratio (NLR), systemic immune inflammation index (SII), and Onodera’s prognostic nutritional index (OPNI), in assessing lymph node metastases in breast cancer patients who had internal mammary lymph node involvement following thoracoscopic surgery. Our study revealed notable pathological distinctions between the groups with and without metastases, while age, tumor size, and histological grade exhibited no significant differences. The analysis unveiled statistically significant variances in NLR, SII, and OPNI when comparing these two groups. Multivariate analysis pinpointed NLR (OR = 1.503), SII (OR = 1.987), and OPNI (OR = 0.612) as robust predictors of lymph node metastases. Remarkably, combining these markers (AUC: 0.897) substantially enhanced the precision of predicting lymph node metastases compared to individual measurements (NLR: 0.749, SII: 0.717, and OPNI: 0.787). In conclusion, this study underscores the pivotal role of NLR, SII, and OPNI in predicting lymph node metastasis among breast cancer patients with internal mammary lymph node involvement post-thoracoscopic surgery, affirming our utility as reliable independent predictors of this critical clinical outcome.

Recently, rapid economic development of the Yangtze River Economic Belt region in China and the growing problem of regional habitat quality have seriously threatened the process of biodiversity conservation in the Yangtze River Basin. Studying the impact of changes in landscape pattern indexes on habitat quality in the Yangtze River Economic Belt can provide policy insights for biodiversity conservation in the Yangtze River Basin. However, existing studies are still lacking in exploring the effects of changing landscape pattern indices on habitat quality under future scenarios. Based on the land use data of the Yangtze River Economic Belt from 2000 to 2020, this study simulates the land use situation in 2030, and analyzes the landscape pattern indexes and habitat quality during the 30 years, to investigate the impact of landscape pattern indexes on habitat quality at global and local scales through various methods. The results show that landscape patterns were significantly affected by human activities and land use types, with the Yangtze River Economic Belt experiencing increased levels of land use and structural stabilization during the three decades (Shannon Diversity Index increased from 0.90 in 2000 to 0.94 in 2030), fragmentation of the landscape (Landscape fragmentation index increase from 0.094 in 2000 to 0.102 in 2030), and weakened connectivity (contagion index decrease from 48.213 in 2000 to 45.437 in 2030). The Habitat Quality has a large variation in spatial distribution at the county scale, with an average change in habitat quality of 1.04 % from 2000 to 2030, and an overall downward trend. There is a strong localized spatial autocorrelation between landscape pattern indices and habitat quality, with significant spatial heterogeneity and some form of variability at time scales. The results of this study help to further understand the eco-environmental problems of the Yangtze River Economic Belt, and provide theoretical references for the formulation of ecological environmental protection policies and ecological functional area planning.

The reliability of the power supply for 5G base stations (BSs) is increasing. A large amount of BS backup energy storage (BES) remains underutilized. This study establishes a double-layer optimization distribution network (DN) considering BS clusters. An energy consumption characteristics and scheduling ability model of the BSs was established to address the differences in the characteristics of different traffic flows. A double-tier planning model for BS-joining grid market ancillary services is proposed. The upper-layer model addresses optimal tidal flow problems in DNs to minimize integrated operating costs, while the lower-layer model focuses on BES economic optimization. The double-layer model changes into a single-layer linear model using the Karush–Kuhn–Tucker (KKT) condition and the Big M method. Simulation validation using the IEEE-33 node DN proves that this approach can reduce DN operating costs, regulate voltage fluctuations, and guarantee economical and safe DN operation.

As a deep connection between agriculture and energy, the rural integrated energy system (RIES) is a micro-scale supply–distribution–storage–demand network, which provides an important means to realize the utilization of rural clean energy. This paper proposes a day-ahead scheduling model of the RIES to improve its economical effectiveness, where three energy carriers, namely, biogas, electric power, and heat, are integrated. To address the source and load uncertainties composed of photovoltaic power, power load, and heat load, this paper develops a constrained distributionally robust optimization (CDRO), which optimizes the cost expectation related to the extreme distribution to enhance the robustness, while limiting the loss of cost expectation in the historical distribution to ensure economical effectiveness. In addition, an ambiguous set of the source and load uncertainties incorporating 1-norm and infinity-norm constraints is established, which realizes a flexible adjustment for the conservativeness of CDRO. The distributionally robust dispatch is formulated as a deterministic programming in a two-stage solving framework, where the subproblem uploads its extreme probability distribution to the master problem, and these two problems are iteratively optimized until the convergence. Finally, the numerical simulations in a modern farm park prove the performance of the constructed dispatch model and the flexibility of CDRO in balancing the economical effectiveness and robustness of the dispatch.

The advent of the peer-to-peer energy trading has dramatically altered the conventional dynamics of distribution networks. Prosumers, managing independently and engaging in peer-to-peer (P2P) energy exchanges, introduce critical challenges for the economical and secure operations of these networks. This research presents a hierarchical framework designed to manage P2P energy interactions between prosumers and to facilitate flexible operation within the distribution network at the substation level. The upper layer of the model aims to stabilize market prices within the distribution framework, while the lower layer establishes a P2P energy trading platform that upholds fairness and safeguards the privacy of the prosumer participants. A fixed-point mapping approach is utilized to assess the interactions between market stabilization efforts and prosumer bidding strategies within this framework. Through simulations, we illustrate the logical soundness and effectiveness of our proposed model and approach. The findings indicate that the proposed model and the energy trading framework could substantially improve the overall welfare of all stakeholders involved.

With the emergence of substantial amounts of data featuring spatio-temporal characteristics, research on spatio-temporal knowledge has garnered widespread attention. However, the existing knowledge graph embedding methods are difficult to embed spatio-temporal knowledge in continuous time, failing to meet the unique embedding requirements of geographic entities for uninterrupted, constantly changing, and smoothly continuous embeddings. To address this issue, we begin by outlining a version-based representation of spatio-temporal knowledge. Building on this foundation, we propose a novel and effective knowledge graph embedding model called Version Embedding (VerE), which embeds continuous time into vector space, transforms geographic entities into corresponding versions using an attention mechanism, and calculates spatio-temporal knowledge scores under the constraint of version similarity regularization. Subsequently, we introduce a method for link prediction based on unknown time with the aim of assessing the model’s generalization capabilities in time representation. Finally, experiments conducted on two real-world datasets demonstrate significant performance improvement of VerE compared to most existing models, and its ability to maintain stability and continuity in link prediction under unknown time. These experiments confirmed the effectiveness of the proposed model and provided new perspectives and methods for spatio-temporal knowledge embedding.

The performance of asphalt mixtures greatly influences the long-term performance of bridge deck pavements. It is essential to optimise the asphalt mixtures with the best overall performance according to different regional conditions for use in engineering practice. This study proposes a comprehensive assessment method based on the Analytical Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) to evaluate the serviceability of asphalt mixtures from different perspectives. It is used to optimise the best asphalt mixtures. The results show that the skeleton-dense structure asphalt mixture has better engineering applicability than the suspension-dense structure asphalt mixture, and the comprehensive performance of the asphalt mixture decreases with the increase of the nominal maximum particle size. The FCE determines that the total performance of the seven types of asphalt mixtures in the order of their superiority and inferiority are SMA-13 >asphalt mastic sand (AMS)>SMA-10 >AC-25 >AC-13 >AC-16 >AC-20. The study combines qualitative and quantitative factors, which makes the selection of engineering materials more scientific and rigorous and improves the rationality of material suitability evaluation.

Rock mass structure rupture is an important factor that seriously restricts the construction and safe operation of underground space engineering projects such as mines, subways and tunnels. Realizing the identification of rock mass fracture state is one of the hotspots and emphases of current research. In this study, some experiments of sandstone loading failure under different conditions were carried out, the acoustic emission Mel-frequency cepstral coefficient (MFCC) and its fluctuation difference during the whole loading process were extracted, the variation law of the coefficient and its fluctuation difference during the whole loading failure process was studied, and the correlation characteristics of coefficient No.1 (According to the calculation of acoustic emission Mel-frequency cepstral coefficients, it can be seen that a set of acoustic emission Mel-frequency cepstral coefficient includes 12, and coefficient No.1 refers to the first Mel-frequency cepstral coefficient) and its fluctuation difference with the fracture state of sandstone were analyzed. Based on this, a method to identify sandstone fracture state using the Mel-frequency cepstral of acoustic emission was proposed, and the identification criteria was constructed. The identification effect was finally verified. The results show that with loading increase, the coefficient No.1 increases as a whole, and the coefficient value and its discreteness increase significantly in the failure stage and show significant regular fluctuations. The fluctuation difference of the coefficient has the characteristics of periodic variation. The size of the fluctuation difference and its fluctuation can characterize the fracture of sandstone. The overall increase and sudden increase of the fluctuation difference can reflect the macroscopic fracture of sandstone in the unstable deformation and post-peak failure stage, and the sudden increase level of the fluctuation difference can reflect the fracture degree of sandstone. The acoustic emission Mel-frequency cepstral coefficient and its fluctuation difference show good response characteristics to sandstone fracture, which is less affected by different loading conditions, thus they have applicability in reflecting sandstone fracture. The coefficient No.1 and its fluctuation difference have a good correlation with the fracture state of sandstone. The correlation can be divided into three stages as: in the micro-fracture stage of sandstone, the coefficient No.1 and its fluctuation difference are intensively distributed; in the unstable deformation stage just prior to the peak load, the distribution range increases sharply, the overall value increases and the high abnormal value appears; in the post-peak failure stage, the distribution range further increases, the overall value is higher, and more high abnormal values appear. The identification method and criteria of sandstone fracture state were constructed by using the 75% site value and outliers of coefficient No.1 and the 75% site value and outliers of the fluctuation difference of coefficient No.1. The effect of the identification criteria was tested by the confusion matrix of the three-classification model. The accuracy and precision of identification are 90.43% and 94.45%, respectively, which indicate the identification effect is good. The results can provide a reference for the identification of the fracture state of other types of coal and rocks, and for the monitoring and early warning of coal rock instability.

Abstract We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensional (3D) generative modeling method Pocket2Mol, for the de novo design of molecules in spatial perspective for the targeted protein structures, followed by filters for chemical-physical properties and drug-likeness, structure–activity relationship analysis, and clustering to generate top virtual hit scaffolds. In our WDR5 case study, we acquired a focused set of 2029 compounds after a targeted searching within Novartis archived library based on the virtual scaffolds. Subsequently, we experimentally profiled these compounds, resulting in a novel chemical scaffold series that demonstrated activity in biochemical and biophysical assays. Pocket Crafter successfully prototyped an effective end-to-end 3D generative chemistry-based workflow for the exploration of new chemical scaffolds, which represents a promising approach in early drug discovery for hit identification.

Abstract Background The COVID-19 pandemic has significantly increased the risk of burnout among frontline nurses. However, the prevalence of burnout and its associated factors in the post-pandemic era remain unclear. This research aims to investigate burnout prevalence among frontline nurses in the post-pandemic period and pinpoint associated determinants in China. Methods From April to July 2023, a cross-sectional study was carried out across multiple centers, focusing on frontline nurses who had been actively involved in the COVID-19 pandemic. The data collection was done via an online platform. The Maslach Burnout Inventory-Human Services Survey was utilized to evaluate symptoms of burnout. A multivariable logistic regression analysis was used to pinpoint factors associated with burnout. Results Of the 2210 frontline nurses who participated, 75.38% scored over the cut-off for burnout. Multivariable logistic regression revealed that factors like being female [odds ratio (OR) = 0.41, 95%CI = 0.29–0.58] and exercising 1–2 times weekly[OR = 0.53, 95%CI = 0.42–0.67] were protective factors against burnout. Conversely, having 10 or more night shifts per month[OR = 1.99, 95%CI = 1.39–2.84], holding a master’s degree or higher[OR = 2.86, 95% CI = 1.59–5.15], poor health status[OR = 2.43, 95% CI = 1.93–3.08] and [OR = 2.82, 95%CI = 1.80–4.43], under virus infection[OR = 7.12, 95%CI = 2.10-24.17], and elevated work-related stress[OR = 1.53, 95% CI = 1.17-2.00] were all associated with an elevated risk of burnout. Conclusion Our findings indicate that post-pandemic burnout among frontline nurses is influenced by several factors, including gender, monthly night shift frequency, academic qualifications, weekly exercise frequency, health condition, and viral infection history. These insights can inform interventions aimed at safeguarding the mental well-being of frontline nurses in the post-pandemic period.

Obtaining high strength without sacrificing ductility in Mg alloys is of great importance. However, the hexagonal close-packed crystal structure critically limits the deformation of Mg alloys. In this work, novel Mg-1.5Zn-0.5Zr-0.5Sr (wt.%) alloys were fabricated through homogenization, direct extrusion (DE), and extrusion-shearing (ES) processes. The effects of three different processes on microstructures, texture, and mechanical properties were thoroughly investigated. The results show that the average grain size of the alloy was greatly refined after hot extrusion. The alloy after the DE process exhibited a typical bimodal microstructure with dynamic recrystallized (DRXed) grains showing a strong < 101‾0 > fiber texture parallel to extrusion direction (ED), while the small-sized unDRXed grains showed relatively weak basal texture. In addition, the strength was significantly improved, with the value of yield strength (YS) reaching ∼229 MPa and ultimate tensile strength (UTS) reaching ∼262 MPa. This is mainly attributed to grain boundary strengthening and dislocation strengthening. Compared to the DE-processed alloy, the basal texture intensity was significantly decreased and non-basal slip was activated after the ES process, which indicates that the shearing deformation during ES could improve the ductility, with the fracture elongation (FE) increased from ∼13.9 % to ∼21.4 %. This work aims to unveil the deformation mechanisms in Mg-1.5Zn-0.5Zr-0.5Sr alloy and provides an efficient way for preparing micro-alloying Mg alloys with low cost and significant improvement of comprehensive properties.

Abstract Phosphorylation proteomics is the basis for the study of abnormally activated kinase signaling pathways in breast cancer, which facilitates the discovery of new oncogenic agents and drives the discovery of potential targets for early diagnosis and therapy of breast cancer. In this study, we have explored the aberrantly active kinases in breast cancer development and to elucidate the role of PRKCD_pY313 in triple negative breast cancer (TNBC) progression. We collected 47 pairs of breast cancer and paired far-cancer normal tissues and analyzed phosphorylated tyrosine (pY) peptides by Superbinder resin and further enriched the phosphorylated serine/threonine (pS/pT) peptides using TiO2 columns. We mapped the kinases activity of different subtypes of breast cancer and identified PRKCD_pY313 was upregulated in TNBC cell lines. Gain-of-function assay revealed that PRKCD_pY313 facilitated the proliferation, enhanced invasion, accelerated metastasis, increased the mitochondrial membrane potential and reduced ROS level of TNBC cell lines, while Y313F mutation and low PRKCD_pY313 reversed these effects. Furthermore, PRKCD_pY313 significantly upregulated Src_pY419 and p38_pT180/pY182, while low PRKCD_pY313 and PRKCD_Y313F had opposite effects. Dasatinib significantly inhibited the growth of PRKCD_pY313 overexpression cells, and this effect could be enhanced by Adezmapimod. In nude mice xenograft model, PRKCD_pY313 significantly promoted tumor progression, accompanied by increased levels of Ki-67, Bcl-xl and Vimentin, and decreased levels of Bad, cleaved caspase 3 and ZO1, which was opposite to the trend of Y313F group. Collectively, the heterogeneity of phosphorylation exists in different molecular subtypes of breast cancer. PRKCD_pY313 activates Src and accelerates TNBC progression, which could be inhibited by Dasatinib.

ABSTRACT: Objectives: This study aimed to explore the influence of alveolar bone morphologic variables on the outcome of guided bone regeneration (GBR) in the anterior maxilla region. Methods: Twenty-eight patients who received single maxillary anterior tooth delayed implant placed simultaneously with GBR were recruited. Baseline data including age, gender, implant site, implant brand, and bone graft materials were recorded. The resorption rate of the grafted bone (RRGB), labial bone width at 0 mm, 2 mm, and 4 mm apical to the implant platform at Tn (LBW0Tn, LBW2Tn, LBW4Tn), implant angulation (IA), maximum bone graft thickness (MBGT), bone graft volume (BGV), and the initial bone morphologic variables bone concavity depth (BCD) and bone concavity angulation (BCA) were measured. The Pearson correlation analysis, analysis of variance (ANOVA), and optimal binning method were used to explore the potential predictors for GBR. Results: Among 28 patients, the labial bone width of implant and bone graft volume decreased significantly when measured 6 months after surgery. The mean percentage of RRGB was 49.78%. RRGB was not correlated with gender, age, bone graft material, IA, MBGT, bone graft volume at T1, implant site, and implant brand (P > .05). BCD and BCA were each moderately correlated with RRGB (r = −0.872 [P < .001] and r = 0.686 [P < .001], respectively). A BCD ≥1.03 mm and a BCA

Microwave devices, including microwave switches, are more prone to high power discharge in the L-band. In order to improve the multipactor threshold of coaxial SPDT switches, a rectangular coaxial cavity with a ridged structure is proposed. The introduction of the ridged structure can effectively change the motion path and time of secondary electrons from the inner conductor to the surface of the cavity, thus suppressing the resonant discharge effect of electrons. Compared with the method of changing the surface treatment, the multipactor threshold is increased by 4.1 dB with no additional insertion loss. The structure is easy to manufacture and can be extended to other high-power demanding products, such as power dividers and filters.

Abstract Background Combined oxidative phosphorylation deficiency (COXPD) is a severe disorder with early onset and autosomal recessive inheritance, and has been divided into 51 types (COXPD1–COXPD51). COXPD14 is caused by a mutation in the FARS2 gene, which encodes mitochondrial phenylalanyl-tRNA synthetase (mt-PheRS), an enzyme that transfers phenylalanine to its cognate tRNA in mitochondria. Since the first case was reported in 2012, an increasing number of FARS2 variations have been subsequently identified, which present three main phenotypic manifestations: early onset epileptic encephalopathy, hereditary spastic paraplegia, and juvenile-onset epilepsy. To our knowledge, no adult cases have been reported in the literature. Methods We report in detail a case of genetically confirmed COXPD14 and review the relevant literature. Results Approximately 58 subjects with disease-causing variants of FARS2 have been reported, including 31 cases of early onset epileptic encephalopathy, 16 cases of hereditary spastic paraplegia, 3 cases of juvenile-onset epilepsy, and 8 cases of unknown phenotype. We report a case of autosomal recessive COXPD14 in an adult with status epilepticus as the only manifestation with a good prognosis, which is different from that in neonatal or infant patients reported in the literature. c.467C > T (p.T156M) has been previously reported, while c.119_120del (p.E40Vfs*87) is novel, and, both mutations are pathogenic. Conclusions This case of autosomal recessive COXPD14 in an adult only presented as status epilepticus, which is different from the patients reported previously. Our study expands the mutation spectrum of FARS2, and we tended to define the phenotypes based on the clinical manifestation rather than the age of onset.

Abstract Background Environmental lead (Pb) exposure have been suggested as a causative factor for amyotrophic lateral sclerosis (ALS). However, the role of Pb content of human body in ALS outcomes has not been quantified clearly. The purpose of this study was to apply Bayesian networks to forecast the risk of Pb exposure on the disease occurrence. Methods We retrospectively collected medical records of ALS inpatients who underwent blood Pb testing, while matched controlled inpatients on age, gender, hospital ward and admission time according to the radio of 1:9. Tree Augmented Naïve Bayes (TAN), a semi-naïve Bayes classifier, was established to predict probability of ALS or controls with risk factors. Results A total of 140 inpatients were included in this study. The whole blood Pb levels of ALS patients (57.00 μg/L) were more than twice as high as the controls (27.71 μg/L). Using the blood Pb concentrations to calculate probability of ALS, TAN produced the total coincidence rate of 90.00%. The specificity, sensitivity of Pb for ALS prediction was 0.79, or 0.74, respectively. Conclusion Therefore, these results provided quantitative evidence that Pb exposure may contribute to the development of ALS. Bayesian networks may be used to predict the ALS early onset with blood Pb levels.

Background & Aims: The functional maturation of the liver largely occurs after birth. In the early stages of life, the liver of a newborn encounters enormous high-fat metabolic stress caused by the consumption of breast milk. It is unclear how the maturing liver adapts to high lipid metabolism. Liver sinusoidal endothelial cells (LSECs) play a fundamental role in establishing liver vasculature and are decorated with many glycoproteins on their surface. The Slc35a1 gene encodes a cytidine-5'-monophosphate (CMP)-sialic acid transporter responsible for transporting CMP-sialic acids between the cytoplasm and the Golgi apparatus for protein sialylation. This study aimed to determine whether endothelial sialylation plays a role in hepatic vasculogenesis and functional maturation. Methods: Endothelial-specific Slc35a1 knockout mice were generated. Liver tissues were collected for histologic analysis, lipidomic profiling, RNA sequencing, confocal immunofluorescence, and immunoblot analyses. Results: Endothelial Slc35a1-deficient mice exhibited excessive neonatal hepatic lipid deposition, severe liver damage, and high mortality. Endothelial deletion of Slc35a1 led to sinusoidal capillarization and disrupted hepatic zonation. Mechanistically, vascular endothelial growth factor receptor 2 (VEGFR2) in LSECs was desialylated and VEGFR2 signaling was enhanced in Slc35a1-deficient mice. Inhibition of VEGFR2 signaling by SU5416 alleviated lipid deposition and restored hepatic vasculature in Slc35a1-deficient mice. Conclusions: Our findings suggest that sialylation of LSECs is critical for maintaining hepatic vascular development and lipid homeostasis. Targeting VEGFR2 signaling may be a new strategy to prevent liver disorders associated with abnormal vasculature and lipid deposition.

Abstract Backgrounds The pathogenic microorganisms and clinical manifestations of caries and periodontitis are different, caries and periodontitis are usually discussed separately, and the relationship between them is ignored. Clinically, patients prone to dental caries generally have a healthier periodontal status, whereas patients with periodontitis generally have a lower incidence of dental caries. The relationship between dental caries and periodontitis remains unclear. Objectives This study aimed to explain the clinical phenomenon of antagonism between dental caries and periodontitis by exploring the ecological chain and bacterial interactions in dental caries, periodontitis, and other comorbid diseases. Methods The dental plaque microbiomes of 30 patients with oral diseases (10 each with caries, periodontitis, and comorbid diseases) were sequenced and analysed using 16 S rRNA gene sequencing. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) database was used for a differential functional analysis of dental plaque microbial communities in caries, periodontitis, and comorbid diseases. Results The coinfection group had the greatest bacterial richness in dental plaque. The principal coordinate analysis showed that caries and periodontitis were separate from each other, and comorbid diseases were located at the overlap of caries and periodontitis, with most of them being periodontitis. Simultaneously, we compared the microbiomes with significant differences among the three groups and the correlations between the microbiome samples. In addition, KEGG pathway analysis revealed significant differences in functional changes among the three groups. Conclusions This study revealed the composition of the dental plaque microbial communities in caries, periodontitis, and comorbidities and the differences among the three. Additionally, we identified a possible antagonism between periodontitis and caries. We identified a new treatment strategy for the prediction and diagnosis of caries and periodontitis.

Abstract Linear B-cell epitopes (BCEs) play a key role in the development of peptide vaccines and immunodiagnostic reagents. Therefore, the accurate identification of linear BCEs is of great importance in the prevention of infectious diseases and the diagnosis of related diseases. The experimental methods used to identify BCEs are both expensive and time-consuming and they do not meet the demand for identification of large-scale protein sequence data. As a result, there is a need to develop an efficient and accurate computational method to rapidly identify linear BCE sequences. In this work, we developed the new linear BCE prediction method LBCE-BERT. This method is based on peptide chain sequence information and natural language model BERT embedding information, using an XGBoost classifier. The models were trained on three benchmark datasets. The model was training on three benchmark datasets for hyperparameter selection and was subsequently evaluated on several test datasets. The result indicate that our proposed method outperforms others in terms of AUROC and accuracy. The LBCE-BERT model is publicly available at: https://github.com/Lfang111/LBCE-BERT .

Interferometric synthetic aperture radar (InSAR) technology is widely used to create digital elevation models and measure dynamics on the Earth’s surface, including monitoring ground displacements. The lack of or limited-collected ground-truth data, however, often poses a bottleneck in validating the research outcome, particularly at high precision and resolution levels. To mitigate the gap, we introduce a new deep generative model (DGM) for the simulation of linear deformation rate maps. We demonstrate that our adversarial DGM architecture with carefully designed preprocessing and postprocessing modules performs well for InSAR deformation signal synthesis, even when limited data are available. We also introduce a dimensionality reduction method, based on the distance between the real-world and generated image feature vectors, to address the lack of quantitative evaluation for data simulation. Furthermore, we introduce a hybrid evaluation metric integrating quantitative and qualitative measures, which is more intuitive than the existing methods and makes it easier for domain experts to participate in the evaluation. We compare the results of our model with established methods. The comparison result illustrates the superior performance of our proposed method.

A digital controlled unipolar hysteresis current control strategy applied to the single-phase grid-connected inverter is studied in the paper. In view of the problem of current zero-crossing distortion in the traditional unipolar hysteresis current control based on finite state machines (FSM), a new unipolar hysteresis current control strategy based on current decoupling is proposed. By introducing a virtual zero-sequence current, the single-phase full-bridge inverter is decoupled into two independent half-bridge inverter units, which are controlled by two bipolar hysteresis current control loops under the constraints of a finite state machine. Therefore, the operation rules of the FSM ensure the frequency doubling output of the unipolar modulation, and the virtual two-phase decoupled current eliminates the zero-crossing distortion problem of inverter output current. Finally, the effectiveness and feasibility of the proposed method were verified by building a 1kW single-phase full-bridge grid-connected inverter in the laboratory.

With the rapid advancement of Internet of Things (IoT) technology, its applications in road infrastructure have garnered attention. However, challenges persist when applying IoT to road infrastructure monitoring, including insufficient durability of front-end sensors, pavement damage due to sensor embedding, and the redundancy of a vast amount of real-time data, hindering the long-term real-time monitoring of pavements. To address these challenges, this study developed a self-powered distributed intelligent pavement monitoring system based on IoT, encompassing a sensor network, cloud platform, communication network, and power supply system. Considering the specific characteristics of slipform paving for cement concrete pavements, an integrated paving process was proposed, merging embedded sensors with pavement material structures. Through on-site engineering monitoring, the system actively collects and analyzes various data types such as system energy consumption, temperature and humidity, environmental noise, wind speed and direction, and pavement structural vibrations, providing data support for pavement design, maintenance, and vehicle-road synergy applications. Future efforts will continue to promote the application of IoT technology in digital road maintenance, traffic safety, and optimized pavement material structure design.

Abstract Background Peri-implantitis is a polybacterial infection that can lead to the failure of dental implant rehabilitation. This study aimed to profile the microbiome of the peri-implant plaque and estimate the effect of periodontitis on it among 40 Chinese participants with dental implant prostheses and presenting with varying peri-implant and periodontal health states. Methods Submucosal plaque samples were collected from four distinct clinical categories based on both their implant and periodontal health status at sampling point. Clinical examinations of dental implant and remaining teeth were carried out. Metagenomic analysis was then performed. Results The microbiome of the peri-implantitis sites differed from that of healthy implant sites, both taxonomically and functionally. Moreover, the predominant species in peri-implantitis sites were slightly affected by the presence of periodontitis. T. forsythia, P. gingivalis, T. denticola, and P. endodontalis were consistently associated with peri-implantitis and inflammatory clinical parameters regardless of the presence of periodontitis. Prevotella spp. and P. endodontalis showed significant differences in the peri-implantitis cohorts under different periodontal conditions. The most distinguishing function between diseased and healthy implants is related to flagellar assembly, which plays an important role in epithelial cell invasion. Conclusions The composition of the peri-implant microbiome varied in the diseased and healthy states of implants and is affected by individual periodontal conditions. Based on their correlations with clinical parameters, certain species are associated with disease and healthy implants. Flagellar assembly may play a vital role in the process of peri-implantitis.

Abstract Background Low back pain is the leading cause of productivity loss, imposes a significant economic burden on the patients and society. Oxidative stress is considered a critical factor in the complex pathophysiological process and pathogenic mechanism of low back pain. Adjustment dietary pattern can effectively increase antioxidant biomarkers levels within the body to reduce oxidative stress. The composite dietary antioxidant index (CDAI) serves a reliable scoring system for quantifying the potential dietary antioxidant capacity of daily diets. Objective We aim to investigate the potential association between CDAI and low back pain, in order to enhance the management of low back pain through dietary guidance. Methods This study included 17,682 participants from the National Health and Nutrition Examination Survey (NHANES) 1999–2000, 2001–2002, 2003–2004 and 2009–2010. The weighted logistic regression model was used to investigate the association between CDAI and low back pain, while restricted cubic spline (RCS) was employed to examine non-linear trend and cutoffs. Results After adjusting for all confounders, the results showed that there was no significant association between CDAI and low back pain. However, individuals in the highest quartile of CDAI exhibited an 11.7% less likelihood of experiencing a low back pain than those in the lowest quartile (OR = 0.883; 95% CI [0.787,0.991], P = 0.034), and the trend test was also significant (P for trend

ABSTRACTGut microbiota plays an essential role in nonalcoholic fatty liver disease (NAFLD). However, the contribution of individual bacterial strains and their metabolites to childhood NAFLD pathogenesis remains poorly understood. Herein, the critical bacteria in children with obesity accompanied by NAFLD were identified by microbiome analysis. Bacteria abundant in the NAFLD group were systematically assessed for their lipogenic effects. The underlying mechanisms and microbial-derived metabolites in NAFLD pathogenesis were investigated using multi-omics and LC-MS/MS analysis. The roles of the crucial metabolite in NAFLD were validated in vitro and in vivo as well as in an additional cohort. The results showed that Enterococcus spp. was enriched in children with obesity and NAFLD. The patient-derived Enterococcus faecium B6 (E. faecium B6) significantly contributed to NAFLD symptoms in mice. E. faecium B6 produced a crucial bioactive metabolite, tyramine, which probably activated PPAR-γ, leading to lipid accumulation, inflammation, and fibrosis in the liver. Moreover, these findings were successfully validated in an additional cohort. This pioneering study elucidated the important functions of cultivated E. faecium B6 and its bioactive metabolite (tyramine) in exacerbating NAFLD. These findings advance the comprehensive understanding of NAFLD pathogenesis and provide new insights for the development of microbe/metabolite-based therapeutic strategies.

Background: Atopic dermatitis is a common chronic inflammatory skin disease characterized by relapsing eczema and intense itch. DGT is a novel synthetic heterocyclic diterpenoid derived from plants. Its therapeutic potential and mechanism(s) of action are poorly understood. Objectives: We investigated the potent therapeutic effect of DGT on atopic dermatitis, exploring the underlying mechanisms and determining whether DGT is a safe and well-tolerated topical treatment. Methods: We observed anti-inflammatory effects of DGT on tumor necrosis factor-α/interferon-γ–treated human keratinocytes, and anti-allergic effects on immunoglobulin E–sensitized bone marrow–derived mast cells. In vivo, DGT was topically applied to two experimental mouse models of atopic dermatitis: oxazolone-induced sensitization and topically applied calcipotriol. Then the therapeutic effects of DGT were evaluated physiologically and morphologically. Moreover, we performed nonclinical toxicology and safety pharmacology research, including general toxicity, pharmacokinetics, and safety pharmacology on the cardiovascular, respiratory, and central nervous systems. Results: In keratinocytes, DGT reduced the expression of inflammatory factors, promoting the expression of barrier functional proteins and tight junctions and maintaining the steady state of barrier function. DGT also inhibited the activation and degranulation of mast cells induced by immunoglobulin E. Moreover, we found that interleukin-4 receptor-α was the possible target of DGT. Meanwhile, DGT had therapeutic effects on oxazolone/calcipotriol-treated mice. Notably, our pharmacology results demonstrated that DGT was safe and nontoxic in our studies. Conclusion: DGT’s potent anti-inflammatory effects and good safety profile suggest that it is a potential candidate for the treatment of atopic dermatitis.

Abstract Background and Aim According to the European Society of Gastrointestinal Endoscopy (ESGE), gastroscopy should be conducted within 6 h for complete obstruction and 24 h for incomplete obstruction due to food bolus impaction. This study explores whether adults with acute esophageal food bolus (FB) impaction experience adverse outcomes when their time to esophagogastroduodenoscopy (EGD) deviates from the recommended guidelines. Methods A retrospective review was performed on the records of 248 patients who presented at the study site between 2015 and 2022 with symptoms of FB impaction. Results Two hundred and forty‐eight patients underwent EGD for FB impaction. Grade 1 (erosion, ulceration), Grade 2 (tear), and Grade 3 (perforation) complications were present in 31.6%, 6.9%, and 0.8% of cases, respectively. Of the 134 (54.0%) patients with complete obstruction, 51 (38.1%) received EGD within the recommended 6 h. Of the 114 (46%) patients with incomplete obstructions, 93 (81.6%) received EGD within the recommended 24 h. There was no statistically significant correlation between length of stay (LOS) post‐EGD and any of ingestion to presentation time, presentation to EGD time, or ingestion to EGD time. Age and complication level were greater predictors of longer LOS than presentation to EGD time. Patients who presented in hours were significantly more likely to receive EGD within the 6‐ and 24‐h guidelines than those who presented out of hours (50.7% vs 22.0%). Conclusion Neither time to EGD from ingestion of food bolus nor time to EGD from hospital presentation correlated with complication rate, complication severity, or length of stay post‐EGD.

Abstract Mollisols are highly fertile soils and function as significant carbon reservoirs. However, determining their ages and formation processes is challenging due to extensive pedoturbation, which undermines conventional dating methods. Here, we employed luminescence, a light‐sensitive property of minerals widely used in geological dating, to investigate and quantify soil mixing. We analyzed over 2,400 luminescence ages of individual K‐feldspar grains from a Mollisol profile in Northeast China, and for the first time, we were able to determine the intensity of pedoturbation in the Mollisol profile over the past 50,000 years. The results showed that the current pedoturbation can penetrate to a depth of approximately 80 cm, with the intensity decreasing with depth. By identifying a significant intensification in historical pedoturbation, we inferred that the paleoenvironment might be suitable for the formation of Mollisols 16,400 years before present.

Summary: The hemoglobinless Antarctic icefish develop large hearts to compensate for reduced oxygen-carrying capacity, which serves as a naturally occurred model to explore the factors regulating cardiogenesis. Through miRNAome and microRNAome comparisons between an icefish (Chionodraco hamatus) and two red-blooded notothenioids, we discovered significant upregulation of factors in the BMP signaling pathways and altered expression of many miRNAs, including downregulation of 14 miRNAs in the icefish heart. Through knocking down of these miRNAs, we identified two of them, miR-458-3p and miR-144-5p, involved in enlarged heart development. The two miRNAs were found to regulate cardiomyocyte proliferation by targeting bone morphogenetic protein-2 (bmp2). We further validated that activation of the miRNA-bmp2 signaling in the fish heart could be triggered by hypoxic exposure. Our study suggested that a few miRNAs play important roles in the hypoxia-induced cardiac remodeling of the icefish which shed new light on the mechanisms regulating cardiomyocyte proliferation in heart.

The protective effects of docosahexaenoic acid-enriched phosphatidylserine (DHA-PS, 50 or 100 mg/kg) on bisphenol A (BPA)-induced intestinal damage were assessed. The biochemical indices, pathological examination, non-targeted metabolomics integrated with gut microbiota analysis, and immunofluorescence analysis were used to investigate the protective effects of DHA-PS and its underlying regulatory mechanism. The DHA-PS treatment improved the pathology of intestinal tract and increased the expression levels of Claudin-1, Occludin, and ZO-1. In addition, the DHA-PS treatment also notably decreased the levels of interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α, and increased the antioxidant enzymes activities. Moreover, DHA-PS treatment increased the relative abundances of Akkermansia, Alistipes, Butyricicoccus, Coriobacteriaceae_UCG-002, Enterorhabdus, and Lachnospiraceae_UCG-006. DHA-PS treatment alleviated BPA-induced intestinal damage by regulating the kynurenine pathway of tryptophan, lipid, and arachidonic acid metabolisms. Overall, this study suggested that DHA-PS could alleviate BPA-induced intestinal damage by enhancing the intestinal barrier integrity, improving gut microbial composition and metabolites, and inhibiting the TLR4/NF-κB pathways.