Mapping the hepatic immune landscape identifies monocytic macrophages as key drivers of steatohepatitis and cholangiopathy progression.

BACKGROUND AND AIMS: The progression of chronic liver diseases towards liver cirrhosis is accompanied by drastic tissue changes. This study combines elaborate transcriptomic and histological methods aiming at spatially resolving the hepatic immune microenvironment in NAFLD (including NASH, primary sclerosing cholangitis, primary biliary cholangitis, and severe alcoholic hepatitis). APPROACH AND RESULTS: Human liver samples were subjected to RNA-sequencing (n=225) and imaging cytometry (n=99) across 3 independent patient cohorts. Liver samples from alcoholic hepatitis and primary biliary cholangitis patients were used for comparison. Myeloid populations were further characterized in corresponding mouse models. Imaging, clinical, and phenotypical data were combined for multidimensional analysis. NAFLD/NASH and primary sclerosing cholangitis disease stages were associated with loss of parenchymal areas, increased ductular cell accumulation, and infiltration of immune cells. NASH patients predominantly exhibited myeloid cell accumulation, whereas primary sclerosing cholangitis patients additionally had pronounced lymphoid cell responses. Correlating to disease stage, both etiologies displayed intense IBA1 + CD16 low CD163 low macrophage aggregation in nonparenchymal areas, with a distinct spatial proximity to ductular cells. Mouse models revealed that disease-associated IBA1 + hepatic macrophages originated from bone marrow-derived monocytes. Using an unbiased, machine learning-based algorithm, IBA1 in combination with hepatocyte and ductular cell immunostaining-predicted advanced cirrhosis in human NASH, primary sclerosing cholangitis, and alcoholic hepatitis. CONCLUSIONS: Loss of hepatocytes and increased ductular reaction are tightly associated with monocyte-derived macrophage accumulation and represent the most prominent common immunological feature revealing the progression of NAFLD, primary sclerosing cholangitis, primary biliary cholangitis, and alcoholic hepatitis, suggesting IBA1 + CD163 low macrophages are key pathogenic drivers of human liver disease progression across diverse etiologies.

CDK4/6 inhibition enhances T-cell immunotherapy on hepatocellular carcinoma cells by rejuvenating immunogenicity.

Hepatocellular carcinoma (HCC) poses a significant clinical challenge, necessitating the integration of immunotherapeutic approaches. Palbociclib, a selective CDK4/6 inhibitor, has demonstrated promising efficacy in preclinical HCC models and is being evaluated as a novel therapeutic option in clinical trials. Additionally, CDK4/6 inhibition induces cellular senescence, potentially influencing the tumor microenvironment and immunogenicity of cancer cells. In this study, we conducted comprehensive bioinformatic analyses using diverse HCC transcriptome datasets, including bulk and single-cell RNA-sequencing data from public databases. We also utilized human and mouse HCC cells to investigate functional aspects. Primary T cells isolated from mouse blood were employed to assess T cell immunity against HCC cells. Results revealed that CD8+ T-cell infiltration correlates with improved outcomes in HCC patients with suppressed CDK4/6 expression. Moreover, CDK4/6 expression was associated with alterations in the immune landscape and immune checkpoint expression within the liver tumor microenvironment. Furthermore, we found that treatment with Palbociclib and Doxorubicin induces cellular senescence and a senescence-associated secretory phenotype in HCC cells. Notably, pretreatment with Palbociclib augmented T cell-mediated cytotoxicity against HCC cells, despite upregulation of PD-L1, surpassing the effects of Doxorubicin pretreatment. In conclusion, our study elucidates a novel mechanism by which CDK4/6 inhibition enhances T-cell-associated cancer elimination and proposes a potential therapeutic strategy to enhance T-cell immunotherapy on HCC.

Ectopic expression of the yeast Mn2+ transporter SMF2 enhances tolerance and resistance to cadmium and arsenic in transgenic Arabidopsis.

Vesicular sequestration is a potential strategy for enhancing plant tolerance to cadmium (Cd) and arsenic (As). In this study, the ectopic overexpression of yeast-derived ScSMF2 in Arabidopsis thaliana was found to enhance the accumulation and tolerance of Cd and As in transgenic plants. ScSMF2 was localized on vacuole membranes and formed puncta structures in plant cells when agro-infiltrated for transient expression. Transgenic Arabidopsis showed less retardation on root elongation and shoot weight and more accumulation of Cd, As (III) and As (V) when cultured on medium containing Cd or As. Overexpression of ScSMF2 promoted accumulation of Cd and arsenic in transgenic Arabidopsis, which were over twice higher than in WT plants when cultured in soil. This study provides insights into the mechanisms involved in the vesicular sequestration of heavy metals in plant and presents a potential strategy for enhancing the phytoremediation capacity of plants toward heavy metals.

Ectopic overexpression of the yeast Mn²⁺ transporter SMF2 in Arabidopsis thaliana substantially boosts the accumulation and tolerance to Cd and As in plants. This augmentation is attributed to the enhanced efficacy of intracellular vesicle sequestration, thereby bolstering the capacity of plants to sequester and detoxify these toxic heavy metals. This investigation introduces a potential approach for cultivating plants with improved phytoremediation capabilities, thereby advancing eco-friendly and sustainable remediation initiatives against heavy metal pollution.

Learning Response-Consistent and Background-Suppressed Correlation Filters for Real-Time UAV Tracking.

With the advantages of discriminative correlation filter (DCF) in tracking accuracy and computational efficiency, the DCF-based methods have been widely used in the field of unmanned aerial vehicles (UAV) for target tracking. However, UAV tracking inevitably encounters various challenging scenarios, such as background clutter, similar target, partial/full occlusion, fast motion, etc. These challenges generally lead to multi-peak interferences in the response map that cause the target drift or even loss. To tackle this problem, a response-consistent and background-suppressed correlation filter is proposed for UAV tracking. First, a response-consistent module is developed, in which two response maps are generated by the filter and the features extracted from adjacent frames. Then, these two responses are kept to be consistent with the response from the previous frame. By utilizing the l2-norm constraint for consistency, this module not only can avoid sudden changes of the target response caused by background interferences but also enables the learned filter to preserve the discriminative ability of the previous filter. Second, a novel background-suppressed module is proposed, which makes the learned filter to be more aware of background information by using an attention mask matrix. With the introduction of this module into the DCF framework, the proposed method can further suppress the response interferences of distractors in the background. Finally, extensive comparative experiments have been conducted on three challenging UAV benchmarks, including UAV123@10fps, DTB70 and UAVDT. Experimental results have proved that our tracker has better tracking performance compared with 22 other state-of-the-art trackers. Moreover, our proposed tracker can run at ∼36 FPS on a single CPU for real-time UAV tracking.

Systematic molecular analysis of the human secretome and membrane proteome in gastrointestinal adenocarcinomas.

The human secretome and membrane proteome are a large source of cancer biomarkers. Membrane-bound and secreted proteins are promising targets for many clinically approved drugs, including for the treatment of tumours. Here, we report a deep systematic analysis of 957 adenocarcinomas of the oesophagus, stomach, colon and rectum to examine the cancer-associated human secretome and membrane proteome of gastrointestinal tract adenocarcinomas (GIACs). Transcriptomic data from these GIACs were applied to an innovative majority decision-based algorithm. We quantified significantly expressed protein-coding genes. Interestingly, we found a consistent pattern in a small group of genes found to be overexpressed in GIACs, which were associated with a cytokine-cytokine interaction pathway (CCRI) in all four cancer subtypes. These CCRI associated genes, which spanned both one secretory and one membrane isoform were further analysed, revealing a putative biomarker, interleukin-1 receptor accessory protein (IL1RAP), which indicated a poor overall survival, a positive correlation with cancer stemness and a negative correlation with several kinds of T cells. These results were further validated in vitro through the knockdown of IL1RAP in two human gastric carcinoma cell lines, which resulted in a reduced indication of cellular proliferation, migration and markers of invasiveness. Following IL1RAP silencing, RNA seq results showed a consistent pattern of inhibition related to CCRI, proliferation pathways and low infiltration of regulatory T cells (Tregs) and CD8 naive cells. The significance of the human secretome and membrane proteome is elucidated by these findings, which indicate IL1RAP as a potential candidate biomarker for cytokine-mediated cancer immunotherapy in gastric carcinoma.

Personalized Surgical Transfusion Risk Prediction Using Machine Learning to Guide Preoperative Type and Screen Orders.

BACKGROUND: Accurate estimation of surgical transfusion risk is essential for efficient allocation of blood bank resources and for other aspects of anesthetic planning. This study hypothesized that a machine learning model incorporating both surgery- and patient-specific variables would outperform the traditional approach that uses only procedure-specific information, allowing for more efficient allocation of preoperative type and screen orders. METHODS: The American College of Surgeons National Surgical Quality Improvement Program Participant Use File was used to train four machine learning models to predict the likelihood of red cell transfusion using surgery-specific and patient-specific variables. A baseline model using only procedure-specific information was created for comparison. The models were trained on surgical encounters that occurred at 722 hospitals in 2016 through 2018. The models were internally validated on surgical cases that occurred at 719 hospitals in 2019. Generalizability of the best-performing model was assessed by external validation on surgical cases occurring at a single institution in 2020. RESULTS: Transfusion prevalence was 2.4% (73,313 of 3,049,617), 2.2% (23,205 of 1,076,441), and 6.7% (1,104 of 16,053) across the training, internal validation, and external validation cohorts, respectively. The gradient boosting machine outperformed the baseline model and was the best- performing model. At a fixed 96% sensitivity, this model had a positive predictive value of 0.06 and 0.21 and recommended type and screens for 36% and 30% of the patients in internal and external validation, respectively. By comparison, the baseline model at the same sensitivity had a positive predictive value of 0.04 and 0.144 and recommended type and screens for 57% and 45% of the patients in internal and external validation, respectively. The most important predictor variables were overall procedure-specific transfusion rate and preoperative hematocrit. CONCLUSIONS: A personalized transfusion risk prediction model was created using both surgery- and patient-specific variables to guide preoperative type and screen orders and showed better performance compared to the traditional procedure-centric approach.

Predicting physician burnout using clinical activity logs: Model performance and lessons learned.

BACKGROUND: Burnout is a significant public health concern affecting more than half of the healthcare workforce; however, passive screening tools to detect burnout are lacking. We investigated the ability of machine learning (ML) techniques to identify burnout using passively collected electronic health record (EHR)-based audit log data. METHOD: Physician trainees participated in a longitudinal study where they completed monthly burnout surveys and provided access to their EHR-based audit logs. Using the monthly burnout scores as the target outcome, we trained ML models using combinations of features derived from audit log data-aggregate measures of clinical workload, time series-based temporal measures of EHR use, and the baseline burnout score. Five ML models were constructed to predict burnout as a continuous score: penalized linear regression, support vector machine, neural network, random forest, and gradient boosting machine. RESULTS: 88 trainee physicians participated and completed 416 surveys; greater than10 million audit log actions were collected (Mean [Standard Deviation] = 25,691 [14,331] actions per month, per physician). The workload feature set predicted burnout score with a mean absolute error (MAE) of 0.602 (95% Confidence Interval (CI), 0.412-0.826), and was able to predict burnout status with an average AUROC of 0.595 (95% CI 0.355-0.808) and average accuracy 0.567 (95% CI 0.393-0.742). The temporal feature set had a similar performance, with MAE 0.596 (95% CI 0.391-0.826), and AUROC 0.581 (95% CI 0.343-0.790). The addition of the baseline burnout score to the workload features improved the model performance to a mean AUROC of 0.829 (95% CI 0.607-0.996) and mean accuracy of 0.781 (95% CI 0.587-0.936); however, this performance was not meaningfully different than using the baseline burnout score alone. CONCLUSIONS: Current findings illustrate the complexities of predicting burnout exclusively based on clinical work activities as captured in the EHR, highlighting its multi-factorial and individualized nature. Future prediction studies of burnout should account for individual factors (e.g., resilience, physiological measurements such as sleep) and associated system-level factors (e.g., leadership).

Nuclear Receptors Linking Metabolism, Inflammation, and Fibrosis in Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) and its progressive form nonalcoholic steatohepatitis (NASH) comprise a spectrum of chronic liver diseases in the global population that can lead to end-stage liver disease and hepatocellular carcinoma (HCC). NAFLD is closely linked to the metabolic syndrome, and comorbidities such as type 2 diabetes, obesity and insulin resistance aggravate liver disease, while NAFLD promotes cardiovascular risk in affected patients. The pathomechanisms of NAFLD are multifaceted, combining hepatic factors including lipotoxicity, mechanisms of cell death and liver inflammation with extrahepatic factors including metabolic disturbance and dysbiosis. Nuclear receptors (NRs) are a family of ligand-controlled transcription factors that regulate glucose, fat and cholesterol homeostasis and modulate innate immune cell functions, including liver macrophages. In parallel with metabolic derangement in NAFLD, altered NR signaling is frequently observed and might be involved in the pathogenesis. Therapeutically, clinical data indicate that single drug targets thus far have been insufficient for reaching patient-relevant endpoints. Therefore, combinatorial treatment strategies with multiple drug targets or drugs with multiple mechanisms of actions could possibly bring advantages, by providing a more holistic therapeutic approach. In this context, peroxisome proliferator-activated receptors (PPARs) and other NRs are of great interest as they are involved in wide-ranging and multi-organ activities associated with NASH progression or regression. In this review, we summarize recent advances in understanding the pathogenesis of NAFLD, focusing on mechanisms of cell death, immunometabolism and the role of NRs. We outline novel therapeutic strategies and discuss remaining challenges.

Vertical distributions and potential sources of wintertime atmospheric pollutants and the corresponding ozone production on the coast of Bohai Sea.

This study investigated the wintertime vertical distributions and source areas of aerosols, NO2, and HCHO in a coastal city of Dongying from December 2020 to March 2021, using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) and a potential source contribution function (PSCF) model, respectively. Moreover, the chemical production sensitivity of O3 at different height layers was analyzed using HCHO/NO2 ratios. The results revealed that the wintertime averaged highest concentrations of aerosol (1.25 km-1), NO2 (14.81 ppb), and HCHO (2.32 ppb) were mainly distributed at the surface layer, 100-200 m layer, and 200-300 m layer, respectively. Regarding the diurnal cycles, high concentrations of aerosol (>1.4 km-1) and NO2 (>16.0 ppb) usually appeared in the early morning and late afternoon, while high concentrations of HCHO (>2.5 ppb) usually occurred during 12:00-15:00. The PSCF model revealed that the wintertime aerosol mainly originated from Shandong, northern Jiangsu, Korea, and the northwestern Mongolian Plateau. Below 200 m, NO2 was mainly from western Shandong, whereas above 600 m, it was mainly from northern Shandong and the Beijing-Tianjin-Hebei (BTH) region. The corresponding sources for HCHO were central and southern Shandong (below 200 m) and northern Shandong, northern Jiangsu, and southeastern BTH (above 600 m). In addition, the chemical production sensitivity of O3 below 100 m was observed only in the VOC-limited regime. The percentages of O3 production under the NOx-limited, NOx-VOC-limited, and VOC-limited regimes were 10.75% (31.18%), 4.30% (19.35%), and 84.95% (49.47%) at the 500-600 m (900-1000 m) layer. This study has guiding significance for the coordinated control of PM2.5 and O3, and can assist in the implementation of regional joint prevention and control strategies for air pollutants.

Polycyclic aromatic hydrocarbons (PAHs) in urban stream sediments of Suzhou Industrial Park, an emerging eco-industrial park in China: Occurrence, sources and potential risk.

In this study, urban stream sediment samples were collected in the Suzhou Industrial Park (SIP), one of the earliest national demonstration eco-industrial parks of China. PAHs were analyzed in these sediments, and concentrations of total PAHs were 180-81,000 ng g-1 (5700 ± 14,000 ng g-1). Medium molecular weight (4- ring) PAHs were predominant (42 ± 12%), followed by high molecular weight (5- and 6- ring) PAHs (31 ± 10%). No correlation was found between concentrations of PAHs and land uses of SIP in this study. Diagnostic ratios and a positive matrix factorization (PMF) model indicated that coal/biomass combustion might be the primary PAH source (61%), followed by non-combustion sources (21%) and vehicular emission (18%). According to the spatial analysis, PAHs in the sediments of SIP might be mainly associated with the coal/biomass combustion in the northeast industrial zone. Residential & commercial activities seem not to be the major causes of PAH contamination. Total PAH toxic equivalent concentrations, effect range low/effect range median values, and mean effects range-median quotient all showed that PAHs were present at a low toxicity risk level in most regions of the SIP. However, vigilance is required at some sampling sites with extremely high PAH concentrations or high mean effects range-median quotient.

TMEM158 promotes pancreatic cancer aggressiveness by activation of TGFß1 and PI3K/AKT signaling pathway.

Pancreatic cancer (PC) is one of the most deadly digestive cancers world-wide, with a dismal five-year survival rate of <8%. Upregulation of transmembrane protein 158 (TMEM158) is known to facilitate the progression of several carcinomas. However, little is known concerning the potential roles of TMEM158 in PC. Herein, we first found that TMEM158 was significantly upregulated in PC samples as well as PC cell lines. The overexpression of TMEM158 was significantly correlated with advanced clinicopathologic features (including tumor size, TNM stage, and blood vessel invasion) and poorer prognosis of patients with PC in clinic. Evidenced based on a series of loss- and gain-of-function assays uncovered that TMEM158 enhanced PC cell proliferation, migration, and invasion by stimulating the progression of cell cycle, epithelial-mesenchymal transition, and MMP-2/9 production. Furthermore, mechanism-related investigations disclosed that activation of TGFß1 and PI3K/AKT signal might be responsible for TMEM158-triggered PC aggressiveness. Collectively, TMEM158 was upregulated in PC and promoted PC cell proliferation, migration, and invasion through the activation of TGFß1 and PI3K/AKT signaling pathways, highlighting its potential as a tumor promoter and a therapeutic target for PC.

Development and application of a novel whole sediment toxicity test using immobilized sediment and Chlorella vulgaris.

The sediments of water bodies are not only pollutants sink but also sources of pollution. The assessment for the whole-sediment toxicity is still challenging research. Although the application of immobilized algal bead could overcome the practical difficulties in sediment toxicity assay, the weak growth and reduced sensitivity of algae inside the bead restricted its application. In this study, a sediment toxicity test was developed using immobilized sediment and Chlorella vulgaris. The immobilized sediment was prepared by mixing 2 g freeze-dried sediment and 15-mL 3% (w/v) alginate and hardened in a 4% (w/v) CaCl2 solution. Based on a C. vulgaris growth inhibition test and using the immobilized sediment, the median effective concentration value (EC50) of the spiked Cu and diuron was 506.23 and 2.37 mg/kg respectively, lower than that of using immobilized algae (719.62 and 3.12 mg/kg respectively). The Cu and diuron concentrations in the corresponding overlying water from the spiked immobilized and free sediment showed that sediment pollutants' diffusion capacity was not decreased after immobilization. By using the immobilized sediment in algae toxicity bioassay, the changes in the sediment toxicity of a polluted river before and after dredging was evaluated. The C. vulgaris growth inhibition in sediment A decreased from 81.94% to 8.43%; sediment B remained unchanged; sediment C stimulated the growth of C. vulgaris before dredging (-15.56%), but inhibited the algae growth after dredging (26.88%), and sediment D decreased growth inhibition from 32.66% to -12.60%.

Methylxanthine derivatives promote autophagy in gastric cancer cells targeting PTEN.

Methylxanthine derivatives, such as caffeine and theophylline, enhance cell apoptosis and autophagy and reportedly induce the activity of phosphatase and tensin homologue (PTEN) and inhibit the mammalian target of rapamycin (mTOR). This study investigated the impacts of caffeine and theophylline on gastric cancer cell apoptosis and autophagy using a gastric cancer cell line (MGC-803) and a nude mouse model. Peritumoural and tumour tissues were collected from five patients diagnosed with gastric carcinoma who underwent laparoscopic radical gastrectomy at our hospital. Autophagy was suppressed in gastric cancer tumour tissue compared with peritumoural tissue. In vitro, both caffeine and theophylline effectively suppressed MGC-803 cell proliferation and migration and induced autophagy. To assess the involvement of PTEN in caffeine-mediated and theophylline-mediated gastric cancer cell death, we transiently transfected MGC-803 cells with an siRNA targeting PTEN. PTEN knockdown impaired the methylxanthine derivative-mediated inhibition of PI3K/Akt/mTOR signalling. In nude mice treated with caffeine or theophylline, MGC-803 cell tumours injected with siPTEN were larger than those injected with negative control siRNA. These results show that the methylxanthine derivatives (caffeine and theophylline) effectively induce gastric cancer cell apoptosis and autophagy by PTEN activation and PI3K/Akt/mTOR pathway suppression and strongly support the use of methylxanthine derivatives as potential anticancer therapeutics.

Evaluation of drug combination for glioblastoma based on an intestine-liver metabolic model on microchip.

An intestine-liver-glioblastoma biomimetic system was developed to evaluate the drug combination therapy for glioblastoma. A hollow fiber (HF) was embedded into the upper layer of the microfluidic chip for culturing Caco-2 cells to mimic drug delivery as an artificial intestine. HepG2 cells cultured in the bottom chamber of the chip acted as an artificial liver for metabolizing the drugs. The dual-drug combination to glioblastoma U251 cells was evaluated based on the intestine-liver metabolic model. The drugs, irinotecan (CPT-11), temozolomide (TMZ) and cyclophosphamide (CP), were used to dynamically stimulate the cells by continuous infusion into the intestine unit. After intestine absorption and liver metabolism, the prodrugs were transformed to active metabolites, which induced glioblastoma cells apoptosis. The anticancer activity of the CPT-11 and TMZ combination is significantly enhanced compared to that of the single drug treatments. Combination index (CI) values of the combination groups, CPT-11 and TMZ, CPT-11 and CP, and TMZ and CP, at half maximal inhibitory concentration were 0.137, 0.288, and 0.482, respectively. The results indicated that the CPT-11 and TMZ combination was superior to the CPT-11 and CP group as well as the TMZ and CP group towards the U251 cells. The metabolism mechanism of CPT-11 and TMZ was further studied by coupling with mass spectrometric analysis. The biomimetic model enables the performance of long-term cell co-culture, drug delivery, metabolism and real-time analysis of drug effects, promising systematic in vitro mimicking of physiological and pharmacological processes.

Dispersive solid-phase extraction followed by vortex-assisted dispersive liquid-liquid microextraction based on the solidification of a floating organic droplet for the determination of benzoylurea insecticides in soil and sewage sludge.

A novel dispersive solid-phase extraction combined with vortex-assisted dispersive liquid-liquid microextraction based on solidification of floating organic droplet was developed for the determination of eight benzoylurea insecticides in soil and sewage sludge samples before high-performance liquid chromatography with ultraviolet detection. The analytes were first extracted from the soil and sludge samples into acetone under optimized pretreatment conditions. Clean-up of the extract was conducted by dispersive solid-phase extraction using activated carbon as the sorbent. The vortex-assisted dispersive liquid-liquid microextraction based on solidification of floating organic droplet procedure was performed by using 1-undecanol with lower density than water as the extraction solvent, and the acetone contained in the solution also acted as dispersive solvent. Under the optimum conditions, the linearity of the method was in the range 2-500 ng/g with correlation coefficients (r) of 0.9993-0.9999. The limits of detection were in the range of 0.08-0.56 ng/g. The relative standard deviations varied from 2.16 to 6.26% (n = 5). The enrichment factors ranged from 104 to 118. The extraction recoveries ranged from 81.05 to 97.82% for all of the analytes. The good performance has demonstrated that the proposed methodology has a strong potential for application in the multiresidue analysis of complex matrices.

Detection and differentiation of Japanese encephalitis virus genotype I and genotype III by reverse transcription loop-mediated isothermal amplification combined with restriction fragment length polymorphism.

Japanese encephalitis (JE), which is a mosquito-borne arboviral infection, is the leading cause of viral encephalitis in Asian countries. The causative agent of JE is Japanese encephalitis virus (JEV), in which the predominant genotype has changed from genotype III (G III) to genotype I (G I). However, a method for the rapid differentiation between JEV G I and G III remains unavailable. This study aimed to establish a rapid JEV genotyping method using reverse transcription loop-mediated isothermal amplification (RT-LAMP). An Spe I site, which was located in the target sequence (C gene) of JEV G III strains but not in JEV G I strains, was selected as the RT-LAMP target. After testing 64 specimens, results showed that RT-LAMP can detect and differentiate JEV G I and G III specifically. Thus, a novel RT-LAMP system for the rapid detection and differentiation of JEV G I and G III was developed successfully.

Enhancing antitumor immunity and achieving tumor eradication with IL11RA mRNA immunotherapy.

Current methods for delivering genes to target tumors face significant challenges, including off-target effects and immune responses against delivery vectors. In this study, we developed a novel approach using messenger RNA (mRNA) to encode IL11RA for local immunotherapy, aiming to harness the immune system to combat tumors. Our research uncovered a compelling correlation between IL11RA expression and CD8 + T cell levels across multiple tumor types, with elevated IL11RA expression correlating with improved overall survival. Examination of the Pan-Cancer Atlas dataset showed a significant reduction in IL11RA expression in various cancer types compared to normal tissue, raising questions about its potential role in tumorigenesis. To achieve efficient in vivo expression of IL11RA, we synthesized two mRNA sequences mimicking the wild-type protein. These mRNA sequences were formulated and capped to ensure effective delivery, resulting in robust expression within tumor sites. Our investigation into IL11RA mRNA therapy demonstrated its effectiveness in controlling tumor growth when administered both intratumorally and intravenously in mouse models. Additionally, IL11RA mRNA treatment significantly stimulated the expansion of CD8 + T cells within tumors, draining lymph nodes, and the spleen. Transcriptome analysis revealed distinct transcriptional patterns associated with T cell functions. Using multiple deconvolution algorithms, we found substantial infiltration of CD8 + T cells following IL11RA mRNA treatment, highlighting its immunomodulatory effects within the tumor microenvironment. In conclusion, IL11RA mRNA therapy presents a promising strategy for tumor regression with potential immunomodulatory effects and clinical implications for improved survival outcomes.

Multiomics analyses decipher intricate changes in the cellular and metabolic landscape of steatotic livers upon dietary restriction and sleeve gastrectomy.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic, progressive liver disease that encompasses a spectrum of steatosis, steatohepatitis (or MASH), and fibrosis. Evidence suggests that dietary restriction (DR) and sleeve gastrectomy (SG) can lead to remission of hepatic steatosis and inflammation through weight loss, but it is unclear whether these procedures induce distinct metabolic or immunological changes in MASLD livers. This study aims to elucidate the intricate hepatic changes following DR, SG or sham surgery in rats fed a high-fat diet as a model of obesity-related MASLD, in comparison to a clinical cohort of patients undergoing SG. Single-cell and single-nuclei transcriptome analysis, spatial metabolomics, and immunohistochemistry revealed the liver landscape, while circulating biomarkers were measured in serum samples. Artificial intelligence (AI)-assisted image analysis characterized the spatial distribution of hepatocytes, myeloid cells and lymphocytes. In patients and experimental MASLD rats, SG improved body mass index, circulating liver injury biomarkers and triglyceride levels. Both DR and SG attenuated liver steatosis and fibrosis in rats. Metabolism-related genes (Ppara, Cyp2e1 and Cyp7a1) were upregulated in hepatocytes upon DR and SG, while SG broadly upregulated lipid metabolism on cholangiocytes, monocytes, macrophages, and neutrophils. Furthermore, SG promoted restorative myeloid cell accumulation in the liver not only ameliorating inflammation but activating liver repair processes. Regions with potent myeloid infiltration were marked with enhanced metabolic capacities upon SG. Additionally, a disruption of periportal hepatocyte functions was observed upon DR. In conclusion, this study indicates a dynamic cellular crosstalk in steatotic livers of patients undergoing SG. Notably, PPARα- and gut-liver axis-related processes, and metabolically active myeloid cell infiltration indicate intervention-related mechanisms supporting the indication of SG for the treatment of MASLD.

Dissecting Acute Drug-Induced Hepatotoxicity and Therapeutic Responses of Steatotic Liver Disease Using Primary Mouse Liver and Blood Cells in a Liver-On-A-Chip Model.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is hallmarked by hepatic steatosis, cell injury, inflammation, and fibrosis. This study elaborates on a multicellular biochip-based liver sinusoid model to mimic MASLD pathomechanisms and investigate the therapeutic effects of drug candidates lanifibranor and resmetirom. Mouse liver primary hepatocytes, hepatic stellate cells, Kupffer cells, and endothelial cells are seeded in a dual-chamber biocompatible liver-on-a-chip (LoC). The LoC is then perfused with circulating immune cells (CICs). Acetaminophen (APAP) and free fatty acids (FFAs) treatment recapitulate acute drug-induced liver injury and MASLD, respectively. As a benchmark for the LoC, multiplex immunofluorescence on livers from APAP-injected and dietary MASLD-induced mice reveals characteristic changes on parenchymal and immune cell populations. APAP exposure induces cell death in the LoC, and increased inflammatory cytokine levels in the circulating perfusate. Under FFA stimulation, lipid accumulation, cellular damage, inflammatory secretome, and fibrogenesis are increased in the LoC, reflecting MASLD. Both injury conditions potentiate CIC migration from the perfusate to the LoC cellular layers. Lanifibranor prevents the onset of inflammation, while resmetirom decreases lipid accumulation in hepatocytes and increases the generation of FFA metabolites in the LoC. This study demonstrates the LoC potential for functional and molecular evaluation of liver disease drug candidates.

Mechanical thrombectomy for symptomatic stent thrombosis after carotid artery stenting.

Background: As there is still no consensus on the treatment of carotid stent thrombosis (CST), we would like to describe our experience with the revascularization of CST by mechanical thrombectomy. Methods: We retrospectively studied patients who underwent mechanical thrombectomy after CST at Xuzhou Municipal First People's Hospital and Xuzhou Central Hospital between January 2020 and November 2022. The results of the procedures, complications, and clinical and imaging follow-up were recorded. Results: A total of six patients were included in this study. The stenosis grade before stent implantation was ≥85% in all patients, and the stenosis length ranged from 7 to 20 mm. Patients experienced CST within 6 days to 45 months after carotid artery stenting (CAS); the median admission on the National Institutes of Health Stroke Scale (NIHSS) at CST was 12 (range 8-25). Mechanical thrombectomy was successfully performed in all patients. There was no periprocedural death, and the modified Rankin Scale (mRS) at the 3-month follow-up was 0-2. All patients showed recovery from their neurological deficits. Conclusion: The treatment of symptomatic CST with mechanical thrombectomy resulted in satisfactory clinical outcomes. This regimen could be effective and safe, and future prospective and randomized studies are warranted.