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Salmonella Typhimurium establishes systemic infection by replicating in host macrophages. Here we show that macrophages infected with S . Typhimurium exhibit upregulated glycolysis and decreased serine synthesis, leading to accumulation of glycolytic intermediates. The effects on serine synthesis are mediated by bacterial protein SopE2, a type III secretion system (T3SS) effector encoded in pathogenicity island SPI-1. The changes in host metabolism promote intracellular replication of S . Typhimurium via two mechanisms: decreased glucose levels lead to upregulated bacterial uptake of 2- and 3-phosphoglycerate and phosphoenolpyruvate (carbon sources), while increased pyruvate and lactate levels induce upregulation of another pathogenicity island, SPI-2, known to encode virulence factors. Pharmacological or genetic inhibition of host glycolysis, activation of host serine synthesis, or deletion of either the bacterial transport or signal sensor systems for those host glycolytic intermediates impairs S . Typhimurium replication or virulence. Salmonella Typhimurium establishes systemic infection by replicating in host macrophages. Here, Jiang et al. show that infected macrophages exhibit upregulated glycolysis and decreased serine synthesis, leading to accumulation of glycolytic intermediates that promote intracellular replication and virulence of S . Typhimurium.

Background Laryngeal cancer has the highest mortality rate among head and neck tumours. RNA N6-methyladenosine (m6A) is the most plentiful and variable in mammalian mRNA. Yet, the m6A regulatory mechanism underlying the carcinogenesis or progression of LSCC remains poorly understood. Methods The m6A RNA methylation quantification kit was used to detect tissue methylation levels. m6A microarray analysis, mRNA transcriptomic sequencing (mRNA-seq), and proteomics were used to determine RBM15, TMBIM6, and IGF2BP3. Immunohistochemical (IHC), quantitative real-time PCR (qRT-PCR) and Western blot were used to investigate RBM15, TMBIM6, and IGF2BP3 expression in tissue samples and cell lines. The biological effects of RBM15 were detected both in vitro and in vivo. The combination relationship between RBM15/IGF2BP3 and TMBIM6 was verified by RNA immunoprecipitation (RIP) assay, Methylated RNA immunoprecipitation sequencing (MeRIP-seq), RNase Mazf, and luciferase report assay. RNase Mazf was used to determine the methylation site on TMBIM6 mRNA. Hoechst staining assay was used to confirm the apoptotic changes. The actinomycin D verified TMBIM6 stability. Results The global mRNA m6A methylation level significantly increased in LSCC patients. RBM15, as a “writer” of methyltransferase, was significantly increased in LSCC and was associated with unfavorable prognosis. The knockdown of RBM15 reduced the proliferation, invasion, migration, and apoptosis of LSCC both in vitro and in vivo. The results were reversed after overexpressing RBM15. Mechanically, TMBIM6 acted as a downstream target of RBM15-mediated m6A modification. Furthermore, RBM15-mediated m6A modification of TMBIM6 mRNA enhanced TMBIM6 stability through IGF2BP3-dependent. Conclusion Our results revealed the essential roles of RBM15 and IGF2BP3 in m6A methylation modification in LSCC, thus identifying a novel RNA regulatory mechanism.

A three-dimensional (3-D) Multi-Layers Method (MLM) of an extension of the axisymmetric version has been developed to compute non-axisymmetric tokamak plasma equilibria with a separatrix. Conventional axisymmetric tokamak control codes cannot simulate non-axisymmetric effects, while stellarator equilibrium solvers such as VMEC do not include the effects of conducting structures. Moreover, VMEC cannot obtain equilibria with separatrices since it uses magnetic coordinates. The 3-D MLM removes these limitations by using a deformable circuit model of a magnetic confinement system. Plasma is modeled by multiple current layers coinciding with magnetic surfaces, and equilibria are obtained as solutions of a variational problem of a free energy functional with current sources. Validations of equilibrium solutions against a stellarator vacuum field and a VMEC solution for a small non-axisymmetric tokamak show good agreement in magnetic configurations, pressure profile, and plasma current. By incorporating conducting structures and extension to dynamic simulations, the 3-D MLM establishes a method for simulating tokamak plasma control under non-axisymmetric magnetic fields.

Purpose The objective of this study was to identify potential predictors of immune-related adverse events (irAEs) in cancer patients receiving immune checkpoint inhibitor therapy among serum indexes, case data, and liquid biopsy results. Methods We retrospectively analyzed 418 patients treated with anti-programmed cell death 1(PD-1)/PD-1 ligand (PD-L1) inhibitors from January 2018 to May 2022 in our cancer center. We identified factors that correlated with the occurrence of irAEs and evaluated associations between irAEs and anti-PD-1/PD-L1 inhibitor responses. Results The incidence of irAEs was 42.1%, and pneumonitis (9.1%), thyroid toxicity (9.1%), cardiotoxicity (8.1%), and dermatologic toxicity (6.9%) were the four most common irAEs. Multivariate logistic analysis identified female sex, antibiotic use, higher post-treatment neutrophil-to-lymphocyte ratio (NLR), and higher baseline circulating tumor cell (CTC) level, as predictive biomarkers for the occurrence of irAEs. A lower baseline prognostic nutritional index (PNI), body mass index (BMI) ≥ 25 kg/m 2 , and higher post-treatment lactate dehydrogenase (LDH) level were predictive factors for more severe irAEs (higher severity grade). Patients without irAEs had better overall survival than those with irAEs. Specifically, pneumonitis and cardiotoxicity were found to be significant predictors of poor prognosis in the irAE subgroup with different organ-related irAEs. Low-dose steroid (dexamethasone 10 mg) treatment had no significant effect on outcomes. Conclusions Gender, antibiotic use, post-treatment NLR, and baseline CTC level are potential predictive biomarkers of irAEs, while baseline PNI, BMI, and post-treatment LDH may predict the severity of irAEs. The predictive effect of irAE occurrence on survival benefit may depend on the type of irAE.

Exosomes are a new way of the communication between the tumor cell and macrophage in the micro-environment. The macrophage can be induced to different phenotypes according to the different tumors. In the present study, long-chain noncoding RNA HOTAIR (lncRNA HOTAIR) was highly expressed in LSCC and exosomes. The pathway of exosomal lncRNA HOTAIR inducing macrophage to M2 polarization in the LSCC was investigated. The carcinoma tissues and adjacent tissues were collected from 104 LSCC cases, and the positive relationship between CD163-/CD206-M2 macrophage infiltration and clinical phase, lymph node spreading and pathological phase in LSCC was observed. To examine the role of exosomal lncRNA HOTAIR, macrophages were co-cultured with LSCC-exosomes of high lncRNA HOTAIR expression or transferred with HOTAIR mimics. It was suggested that exosomal lncRNA HOTAIR can induce macrophages to M2 polarization by PI3K/p-AKT/AKT signaling pathway. Furthermore, exo-treated M2 macrophages facilitate the migration, proliferation, and EMT of LSCC.

Accurate traffic flow prediction not only relies on historical traffic flow information, but also needs to take into account the influence of a variety of external factors such as weather conditions and the distribution of neighbouring POIs. However, most of the existing studies have used historical data to predict future traffic flows for short periods of time. Spatio-Temporal Graph Neural Networks (STGNN) solves the problem of combining temporal properties and spatial dependence, but does not extract long-term trends and cyclical features of historical data. Therefore, this paper proposes a MIFPN (Multi information fusion prediction network) traffic flow prediction method based on the long and short-term features in the historical traffic flow data and combining with external information. First, a subsequence converter is utilised to allow the model to learn the temporal relationships of contextual subsequences from long historical sequences that incorporate external information. Then, a superimposed one-dimensional inflated convolutional layer is used to extract long-term trends, a dynamic graph convolutional layer to extract periodic features, and a short-term trend extractor to learn short-term temporal features. Finally, long-term trends, cyclical features and short-term features are fused to obtain forecasts. Experiments on real datasets show that the MIFPN model improves by an average of 11.2% over the baseline model in long term predictions up to 60 min ago.

The former Italian concession in Tianjin (1901–1945) has assumed symbolic significance for the modern urban redevelopment of this municipality through experimentation with distinctive practices of conservation management. In 1986, when the Historic Buildings Protection Area was defined, the former Italian concession was identified as a pilot urban conservation project. In 2002, the public company Haihe Construction and Development Investment Ltd. was put in charge of the design and implementation plan for the site, which progressively assumed the semblance of an ‘Italian-Style Town’. The distinctive transformation raised significant questions regarding the architectural restyling as well as its specific historical and cultural value. In August 2020, the management of the Italian-Style town was handed over to the Hebei District Government. This coincided with the emergence of a proposal for the creation of a ‘Larger Italian-Style Town’, that extended beyond the borders of the original Italian concession to include the former Austrian concession and the western section of the ex-Russian concession. The redevelopment strategy for this larger area aimed to create a service-oriented commercial area, presented as an ‘urban living room’, while showcasing Tianjin as an international metropolis. This article analyses the evolution of the conservation strategy as well as the relevant legislation, management, and practices during the redevelopment of the former Italian concession. The aim of this study is to address the conflict between heritage protection and commercialisation. Thus, this article offers a critique of the trend towards functional replacement and structural adaptation to cater to the tourism industry rather than to the value of the community’s livelihood as a living heritage.

Deep venous thrombosis (DVT) is a leading cause of cardiovascular-related mortality, with an increasing incidence in elderly patients. However, existing risk assessment tools remain limited for this population. This study aimed to develop and validate machine learning (ML)-based models for predicting DVT risk in elderly patients. We retrospectively analyzed data from 1226 elderly patients discharged from the cardiovascular surgery department between January 2022 and December 2023. Risk factors were identified using the least absolute shrinkage and selection operator (LASSO), and seven ML models were subsequently trained on the selected features. Optimal hyperparameters for each model were selected through grid search with ten-fold cross-validation. Logistic regression (LR) and random forest (RF) demonstrated the best performance, with areas under the receiver operating characteristic curve (AUCs) of 0.835 and 0.819, respectively. SHapley Additive exPlanations (SHAP) revealed swelling, pain, albumin (ALB), and D-dimer as key predictors. These models may facilitate accurate risk stratification in elderly patients and provide clinical decision support through an interactive web-based tool.

Digestive system cancers are associated with high morbidity and mortality. Chemotherapy and radiotherapy are the main treatment modalities for these cancers. However, the development of therapy resistance leads to high rates of tumor recurrence and metastasis, resulting in dismal prognosis. Long non-coding RNA (LncRNA) H19, one of the most intriguing non-coding RNAs, has been shown to play a key role in the development and therapy resistance of various digestive system cancers (including hepatocellular carcinoma, colorectal cancer, pancreatic ductal adenocarcinoma, esophageal carcinoma, gastric cancer, and biliary system cancer) by regulating the abnormal expression of genes. In this review, we discuss the potential mechanisms of LncRNA H19 related therapy resistance in the context of digestive system cancers. LncRNA H19 is a potential novel therapeutic target for amelioration of cancer therapy resistance.

Introduced ecosystem engineers are expected to have extensive ecological impacts on a broad range of resident biota by altering the physical–chemical structure of ecosystems. Livestock that are potentially important introduced ecosystem engineers in grassland systems could create and/or modify habitats for native plant-dwelling insects. Yet, there is little knowledge of how insects respond to engineering effects of introduced livestock. To bridge this gap, we tested how domestic sheep affects the behavior and abundance of a native grasshopper Euchorthippus unicolor at both low (11.8 ± 0.4 plant species per plot) and high (19.8 ± 0.5 plant species per plot) diversity sites. Results found grasshoppers shifted their resting and feeding locations from the upper to the intermediate or low layers of vegetation, and fed on more plants species following livestock engineering effects. In the low plant diversity habitats, grazing caused grasshoppers to increase switching frequency, spend more time searching for host plants, and reduce time spent feeding, but had opposite effects on all the three behaviors in the high-diversity habitats. Moreover, grazing engineering effects on behavioral changes of grasshoppers were potentially related to their abundance. Overall, this study highlights native insect species’ behavior and abundance in responses to introduced ecological engineers, and suggests that ecosystem engineers of non-native species have strong and important impacts extending beyond their often most obvious and frequently documented direct ecological effects.