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Summary: Castration-resistant prostate cancer (CRPC) presents a significant challenge in treatment following androgen deprivation therapy. This study evaluates Trillin, a compound with antioxidant and anti-inflammatory properties, for its therapeutic potential against CRPC. Using DU145 and PC3 cell lines and a mouse xenograft model, we demonstrate that Trillin effectively inhibits CRPC cell viability, proliferation, migration, and invasion while promoting apoptosis and cell-cycle arrest. Mechanistic investigations reveal that Trillin disrupts NF-κB/COX-2 signaling by downregulating MAP3K11 and COX-2 and inhibiting the nuclear translocation of NF-κB subunits. Additionally, Trillin enhances the expression of miR-145-5p, further modulating pathways critical for CRPC progression. These findings suggest that Trillin may offer a promising alternative approach for targeting CRPC, highlighting its potential as a therapeutic agent to improve patient outcomes.

The study explored the impact of water management on rice cultivation in mercury-contaminated paddy soil. The objective was to analyze the characteristics of mercury translocation by converting flooded soils to dry farming (non-flooded) to alleviate mercury accumulation in rice grains. The experiment was conducted over three consecutive rice-growing seasons, employing two distinct water management models: a continuously flooded rice cultivation mode and a flooded rice planting mode in the first season, followed by a non-flooded rice farming mode in the second and third seasons. The results showed that the change from flooded to non-flooded rice cultivation patterns presented extremely excellent environmental potential for inhibiting the uptake of both methylmercury and total mercury in rice. When transitioning from flooded cultivation to dry farming, the concentration of methylmercury and total mercury in the grains of non-flooded rice decreased by 87.15 % and 9.57 %, respectively, compared to that in the grains of flooded rice. In the third season, the methylmercury and total mercury in the grains of non-flooded rice decreased further by 95.03 % and 69.45 %, respectively. This study verified that the conversion of rice cultivation from flooded to non-flooded is an efficient strategy for suppressing the accumulation of methylmercury in rice grains, and it might offer a promising solution for managing soil mercury risks and ensuring the safety of rice for human consumption.

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components.Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation.Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

To enhance the stability and anti-inflammatory efficacy of dihydromyricetin (DYM), suitable excipients were selected for the development of a self-microemulsifying drug delivery system (SMEDDS). The formulated SMEDDS exhibited remarkable drug loading (117.47 ± 4.5 mg/g) and encapsulation rates (93.98 ± 3.6 %). Transmission electron microscope (TEM) revealed the nanoscale and spherical morphology of DYM-SMEDDS. Stability assessments demonstrated that DYM-SMEDDS maintained a consistent uniform small particle size after various cycles of exposure. In vitro release curve exhibited that DYM-SMEDDS released 91.27 ± 1.44 % of DYM within 24 h, surpassing the suspension by 2-fold. Furthermore, in vivo studies indicated that DYM-SMEDDS significantly inhibited the levels of pro-inflammatory factors, while promoting the activity of antioxidant enzymes (p

Short-term energy-consumption prediction is the basis of anomaly detection, real-time scheduling, and energy-saving control in manufacturing systems. Most existing methods focus on single-node energy-consumption prediction and suffer from difficult parameter collection and modelling. Although several methods have been presented for multinode energy-consumption prediction, their prediction performance needs to be improved owing to a lack of appropriate knowledge guidance and learning networks for complex spatiotemporal relationships. This study presents a symmetric spatiotemporal learning network (SSTLN) with a sparse meter graph (SMG) (SSTLN-SMG) that aims to predict multiple nodes based on energy-consumption time series and general process knowledge. The SMG expresses process knowledge by abstracting production nodes, material flows, and energy usage, and provides initial guidance for the SSTLN to extract spatial features. SSTLN, a symmetrical stack of graph convolutional networks (GCN) and gated linear units (GLU), is devised to achieve a trade-off not only between spatial and temporal feature extraction but also between detail capture and noise suppression. Extensive experiments were performed using datasets from an aluminium profile plant. The experimental results demonstrate that the proposed method allows multinode energy-consumption prediction with less prediction error than state-of-the-art methods, methods with deformed meter graphs, and methods with deformed learning networks.

Users of the digital image correlation method are faced with the problem of poor operability, low repeatability, and lack of standardized specifications for spraying speckles. To solve the problem, the research proposed a rock deformation measurement method that obviates the need to spray speckles. A local binary model was established by using the local binary pattern (LBP) operator based on deep texture features on rock surfaces. The resulting LBP digital speckle pattern can substitute artificial speckle patterns and demonstrates high quality and strong applicability. Based on the LBP digital speckle pattern, the target tracking algorithm was employed to achieve non-contact measurement of the dynamic displacements of rocks. The feasibility and effectiveness of the algorithm in practical application were verified by conducting shear tests on granite and siltstone. Test results show that the deformation characteristics in the displacement nephograms are in line with the measured data pertaining to rock fracturing and conform to the basic characteristics of the shear failure of rocks. The deformation measurement method based on surface texture information can realize non-contact displacement measurement of rocks under conditions without speckles: this obviates the influence of the quality of sprayed speckles on the accuracy of the measurement of deformation.

To understand the mechanism of dark abiotic mercury (Hg) methylation by algae-derived dissolved organic matter (DOM) and effectively manage the environmental risks of mercury methylation in aquaculture areas, we investigated the influence of subfractions of DOM released from algae (Ulothrix sp.) decomposition on mercury methylation. The results showed that the hydrophobic basic component (HOB) in DOM exhibited the most substantial promotion effect on Hg methylation. The methylmercury (MeHg) production in the HOB treatment increased significantly, while the production rate of MeHg (%MeHg represented the concentration ratio of MeHg to THg) in the six subfractions treated solutions decreased significantly with the increase of Hg concentration. The change of the %MeHg was more evident at low Hg concentration, indicating the limited number of binding sites and methyl donors on DOM. As a consequence, Hg(Ⅱ) in the solution could not be converted into MeHg in equal proportion. Furthermore, the production of MeHg in solution was significantly reduced by the decomposed algae DOM, and its concentration was in the range of 0.017–0.085 ng·L−1 (significantly lower than undecomposed algal). The difference between the decomposed and the non-decomposed algae DOM reached a significant level (P

Cell misuse and cross-contamination can affect the accuracy of cell research results and result in wasted time, manpower and material resources. Thus, cell line identification is important and necessary. At present, the commonly used cell line identification methods need cell staining and culturing. There is therefore a need to develop a new method for the rapid and automated identification of cell lines. Raman spectroscopy has become one of the emerging techniques in the field of microbial identification, with the advantages of being rapid and noninvasive and providing molecular information for biological samples, which is beneficial in the identification of cell lines. In this study, we built a library of Raman spectra for gastric mucosal epithelial cell lines GES-1 and gastric cancer cell lines, such as AGS, BGC-823, HGC-27, MKN-45, MKN-74 and SNU-16. Five spectral datasets were constructed using spectral data and included the full spectrum, fingerprint region, high-wavelength number region and Raman background of Raman spectra. A stacking ensemble learning model, SL-Raman, was built for different datasets, and gastric cancer cell identification was achieved. For the gastric cancer cells we studied, the differentiation accuracy of SL-Raman was 100% for one of the gastric cancer cells and 100% for six of the gastric cancer cells. Additionally, the separation accuracy for two gastric cancer cells with different degrees of differentiation was 100%. These results demonstrate that Raman spectroscopy combined with SL-Raman may be a new method for the rapid and accurate identification of gastric cancer. In addition, the accuracy of 94.38% for classifying Raman spectral background data using machine learning demonstrates that the Raman spectral background contains some useful spectral features. These data have been overlooked in previous studies.

Fiscal decentralization, widely believed to be one essential tool to boost economic growth, is typically presented as something that works for developed countries. However, this needs to be investigated, which is what this paper aims to do. This paper investigates the relationship between fiscal decentralization and economic growth, specifically focusing on its applicability in both developed and developing countries. Using cross-sectional data from 23 African and 23 OECD countries, we employ two-stage estimation methods, including two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML), to address concerns related to endogeneity. The inclusion of instruments representing country size, ethnoreligious diversity, and administrative structure enhances the analysis. The dependent variable is based on average values for the five-year period between 2015 and 2019, while the explanatory variables are derived from data in 2017, representing the midpoint of the 2013–2021 period. The results highlight the effectiveness of the 2SLS method in estimating the relationship between fiscal decentralization, control variables, instrument variables, and per capita GDP. Empirical findings indicate significant positive impacts of both expenditure decentralization and revenue decentralization on per capita GDP, holding true for both developed and developing countries, with a slightly stronger effect observed in the latter. These results underscore the potential benefits of fiscal decentralization across diverse economies and offer valuable insights for policymakers.The study uses cross-sectional data from 23 African and 23 OECD countries and applies two-stage estimation methods to effectively address the endogeneity issue in the modeling. A variety of such methods in two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML) are applied and compared against the ordinary least squares (OLS) method. Variables that represent the size, the ethnoreligious diversity and the type of administrative structure of the countries are employed as instruments. The 2SLS method proved to excellently estimate the relationship between the fiscal decentralization terms as well as other control and instrument variables and the per capita GDP. The findings from the empirical analysis showed that both expenditure decentralization and revenue decentralization have significant positive impacts on per capita GDP of a country. This relationship holds not only for developed countries but also for developing ones, even to a slightly better degree in the latter.

Selecting a proper set of covariates is one of the most important factors that influence the accuracy of digital soil mapping (DSM). The statistical or machine learning methods for selecting DSM covariates are not available for those situations with limited samples. To solve the problem, this paper proposed a case-based method which could formalize the covariate selection knowledge contained in practical DSM applications. The proposed method trained Random Forest (RF) classifiers with DSM cases extracted from the practical DSM applications and then used the trained classifiers to determine whether each one potential covariate should be used in a new DSM application. In this study, we took topographic covariates as examples of covariates and extracted 191 DSM cases from 56 peer-reviewed journal articles to evaluate the performance of the proposed case-based method by Leave-One-Out cross validation. Compared with a novices’ commonly-used way of selecting DSM covariates, the proposed case-based method improved more than 30% accuracy according to three quantitative evaluation indices (i.e., recall, precision, and F1-score). The proposed method could be also applied to selecting the proper set of covariates for other similar geographical modeling domains, such as landslide susceptibility mapping, and species distribution modeling.

5G is the fifth generation wireless network, with a set of characteristics, such as high bandwidth and data rates, massive connectivity, broad coverage, and low latency. The scenarios of using 5G include enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), and ultra-Reliable and Low-Latency Communications (uRLLC). 5G is expected to support a wide variety of applications, such as city management, healthcare, transportation, agriculture, and energy management. In this paper, we conducted a systematic mapping study that covers the literature published between January 2012 and December 2019 regarding using 5G in smart cities. The scenarios, architecture, technologies, challenges, and lessons learned of using 5G in smart cities are summarized and further analyzed based on 32 selected studies, and the results are that: (1) The studies are distributed over 27 publication venues. 17 studies report results based on academic studies and 13 studies use demonstration or toy examples. Only 2 studies report using 5G in smart cities based on industrial studies. 16 studies include assumptions of 5G network design or smart city scenarios. (2) The most discussed smart city scenario is transportation, followed by public safety, healthcare, city tourism, entertainment, and education. (3) 28 studies propose and/or discuss the architecture of 5G-enabled smart cities, containing smart city architecture (treating 5G as a component), 5G network architecture in smart cities, and business architecture of using 5G in smart cities. (4) The most mentioned 5G-related technologies are radio access technologies, network slicing, and edge computing. (5) Challenges are mainly about complex context, challenging requirements, and network development of using 5G in smart cities. (6) Most of the lessons learned identified are benefits regarding 5G itself or the proposed 5G-related methods in smart cities. This work provides a reflection of the past eight years of the state of the art on using 5G in smart cities, which can benefit both researchers and practitioners in this field.

In this study, the catalytic oxidation of formaldehyde present in ambient air at room temperature over MnO2 solids prepared by a simple redox reaction was investigated. For HCHO initial concentrations in the 0.49–4.02 mg/m3 range, the obtained MnO2-MS catalyst provided 100% conversion of HCHO at 25 °C in ~1 h which was kept constant for additional 10 h time-on-stream. The characterization of MnO2-MS showed that the large concentration of manganese vacancies (defect sites) and active oxygen species on the surface of the layered MnO2 play a key role for the oxidation of HCHO performance of the catalyst.

Summary: Volatile anesthetics induce hyperactivity during induction while producing anesthesia at higher concentrations. They also bidirectionally modulate many neuronal functions. However, the neuronal mechanism is unclear. The effects of isoflurane on sodium channel currents were analyzed in acute mouse brain slices, including sodium leak (NALCN) currents and voltage-gated sodium channels (Nav) currents. Isoflurane at sub-anesthetic concentrations increased the spontaneous firing rate of CA3 pyramidal neurons, whereas anesthetic concentrations of isoflurane decreased the firing rate. Isoflurane at sub-anesthetic concentrations enhanced NALCN conductance but minimally inhibited Nav currents. Isoflurane at anesthetic concentrations depressed Nav currents and action potential amplitudes. Isoflurane at sub-anesthetic concentrations depolarized resting membrane potential (RMP) of neurons, whereas hyperpolarized the RMP at anesthetic concentrations. Isoflurane at low concentrations induced hyperactivity in vivo, which was diminished in NALCN knockdown mice. In conclusion, enhancement of NALCN by isoflurane contributes to its bidirectional modulation of neuronal excitability and the hyperactivity during induction. : Anesthesiology; Neuroscience Subject Areas: Anesthesiology, Neuroscience

Because Pb isotopes can be used for tracing, they are widely used in many disciplines. The detection and analysis of Pb isotopes of bulk samples are usually conducted using thermal ionization mass spectrometer (TIMS) and multiple-collector inductively coupled plasma mass spectrometer (MC-ICP-MS), both of which need external reference materials with known isotopic compositions to correct for the mass discrimination effect produced during analysis. NIST NBS 981 is the most widely used reference material for Pb isotope analysis; however, the isotopic compositions reported by various analytical laboratories, especially those using TIMS, vary from each other. In this study, we statistically evaluated 229 reported TIMS analysis values collected by GeoReM in the last 30 years, 176 reported MC-ICP-MS analysis values, and 938 MC-ICP-MS analysis results from our laboratory in the last five years. After careful investigation, only 40 TIMS results were found to have double or triple spikes. The ratios of the overall weighted averages, 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb, obtained from 40 spiked TIMS reports and 1114 MC-ICP-MS results of NIST NBS 981 isotopes were 16.9406 ± 0.0003 (2s), 15.4957 ± 0.0002 (2s), and 36.7184 ± 0.0007 (2s), respectively.

Quantitative structure–activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application of machine learning (ML) algorithms has emerged as an effective strategy. In this study, we applied 12 algorithms, namely, k-nearest neighbor (KNN), kernel k-nearest neighbors (KKNN), support vector machine (SVM), random forest (RF), stochastic gradient boosting (GBM), cubist, bagged multivariate adaptive regression splines (Bagged MARS), eXtreme gradient boosting (XGBoost), boosted generalized linear model (GLMBoost), boosted generalized additive model (GAMBoost), bayesian regularized neural networks (BRNN), and recursive partitioning and regression trees (CART) to build ML models for 225 mixture toxicity of azole fungicides towards Auxenochlorella pyrenoidosa. A total of 36 single ML models and 12 consensus models were developed. The results indicated that models employing concentration addition (CA), independent action (IA), and molecular descriptors (MD) as variables demonstrated superior predictive abilities. The consensus model combining SVM and RF algorithms (labeled as CM0) demonstrated the highest level of accuracy in fitting the data, with a coefficient of determination of 0.980. Additionally, it showed strong predictive abilities when tested with external data, achieving an external R2 value of 0.945 and a Concordance Correlation Coefficient of 0.967. This study provides a positive contribution to the ecological risk assessment of a mixture of azole fungicides.

Microbially-mediated arsenic biotransformation plays a pivotal role in the biogeochemical cycling of arsenic; however, the presence of arsenic biotransformation genes (ABGs) in urban dust remains unclear. To investigate the occurrence and spatiotemporal distributions of ABGs, a total of one hundred and eighteen urban dust samples were collected from different districts of Xiamen city, China in summer and winter. Although inorganic arsenic species, including arsenate [As(V)] and arsenite [As(III)], were found to be predominant, the methylated arsenicals, particularly trimethylarsine oxide [TMAs(V)O] and dimethylarsenate [DMAs(V)], were detected in urban dust. Abundant ABGs were identified in urban dust via AsChip analysis (a high-throughput qPCR chip for ABGs), of which As(III) S-adenosylmethionine methyltransferase genes (arsM), As(V) reductase genes (arsC), As(III) oxidase genes (aioA), As(III) transporter genes (arsB), and arsenic-sensing regulator genes (arsR) were the most prevalent, collectively constituting more than 90 % of ABGs in urban dust. Microbes involved in arsenic methylation were assigned to bacteria (e.g., Actinomycetes and Alphaproteobacteria), archaea (e.g., Halobacteria), and eukaryotes (e.g., Chlamydomonadaceae) in urban dust via the arsM amplicon sequencing. Temperature, a season-dependent environmental factor, profoundly affected the abundance of ABGs and the composition of microbes involved in arsenic methylation. This study provides new insights into the presence of ARGs within the urban dust.

Circular RNAs (circRNAs) are a distinct class of non-coding RNAs that play regulatory roles in the initiation and progression of tumors. With advancements in transcriptome sequencing technology, numerous circRNAs that play significant roles in tumor-related genes have been identified. In this study, we used transcriptome sequencing to analyze the expression levels of circRNAs in normal adjacent tissues, primary colorectal cancer (CRC) tissues, and CRC tissues with liver metastasis. We successfully identified the circRNA hsa_circ_0020134 (circ0020134), which exhibited significantly elevated expression specifically in CRC with liver metastasis. Importantly, high levels of circ0020134 were associated with a poor prognosis among patients. Functional experiments demonstrated that circ0020134 promotes the proliferation and metastasis of CRC cells both in vitro and in vivo. Mechanistically, upregulation of circ0020134 was induced by the transcription factor, PAX5, while miR-183-5p acted as a sponge for circ0020134, leading to partial upregulation of PFN2 mRNA and protein levels, thereby further activating the downstream TGF-β/Smad pathway. Additionally, downregulation of circ0020134 inhibited epithelial-mesenchymal transition (EMT) in CRC cells, which could be reversed by miR-183-5p inhibitor treatment. Collectively, our findings confirm that the circ0020134-miR-183-5p-PFN2-TGF-β/Smad axis induces EMT transformation within tumor cells, promoting CRC proliferation and metastasis, thus highlighting its potential as a therapeutic target for patients with CRC liver metastasis.

The composite technology based on friction stir processing (FSP) can enhance the strength of Al alloys while retaining the original toughness and ductility of Al alloys, thus achieving an improvement in the overall performance of the composites. Ni/Al composites were prepared in three typical Al matrixes by optimized FSP, and the effect of in situ generated intermetallic compounds on the strengthening of different Al substrates during the FSP was investigated. It was found that the reinforcing phase of Ni/Al composites was mainly in situ generation of Al3Ni intermetallic compound using energy dispersive spectrometry (EDS) and transmission electron microscopy (TEM), and the more the number and more uniform the distribution of Al3Ni reinforcing phase, the better the mechanical properties of Ni/Al composites. The results indicate that the Ni/Al composites formed from different series of Al alloy matrix, the Ni/6061Al composite has the most remarkable microstructure uniformity, the greatest strength increase and the least elongation decrease, which is conducive to improving its strength without affecting the processing properties of the 6061 Al alloy. The finding opens new opportunities for the preparation of Ni/Al composites with excellent properties from 6061 Al alloys.

An E3 ubiquitin ligase gene (Genbank accession no.: MD01G1010900) was cloned from the Royal Gala apple genome (Malusxdomestica Borkh.). Sequence analysis showed that the length of the MdPUB29 gene was 1 275 bp, encoding 424 amino acids. Phylogenetic tree analysis indicated that the apple E3 ubiquitin ligase exhibited the greatest sequence similarity to Pyrus×bretschneideri. The predicted protein structural domain of MdPUB29 showed that it contained a U-box domain. qRT-PCR analysis showed that MdPUB29 was expressed widely in different tissues of the Royal Gala apple species, and was highly expressed in the root, while the expression of MdPUB29 was significantly inhibited by exogenous NaCl. Immunoblotting assays revealed that MdPUB29 protein abundance in tissue cultures of the Royal Gala apple accumulated under NaCl stress conditions. Three-dimensional protein structure prediction indicated that MdPUB29 was highly homologous with AtPUB29. The growing potential of MdPUB29-expressing apple calli and Arabidopsis were much stronger than that of the control under salt stress conditions, suggesting that MdPUB29 may positively regulate salt tolerance.

Study Objective: To explore the risk factors associated with local regeneration of the treated uterine fibroids (UFs) after microwave ablation (MWA) and to develop a nomogram model for predicting the risk of local regeneration., Design: Retrospective study., Setting: The Eighth Affiliated Hospital of Sun Yat-Sen University., Patients: Patients with UFs who underwent MWA at our hospital between October 2020 and April 2023 were included., Intervention: MWA was used for the treatment of UFs., Measurements and Main Results: A total of 47 patients with 68 fibroids were included into this study. Over a median follow-up of 13 months (interquartile range, 8-22 months), local regeneration occurred in 11 UFs. The clinical and imaging characteristics of these patients were recorded and compared. Risk factors for local regeneration were determined through univariate and multivariate Cox regression analysis. Multivariate analysis revealed that the fertility desires, larger size of UFs (≥95.3 cm 3 ), and hyperenhancement of UFs on contrast-enhanced ultrasound were independent risk factors for local regeneration after MWA. A predictive nomogram was constructed to predict the local regeneration after MWA of UFs. The concordance index (C-index) (C-index, 0.924; internal validation C-index, 0.895) and the 1- and 2-year area under the curve values (0.962, 0.927) all indicated that the nomogram had good predictive performance. Calibration and decision curve analysis curves further confirmed the model's accuracy and clinical utility., Conclusion: Fertility desires, larger size of UFs, and hyperenhancement on contrast-enhanced ultrasound were independent predictors of UFs local regeneration after MWA in our study. The nomogram constructed based on the abovementioned independent risk factors may help predict which UFs will develop local regeneration after MWA., (Copyright © 2024 AAGL. Published by Elsevier Inc. All rights reserved.)

Prompt learning has demonstrated impressive efficacy in the fine-tuning of multimodal large models to a wide range of downstream tasks. Nonetheless, applying existing prompt learning methods for the diagnosis of neurological disorder still suffers from two issues: (i) existing methods typically treat all patches equally, despite the fact that only a small number of patches in neuroimaging are relevant to the disease, and (ii) they ignore the structural information inherent in the brain connection network which is crucial for understanding and diagnosing neurological disorders. To tackle these issues, we introduce a novel prompt learning model by learning graph prompts during the fine-tuning process of multimodal models for diagnosing neurological disorders. Specifically, we first leverage GPT-4 to obtain relevant disease concepts and compute semantic similarity between these concepts and all patches. Secondly, we reduce the weight of irrelevant patches according to the semantic similarity between each patch and disease-related concepts. Moreover, we construct a graph among tokens based on these concepts and employ a graph convolutional network layer to extract the structural information of the graph, which is used to prompt the pre-trained multimodal models for diagnosing neurological disorders. Extensive experiments demonstrate that our method achieves superior performance for neurological disorder diagnosis compared with state-of-the-art methods and validated by clinicians., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.)

Severe burns related to fires and explosions of lithium-ion batteries of electric motorcycles have not been reported to date. We retrospectively studied 419 patients admitted to our burn intensive care unit from January 2016 to December 2021. Of these 419 patients, 26 (22 male, 4 female; median age, 42 years) had burns related to lithium-ion battery fires and explosions, and all of their injury characteristics were similar to those of traditional flame burns. Lithium-ion battery-related burns were the eighth most common cause of burn injuries among all hospitalized patients. The 26 patients comprised 10 unemployed and 16 employed individuals. Twenty-three patients were injured at home during the battery charging process, and three were injured outdoors (one by a fire while the electric motorcycle was stationary and the others two by a fire while riding the motorcycle). The burn sites were distributed over the whole body; the burn area ranged from 10 % to 100 % of the total body surface area, and the burn depth ranged from superficial second-degree burns to third-degree burns. Twenty-three patients had inhalation injuries, and ten underwent prophylactic tracheostomy and intubation. Multiple operations were required for wound repair. Although convenient, lithium-ion electric motorcycles can also cause severe burns. To prevent these injuries, we must increase public safety awareness and education, develop new battery energy storage systems and battery management systems, and ensure the safety of batteries. Consumers should be aware of the potential dangers of lithium-ion batteries and comply with related security measures., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Dry direct-seeded rice cultivation has gained popularity and expanded its cultivated area due to reduced labor requirements and water consumption. However, the impact of this cultivation method on cadmium (Cd) bioavailability in soil and the accumulation levels in grains remains uncertain. Field experiments were conducted in acidic soils at two locations in southern China to compare rice varieties and evaluate the dry direct-seeding method alongside the wet direct-seeding and traditional transplanting methods. Dry direct-seeded rice reached significantly higher Cd concentrations in its tissues starting from the heading stage than transplanted rice. Cd accumulation levels by the maturation stage in the brown rice of dry direct-seeded rice were 18.33 %-150.69 % higher than those of wet direct-seeded and transplanted rice, with a considerable ability to translocate Cd into brown rice. Furthermore, dry direct seeding decreased iron plaque formation, particularly in the amorphous Fe form; it resulted in high soil temperature and low moisture content during tillering, elevating Cd availability in the soil. Additionally, the proportion of ions and more labile forms of Cd in the soil solution was high. Moreover, the soil under dry direct seeding had high urease and acid phosphatase enzyme activities. However, low richness and diversity in the bacterial community were characterized by a significant increase in the relative abundance of Actinobacteria and Gammaproteobacteria at the class level, while exhibiting decreased relative abundances of Alphaproteobacteria, Bacilli, and KD4-96, along with fewer biomarkers. Nonetheless, these differences are gradually reduced during the maturation stage. Overall, although dry direct seeding offers several advantages, it is crucial to implement additional measures to mitigate the increased health risks linked to rice cultivation through this approach in Cd-contaminated areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The control of carbon emissions from agriculture is imperative in addressing the challenges posed by the greenhouse effect. China must develop a specific pathway for reducing its agricultural carbon emissions, accounting for its unique circumstances and considering the impacts of trade liberalization. (1) The study revealing that agricultural trade liberalization (ATL) has a marked effect on lowering China's agricultural carbon emission intensity (ACEI), with robustness and endogeneity tests supporting these findings. (2) In the pursuit of emissions reduction, the crucial role of technology spillovers (TS) and the optimization of industrial structure (OIS) are essential. (3) The reduction in ACEI is particularly notable in coastal regions, areas with low environmental regulations and during periods characterized by more stable agricultural tariffs. This study shows a synergistic association between ATL and ACEI, indicates the potential for a mutually beneficial situation with advantages in both economic and environmental aspects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Animal hosts harbor diverse assemblages of microbial symbionts that play crucial roles in the host's lifestyle. The link between microbial symbiosis and host development remains poorly understood. In particular, little is known about the adaptive evolution of gut bacteria in host-microbe symbioses. Recently, symbiotic relationships have been categorized as open, closed, or mixed, reflecting their modes of inter-host transmission and resulting in distinct genomic features. Members of the genus Bacteroides are the most abundant human gut microbiota and possess both probiotic and pathogenic potential, providing an excellent model for studying pan-genome evolution in symbiotic systems. Here, we determined the complete genome of an novel clinical strain PL2022, which was isolated from a blood sample and performed pan-genome analyses on a representative set of Bacteroides cellulosilyticus strains to quantify the influence of the symbiotic relationship on the evolutionary dynamics. B. cellulosilyticus exhibited correlated genomic features with both open and closed symbioses, suggesting a mixed symbiosis. An open pan-genome is characterized by abundant accessory gene families, potential horizontal gene transfer (HGT), and diverse mobile genetic elements (MGEs), indicating an innovative gene pool, mainly associated with genomic islands and plasmids. However, massive parallel gene loss, weak purifying selection, and accumulation of positively selected mutations were the main drivers of genome reduction in B. cellulosilyticus. Metagenomic read recruitment analyses showed that B. cellulosilyticus members are globally distributed and active in human gut habitats, in line with predominant vertical transmission in the human gut. However, existence and/or high abundance were also detected in non-intestinal tissues, other animal hosts, and non-host environments, indicating occasional horizontal transmission to new niches, thereby creating arenas for the acquisition of novel genes. This case study of adaptive evolution under a mixed host-microbe symbiosis advances our understanding of symbiotic pan-genome evolution. Our results highlight the complexity of genetic evolution in this unusual intestinal symbiont., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Diabetic vascular complications include diabetic macroangiopathy and diabetic microangiopathy. Diabetic microangiopathy is characterised by impaired microvascular endothelial function, basement membrane thickening, and microthrombosis, which may promote renal, ocular, cardiac, and peripheral system damage in diabetic patients. Therefore, new preventive and therapeutic strategies are urgently required. Sirt1, a member of the nicotinamide adenine dinucleotide-dependent histone deacetylase class III family, regulates different organ growth and development, oxidative stress, mitochondrial function, metabolism, inflammation, and aging. Sirt1 is downregulated in vascular injury and microangiopathy. Moreover, its expression and distribution in different organs correlate with age and play critical regulatory roles in oxidative stress and inflammation. This review introduces the background of diabetic microangiopathy and the main functions of Sirt1. Then, the relationship between Sirt1 and different diabetic microangiopathies and the regulatory roles mediated by different cells are described. Finally, we summarize the modulators that target Sirt1 to ameliorate diabetic microangiopathy as an essential preventive and therapeutic measure for diabetic microangiopathy. In conclusion, targeting Sirt1 may be a new therapeutic strategy for diabetic microangiopathy., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interests regarding the publication of this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Human bocavirus (HBoV) is an emerging health concern worldwide, associated with range of clinical manifestations, including gastroenteritis and respiratory infections. Therefore, it is crucial to comprehend and minimize their prevalence in different systems. In this study, we conducted regular sampling throughout the year in two different sizes and work processes of wastewater treatment plants (WWTPs) in Tianjin, China. Our objective was to investigate the occurrence, prevalence, and endurance of HBoV in wastewater, while also evaluating the efficacy of amplicon target sequencing in directly detecting HBoV in wastewater. At two WWTPs, HBoV2 (45.51 %-45.67 %) and HBoV3 (38.30 %-40.25 %) were the most common genotypes identified, and the mean concentration range of HBoV was 2.54-7.40 log 10 equivalent copies/l as determined by multiplex real-time quantitative PCR assay. A positive rate of HBoV was found in 96.6 % (29/30) samples of A-WWTP, and 96.6 % (26/27) samples of B-WWTP. The phylogenetic analysis indicated that the nucleotide similarity between the HBoV DNA sequences to the reference HBoV sequences published globally ranged from 90.14 %-100 %. A significant variation in the read abundance of HBoV2 and HBoV3 in two wastewater treatment plants (p < 0.05) was detected, specifically in the Winter and Summer seasons. The findings revealed a strong correlation between the genotypes detected in wastewater and the clinical data across various regions in China. In addition, it is worth mentioning that HBoV4 was exclusively detected in wastewater and not found in the clinical samples from patients. This study highlights the high prevalence of human bocavirus in municipal wastewater. This finding illustrates that amplicon target sequencing can amplify a wide variety of viruses, enabling the identification of newly discovered viruses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appreciated to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Utilizing an acid-resistant biological soil crust (BSC) species that we discovered, we developed a device capable of efficiently removing cadmium (Cd) from mine wastewater with varying levels of acidity. Our research has demonstrated that this particular BSC species adapts to acidic environments by regulating the balance of fatty acids and acid-resistant enzymes. At a Cd concentration of 5 mg/L, the BSC grew well. When the initial Cd concentration was 2 mg/L, and the flow rate was set at 1 mL/min (at pH levels of 3, 4, and 5), BSC had a high removal rate of Cd, and the removal rate increased with the increase of pH (from 90% to 97%). Chemisorption is the primary removal mechanism in the initial stage, where the functional groups and minerals on the surface of the BSC play a significant role. In addition, BSC also adapts to Cd stress by changing bacterial community structure. It was discovered through infrared spectroscopy and two-dimensional correlation analysis that hydrophilic groups, specifically phosphate and carboxyl groups, exhibited the highest reactivity during the Cd binding process. Protein secondary structure analysis confirmed that as the pH increased, the adsorption capacity of the BSC increased; making biofilm formation easier. This study presents a novel approach for the treatment of acidic wastewater., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)