A Novel Joint Motion Compensation Algorithm for ISAR Imaging Based on Entropy Minimization.

Space targets move in orbit at a very high speed, so in order to obtain high-quality imaging, high-speed motion compensation (HSMC) and translational motion compensation (TMC) are required. HSMC and TMC are usually adjacent, and the residual error of HSMC will reduce the accuracy of TMC. At the same time, under the condition of low signal-to-noise ratio (SNR), the accuracy of HSMC and TMC will also decrease, which brings challenges to high-quality ISAR imaging. Therefore, this paper proposes a joint ISAR motion compensation algorithm based on entropy minimization under low-SNR conditions. Firstly, the motion of the space target is analyzed, and the echo signal model is obtained. Then, the motion of the space target is modeled as a high-order polynomial, and a parameterized joint compensation model of high-speed motion and translational motion is established. Finally, taking the image entropy after joint motion compensation as the objective function, the red-tailed hawk-Nelder-Mead (RTH-NM) algorithm is used to estimate the target motion parameters, and the joint compensation is carried out. The experimental results of simulation data and real data verify the effectiveness and robustness of the proposed algorithm.

Active biointegrated living electronics for managing inflammation.

Seamless interfaces between electronic devices and biological tissues stand to revolutionize disease diagnosis and treatment. However, biological and biomechanical disparities between synthetic materials and living tissues present challenges at bioelectrical signal transduction interfaces. We introduce the active biointegrated living electronics (ABLE) platform, encompassing capabilities across the biogenic, biomechanical, and bioelectrical properties simultaneously. The living biointerface, comprising a bioelectronics layout and a Staphylococcus epidermidis-laden hydrogel composite, enables multimodal signal transduction at the microbial-mammalian nexus. The extracellular components of the living hydrogels, prepared through thermal release of naturally occurring amylose polymer chains, are viscoelastic, capable of sustaining the bacteria with high viability. Through electrophysiological recordings and wireless probing of skin electrical impedance, body temperature, and humidity, ABLE monitors microbial-driven intervention in psoriasis.

Serratia plymuthica HK9-3 enhances tomato resistance against Phytophthora capsici by modulating antioxidant defense systems and rhizosphere micro-ecological condition.

Tomatoes are frequently challenged by various pathogens, among which Phytophthora capsici (P. capsici) is a destructive soil-borne pathogen that seriously threatens the safe production of tomatoes. Plant growth-promoting rhizobacteria (PGPR) positively induced plant resistance against multiple pathogens. However, little is known about the role and regulatory mechanism of PGPR in tomato resistance to P. capsici. Here, we identified a new strain Serratia plymuthica (S. plymuthica), HK9-3, which has a significant antibacterial effect on P. capsici infection. Meanwhile, stable colonization in roots by HK9-3, even under P. capsici infection, improved tomato growth parameters, root system architecture, photosynthetic capacity, and boosted biomass. Importantly, HK9-3 colonization significantly alleviated the damage caused by P. capsici infection through enhancing ROS scavenger ability and inducing antioxidant defense system and pathogenesis-related (PR) proteins in leaves, as evidenced by elevating the activities of peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), and chitinase, ß-1,3-glucanase, and increasing the transcripts of POD, SOD, CAT, APX1, PAL1, PAL2, PAL5, PPO2, CHI17 and ß-1,3-glucanase genes. Notably, HK9-3 colonization not only effectively improved soil microecology and soil fertility, but also significantly enhanced fruit yield by 44.6% and improved quality. Our study presents HK9-3 as a promising and effective solution for controlling P. capsici infection in tomato cultivation while simultaneously promoting plant growth and increasing yield, which may have implications for P. capsici control in vegetable production.

Diagnostic performance of machine learning in systemic infection following percutaneous nephrolithotomy and identification of associated risk factors.

Objective: This study aims to investigate the predictive performance of machine learning in predicting the occurrence of systemic inflammatory response syndrome (SIRS) and urosepsis after percutaneous nephrolithotomy (PCNL). Methods: A retrospective analysis was conducted on patients who underwent PCNL treatment between January 2016 and July 2022. Machine learning techniques were employed to establish and select the best predictive model for postoperative systemic infection. The feasibility of using relevant risk factors as predictive markers was explored through interpretability with Machine Learning. Results: A total of 1067 PCNL patients were included in this study, with 111 (10.4 %) patients developing SIRS and 49 (4.5 %) patients developing urosepsis. In the validation set, the risk model based on the GBM protocol demonstrated a predictive power of 0.871 for SIRS and 0.854 for urosepsis. Preoperative and postoperative platelet changes were identified as the most significant predictors. Both thrombocytopenia and thrombocytosis were found to be risk factors for SIRS or urosepsis after PCNL. Furthermore, it was observed that when the change in platelet count before and after PCNL surgery exceeded 30*109/L (whether an increase or decrease), the risk of developing SIRS or urosepsis significantly increased. Conclusion: Machine learning can be effectively utilized for predicting the occurrence of SIRS or urosepsis after PCNL. The changes in platelet count before and after PCNL surgery serve as important predictors.

Exploring Present and Future Directions in Nano-Enhanced Optoelectronic Neuromodulation.

Electrical neuromodulation has achieved significant translational advancements, including the development of deep brain stimulators for managing neural disorders and vagus nerve stimulators for seizure treatment. Optoelectronics, in contrast to wired electrical systems, offers the leadless feature that guides multisite and high spatiotemporal neural system targeting, ensuring high specificity and precision in translational therapies known as "photoelectroceuticals". This Account provides a concise overview of developments in novel optoelectronic nanomaterials that are engineered through innovative molecular, chemical, and nanostructure designs to facilitate neural interfacing with high efficiency and minimally invasive implantation.This Account outlines the progress made both within our laboratory and across the broader scientific community, with particular attention to implications in materials innovation strategies, studying bioelectrical activation with spatiotemporal methods, and applications in regenerative medicine. In materials innovation, we highlight a nongenetic, biocompatible, and minimally invasive approach for neuromodulation that spans various length scales, from single neurons to nerve tissues using nanosized particles and monolithic membranes. Furthermore, our discussion exposes the critical unresolved questions in the field, including mechanisms of interaction at the nanobio interface, the precision of cellular or tissue targeting, and integration into existing neural networks with high spatiotemporal modulation. In addition, we present the challenges and pressing needs for long-term stability and biocompatibility, scalability for clinical applications, and the development of noninvasive monitoring and control systems.In addressing the existing challenges in the field of nanobio interfaces, particularly for neural applications, we envisage promising strategic directions that could significantly advance this burgeoning domain. This involves a deeper theoretical understanding of nanobiointerfaces, where simulations and experimental validations on how nanomaterials interact spatiotemporally with biological systems are crucial. The development of more durable materials is vital for prolonged applications in dynamic neural interfaces, and the ability to manipulate neural activity with high specificity and spatial resolution, paves the way for targeting individual neurons or specific neural circuits. Additionally, integrating these interfaces with advanced control systems, possibly leveraging artificial intelligence and machine learning algorithms and programming dynamically responsive materials designs, could significantly ease the implementation of stimulation and recording. These innovations hold the potential to introduce novel treatment modalities for a wide range of neurological and systemic disorders.

Finite element method-based study for spinal vibration characteristics of the scoliosis and kyphosis lumbar spine to whole-body vibration under a compressive follower preload.

PURPOSE: To analyze the dynamic response of the lumbosacral vertebrae structure of a scoliosis spine and a kyphosis spine under whole-body vibration. METHODS: Typical Lenke4 (kyphosis) and Lenke3 (scoliosis) spinal columns were used as research objects. A finite element model of the lumbosacral vertebrae segment was established and validated based on CT scanning images. Modal, harmonic response, and transient dynamic analyses were performed on the lumbar-sacral scoliosis model using the finite element software abaqus. RESULTS: The first four resonance frequencies of kyphosis spine extracted from modal analysis were 0.86, 1.45, 8.51, and 55.71 Hz. The first four resonance frequencies of scoliosis spine extracted from modal analysis were 0.76, 1.45, 10.51, and 63.82 Hz. The scoliosis spine had the maximum resonance amplitude in the transverse direction, while the kyphosis spine had the maximum resonance amplitude in the anteroposterior direction. The dynamic response in transient analysis exhibited periodic response over time at all levels. CONCLUSION: The scoliosis and kyphosis deformity of the spine significantly complicates the vibration response in the scoliosis and kyphosis areas at the top of the spine. Scoliosis and kyphosis patients are more likely to experience vibrational spinal diseases than healthy people. Besides, applying vertical cyclic loads on a malformed spine may cause further rotation of scoliosis and kyphosis deformities.

Biofilm formation of Hafnia paralvei induced by c-di-GMP through facilitating bcsB gene expression promotes spoilage of Yellow River carp (Cyprinus carpio).

Hafnia paralvei, a Gram-negative foodborne pathogen, is found ubiquitously in various aquatic animals and seafoods, which can form biofilm as a dominant virulence factor that contributes to its pathogenesis. However, the biofilm formation mechanism of H. paralvei and its effect on food spoilage has not been fully characterized. Here we show that biofilm formation, is regulated by c-di-GMP which mediated by bcsB, can increase the spoilage ability of H. paralvei. We found that GTP was added exogenously to enhance the synthesis of c-di-GMP, which further promoted biofilm formation. The gene dgcC, one of 11 genes encoding GGDEF domain-containing proteins in H. paralvei, was significantly upregulated with GTP as substrate. The upregulation of dgcC contributes to a significant increase of c-di-GMP and the formation of biofilm. In addition, the overexpression of dgcC induced upregulation of bcsB, a reported effector protein encoding gene, which was further demonstrated that overexpression of bcsB can encourage the synthesis of bacterial cellulose and biofilm formation. The effect of biofilm formation induced by c-di-GMP on spoilage of Yellow River carp (Cyprinus carpio) was evaluated by sensory evaluation, the total viable count, and the total volatile basic nitrogen, which showed that biofilm formation can significantly increase the spoilage ability of H. paralvei on C. carpio. Our findings provide the regulation of c-di-GMP on expression of bcsB, that can contribute to biofilm formation and spoilage ability of H. paralvei, which is favor to understanding the pathogenesis of Hafnia paralvei and its role in food spoilage.

LRP1 induces anti-PD-1 resistance by modulating the DLL4-NOTCH2-CCL2 axis and redirecting M2-like macrophage polarisation in bladder cancer.

The tumour microenvironment (TME) drives bladder cancer (BLCA) progression. Targeting the TME has emerged as a promising strategy for BLCA treatment in recent years. Furthermore, checkpoint blockade therapies are only beneficial for a minority of patients with BLCA, and drug resistance is a barrier to achieving significant clinical effects of anti-programmed cell death protein-1 (PD-1)/programmed death protein ligand-1 (PD-L1) therapy. In this study, higher low-density lipoprotein receptor-related protein 1 (LRP1) levels were related to a poorer prognosis for patients with various cancers, including those with higher grades and later stages of BLCA. Enrichment analysis demonstrated that LRP1 plays a role in the epithelial-mesenchymal transition (EMT), NOTCH signalling pathway, and ubiquitination. LRP1 knockdown in BLCA cells delayed BLCA progression both in vivo and in vitro. Furthermore, LRP1 knockdown suppressed EMT, reduced DLL4-NOTCH2 signalling activity, and downregulated M2-like macrophage polarisation. Patients with BLCA and higher LRP1 levels responded weakly to anti-PD-1 therapy in the IMvigor210 cohort. Moreover, LRP1 knockdown enhanced the therapeutic effects of anti-PD-1 in mice. Taken together, our findings suggest that LRP1 is a potential target for improving the efficacy of anti-PD-1/PD-L1 therapy by preventing EMT and M2-like macrophage polarisation by blocking the DLL4-NOTCH2 axis.

A nomogram based on TFE3 IHC results and clinical factors as a preliminary screening scheme for TFE3-rearranged renal cell carcinoma.

BACKGROUND: TFE3 immunohistochemistry (TFE3-IHC) is controversial in the diagnosis of TFE3-rearranged renal cell carcinoma (TFE3-rearranged RCC). This study is to investigate the accuracy and sensitivity of IHC and establish a predictive model to diagnose TFE3-rearranged RCC. METHODS: Retrospective analysis was performed by collecting IHC and fluorescence in situ hybridization (FISH) results from 228 patients. IHC results were evaluated using three scoring systems. Scoring system 1 is graded based on nuclear staining intensity, scoring system 2 is graded based on the percentage of stained tumor cell nuclei, and scoring system 3 is graded based on both the nuclear staining intensity and the percentage. We collected patients' IHC results and clinical information. Important variables were screened based on univariate logistic regression analysis. Then, independent risk factors were established through multivariate logistic regression, and a nomogram model was constructed. The model was validated in internal test set and external validation set. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) were generated to assess discriminative ability of the model. RESULTS: The accuracy of IHC based on three scoring systems were 0.829, 0.772, and 0.807, respectively. The model included four factors including age, gender, lymph node metastasis and IHC results. Area under the curve (AUC) values were 0.935 for the training set, 0.934 for the internal test set, 0.933 for all 228 patients, and 0.916 for the external validation set. CONCLUSIONS: TFE3 IHC has high accuracy in the diagnosis of TFE3-rearranged RCC. Clinical information such as age and lymph node metastasis are independent risk factors, which can be used as a supplement to the results of TFE3 IHC. This study confirms the value of IHC in the diagnosis of TFE3-rearranged RCC. The accuracy of the diagnosis can be improved by incorporating IHC with other clinical risk factors.

Monolithic silicon for high spatiotemporal translational photostimulation.

Electrode-based electrical stimulation underpins several clinical bioelectronic devices, including deep-brain stimulators1,2 and cardiac pacemakers3. However, leadless multisite stimulation is constrained by the technical difficulties and spatial-access limitations of electrode arrays. Optogenetics offers optically controlled random access with high spatiotemporal capabilities, but clinical translation poses challenges4-6. Here we show tunable spatiotemporal photostimulation of cardiac systems using a non-genetic platform based on semiconductor-enabled biomodulation interfaces. Through spatiotemporal profiling of photoelectrochemical currents, we assess the magnitude, precision, accuracy and resolution of photostimulation in four leadless silicon-based monolithic photoelectrochemical devices. We demonstrate the optoelectronic capabilities of the devices through optical overdrive pacing of cultured cardiomyocytes (CMs) targeting several regions and spatial extents, isolated rat hearts in a Langendorff apparatus, in vivo rat hearts in an ischaemia model and an in vivo mouse heart model with transthoracic optical pacing. We also perform the first, to our knowledge, optical override pacing and multisite pacing of a pig heart in vivo. Our systems are readily adaptable for minimally invasive clinical procedures using our custom endoscopic delivery device, with which we demonstrate closed-thoracic operations and endoscopic optical stimulation. Our results indicate the clinical potential of the leadless, lightweight and multisite photostimulation platform as a pacemaker in cardiac resynchronization therapy (CRT), in which lead-placement complications are common.

Estuarine hydrodynamic processes driving the molecular changes of terrestrial dissolved organic nitrogen: From mixing to biological modification.

Estuaries receive substantial amounts of terrestrial dissolved organic nitrogen (tDON), which will be transported from the freshwater to the oceanic terminus through vigorous exchange processes. However, the intricate migration and transformation dynamics of tDON during this transportation, particularly at a molecular level, remain constrained. To address this knowledge gap, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used for the analysis of DON molecular composition in the Pearl River Estuary (PRE), a river-dominated estuarine system influenced by intensified anthropogenic activities in southern China. The results showed a pronounced spatial-temporal variation in DON concentration in the study area. At the molecular level, tDON exhibited reduced unsaturation and aromaticity, coupled with an elevated abundance of DON compounds containing one­nitrogen atom (1 N-DON, 53.17 %) and compounds containing carbon, hydrogen, oxygen, nitrogen, and sulfur (CHONS) (27.46 %). It was evident that lignin was depleted while more oxygenated tannin compounds were generated in the freshwater-seawater mixing zone. This transformation is attributed to heightened biological activities, likely influenced by the priming effect of terrestrial nutrient inputs. In summer, the prevailing plume combined with biological activities in the strong mixing area and outer estuary increased the abundance of 3 N-DON molecules and a concurrent rise in the abundance of DON compounds containing only carbon, hydrogen, oxygen, and nitrogen (CHON), DON compounds containing carbon, hydrogen, oxygen, nitrogen, sulfur, and phosphorus (CHONSP), and CHONS. This trend also underscores the expanding role of marine plankton and microbes in the utilization of DON compounds containing carbon, hydrogen, oxygen, nitrogen, and phosphorus (CHONP). These findings provide details of tDON transformation processes at the molecular level in a river-dominated estuary and underline the estuarine hydrodynamics involved in transporting and altering DON within the estuary.

Co-exposure of nanoplastics and arsenic causes neurotoxicity in zebrafish (Danio rerio) through disrupting homeostasis of microbiota-intestine-brain axis.

Nanoplastics (NPs) and arsenic (As) are toxic pollutants prevalent on the earth and have gained considerable attention in recent decades. Although numerous studies reported NPs and As can cause neurotoxicity there are still significant knowledge gaps in illustrating their combined toxicity and its mechanism. In this study, the co-exposure of environmentally relevant concentrations of NPs and As caused neurobehavioral toxicity in zebrafish, as evidenced by reduced swimming ability, anxiety and impaired short-term learning memory. Potentially, its toxicity mechanism is through disrupting the homeostasis of microbiota-intestine-brain axis in zebrafish. Specifically, the co-exposure reduced the 5-hydroxytryptamine (5-HT) production in intestine, which led to lower levels of 5-HT transported by the blood circulation to the brain. Ultimately, neurobehavior was adversely affected by the reduced binding of 5-HT to its receptors. Intestine, the primary source of 5-HT, its impaired health (aggravation in oxidative stress, mitochondrial damage and histopathological alterations) induced the dysregulation in the 5-HT system, which may be induced by the increased accumulation of As in the intestine by the co-exposure. Besides, the reduced 5-HT levels were correlated with decreased Firmicutes and Protecbacteria and increased Actinobacteriota and Chloroflexi in intestines. Potentially, intestinal microbiota adversely regulates the intestine-brain axis by reducing SCFAs levels. Thus, the alteration of intestinal microbiota structure may be the other reason for the dysregulation of intestine-brain axis. In summary, co-exposure of NPs and As induced neurobehavior toxicity probably through disrupting the homeostasis of microbiota-intestine-brain axis. This study provides insights into assessing the environmental health risks of the pollution of NPs and As to aquatic organisms.

Coulomb blockade and Coulomb staircases in CoBi nanoislands on SrTiO3(001).

We successfully fabricated two-dimensional metallic CoBi nanoislands on SrTiO3(001) substrate by molecular beam epitaxy, and systematically investigated their electronic structures by scanning tunneling microscopy and spectroscopyin situat 4.2 K. Coulomb blockade and Coulomb staircases with discrete and well-separated levels are observed for the individual nanoisland, which is attributed to single-electron tunneling via two tunnel junction barriers. They are in excellent agreement with the simulations based on orthodox theory. Furthermore, we demonstrated that the Coulomb blockade becomes weaker with increasing temperature and almost disappears at ∼22 K in our variable temperature experiment, and its full-width at half-maximum of dI/dVpeaks with temperature is ∼6 mV. Our results provide a new platform for designing single-electron transistors that have potential applications in future microelectronics.

Displacement Measurement Method Based on Double-Arrowhead Auxetic Tubular Structure.

This research paper introduces an innovative technique for measuring displacement using auxetic tubular structure (ATS). The proposed displacement measurement method is based on tubular structures with a negative Poisson's ratio. It capitalizes on the underlying principle that the elastic deformation-induced change in transmittance of the ATS can be translated into a corresponding modification in the output current of the solar cell. This method allows for the conversion of the variation in light transmission into a corresponding variation in output voltage. The construction of the ATS can be achieved through 3D-printing technology, enhancing the accessibility of displacement measurement and design flexibility. The experimental results demonstrate that the proposed measurement method exhibits a linear error of less than 8% without any subsequent signal processing and achieves a sensitivity of 0.011 V/mm without signal amplification. Furthermore, experimental results also show that the proposed method has good repeatability and can maintain a high level of reliability and sensitivity when using different measurement devices. This confirms the effectiveness and feasibility of the proposed method, showing a favorable linear relationship between the input and output of the measurement system with an acceptable sensitivity, repeatability, and reliability.

Selenium reduces hepatopancreas lipid accumulation of grass carp (Ctenopharyngodon idella) fed high-fat diet via lipophagy activation.

It has been reported that selenium (Se) can reduce hepatopancreas lipid accumulation induced by high-fat diet. However, its mechanism is still unknown. This study aims to investigate the specific mechanisms by which Se alleviates high-fat diet-induced lipid accumulation. Grass carp were fed control diet (4.8% lipid, Con), high-fat diet (8.8% lipid, HFD) or HFD supplemented with 0.3 mg/kg nano-Se (HSe0.3) for 10 weeks. Growth performance, Se deposition, lipid accumulation, hepatic ultrastructure, and gene and protein expression levels associated with autophagy were examined. Furthermore, oleic acid (OA) was used to incubate the grass carp hepatocytes (L8824) for 24 h, and then the L8824 were incubated with sodium selenite in presence or absence of an autophagy inhibitor for 24 h. L8824 was analyzed for triglyceride concentration, immunofluorescence, and gene and protein expression levels associated with autophagy. We found that dietary nano-Se improved the growth of fish fed HFD and also decreased hepatosomatic index and intraperitoneal fat ratio of fish fed HFD (P < 0.05). HFD significantly increased hepatopancreas lipid accumulation and decreased autophagic activity (P < 0.05). Treatment of grass carp fed HFD with nano-Se decreased lipid accumulation and restored hepatic autophagy (P < 0.05). In vitro, Se (100 µM sodium selenite) obviously activated autophagy in L8824 incubated with OA, and consequently reduced the lipid accumulation induced by OA (P < 0.05). Furthermore, using pharmacological inhibition (chloroquine) of the autophagy greatly diminished the beneficial effects of Se on alleviating OA-induced lipid accumulation and increased the co-localization of lipid droplets with autophagosome (P < 0.05), which indicated that Se increased autophagic flux. In conclusion, these results suggest that Se alleviates HFD-induced hepatopancreas lipid accumulation by activating lipophagy.

Using Vertically Aligned Carbon Nanofiber Arrays on Rigid or Flexible Substrates for Delivery of Biomolecules and Dyes to Plants.

The delivery of biomolecules and impermeable dyes to intact plants is a major challenge. Nanomaterials are up-and-coming tools for the delivery of DNA to plants. As exciting as these new tools are, they have yet to be widely applied. Nanomaterials fabricated on rigid substrate (backing) are particularly difficult to successfully apply to curved plant structures. This study describes the process for microfabricating vertically aligned carbon nanofiber arrays and transferring them from a rigid to a flexible substrate. We detail and demonstrate how these fibers (on either rigid or flexible substrates) can be used for transient transformation or dye (e.g., fluorescein) delivery to plants. We show how VACNFs can be transferred from rigid silicon substrate to a flexible SU-8 epoxy substrate to form flexible VACNF arrays. To overcome the hydrophobic nature of SU-8, fibers in the flexible film were coated with a thin silicon oxide layer (2-3 nm). To use these fibers for delivery to curved plant organs, we deposit a 1 µL droplet of dye or DNA solution on the fiber side of VACNF films, wait 10 min, place the films on the plant organ and employ a swab with a rolling motion to drive fibers into plant cells. With this method, we have achieved dye and DNA delivery in plant organs with curved surfaces.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood. METHOD: RNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan-Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry. RESULTS: Twenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells' malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization. CONCLUSION: The study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

Development and validation of a novel defined mutation classifier based on Lasso logistic regression for predicting the overall survival of immune checkpoint inhibitor therapy in renal cell carcinoma.

Background: Currently, immune checkpoint inhibitor (ICI)-based therapy has become the first-line treatment for advanced renal cell carcinoma (RCC). However, few biomarkers have been identified to predict the response to ICI therapy in RCC patients. Herein, our research aimed to build a gene mutation prognostic indicator for ICI therapy. Methods: This multi-cohort study explored the mutation patterns in 2 publicly available advanced RCC ICI therapy cohorts, the Memorial Sloan Kettering Cancer Center (MSKCC) advanced RCC ICI therapy cohort and the CheckMate ICI therapy cohort. A total of 261 patients in the CheckMate ICI therapy cohort were randomly assigned to either the training or validation set. Least absolute shrinkage and selection operator (Lasso) logistic regression analysis was subsequently used to develop a mutation classifier utilizing the training set. The classifier was then validated internally in the validation set and externally in 2 ICI therapy cohorts and 2 non-ICI therapy cohorts. Survival analysis, receiver operator characteristic curves and Harrell's concordance index were performed to assess the prognostic value of the classifier. Function and immune microenvironment analysis in each subgroup defined by the classifier were performed. Results: A 10-gene mutation classifier was constructed based on the CheckMate ICI therapy cohort to separate patients into 2 risk groups, with patients in the high-risk group showing significantly lower overall survival probability than those in the low-risk group [the training set (HR: 1.791; 95% CI: 1.207-2.657; P=0.003), the validation set (HR: 1.842; 95% CI: 1.133-2.996; P=0.012) and combination set (HR: 1.819; 95% CI: 1.339-2.470; P<0.001)]. Further validation confirmed that the mutation classifier only showed predictive value for patients receiving ICI therapy instead of non-ICI therapy. Combined with the clinical characteristics, the risk score was proven to be an independent prognostic factor for overall survival in ICI therapy by multivariate Cox regression analysis. Functional and immune infiltration analysis demonstrated that lower risk scores tended to associate with immunologically "hot" status in RCC. Conclusions: Our 10-gene mutation classifier was found to be a biomarker for predicting the overall survival of patients with advanced RCC to ICI therapy.

Overexpression of TREM1 is Associated with the Immune-Suppressive Microenvironment and Unfavorable Prognosis in Pan-Cancer.

Background: Triggering receptors expressed by myeloid cells-1 (TREM1) is a receptor belonging to the immunoglobulin superfamily and plays an important role in pro-inflammation in acute and chronic inflammatory disorders. However, the understanding of the immunomodulatory roles of TREM1 in the tumor microenvironment remains incomplete. Methods: The expression patterns of TREM1 mRNA in tumors and adjacent normal tissues were compared by analyzing data obtained from the Genotype-Tissue Expression and The Cancer Genome Atlas datasets. Survival analysis was performed to determine the prognostic value of TREM1. Functional enrichment analysis was applied to decipher the discrepancy in biological processes between high- and low-TREM1 groups across various cancers. The correlation between TREM1 and immune cell infiltration determined by using multiple algorithms was evaluated with the Pearson method. Four independent immunotherapy cohorts were adopted to validate the role of TREM1 as a biomarker. Results: TREM1 was elevated in most cancers as verified with clinical samples. Overexpression of TREM1 was linked with undesirable prognosis in patients. Further analysis revealed that TREM1 was positively correlated with immune response, pro-tumor pathways, and myeloid cell infiltration, while being negatively correlated with CD8+ T cell (including infiltration level and biological processes). Concordantly, tumors with high TREM1 levels were more resistant to immunotherapy. Through connective map analysis, therapeutically potential compounds like tozasertib and TPCA-1 were identified, which can be used synergistically with immunotherapy to improve the poor prognosis of patients with high TREM1 levels. Conclusion: Through a systematic and comprehensive pan-cancer analysis, we demonstrated that overexpression of TREM1 in tumors correlated closely with unfavorable outcome, infiltration of immune-suppressive cells, and immune regulation, which highlights its potential use as a tumor prognostic biomarker and a novel target for immunotherapy.

Activating SIRT1 deacetylates NF-κB p65 to alleviate liver inflammation and fibrosis via inhibiting NLRP3 pathway in macrophages.

Background and aims: Macrophages play a critical role in the development of liver diseases. As an NAD+-dependent histone deacetylase, SIRT1 inhibits liver inflammation and fibrosis, but the mechanisms are not fully understood. Our aim was to investigate the molecular mechanism of SIRT1 in macrophages in liver inflammation and fibrosis. Methods: We employed the CCl4-induced hepatic fibrosis rat models and cultured murine macrophages RAW 264.7 in vitro to explore the anti-fibrosis effect of SIRT1. The content of cytokines was measured with ELISA. The expression of proteins associated with the NF-κB /NLPR3 signaling pathway was detected by Western blot, co-immunoprecipitation, and immunofluorescence. SIRT1, NF-κB, and NLRP3 genes were knocked down in RAW 264.7 cells by small interfering RNA (siRNA) transfection. Results: The expression of NF-κB p65, NLRP3, α-SMA, and iNOS increased in liver tissue, with high plasma LPS level and low expression of SIRT1 in CCl4-induced rat models. Overexpressing SIRT1 could inhibit these protein levels, decrease plasma LPS level, and attenuate liver injury and fibrosis. In vitro, LPS induced cytomorphology changes and up-regulated NF-κB/NLRP3 pathway, with the low expression of SIRT1 in RAW 264.7; meanwhile, the secretion of inflammatory factors increased. Nevertheless, knockdown of NF-κB or NLRP3 and activation of SIRT1 inhibited inflammation of macrophages; inhibition or knockdown of SIRT1 enhanced macrophage inflammation. Furthermore, activation of SIRT1 could inhibit LPS-treated macrophages from activating hepatic stellate cells (HSCs). Conclusions: Activating SIRT1 inhibits the inflammation in macrophages by down-regulating NLRP3 pathway through deacetylating NF-κB p65, which in turn inhibits the activation of HSCs to alleviate hepatic inflammation and fibrosis.