Tumour immune rejection triggered by activation of α2-adrenergic receptors.

Immunotherapy based on immunecheckpoint blockade (ICB) using antibodies induces rejection of tumours and brings clinical benefit in patients with various cancer types1. However, tumours often resist immune rejection. Ongoing efforts trying to increase tumour response rates are based on combinations of ICB with compounds that aim to reduce immunosuppression in the tumour microenvironment but usually have little effect when used as monotherapies2,3. Here we show that agonists of α2-adrenergic receptors (α2-AR) have very strong anti-tumour activity when used as monotherapies in multiple immunocompetent tumour models, including ICB-resistant models, but not in immunodeficient models. We also observed marked effects in human tumour xenografts implanted in mice reconstituted with human lymphocytes. The anti-tumour effects of α2-AR agonists were reverted by α2-AR antagonists, and were absent in Adra2a-knockout (encoding α2a-AR) mice, demonstrating on-target action exerted on host cells, not tumour cells. Tumours from treated mice contained increased infiltrating T lymphocytes and reduced myeloid suppressor cells, which were more apoptotic. Single-cell RNA-sequencing analysis revealed upregulation of innate and adaptive immune response pathways in macrophages and T cells. To exert their anti-tumour effects, α2-AR agonists required CD4+ T lymphocytes, CD8+ T lymphocytes and macrophages. Reconstitution studies in Adra2a-knockout mice indicated that the agonists acted directly on macrophages, increasing their ability to stimulate T lymphocytes. Our results indicate that α2-AR agonists, some of which are available clinically, could substantially improve the clinical efficacy of cancer immunotherapy.

Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects.

Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. We developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.

Identification of blood metabolites associated with risk of Alzheimer's disease by integrating genomics and metabolomics data.

Specific metabolites have been reported to be potentially associated with Alzheimer's disease (AD) risk. However, the comprehensive understanding of roles of metabolite biomarkers in AD etiology remains elusive. We performed a large AD metabolome-wide association study (MWAS) by developing blood metabolite genetic prediction models. We evaluated associations between genetically predicted levels of metabolites and AD risk in 39,106 clinically diagnosed AD cases, 46,828 proxy AD and related dementia (proxy-ADD) cases, and 401,577 controls. We further conducted analyses to determine microbiome features associated with the detected metabolites and characterize associations between predicted microbiome feature levels and AD risk. We identified fourteen metabolites showing an association with AD risk. Five microbiome features were further identified to be potentially related to associations of five of the metabolites. Our study provides new insights into the etiology of AD that involves blood metabolites and gut microbiome, which warrants further investigation.

A novel subpopulation of monocytes with a strong interferon signature indicated by SIGLEC-1 is present in patients with in recent-onset type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes is a T cell-mediated autoimmune disease characterised by pancreatic beta cell destruction. In this study, we explored the pathogenic immune responses in initiation of type 1 diabetes and new immunological targets for type 1 diabetes prevention and treatment. METHODS: We obtained peripheral blood samples from four individuals with newly diagnosed latent autoimmune diabetes in adults (LADA) and from four healthy control participants. Single-cell RNA-sequencing (scRNA-seq) was performed on peripheral blood mononuclear cells to uncover transcriptomic profiles of early LADA. Validation was performed through flow cytometry in a cohort comprising 54 LADA, 17 adult-onset type 2 diabetes, and 26 healthy adults, matched using propensity score matching (PSM) based on age and sex. A similar PSM method matched 15 paediatric type 1 diabetes patients with 15 healthy children. Further flow cytometry analysis was performed in both peripheral blood and pancreatic tissues of non-obese diabetic (NOD) mice. Additionally, cell adoptive transfer and clearance assays were performed in NOD mice to explore the role of this monocyte subset in islet inflammation and onset of type 1 diabetes. RESULTS: The scRNA-seq data showed that upregulated genes in peripheral T cells and monocytes from early-onset LADA patients were primarily enriched in the IFN signalling pathway. A new cluster of classical monocytes (cluster 4) was identified, and the proportion of this cluster was significantly increased in individuals with LADA compared with healthy control individuals (11.93% vs 5.93%, p=0.017) and that exhibited a strong IFN signature marked by SIGLEC-1 (encoding sialoadhesin). These SIGLEC-1+ monocytes expressed high levels of genes encoding C-C chemokine receptors 1 or 2, as well as genes for chemoattractants for T cells and natural killer cells. They also showed relatively low levels of genes for co-stimulatory and HLA molecules. Flow cytometry analysis verified the elevated levels of SIGLEC-1+ monocytes in the peripheral blood of participants with LADA and paediatric type 1 diabetes compared with healthy control participants and those with type 2 diabetes. Interestingly, the proportion of SIGLEC-1+ monocytes positively correlated with disease activity and negatively with disease duration in the LADA patients. In NOD mice, the proportion of SIGLEC-1+ monocytes in the peripheral blood was highest at the age of 6 weeks (16.88%), while the peak occurred at 12 weeks in pancreatic tissues (23.65%). Adoptive transfer experiments revealed a significant acceleration in diabetes onset in the SIGLEC-1+ group compared with the SIGLEC-1- or saline control group. CONCLUSIONS/INTERPRETATION: Our study identified a novel group of SIGLEC-1+ monocytes that may serve as an important indicator for early diagnosis, activity assessment and monitoring of therapeutic efficacy in type 1 diabetes, and may also be a novel target for preventing and treating type 1 diabetes. DATA AVAILABILITY: RNA-seq data have been deposited in the GSA human database ( https://ngdc.cncb.ac.cn/gsa-human/ ) under accession number HRA003649.

Elucidating the role of blood metabolites on pancreatic cancer risk using two-sample Mendelian randomization analysis.

Pancreatic ductal adenocarcinoma (PDAC) is an uncommon but highly fatal malignancy. Identifying causal metabolite biomarkers offers an opportunity to facilitate effective risk assessment strategies for PDAC. In this study, we performed a two-sample Mendelian randomization (MR) study to characterize the potential causal effects of metabolites in plasma on PDAC risk. Genetic instruments were determined for a total of 506 metabolites from one set of comprehensive genome-wide association studies (GWAS) involving 913 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts. Another set of genetic instruments was developed for 483 metabolites from an independent GWAS conducted with 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging (CLSA) cohort. We analyzed GWAS data of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), comprising 8275 PDAC cases and 6723 controls of European ancestry. The association of metabolites with PDAC risk was assessed using the inverse-variance weighted (IVW) method, and complemented with sensitivity analyses of MR-Egger and MR-PRESSO tests. Potential side effects of targeting the identified metabolites for PDAC intervention were further evaluated by a phenome-wide MR (Phe-MR) analysis. Forty-four unique metabolites were identified to be significantly associated with PDAC risk, of which four top-ranking metabolites (X: 12798, X: 11787, X: 11308 and X: 19141) showed replication evidence when using instruments developed from both two cohorts. Our results highlight novel blood metabolites related to PDAC risk, which may help prioritize metabolic features for PDAC mechanistic research and further evaluation of their potential role in PDAC risk assessment.

Regulome-wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk.

Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.

Trade-off in the partitioning of recent photosynthate carbon under global change.

There may be trade-offs in the allocation patterns of recent photosynthetic carbon (RPC) allocation in response to environmental changes, with a greater proportion of RPC being directed towards compartments experiencing limited resource availability. Alternatively, the allocation of RPC could shift from sources to sinks as plants processing excess photosynthates. It prompts the question: Does the pattern of RPC allocation vary under global changes? If so, is this variation driven by optimal or by residual C allocation strategies? We conducted a meta-analysis by complicating 273 pairwise observations from 55 articles with 13 C or 14 C pulse or continuous labeling to assess the partitioning of RPC in biomass (leaf, stem, shoot, and root), soil pools (soil organic C, rhizosphere, and microbial biomass C) and CO2 fluxes under elevated CO2 (eCO2 ), warming, drought and nitrogen (N) addition. We propose that the increased allocation of RPC to belowground under sufficient CO2 results from the excretion of excess photosynthates. Warming led to a significant reduction in the percentage of RPC allocated to shoots, alongside an increase in roots allocation, although this was not statistically significant. This pattern is due to the reduced water availability resulting from warming. In conditions of drought, there was a notable increase in the partitioning of RPC to stems (+7.25%) and roots (+36.38%), indicative of a greater investment of RPC in roots for accessing water from deeper soil. Additionally, N addition led to a heightened allocation of RPC in leaves (+10.18%) and shoots (+5.78%), while reducing its partitioning in soil organic C (-8.92%). Contrary to the residual C partitioning observed under eCO2 , the alterations in RPC partitioning in response to warming, drought, and N supplementation are more comprehensively explained through the lens of optimal partitioning theory, showing a trade-off in the partitioning of RPC under global change.

Body Fat Depletion: the Yin Paradigm for Treating Type 2 Diabetes.

PURPOSE OF REVIEW: To highlight that body fat depletion (the Yin paradigm) with glucose-lowering treatments (the Yang paradigm) are associated with metabolic benefits for patients with type 2 diabetes mellitus (T2DM). RECENT FINDINGS: The sodium-glucose cotransporter-2 inhibitor-mediated sodium/glucose deprivation can directly improve glycemic control and kidney outcome in patients with T2DM. The glucose deprivation might also promote systemic fatty acid ß-oxidation to deplete ectopic/visceral fat and thereby contribute to the prevention of cardiovascular diseases. As with metabolic surgery, bioengineered incretin-based medications with potent anorexigenic and insulinotropic efficacy can significantly reduce blood glucose as well as body weight (especially in the ectopic/visceral fat depots). The latter effects could be a key contributor to their cardiovascular-renal protective effects. In addition to a healthy diet, the newer glucose-lowering medications, with body fat reduction effects, should be prioritized when treating patients with T2DM, especially for those with established cardiovascular/renal risks or diseases.

Long-term changes in frailty and incident type 2 diabetes: A prospective cohort study based on the UK Biobank.

AIMS: To estimate the association between long-term changes in frailty and the risk of incident type 2 diabetes (T2DM) and to evaluate the effect of preventing the worsening of frailty on the risk of T2DM. METHODS: We included 348 205 participants free of baseline T2DM and with frailty phenotype (FP) data from the UK Biobank; among them, 36 175 had at least one follow-up assessment. According to their FP score, participants were grouped into nonfrailty, prefrailty and frailty groups. Frailty assessed at baseline and at follow-up was used to derive the trajectory of frailty (ΔFP). Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Compared with those in the nonfrailty group at baseline, the HRs of T2DM for the prefrailty and frailty groups were 1.38 (95% CI 1.33-1.43) and 1.69 (95% CI 1.59-1.79), respectively (both p < 0.001), in the multivariable-adjusted model. During a median follow-up of 5.4 years after the final assessment, data for 472 T2DM patients were recorded. A 1-point increase in the final FP was associated with a 25% (95% CI 1.14-1.38; p < 0.001) increased risk of T2DM. For the trajectory of frailty, each 0.5-point/year increase in ΔFP was associated with a 52% (95% CI 1.18-1.97; p < 0.001) greater risk of T2DM, independent of the FP score at baseline. Compared with those that remained in the nonfrailty group, the greatest risk of T2DM over time was prefrailty aggravation (HR 3.03, 95% CI 2.00-4.58; p < 0.001). Using the frailty index did not materially change the results. CONCLUSIONS: Long-term changes in frailty were associated with the risk of incident T2DM, irrespective of baseline frailty status. Preventing the worsening of frailty may reduce T2DM risk.

Optimization of Flavonoid Extraction from Eucommia ulmoides pollen using Respond Surface Methodology and its biological activities.

Flavonoids, known for their abundance in Eucommia ulmoides pollen, possess diverse biological functions, including antioxidants, antibacterial agents, and anti-tumor properties. This study aims to establish effective parameters for flavonoid extraction from Eucommia ulmoides pollen using a microwave-assisted method, characterize the flavonoid composition of the extracted material, and explore its biological activities. Building upon the initial results from single-factor experiments, response surface methodology was employed to optimize the extraction parameters. The inhibitory effect of human breast cancer cells (MCF-7) was evaluated by CCK assay and Live/dead staining. Simultaneously, the extract's scavenging ability against DPPH free radicals and its antibacterial properties against Escherichia coli and Staphylococcus aureus were investigated. The results demonstrated that the flavonoid yield reached 3.28 g per 100 g of pollen, closely aligning with the predicted value. The IC50 for flavonoid-mediated DPPH radical scavenging was 0.04 mg/mL. The extract exhibited a robust inhibitory effect on both Escherichia coli and Staphylococcus aureus. Concurrently, the extract displayed a significant inhibitory effect on the growth and proliferation of MCF-7 cells in a dose-dependent and time-dependent manner. In addition, six kinds of flavonoids have been identified by UPLC-TOF-MS/MS technology, providing further support to the study on the anti-oxidation and anti-tumor mechanism of Eucommia ulmoides pollen extracts.

Selecting Flap Transfer Methods to Repair Helix Soft Tissue Defect Based on the Direction of Long Axis.

BACKGROUND: The posterior auricular flap has long been favored for repairing skin defects on the ear's surface. However, achieving optimal esthetic outcomes in ear reconstruction requires a flexible approach to flap transfer methods. While bipedicle advancement flaps are commonly used for body wound coverage, they are rarely used in auricular defect repair. OBJECTIVE: To propose a modified flap transfer approach based on the orientation of the auricular defect's long axis and assess the postoperative esthetic outcomes. METHODS: The authors reported 12 patients treated using 2 distinct flap transfer techniques. Mild to moderate helix soft tissue defects remained after excision of the masses. A direct island flap was created for patients with longitudinal defects to cover the defect. For patients with transverse defects, a combination of bipedicle and island flaps was used for repair. Scar quality and esthetic outcomes were assessed at least 6 months postsurgery using the Scar Cosmesis Assessment and Rating scale. RESULTS: All patients experienced no serious complications and achieved excellent cosmetic results. Patients undergoing combined flap transfer exhibited relatively more favorable esthetic outcomes. CONCLUSION: The authors propose a novel concept for repairing helix soft tissue defects by designing local flaps based on the direction of the defect's long axis. For repairing helix soft tissue defects with a long axis parallel to the auricular edge, the combined utilization of bipedicle advancement flap and island rotation flap transfer should be consideration more.

The Facial Artery Perforator Flap for Reconstruction of Facial Defects: Surgical Pearls and Clinical Series.

BACKGROUND: Based on the knowledge of facial vascularity, facial artery perforator flaps could be used as potent tools for facial defect reconstruction. However, lack of experience and misconception of this technique limits the broad application in the clinical background. Here, we discussed surgical techniques based on our previous experience with facial artery perforator (FAP)-based facial defect reconstruction. METHODS: A retrospective review of 12 patients undergoing facial defect reconstruction using an FAP flap was performed, including 8 defects in the mid-facial part and 4 defects in the nasal area generally resulted from basal cell carcinoma (8 patients), squamous cell carcinoma (3 patients), and actinic keratosis (one patient). RESULTS: All patients received one-stage FAP flap reconstruction. The overall follow-up period was 6 to 12 months. All reconstructions were successful with satisfactory patient-reported outcome and no local recurrence. No significant complications were observed in most cases, except for one instance of partial flap loss. CONCLUSIONS: Overall, taking advantage of FAP flaps will contribute to a good functional and esthetic outcome of facial defect reconstructions.

Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk.

A large proportion of the heritability of pancreatic cancer risk remains elusive, and the contribution of specific mRNA splicing events to pancreatic cancer susceptibility has not been systematically evaluated. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies (Enet, LASSO and MCP) to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for pancreatic cancer risk by assessing 8275 pancreatic cancer cases and 6723 controls of European ancestry. Data from 305 subjects of whom the majority are of European descent in the Genotype-Tissue Expression Project (GTEx) were used and both cis-acting and promoter-enhancer interaction regions were considered to build these models. We identified nine splicing events of seven genes (ABO, UQCRC1, STARD3, ETAA1, CELA3B, LGR4 and SFT2D1) that showed an association of genetically predicted expression with pancreatic cancer risk at a false discovery rate ≤0.05. Of these genes, UQCRC1 and LGR4 have not yet been reported to be associated with pancreatic cancer risk. Fine-mapping analyses supported likely causal associations corresponding to six splicing events of three genes (P4HTM, ABO and PGAP3). Our study identified novel genes and splicing events associated with pancreatic cancer risk, which can improve our understanding of the etiology of this deadly malignancy.

A splicing transcriptome-wide association study identifies novel altered splicing for Alzheimer's disease susceptibility.

Alzheimer's disease (AD) is a common neurodegenerative disease in aging individuals. Alternative splicing is reported to be relevant to AD development while their roles in etiology of AD remain largely elusive. We performed a comprehensive splicing transcriptome-wide association study (spTWAS) using intronic excision expression genetic prediction models of 12 brain tissues developed through three modelling strategies, to identify candidate susceptibility splicing introns for AD risk. A total of 111,326 (46,828 proxy) cases and 677,663 controls of European ancestry were studied. We identified 343 associations of 233 splicing introns (143 genes) with AD risk after Bonferroni correction (0.05/136,884 = 3.65 × 10-7). Fine-mapping analyses supported 155 likely causal associations corresponding to 83 splicing introns of 55 genes. Eighteen causal splicing introns of 15 novel genes (EIF2D, WDR33, SAP130, BYSL, EPHB6, MRPL43, VEGFB, PPP1R13B, TLN2, CLUHP3, LRRC37A4P, CRHR1, LINC02210, ZNF45-AS1, and XPNPEP3) were identified for the first time to be related to AD susceptibility. Our study identified novel genes and splicing introns associated with AD risk, which can improve our understanding of the etiology of AD.

Associations between genetically predicted levels of blood metabolites and pancreatic cancer risk.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid malignancies, which is featured by systematic metabolism. Thus, a better understanding of metabolic dysregulation in PDAC is important to better characterize its etiology. Here, we performed a large metabolome-wide association study (MWAS) to systematically explore associations between genetically predicted metabolite levels in blood and PDAC risk. Using data from 881 subjects of European descent in the TwinsUK Project, comprehensive genetic models were built to predict serum metabolite levels. These prediction models were applied to the genetic data of 8275 cases and 6723 controls included in the PanScan (I, II and III) and PanC4 consortia. After assessing the metabolite-PDAC risk associations by a slightly modified TWAS/FUSION framework, we identified five metabolites (including two dipeptides) showing significant associations with PDAC risk at false discovery rate (FDR) <0.05. Integrated with gut microbial information, two-sample Mendelian randomization (MR) analyses were further performed to investigate the relationship among serum metabolites, gut microbiome features and PDAC. The flavonoid-degrading bacteria Flavonifractor sp90199495 was found to be associated with metabolite X-21849 and it was also shown to be associated with PDAC risk. Collectively, our study identified novel candidate metabolites for PDAC risk, which could lead to new insights into the etiology of PDAC and improved treatment options.

A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer's disease risk.

Alzheimer's disease (ad) adversely affects the health, quality of life and independence of patients. There is a critical need to identify novel blood gene biomarkers for ad risk assessment. We performed a transcriptome-wide association study to identify biomarker candidates for ad risk. We leveraged two sets of gene expression prediction models of blood developed using different reference panels and modeling strategies. By applying the prediction models to a meta-GWAS including 71 880 (proxy) cases and 383 378 (proxy) controls, we identified significant associations of genetically determined expression of 108 genes in blood with ad risk. Of these, 15 genes were differentially expressed between ad patients and controls with concordant directions in measured expression data. With evidence from the analyses based on both genetic instruments and directly measured expression levels, this study identifies 15 genes with strong support as biomarkers in blood for ad risk, which may enhance ad risk assessment and mechanism-focused studies.

The transcription factor T-bet promotes the pathogenesis of nonalcoholic fatty liver disease by upregulating intrahepatic inflammation.

OBJECTIVE: To investigate the effect of the transcription factor T-bet on the pathogenesis of nonalcoholic fatty liver disease (NAFLD) and the regulation of the intrahepatic immune microenvironment. METHODS: Wild-type and T-bet knockout NASH mouse models were constructed. The effect of T-bet knockout on the pathogenesis of NAFLD was observed by histochemical staining. The expression of T-bet in immune cells in the liver and the effect of T-bet knockout on the proportion and function of immune cell subsets in the liver were determined by flow analysis. RESULTS: Flow cytometry results indicated that T-bet expression was increased in immune cells, especially NKT cells, in the livers of NAFLD mice. Knocking out the transcription factor T-bet reduced intrahepatic inflammation, reduced lipid accumulation, and ameliorated the pathogenesis of NAFLD. Based on the analysis of immune cell subsets, knocking out the transcription factor T-bet decreased the proportion, survival, and degree of activation of NK, NKT, and CD8 T cells in NAFLD liver; additionally, it decreased the secretion of IFN-γ by T cells and NKT cells but had no effect on the proportion of Th17 cells and Treg cells. Knocking out the transcription factor T-bet also reduced the proportion of proinflammatory myeloid-derived macrophages (MoMFs) in NAFLD liver, mainly the proportion of proinflammatory Ly6Chigh MoMFs. Furthermore, knocking out the transcription factor T-bet had no significant effect on the secretion of TNF-α from MoMFs but significantly reduced the expression of MHC class II molecules. Further analysis showed that the transcription factor T-bet may directly affect the expression of MHC class II molecules H2-AB1 and H2-Dmb1 through transcriptional regulation. CONCLUSIONS: Knocking out the transcription factor T-bet reduced the proinflammatory effect of innate immune cells (MoMFs, NK cells, and NKT cells) and T lymphocytes in NAFLD liver, thereby reducing intrahepatic inflammation and delaying the pathogenesis of NAFLD.

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integration sites. However, a published bioinformatic tool is not available to date. Thus, we developed an attention-based deep learning model DeepHPV to predict HPV integration sites by learning environment features automatically. In total, 3608 known HPV integration sites were applied to train the model, and 584 reviewed HPV integration sites were used as the testing dataset. DeepHPV showed an area under the receiver-operating characteristic (AUROC) of 0.6336 and an area under the precision recall (AUPR) of 0.5670. Adding RepeatMasker and TCGA Pan Cancer peaks improved the model performance to 0.8464 and 0.8501 in AUROC and 0.7985 and 0.8106 in AUPR, respectively. Next, we tested these trained models on independent database VISDB and found the model adding TCGA Pan Cancer performed better (AUROC: 0.7175, AUPR: 0.6284) than the model adding RepeatMasker peaks (AUROC: 0.6102, AUPR: 0.5577). Moreover, we introduced attention mechanism in DeepHPV and enriched the transcription factor binding sites including BHLHA15, CHR, COUP-TFII, DMRTA2, E2A, HIC1, INR, NPAS, Nr5a2, RARa, SCL, Snail1, Sox10, Sox3, Sox4, Sox6, STAT6, Tbet, Tbx5, TEAD, Tgif2, ZNF189, ZNF416 near attention intensive sites. Together, DeepHPV is a robust and explainable deep learning model, providing new insights into HPV integration preference and mechanism. Availability: DeepHPV is available as an open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepHPV.git, Contact: huzheng1998@163.com, liangjiuxing@m.scnu.edu.cn, lizheyzy@163.com.

Porcine promyelocytic leukemia protein isoforms suppress Japanese encephalitis virus replication in PK15 cells.

BACKGROUND: Promyelocytic leukemia protein (PML) is a primary component of PML nuclear bodies (PML-NBs). PML and PML-NBs play critical roles in processes like the cell cycle, DNA damage repair, apoptosis, and the antiviral immune response. Previously, we identified five porcine PML alternative splicing variants and observed an increase in the expression of these PML isoforms following Japanese encephalitis virus (JEV) infection. In this study, we examined the functional roles of these PML isoforms in JEV infection. METHODS: PML isoforms were either knocked down or overexpressed in PK15 cells, after which they were infected with JEV. Subsequently, we analyzed the gene expression of PML isoforms, JEV, and the interferon (IFN)-ß signaling pathway using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot. Viral titers were determined through 50% tissue culture infectious dose (TCID50) assays. RESULTS: Our results demonstrated that the knockdown of endogenous PML promoted JEV replication, while the overexpression of PML isoforms 1, 3, 4, and 5 (PML1, PML3, PML4, and PML5) inhibited JEV replication. Further investigation revealed that PML1, PML3, PML4, and PML5 negatively regulated the expression of genes involved in the interferon (IFN)-ß signaling pathway by inhibiting IFN regulatory factor 3 (IRF3) post-JEV infection. CONCLUSIONS: These findings demonstrate that porcine PML isoforms PML1, PML3, PML4, and PML5 negatively regulate IFN-ß and suppress viral replication during JEV infection. The results of this study provide insight into the functional roles of porcine PML isoforms in JEV infection and the regulation of the innate immune response.

Study of radiochemotherapy decision-making for young high-risk low-grade glioma patients using a macroscopic and microscopic combined radiomics model.

OBJECTIVES: As a few types of glioma, young high-risk low-grade gliomas (HRLGGs) have higher requirements for postoperative quality of life. Although adjuvant chemotherapy with delayed radiotherapy is the first treatment strategy for HRLGGs, not all HRLGGs benefit from it. Accurate assessment of chemosensitivity in HRLGGs is vital for making treatment choices. This study developed a multimodal fusion radiomics (MFR) model to support radiochemotherapy decision-making for HRLGGs. METHODS: A MFR model combining macroscopic MRI and microscopic pathological images was proposed. Multiscale features including macroscopic tumor structure and microscopic histological layer and nuclear information were grabbed by unique paradigm, respectively. Then, these features were adaptively incorporated into the MFR model through attention mechanism to predict the chemosensitivity of temozolomide (TMZ) by means of objective response rate and progression free survival (PFS). RESULTS: Macroscopic tumor texture complexity and microscopic nuclear size showed significant statistical differences (p < 0.001) between sensitivity and insensitivity groups. The MFR model achieved stable prediction results, with an area under the curve of 0.950 (95% CI: 0.942-0.958), sensitivity of 0.833 (95% CI: 0.780-0.848), specificity of 0.929 (95% CI: 0.914-0.936), positive predictive value of 0.833 (95% CI: 0.811-0.860), and negative predictive value of 0.929 (95% CI: 0.914-0.934). The predictive efficacy of MFR was significantly higher than that of the reported molecular markers (p < 0.001). MFR was also demonstrated to be a predictor of PFS. CONCLUSIONS: A MFR model including radiomics and pathological features predicts accurately the response postoperative TMZ treatment. CLINICAL RELEVANCE STATEMENT: Our MFR model could identify young high-risk low-grade glioma patients who can have the most benefit from postoperative upfront temozolomide (TMZ) treatment. KEY POINTS: • Multimodal radiomics is proposed to support the radiochemotherapy of glioma. • Some macro and micro image markers related to tumor chemotherapy sensitivity are revealed. • The proposed model surpasses reported molecular markers, with a promising area under the curve (AUC) of 0.95.