Integration of single-nucleus and exosome RNA sequencing dissected inter-cellular communication and biomarkers in pancreatic ductal adenocarcinoma

Background

Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication.

Method

We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network.

Results

We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes.

Conclusion

Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

ARID3A enhances chemoresistance of pancreatic cancer via inhibiting PTEN-induced ferroptosis

Currently, chemotherapy remains occupying a pivotal place in the treatment of pancreatic ductal adenocarcinoma (PDAC). Nonetheless, the emergence of drug resistance in recent years has limited the clinical efficacy of chemotherapeutic agents, especially gemcitabine (GEM). Through bioinformatics analysis, AT-rich Interactive Domain-containing Protein 3A (ARID3A), one of transcription factors, is discovered to possibly participate in this progress. This study thoroughly investigates the potential role of ARID3A in the malignant progression and GEM chemoresistance of PDAC and explores the underlying mechanisms. The results indicate that ARID3A knockdown suppresses tumor development and enhances the sensitivity of PDAC cells to GEM in vitro and vivo. Mechanically, CUT&Tag profiling sequencing, RNA-sequencing and functional studies demonstrates that decreased ARID3A expression alleviates the transcriptional inhibition of phosphatase and tensin homolog (PTEN), consequently leading to glutathione peroxidase 4 (GPX4) depletion and increased lipid peroxidation levels. Activated ferroptosis induced by the inhibition of GPX4 subsequently restricts tumor progression and reduces GEM resistance in PDAC. This research identifies the ferroptosis regulatory pathway of ARID3A-PTEN-GPX4 axis and reveals its critical role in driving the progression and chemoresistance of pancreatic cancer. Notably, both inhibition of ARID3A and enhancement of ferroptosis can increase chemosensitivity to GEM, which offers a promising opportunity for developing therapeutic strategies to combat acquired chemotherapy resistance in pancreatic cancer.

CPT1B maintains redox homeostasis and inhibits ferroptosis to induce gemcitabine resistance via the KEAP1/NRF2 axis in pancreatic cancer

BACKGROUND

Although we have made progress in treatment and have increased the 5-year survival by ≤30% in pancreatic cancer, chemotherapy resistance remains a major obstacle. However, whether reprogrammed lipid metabolism contributes to chemoresistance still needs to be further studied.

METHODS

Gene expression was determined using Western blotting and quantitative reverse transcription polymerase chain reaction. Cell cloning formation assay, Cell Counting Kit-8, EdU assay, wound healing assay, transwell assay, and flow cytometry were used to detect apoptosis, cell proliferation capacity, migration capacity, and cytotoxicity of gemcitabine. Confocal fluorescence microscopy, transmission electron microscopy, etc., were used to detect the changes in intracellular reactive oxygen species, glutathione, lipid peroxidation level, and cell morphology. An animal study was performed to evaluate the effect of CPT1B knockdown on tumor growth and gemcitabine efficacy.

RESULTS

In our study, we observed that the CPT1B expression level was higher in pancreatic ductal adenocarcinoma tissues than in normal tissues and correlated with a low rate of survival. Moreover, silencing of CPT1B significantly suppressed the proliferative ability and metastasis of pancreatic cancer cells. Furthermore, we discovered that CPT1B interacts with Kelch-like ECH-associated protein 1, and CPT1B knockdown led to decreased NRF2 expression and ferroptosis induction. In addition, CPT1B expression increased after gemcitabine treatment, and it was highly expressed in gemcitabine-resistant pancreatic ductal adenocarcinoma cells. Finally, we discovered that ferroptosis induced by CPT1B knockdown enhanced the gemcitabine toxicity in pancreatic ductal adenocarcinoma.

CONCLUSION

CPT1B may act as a promising target in treating patients with gemcitabine-resistant pancreatic ductal adenocarcinoma .

Intratumoral CD38+CD19+B cells associate with poor clinical outcomes and immunosuppression in patients with pancreatic ductal adenocarcinoma

BACKGROUND

The widespread involvement of tumor-infiltrating B cells highlights their potential role in tumor behavior. However, B cell heterogeneity in PDAC remains unexplored. Studying TIL-Bs in PDAC aims to identify new treatment strategies.

METHODS

We performed single-cell RNA sequencing to study the heterogeneity of B cells in PDAC. The prognostic and immunologic value of the identified CD38+ B cells was explored in FUSCC (n = 147) and TCGA (n = 176) cohorts. Flow cytometry was conducted to characterize the relationship between CD38+ B cells and other immune cells, as well as their phenotypic features. In vitro and in vivo experiments were performed to assess the putative effect of CD38+ B cells on antitumor immunity.

FINDINGS

The presence of CD38+ B cells in PDAC was associated with unfavorable clinicopathological features and poorer overall survival (p < 0.001). Increased infiltration of CD38+ B cells was accompanied by reduced natural killer (NK) cells (p = 0.021) and increased regulatory T cells (p = 0.016). Molecular profiling revealed high expression of IL-10, IL-35, TGF-β, GZMB, TIM-1, CD5 and CD21, confirming their putative regulatory B cell-like features. Co-culture experiments demonstrated suppression of NK cell cytotoxicity by CD38+ B cell-derived IL-10 (p < 0.001). Finally, in vivo experiments suggested adoptive transfer of CD38+ B cells reduced antitumor immunity and administration of a CD38 inhibitor hampered tumor growth (p < 0.001).

INTERPRETATION

We discovered regulatory B cell-like CD38+ B cell infiltration as an independent prognostic factor in PDAC. The use of CD38 inhibitor may provide new possibilities for PDAC immunotherapy.

FUNDING

This study was supported by the National Natural Science Foundation of China (U21A20374), Shanghai Municipal Science and Technology Major Project (21JC1401500), Scientific Innovation Project of Shanghai Education Committee (2019-01-07-00-07-E00057), Special Project for Clinical Research in the Health Industry of the Shanghai Health Commission (No. 20204Y0265) and Natural Science Foundation of Shanghai (23ZR1479300).

O-GlcNAcylation stimulates the deubiquitination activity of USP16 and regulates cell cycle progression

Histone 2A monoubiquitination (uH2A) underscores a key epigenetic regulation of gene expression. In this report, we show that the deubiquitinase for uH2A, ubiquitin-specific peptidase 16 (USP16), is modified by O-linked N-acetylglucosamine (O-GlcNAc). O-GlcNAcylation involves the installation of the O-GlcNAc moiety to Ser/Thr residues. It crosstalks with Ser/Thr phosphorylation, affects protein-protein interaction, alters enzyme activity or protein folding, and changes protein subcellular localization. In our study, we first confirmed that USP16 is glycosylated on Thr203 and Ser214, as reported in a previous chemoenzymatic screen. We then discovered that mutation of the O-GlcNAcylation site Thr203, which is adjacent to deubiquitination-required Cys204, reduces the deubiquitination activity toward H2AK119ub in vitro and in cells, while mutation on Ser214 had the opposite effects. Using USP16 Ser552 phosphorylation-specific antibodies, we demonstrated that O-GlcNAcylation antagonizes cyclin-dependent kinase 1-mediated phosphorylation and promotes USP16 nuclear export. O-GlcNAcylation of USP16 is also required for deubiquitination of Polo-like kinase 1, a mitotic master kinase, and the subsequent chromosome segregation and cytokinesis. In summary, our study revealed that O-GlcNAcylation of USP16 at Thr203 and Ser214 coordinates deubiquitination of uH2A and Polo-like kinase 1, thus ensuring proper cell cycle progression.

Bioinformatics analysis identifies a key gene HLA_DPA1 in severe influenza-associated immune infiltration

BACKGROUND

Severe influenza is a serious global health issue that leads to prolonged hospitalization and mortality on a significant scale. The pathogenesis of this infectious disease is poorly understood. Therefore, this study aimed to identify the key genes associated with severe influenza patients necessitating invasive mechanical ventilation.

METHODS

The current study utilized two publicly accessible gene expression profiles (GSE111368 and GSE21802) from the Gene Expression Omnibus database. The research focused on identifying the genes exhibiting differential expression between severe and non-severe influenza patients. We employed three machine learning algorithms, namely the Least Absolute Shrinkage and Selection Operator regression model, Random Forest, and Support Vector Machine-Recursive Feature Elimination, to detect potential key genes. The key gene was further selected based on the diagnostic performance of the target genes substantiated in the dataset GSE101702. A single-sample gene set enrichment analysis algorithm was applied to evaluate the participation of immune cell infiltration and their associations with key genes.

RESULTS

A total of 44 differentially expressed genes were recognized; among them, we focused on 10 common genes, namely PCOLCE2, HLA_DPA1, LOC653061, TDRD9, MPO, HLA_DQA1, MAOA, S100P, RAP1GAP, and CA1. To ensure the robustness of our findings, we employed overlapping LASSO regression, Random Forest, and SVM-RFE algorithms. By utilizing these algorithms, we were able to pinpoint the aforementioned 10 genes as potential biomarkers for distinguishing between both cases of influenza (severe and non-severe). However, the gene HLA_DPA1 has been recognized as a crucial factor in the pathological condition of severe influenza. Notably, the validation dataset revealed that this gene exhibited the highest area under the receiver operating characteristic curve, with a value of 0.891. The use of single-sample gene set enrichment analysis has provided valuable insights into the immune responses of patients afflicted with severe influenza that have further revealed a categorical correlation between the expression of HLA_DPA1 and lymphocytes.

CONCLUSION

The findings indicated that the HLA_DPA1 gene may play a crucial role in the immune-pathological condition of severe influenza and could serve as a promising therapeutic target for patients infected with severe influenza.

[Haploidentical donor peripheral blood stem cell transplantation using third-party cord blood compared with matched unrelated donor transplantation for patients with hematologic malignancies]

Objectives: To assess the efficacy of cord blood-assisted haploid peripheral blood stem cell transplantation (haplo-cord-PBSCT) versus unrelated donor peripheral blood stem cell transplantation (UD-PBSCT) in the treatment of malignant hematological diseases. Methods: A retrospective analysis was performed on one hundred and four patients with malignant hematological diseases who underwent haplo-cord-PBSCT and fifty-two patients who underwent UD-PBSCT at Xiangya Hospital of Central South University between January 2016 and December 2021. Results: ①The median implantation time for neutrophils in the haplo-cord-PBSCT and UD-PBSCT groups was 13 (9-22) days and 13 (10-24) days, respectively (P=0.834), whereas the median implantation time for platelets was 15 (7-103) days and 14 (8-38) days, respectively (P=0.816). The cumulative implantation rate of neutrophils at 30 days after transplantation in the haplo-cord-PBSCT group and the UD-PBSCT group was 100% (P=0.314), and the cumulative platelet implantation rate at 100 days after transplantation was 95.2% (95% CI 88.3% - 98.1% ) and 100% (P=0.927), respectively. 30 days after transplantation, both groups of patients achieved complete donor chimerism, and no umbilical cord blood stem cells were implanted. ②The cumulative incidence rates of grade Ⅱ-Ⅳ acute GVHD within 100 days after transplantation in the haplo-cord-PBSCT group and the UD-PBSCT group were 29.1% (95% CI 20.1% -38.1% ) and 28.8% (95% CI 17.2% -41.6% (P=0.965), respectively. The cumulative incidence rates of grade Ⅲ/Ⅳ acute GVHD were 7.8% (95% CI 3.6% -14.0% ) and 9.6% (95% CI 3.5% -19.5% ) (P=0.725). The cumulative incidence rates of 2-year chronic GVHD in the haplo-cord-PBSCT group and the UD-PBSCT group were 45.3% (95% CI 36.1% -56.1% ) and 35.1% (95% CI 21.6% -44.1% ), respectively (P=0.237). The cumulative incidence rates of severe chronic GVHD at 2 years after transplantation were 13.6% (95% CI 7.6% -21.3% ) and 12.9% (95% CI 5.1% -24.3% ), respectively (P=0.840). ③The 2-year CIR after transplantation in the haplo-cord-PBSCT group and UD-PBSCT group were 12.8% (95% CI 7.0% -20.5% ) and 10.0% (95% CI 3.6% -20.2% ), respectively (P=0.341), and the NRM were 14.7% (95% CI 8.4% -22.6% ) and 16.2% (95% CI 7.4% -28.0% ), respectively (P=0.681). ④The 2-year OS rates in the haplo-cord-PBSCT and UD-PBSCT groups after transplantation were 82.2% (95% CI 74.8% -90.3% ) and 75.5% (95% CI 64.2% -88.7% ), respectively (P=0.276). The 2-year DFS rates were 69.9% (95% CI 61.2% -79.8% ) and 73.8% (95% CI 62.4% -87.3% ), respectively (P=0.551). The 2-year rates of GVHD-free/recurrence-free survival (GRFS) were 55.3% (95% CI 44.8% -64.8% ) and 64.7% (95% CI 52.8% -79.3% ), respectively (P=0.284) . Conclusion: The findings of this study indicate that haplo-cord-PBSCT and UD-PBSCT have comparable efficacy and safety in the treatment of malignant hematological diseases and can be used as an alternative treatment options.

Identification of apoptosis-related gene signatures as potential biomarkers for differentiating active from latent tuberculosis via bioinformatics analysis

Background

Apoptosis is associated with the pathogenesis of Mycobacterium tuberculosis infection. This study aims to identify apoptosis-related genes as biomarkers for differentiating active tuberculosis (ATB) from latent tuberculosis infection (LTBI).

Methods

The tuberculosis (TB) datasets (GSE19491, GSE62525, and GSE28623) were downloaded from the Gene Expression Omnibus (GEO) database. The diagnostic biomarkers differentiating ATB from LTBI were identified by combining the data of protein-protein interaction network, differentially expressed gene, Weighted Gene Co-Expression Network Analysis (WGCNA), and receiver operating characteristic (ROC) analyses. Machine learning algorithms were employed to validate the diagnostic ability of the biomarkers. Enrichment analysis for biomarkers was established, and potential drugs were predicted. The association between biomarkers and N6-methyladenosine (m6A) or 5-methylated cytosine (m5C) regulators was evaluated.

Results

Six biomarkers including CASP1, TNFSF10, CASP4, CASP5, IFI16, and ATF3 were obtained for differentiating ATB from LTBI. They showed strong diagnostic performances, with area under ROC (AUC) values > 0.7. Enrichment analysis demonstrated that the biomarkers were involved in immune and inflammation responses. Furthermore, 24 drugs, including progesterone and emricasan, were predicted. The correlation analysis revealed that biomarkers were positively correlated with most m6A or m5C regulators.

Conclusion

The six ARGs can serve as effective biomarkers differentiating ATB from LTBI and provide insight into the pathogenesis of Mycobacterium tuberculosis infection.

Determining the soil odor control area: A case study of an abandoned organophosphorus pesticide factory in China

Currently, soil odor-active substance screening and evaluation methods for contaminated sites are underdeveloped, with unclear treatment objectives and areas. Consequently, some sites suffer from odor issues during and even after remediation. This study focused on an organophosphorus pesticide factory site in Guangdong Province, China. It established a method of determining the odorant control area using a comprehensive approach combining instrumental and olfactory soil sample analyses. The main odor-active substances identified were ethylbenzene, phenol, m, p-xylene, styrene, toluene, and o-xylene, with odorant control values (the limit of odor-active substance contents) of 35.2, 28.1, 8.0, 11.3, 40.2 and 89.3 mg/kg respectively. Instrumental analysis of soil samples revealed 11 sampling points where the main odor-causing substances exceeded standard levels. Among the substances, ethylbenzene (1.48E+04 mg/kg) had the highest content, exceeding the limit up to 421-fold. Olfactory analysis indicated 14 sampling points with odor intensity surpassing the standard (OI > 2). Based on the instrumental analysis results and the odorant control value, the initial estimated odor control area (area with the risk of odor nuisance) was 5.64E+03 m2. Incorporating the olfactory analysis findings, the control area was adjusted by 1.25E+03 m2, leading to a final calculated soil odor control area of 6.89E+03 m2 for the study site. The comprehensive approach to analyzing soil samples for odor control can help evaluate the extent of soil odor pollution in contaminated sites and provide a scientific basis for effectively removing and managing odor-causing substances in soil.

Source-sink response analysis of heavy metals and soil pollution assessment in non-ferrous metal industrial agglomeration areas based on decision unit

Soil heavy metals (HMs) pollution is a worldwide concern. In this study, decision units based on "source-sink relationship" were established using multi-source data. The source-sink response of heavy metals in agricultural soils at the regional scale was analyzed using machine learning methods, receptor models, and geospatial analysis. The comprehensive pollution risk score (CRS) was proposed by integrating a variety of key evaluation indicators to evaluate the pollution degree of each decision unit. We divided the study area into 193 decision units, the proportions of sites with concentrations of Cd, Hg, As, Pb, and Cr exceeding the most stringent risk screening values were 16.4 %, 2.2 %, 4.0 %, 7.6 %, and 0.2 %, respectively. Agricultural activities (livestock manure, fertilizer, sewage irrigation), industrial activities (rare earth ore and tungsten‑molybdenum mining and smelting), and soil parent material are the dominant pollution sources of HMs in the study area. The risk of contamination of each element is ranked from largest to smallest according to the CRS as Cd > Hg > Pb > As > Cr. The western and southwestern water pollution decision units are the areas with the highest risk of soil HMs contamination. This quantitative evaluation framework can provide a relatively accurate decision basis for soil pollution management.

CRIP1 fosters MDSC trafficking and resets tumour microenvironment via facilitating NF-κB/p65 nuclear translocation in pancreatic ductal adenocarcinoma

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) is among the most immunosuppressive tumour types. The tumour immune microenvironment (TIME) is largely driven by interactions between immune cells and heterogeneous tumour cells. Here, we aimed to investigate the mechanism of tumour cells in TIME formation and provide potential combination treatment strategies for PDAC patients based on genotypic heterogeneity.

DESIGN

Highly multiplexed imaging mass cytometry, RNA sequencing, mass cytometry by time of flight and multiplex immunofluorescence staining were performed to identify the pro-oncogenic proteins associated with low immune activation in PDAC. An in vitro coculture system, an orthotopic PDAC allograft tumour model, flow cytometry and immunohistochemistry were used to explore the biological functions of cysteine-rich intestinal protein 1 (CRIP1) in tumour progression and TIME formation. RNA sequencing, mass spectrometry and chromatin immunoprecipitation were subsequently conducted to investigate the underlying mechanisms of CRIP1.

RESULTS

Our results showed that CRIP1 was frequently upregulated in PDAC tissues with low immune activation. Elevated CRIP1 expression induced high levels of myeloid-derived suppressor cell (MDSC) infiltration and fostered an immunosuppressive tumour microenvironment. Mechanistically, we primarily showed that CRIP1 bound to nuclear factor kappa-B (NF-κB)/p65 and facilitated its nuclear translocation in an importin-dependent manner, leading to the transcriptional activation of CXCL1/5. PDAC-derived CXCL1/5 facilitated the chemotactic migration of MDSCs to drive immunosuppression. SX-682, an inhibitor of CXCR1/2, blocked tumour MDSC recruitment and enhanced T-cell activation. The combination of anti-PD-L1 therapy with SX-682 elicited increased CD8+T cell infiltration and potent antitumor activity in tumour-bearing mice with high CRIP1 expression.

CONCLUSIONS

The CRIP1/NF-κB/CXCL axis is critical for triggering immune evasion and TIME formation in PDAC. Blockade of this signalling pathway prevents MDSC trafficking and thereby sensitises PDAC to immunotherapy.

The multi-media environmental behavior of heavy metals around tailings under the influence of precipitation

Precipitation can lead to significant leaching of heavy metals from abandoned tailings，resulting in a decline in the quality of the surrounding environment. This study aimed to simulate and quantify the migration patterns and fate of heavy metals in tailings caused by precipitation in various environmental media (tailings, air, water, soil, and sediments) using leaching tests, source apportionment, and a fugacity model. Results revealed that the average contents of Cd, Cu, As, Pb, Zn, and Cr in the un-weathered tailings were 3.43, 495.56, 160.70, 138.94, 536.57, and 69.52 mg/kg, respectively. The ecological risk factors in the tailings as well as in sediments and soils, were in the following order: Cd >Cu >As >Pb >Zn >Cr. A fugacity model based on the mass-balance methods was established, achieving a good agreement between simulation and measured values. The total amounts of Cd, Cu, As, Pb, and Zn leached from abandoned tailings over the 30-year evaluation period were estimated to be 1.09, 62.44, 0.16, 0.94, and 102.12 t, respectively. Soil and sediments are important reservoirs for heavy metals. The sum of the As, Cd, Cu, Pb, and Zn storage capacities in the soil and sediment accounted for 77.28%, 75.63%, 73.94%, 69.39%, and 57.80% of the total storage capacity, respectively. This study could provide the means for the establishment of a targeted pollution control plan, a guide for restoration projects, and will aid in controlling pollution risk and improving the surrounding environment.

High-efficiency all-fluorescent white organic light-emitting diode based on TADF material as a sensitizer

The use of TADF materials as both sensitizers and emitters is a promising route to achieve high-efficiency all-fluorescent white organic light-emitting diodes (WOLEDs). In this study, the thermally-activated delayed-fluorescent (TADF) material DMAC-TRZ (9,9-dimethyl-9,10-dihydroacridine-2,4,6-triphenyl-1,3,5-triazine) was selected as a sensitizer for the conventional fluorescent emitter DCJTB (4-(dicyanomethylene)-2-t-butyl-6-(1,1,7,7-tetramethyljulolidyl-9-enyl)-4H-pyran), which was co-doped in a wide bandgap host of DPEPO (bis[2-(diphenylphosphino)phenyl]ether oxide) to fabricate WOLEDs. For the emitting layer of DPEPO:DMAC-TRZ:DCJTB, the DPEPO host can dilute the exciton concentration formed on the DMAC-TRZ sensitizer, which benefits the suppression of exciton quenching. The effect of the doping concentration of DCJTB on the carrier recombination and energy transfer process was investigated. With an optimized doping concentration of DCJTB as 0.8%, highly efficient WOLED was achieved with a maximum external quantum efficiency (EQE), power efficiency (PE), and current efficiency (CE) of 11.05%, 20.83 lm W-1, and 28.83 cd A-1, respectively, corresponding to the Commission Internationale de I' Eclairage (CIE) coordinates of (0.45, 0.46). These superior performances can be ascribed to the fact that the hole-trapping effect of the emitter and Dexter energy transfer (DET) from sensitizer to emitter can be suppressed simultaneously by the extremely low doping concentration.

Targeting neoadjuvant chemotherapy-induced metabolic reprogramming in pancreatic cancer promotes anti-tumor immunity and chemo-response

The molecular dynamics of pancreatic ductal adenocarcinoma (PDAC) under chemotherapy remain incompletely understood. The widespread use of neoadjuvant chemotherapy (NAC) provides a unique opportunity to investigate PDAC samples post-chemotherapy. Leveraging a cohort from Fudan University Shanghai Cancer Center, encompassing PDAC samples with and without exposure to neoadjuvant albumin-bound paclitaxel and gemcitabine (AG), we have compiled data from single-cell and spatial transcriptomes, proteomes, bulk transcriptomes, and metabolomes, deepening our comprehension of the molecular changes in PDACs in response to chemotherapy. Metabolic flux analysis reveals that NAC induces a reprogramming of PDAC metabolic patterns and enhances immunogenicity. Notably, NAC leads to the downregulation of glycolysis and the upregulation of CD36. Tissue microarray analysis demonstrates that high CD36 expression is linked to poorer survival in patients receiving postoperative AG. Targeting CD36 synergistically improves the PDAC response to AG both in vitro and in vivo, including patient-derived preclinical models.

Adaptive Frequency Learning Network With Anti-Aliasing Complex Convolutions for Colon Diseases Subtypes

The automatic and dependable identification of colonic disease subtypes by colonoscopy is crucial. Once successful, it will facilitate clinically more in-depth disease staging analysis and the formulation of more tailored treatment plans. However, inter-class confusion and brightness imbalance are major obstacles to colon disease subtyping. Notably, the Fourier-based image spectrum, with its distinctive frequency features and brightness insensitivity, offers a potential solution. To effectively leverage its advantages to address the existing challenges, this article proposes a framework capable of thorough learning in the frequency domain based on four core designs: the position consistency module, the high-frequency self-supervised module, the complex number arithmetic model, and the feature anti-aliasing module. The position consistency module enables the generation of spectra that preserve local and positional information while compressing the spectral data range to improve training stability. Through band masking and supervision, the high-frequency autoencoder module guides the network to learn useful frequency features selectively. The proposed complex number arithmetic model allows direct spectral training while avoiding the loss of phase information caused by current general-purpose real-valued operations. The feature anti-aliasing module embeds filters in the model to prevent spectral aliasing caused by down-sampling and improve performance. Experiments are performed on the collected five-class dataset, which contains 4591 colorectal endoscopic images. The outcomes show that our proposed method produces state-of-the-art results with an accuracy rate of 89.82%.

Exosomes from TNF-α preconditioned human umbilical cord mesenchymal stromal cells inhibit the autophagy of acinar cells of severe acute pancreatitis via shuttling bioactive metabolites

Severe acute pancreatitis (SAP) is a common critical disease of the digestive system, with high mortality and a lack of effective prevention and treatment measures. Despite mesenchymal stromal cell transplantation having the potential to treat SAP, its clinical application prospect is limited, and the mechanism is unclear. Here, we reveal the therapeutic role of exosomes from TNF-α-preconditioned human umbilical cord mesenchymal stromal cells (HUCMSCs) in attenuating SAP and show that it is partly dependent on exosomal metabolites. Bioactive metabolomics analysis showed that 48 metabolites be significantly differentially expressed between the two groups (Exo-Ctrl group versus Exo-TNF-α group). Then, the further functional experiments indicated that 3,4-dihydroxyphenylglycol could be a key molecule mediating the therapeutic effect of TNF-α-preconditioned HUCMSCs. The animal experiments showed that 3,4-dihydroxyphenylglycol reduced inflammation and oxidative stress in the pancreatic tissue and inhibited acinar cell autophagy in a rat model of SAP. Mechanistically, we revealed that 3,4-dihydroxyphenylglycol activated the mTOR pathway to inhibit acinar cell autophagy and alleviate SAP. In summary, our study demonstrated that exosomes from TNF-α-preconditioned HUMSCs inhibit the autophagy of acinar cells of SAP by shuttling 3,4-dihydroxyphenylglycol and inhibiting the mTOR pathway. This study revealed the vital role and therapeutic potential of metabolite-derived exosomes in SAP, providing a new promising method to prevent and therapy SAP.

Radical antegrade modular pancreatosplenectomy (RAMPS) versus standard retrograde pancreatosplenectomy (SRPS) for resectable body and tail pancreatic adenocarcinoma: protocol of a multicenter, prospective, randomized phase III control trial (CSPAC-3)

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Radical surgical resection offers the only potential cure. There is increasing agreement that radical antegrade modular pancreatosplenectomy (RAMPS) may benefit patients with tumors in the body and tail of the pancreas. To address this, the Chinese Study Group for Pancreatic Cancer (CSPAC)-3 trial is proposed to compare the effect of RAMPS and standard retrograde pancreatosplenectomy (SRPS) on patient survival and preoperative safety METHODS: The randomized controlled trial will be multicenter and two-armed with blinded outcomes and intention-to-treat analysis. Three hundred patients with resectable body and tail pancreatic adenocarcinoma will be enrolled and randomly assigned to RAMPS or SRPS. Adjuvant chemotherapy based on an initial regimen will be recommended 4-6 weeks after surgery if no serious complication occurs. The hypothesis that RAMPS improves survival outcomes compared with SRPS will be tested using a superiority trial. The primary outcome will be overall survival (OS). Secondary outcomes will include recurrence-free survival (RFS), R0 resection rate, the number of harvested lymph nodes, postoperative complications, and quality of life scores.

DISCUSSION

The use of RAMPS has increased over the past decade. It is reported that RAMPS is superior to SRPS in improving both the rate of R0 resection and lymph node yield. Despite these advantages, however, there is little high-level documentation of the superiority of RAMPS in terms of survival and this needs to be investigated. To address this issue, CSPAC has instigated the first prospective, randomized phase III control trials, aiming to explore the optimal surgical strategy for improving the prognosis and OS of patients with left-sided pancreatic cancer Trial registration Chinese Clinical Trial Registry ChiCTR2100053844; pre-results. Registered on December 1, 2021.

Associations Between Primary Residence and Mental Health in Global Marginalized Populations

Scholars suggest that marginalized people in non-urban areas experience higher distress levels and fewer psychosocial resources than in urban areas. Researchers have yet to test whether precise proximity to urban centers is associated with mental health for marginalized populations. We recruited 1733 people who reported living in 45 different countries. Participants entered their home locations and completed measures of anxiety, depression, social support, and resilience. Regression and thematic analyses were used to determine what role distance from legislative and urban centers may play in mental health when marginalized people were disaggregated. Greater distance from legislative center predicted higher anxiety and resilience. Greater distance from urban center also predicted more resilience. Thematic analyses yielded five categories (e.g., safety, connection) that further illustrated the impact of geographic location on health. Implications for community mental health are discussed including the need to better understand and further expand resilience in rural areas.

Identification of cuproptosis-related molecular subtypes as a biomarker for differentiating active from latent tuberculosis in children

BACKGROUND

Cell death plays a crucial role in the progression of active tuberculosis (ATB) from latent infection (LTBI). Cuproptosis, a novel programmed cell death, has been reported to be associated with the pathology of various diseases. We aimed to identify cuproptosis-related molecular subtypes as biomarkers for distinguishing ATB from LTBI in pediatric patients.

METHOD

The expression profiles of cuproptosis regulators and immune characteristics in pediatric patients with ATB and LTBI were analyzed based on GSE39939 downloaded from the Gene Expression Omnibus. From the 52 ATB samples, we investigated the molecular subtypes based on differentially expressed cuproptosis-related genes (DE-CRGs) via consensus clustering and related immune cell infiltration. Subtype-specific differentially expressed genes (DEGs) were found using the weighted gene co-expression network analysis. The optimum machine model was then determined by comparing the performance of the eXtreme Gradient Boost (XGB), the random forest model (RF), the general linear model (GLM), and the support vector machine model (SVM). Nomogram and test datasets (GSE39940) were used to verify the prediction accuracy.

RESULTS

Nine DE-CRGs (NFE2L2, NLRP3, FDX1, LIPT1, PDHB, MTF1, GLS, DBT, and DLST) associated with active immune responses were ascertained between ATB and LTBI patients. Two cuproptosis-related molecular subtypes were defined in ATB pediatrics. Single sample gene set enrichment analysis suggested that compared with Subtype 2, Subtype 1 was characterized by decreased lymphocytes and increased inflammatory activation. Gene set variation analysis showed that cluster-specific DEGs in Subtype 1 were closely associated with immune and inflammation responses and energy and amino acids metabolism. The SVM model exhibited the best discriminative performance with a higher area under the curve (AUC = 0.983) and relatively lower root mean square and residual error. A final 5-gene-based (MAN1C1, DKFZP434N035, SIRT4, BPGM, and APBA2) SVM model was created, demonstrating satisfactory performance in the test datasets (AUC = 0.905). The decision curve analysis and nomogram calibration curve also revealed the accuracy of differentiating ATB from LTBI in children.

CONCLUSION

Our study suggested that cuproptosis might be associated with the immunopathology of Mycobacterium tuberculosis infection in children. Additionally, we built a satisfactory prediction model to assess the cuproptosis subtype risk in ATB, which can be used as a reliable biomarker for the distinguishment between pediatric ATB and LTBI.

Effect of a Mobile App-Based Urinary Incontinence Self-Management Intervention Among Pregnant Women in China: Pragmatic Randomized Controlled Trial

BACKGROUND

Urinary incontinence (UI) is a highly prevalent health concern commonly observed during and after pregnancy that can substantially impact women's physical and psychological well-being and quality of life. Owing to its numerous advantages, mobile health may be a promising solution; however, it is unclear whether the app-based intervention can effectively improve UI symptoms during and after pregnancy.

OBJECTIVE

This study aimed to evaluate the effectiveness of the Urinary Incontinence for Women (UIW) app-based intervention for UI symptom improvement among pregnant women in China.

METHODS

Singleton pregnant women without incontinence before pregnancy who were aged ≥18 years and between 24 and 28 weeks of gestation were recruited from a tertiary public hospital in China and were randomly allocated (1:1) to either an experimental group (n=63) or a control group (n=63). The experimental group received the UIW app intervention and oral pelvic floor muscle training (PFMT) instructions, whereas the control group received oral PFMT instructions alone. Neither the participants nor the researchers were blinded to the intervention. The primary outcome was UI severity. The secondary outcomes included quality of life, self-efficacy with PFMT, and knowledge of UI. All data were collected at baseline, 2 months after randomization, and 6 weeks post partum through electronic questionnaires or by checking the electronic medical record system. Data analysis followed the intention-to-treat principle. A linear mixed model was used to examine the intervention effect on primary and secondary outcomes.

RESULTS

Participants in the experimental and control groups were comparable at baseline. Of the 126 overall participants, 117 (92.9%) and 103 (81.7%) women completed follow-up visits at 2 months after randomization and 6 weeks after delivery, respectively. A statistically significant difference in UI symptom severity was observed between the experimental group and control group (2 months after randomization: mean difference -2.86, 95% CI -4.09 to -1.64, P<.001; 6 weeks post partum: mean difference -2.68, 95% CI -3.87 to -1.49, P<.001). For the secondary outcomes, a statistically significant intervention effect on the quality of life, self-efficacy, and UI knowledge was found at the 2-month follow-up (all P<.05) and 6 weeks post partum (all P<.001).

CONCLUSIONS

The app-based UI self-management intervention (UIW) effectively improved UI symptom severity, quality of life, self-efficacy with PFMT, and knowledge of UI during the late pregnancy and early postnatal periods. Larger multicenter studies with a longer postpartum follow-up are required to further extend these findings.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR1800016171; http://www.chictr.org.cn/showproj.aspx?proj=27455.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/22771.

Assessment of the relative benefits of monotherapy and combination therapy approaches to the treatment of hospital-acquired Stenotrophomonas maltophilia pneumonia: a multicenter, observational, real-world study

PURPOSE

Stenotrophomonas maltophilia is a Gram-negative pathogen that most commonly causes hospital-acquired infections that can be extremely challenging to treat, contributing to underrecognized mortality throughout the world. The relative benefits of monotherapy as compared to combination therapy in patients diagnosed with S. maltophilia pneumonia, however, have yet to be established.

METHODS

Data from 307 patients diagnosed with S. maltophilia hospital-acquired pneumonia (HAP) across four Chinese teaching hospitals from 2016 to 2022 were retrospectively analyzed.

RESULTS

Of the analyzed patients, 55.7% (171/307) were administered combination definitive therapy, with a 30-day all-cause mortality rate of 41.0% (126/307). A propensity score weighting analysis revealed that compared with monotherapy, combination definitive therapy was associated with a comparable 30-day mortality risk in the overall patient cohort (OR 1.124, 95% CI 0.707-1.786, P = 0.622), immunocompetent patients (OR 1.349, 95% CI 0.712-2.554, P = 0.359), and patients with APACHE II scores < 15 (OR 2.357, 95% CI 0.820-6.677, P = 0.111), whereas it was associated with a decreased risk of death in immunocompromised patients (OR 0.404, 95% CI .170-0.962, P = 0.041) and individuals with APACHE II scores ≥ 15 (OR 0.494, 95% CI 0.256-0.951, P = 0.035).

CONCLUSION

The present data suggest that when treating S. maltophilia-HAP, immunocompromised patients and individuals with APACHE II scores ≥ 15 may potentially benefit from combination therapy.

Genetic analysis of cuproptosis subtypes and immunological features in severe influenza

The mechanisms regulating cuproptosis in severe influenza are still unknown. We aimed to identify the molecular subtypes of cuproptosis and immunological characteristics associated with severe influenza in patients requiring invasive mechanical ventilation (IMV). The expression of cuproptosis modulatory factors and immunological characteristics of these patients were analyzed using the public datasets (GSE101702, GSE21802, and GSE111368) from the Gene Expression Omnibus (GEO). Seven cuproptotic-associated genes (ATP7B, ATP7A, FDX1, LIAS, DLD, MTF1, DBT) related to active immune responses were identified in patients suffering from severe and non-severe influenza and two cuproptosis-associated molecular subtypes were discovered in severe influenza patients. Singe-set gene set expression analysis (SsGSEA) indicated that compared with subtype 2, subtype 1 was characterized by reduced adaptive cellular immune responses and increased neutrophil activation. Gene set variation assessment revealed that cluster-specific differentially expressed genes (DEGs) in subtype 1 were involved in autophagy, apoptosis, oxidative phosphorylation, and T cell, immune, and inflammatory responses, amongst others. The random forest (RF) model revealed the most differentiating efficiency with relatively small residual and root mean square error and an increased area under the curve value (AUC = 0.857). Lastly, a five-gene-based RF model (CD247, GADD45A, KIF1B, LIN7A, HLA_DPA1) was established, which showed satisfactory efficiency in the test datasets GSE111368 (AUC = 0.819). Nomogram calibration and decision curve analysis demonstrated its accuracy for the prediction of severe influenza. This study suggests that cuproptosis might be associated with the immunopathology of severe influenza. Additionally, an efficient model for the prediction of cuproptosis subtypes was developed which will contribute to the prevention and treatment of severe influenza patients needing IMV.

Integrated analysis revealed hypoxia signatures and LDHA related to tumor cell dedifferentiation and unfavorable prognosis in pancreatic adenocarcinoma: Hypoxia in PDAC

Pancreatic ductal adenocarcinoma (PDAC) is a highly heterogeneous cancer with limited understanding of its classification and tumor microenvironment. Here, by analyzing single-nucleus RNA sequencing of 43, 817 tumor cells from 15 PDAC tumors and non-tumor, we find that hypoxia signatures were heterogeneous across samples and were potential regulators for tumor progression and more aggressive phenotype. Hypoxia-high PDAC tends to present a basal/squamous-like phenotype and has significantly increased outgoing signaling, which enhances tumor cell stemness and promotes metastasis, angiogenesis, and fibroblast differentiation in PDAC. Hypoxia is related to an extracellular matrix enriched microenvironment, and increased possibility of TP53 mutation in PDAC. TP63 is a specific marker of squamous-like phenotype, and presents elevated transcriptome levels in most hypoxia PDAC tumors. In summary, our research highlights the potential linkage of hypoxia, tumor progression and genome alteration in PDAC, leading to further understand of the formation of inter-tumoral and intra-tumoral heterogenous in PDAC. Our study extends the understanding of the diversity and transition of tumor cells in PDAC, which provides insight into future PDAC management.

DLGNet: A dual-branch lesion-aware network with the supervised Gaussian Mixture model for colon lesions classification in colonoscopy images

Colorectal cancer is one of the malignant tumors with the highest mortality due to the lack of obvious early symptoms. It is usually in the advanced stage when it is discovered. Thus the automatic and accurate classification of early colon lesions is of great significance for clinically estimating the status of colon lesions and formulating appropriate diagnostic programs. However, it is challenging to classify full-stage colon lesions due to the large inter-class similarities and intra-class differences of the images. In this work, we propose a novel dual-branch lesion-aware neural network (DLGNet) to classify intestinal lesions by exploring the intrinsic relationship between diseases, composed of four modules: lesion location module, dual-branch classification module, attention guidance module, and inter-class Gaussian loss function. Specifically, the elaborate dual-branch module integrates the original image and the lesion patch obtained by the lesion localization module to explore and interact with lesion-specific features from a global and local perspective. Also, the feature-guided module guides the model to pay attention to the disease-specific features by learning remote dependencies through spatial and channel attention after network feature learning. Finally, the inter-class Gaussian loss function is proposed, which assumes that each feature extracted by the network is an independent Gaussian distribution, and the inter-class clustering is more compact, thereby improving the discriminative ability of the network. The extensive experiments on the collected 2568 colonoscopy images have an average accuracy of 91.50%, and the proposed method surpasses the state-of-the-art methods. This study is the first time that colon lesions are classified at each stage and achieves promising colon disease classification performance. To motivate the community, we have made our code publicly available via https://github.com/soleilssss/DLGNet.

Assessment of ferroptosis-associated gene signatures as potential biomarkers for differentiating latent from active tuberculosis in children

Ferroptotic cell death is a regulated process that is governed by iron-dependent membrane lipid peroxide accumulation that plays a pathogenic role in several disease-related settings. The use of ferroptosis-related genes (FRGs) to distinguish active tuberculosis (ATB) from latent tuberculosis infection (LTBI) among children, however, remains to be analysed. Tuberculosis-related gene expression data and FRG lists were obtained, respectively, from Gene Expression Omnibus (GEO) and FerrDb. Differentially expressed FRGs (DE-FRGs) detected when comparing samples from paediatric ATB and LTBI patients were explored using appropriate bioinformatics techniques, after which enrichment analyses were performed for these genes and hub genes were identified, with these genes then being used to explore potential drug interactions and construct competing endogenous RNA (ceRNA) networks. The GSE39939 dataset yielded 124 DE-FRGs that were primarily related to responses to oxidative, chemical and extracellular stimulus-associated stress. In total, the LASSO and SVM-RFE algorithms enabled the identification of nine hub genes (MAPK14, EGLN2, IDO1, USP11, SCD, CBS, PARP8, PARP16, CDC25A) that exhibited good diagnostic utility. Functional enrichment analyses of these genes suggested that they may govern ATB transition from LTBI through the control of many pathways, including the immune response, DNA repair, transcription, RNA degradation, and glycan and energy metabolism pathways. The CIBERSORT algorithm suggested that these genes were positively correlated with inflammatory and myeloid cell activity while being negatively correlated with the activity of lymphocytes. A total of 50 candidate drugs targeting 6 hub DE-FRGs were also identified, and a ceRNA network was used to explore the complex interplay among these hub genes. The nine hub FRGs defined in this study may serve as valuable biomarkers differentiating between ATB and LTBI in young patients.

Risk factors analysis and establishment of predictive nomogram of extranodal B-cell lymphoma of mucosal-associated lymphoid tissue

PURPOSE

The role of radiation therapy in mucosa-associated lymphoid tissue (MALT) lymphoma is poorly defined. The objective of this study was to explore the factors associated with the performance of radiotherapy and to assess its prognostic impact in patients with MALT lymphoma.

PATIENTS AND METHODS

Patients with MALT lymphoma diagnosed between 1992 and 2017 were identified in the US Surveillance, Epidemiology, and End Results database (SEER). Factors associated with the delivery of radiotherapy were assessed by chi-square test. Overall survival (OS) and lymphoma-specific survival (LSS) were compared between patients with and without radiotherapy, using Cox proportional hazard regression models, in patients with early stage as well as those with advanced stage.

RESULTS

Of the 10,344 patients identified with a diagnosis of MALT lymphoma, 33.6% had received radiotherapy; this rate was 38.9% for stage I/II patients and 12.0% for stage III/IV patients, respectively. Older patients and those who already received primary surgery or chemotherapy had a significantly lower rate of receiving radiotherapy, regardless of lymphoma stage. After univariate and multivariate analysis, radiotherapy was associated with improved OS and LSS in patients with stage I/II (HR=0.71 [0.65-0.78]) and (HR=0.66 [0.59-0.74]), respectively, but not in patients with stage III/IV (HR=1.01 [0.80-1.26]) and (HR=0.93 [0.67-1.29]). The nomogram built from the significant prognostic factors associated with overall survival of stage I/II patients had a good concordance (C-index=0.749±0.002).

CONCLUSION

This cohort study shows that radiotherapy is significantly associated with a better prognosis in patients with early but not advanced MALT lymphoma. Prospective studies are needed to confirm the prognostic impact of radiotherapy in patients with MALT lymphoma.

Comparison of the relative efficacy of β-lactam/β-lactamase inhibitors and carbapenems in the treatment of complicated urinary tract infections caused by ceftriaxone-non-susceptible Enterobacterales: a multicentre retrospective observational cohort study

BACKGROUND

Treating complicated urinary tract infections (cUTIs) caused by ESBL-producing Enterobacterales represents a significant clinical challenge. The present study was thus developed to explore the relative efficacy of β-lactam/β-lactamase inhibitors (BLBLIs) and carbapenems for the treatment of hospitalized patients suffering from cUTIs caused by BLBLI-susceptible ceftriaxone-non-susceptible Enterobacterales.

METHODS

Data from 557 patients from four Chinese teaching hospitals diagnosed with cUTIs caused by ceftriaxone-non-susceptible Enterobacterales from January 2017 to May 2022 were retrospectively assessed.

RESULT

The 30 day rate of treatment failure, defined by unresolved symptoms or mortality, was 10.4% (58/557). Independent predictors of 30 day treatment failure included immunocompromised status, bacteraemia, septic shock, lack of infection source control and appropriate empirical treatment. When data were controlled for potential confounding variables, BLBLI treatment exhibited a comparable risk of 14 day (OR 1.61, 95% CI 0.86-3.00, P = 0.133) and 30 day treatment failure (OR 1.45, 95% CI 0.66-3.15, P = 0.354) relative to carbapenem treatment for the overall cohort of patients. In contrast, BLBLI treatment in immunocompromised patients was associated with an elevated risk of both 14 day (OR 3.18, 95% CI 1.43-7.10, P = 0.005) and 30 day treatment failure (OR 3.06, 95% CI 1.07-8.80, P = 0.038) relative to carbapenem treatment.

CONCLUSIONS

These results suggested that carbapenem treatment may be superior to BLBLI treatment for immunocompromised patients suffering from cUTIs caused by ceftriaxone-non-susceptible Enterobacterales species. However, these results will need to be validated in appropriately constructed randomized controlled trials to ensure appropriate patient treatment.

Cuproptosis-Related Gene DLAT as a Novel Biomarker Correlated with Prognosis, Chemoresistance, and Immune Infiltration in Pancreatic Adenocarcinoma: A Preliminary Study Based on Bioinformatics Analysis

A novel form of cell death, cuproptosis, was recently identified to be mediated by the binding of copper to lipoylated enzymes of the tricarboxylic acid cycle. Cuproptosis-related genes (CRGs) may play a crucial role in the progression of pancreatic adenocarcinoma (PAAD), which often exhibits metabolic reprogramming. In the present study, univariate Cox regression analysis and Kaplan–Meier survival analysis were performed to identify prognostic CRGs. Data from the Cancer Therapeutics Response Portal and the Genomics of Drug Sensitivity in Cancer database were downloaded for drug sensitivity analysis. DLAT was identified as the only prognostic CRG in PAAD (HR = 2.72; 95% CI, 1.10–6.74). Functional enrichment analyses indicated that the basic function of DLAT is closely related to metabolism, and multiple tumor-promoting and immune response-related pathways were enriched in DLAT-high PAAD samples. The influence of DLAT and related genes on cancer immunity was evaluated by comprehensive immune infiltration analyses, which revealed the value of these genes as biomarkers for evaluating the sensitivity to immunotherapy. Additionally, high DLAT expression induced drug resistance, and significantly increased resistance to commonly used chemotherapeutics in PAAD, such as gemcitabine, oxaliplatin, 5-fluorouracil, and irinotecan. In conclusion, our study preliminarily revealed the prognostic value of DLAT, which is correlated with PAAD progression, chemoresistance, and immune infiltration, providing a valuable reference for PAAD treatment. However, our findings need to be confirmed by further in vivo and in vitro experiments.

Mesenchymal Stromal Cell-Based Targeted Therapy Pancreatic Cancer: Progress and Challenges

Pancreatic cancer is an aggressive malignancy with high mortality rates and poor prognoses. Despite rapid progress in the diagnosis and treatment of pancreatic cancer, the efficacy of current therapeutic strategies remains limited. Hence, better alternative therapeutic options for treating pancreatic cancer need to be urgently explored. Mesenchymal stromal cells (MSCs) have recently received much attention as a potential therapy for pancreatic cancer owing to their tumor-homing properties. However, the specific antitumor effect of MSCs is still controversial. To this end, we aimed to focus on the potential anti-cancer treatment prospects of the MSC-based approach and summarize current challenges in the clinical application of MSCs to treat pancreatic cancer.

Mitochondria-Related Transcriptome Characterization Associated with the Immune Microenvironment, Therapeutic Response and Survival Prediction in Pancreatic Cancer

(1) Background: Pancreatic cancer (PC) is one of the most lethal tumors. Mitochondrial dysfunction has been reported to be involved in cancer development; however, its role in PC has remained unclear. (2) Methods: The differentially expressed NMGs were selected between PC and normal pancreatic tissue. The NMG-related prognostic signature was established by LASSO regression. A nomogram was developed based on the 12-gene signature combined with other significant pathological features. An extensive analysis of the 12 critical NMGs was performed in multiple dimensions. The expression of some key genes was verified in our external cohort. (3) Results: Mitochondria-related transcriptome features was obviously altered in PC compared with normal pancreas tissue. The 12-NMG signature showed good performance in predicting prognosis in various cohorts. The high- and low-risk groups exhibited notable diversity in gene mutation characteristics, biological characteristics, chemotherapy response, and the tumor immune microenvironment. Critical gene expression was demonstrated in our cohort at the mRNA and protein levels and in organelle localization. (4) Conclusions: Our study analyzed the mitochondrial molecular characterization of PC, proving the crucial role of NMGs in PC development. The established NMG signature helps classify patient subtypes in terms of prognosis prediction, treatment response, immunological features, and biological function, providing a potential therapeutic strategy targeting mitochondrial transcriptome characterization.

Personality assessment usage and mental health among Chinese adolescents: A sequential mediation model of the Barnum effect and ego identity

Introduction

Adolescence is a crucial period for establishing ego identity and becoming a social individual. However, numerous adolescents suffer from mental health problems, especially after the conditions surrounding the COVID-19 outbreak. Personality assessments are often used when adolescents look for psychological self-help services. However, the meaning and mechanism of these personality assessments remain unknown. Taking the increasingly popular MBTI personality assessment as an entry point, the current study examined the potential sequential mediation relationship of Barnum effect - ego identity on the link between personality assessment usage and mental health.

Methods

The current study surveyed 308 Chinese high school students, including 109 males and 199 females. MBTI use, Barnum effect, ego-identity, and mental health (subjective well-being, depression, and anxiety) were measured by seven questionnaires, respectively. Sequential mediation models were constructed to analyze the relationship.

Results

The results indicate that the Barnum effect and ego identity together function as a sequential mediation path between personality assessment use and teenagers' mental health, including subjective well-being, depression, and anxiety. Specifically, a higher level of MBTI use triggers a stronger Barnum effect. The Barnum effect then promotes adolescents' ego identity, ultimately increasing subjective well-being levels and reducing anxiety and depression.

Discussion

Our findings suggest that by properly using personality assessment and stimulating the Barnum effect, we can enhance adolescents' mental health. The theoretical and practical implications of our findings are discussed.

Reappraisal of Tumor Deposit as a Prognostic Factor in Pancreatic Cancer

PURPOSE

Tumor deposits (TDs) are discrete tumor nodules within the lymphatic drainage area of the primary tumor without histological evidence of lymph node tissue or identifiable vascular or neural structure. This study aims to analyze the prognostic impact of TDs in patients with pancreatic ductal adenocarcinoma (PDAC) and explore their potential role in staging system.

METHODS

The prospectively maintained database from the Fudan University Shanghai Cancer Center was queried for patients undergoing resection for PDAC. Patients with TDs were matched by propensity score with those without TDs. The cumulative prevalence of recurrence was estimated using the cumulative incidence function. Overall survival was estimated using Kaplan-Meier curves.

RESULTS

A total of 123 patients (9.7%) had TDs, of whom 108 were matched at a 1:3 ratio with 324 patients without TDs. The cumulative incidence of recurrence was significantly higher for TD-positive patients than TD-negative patients (P = 0.04). The median overall survival was significantly shorter for patients with TDs than for those without TDs (15.9 versus 21.8 months, P < 0.001). The presence of TDs attenuated the effect of lymph node metastasis on survival, with no significance between node-negative and node-positive subpopulations (P = 0.165). Patients with TDs had comparable survival to N2 patients without TDs (15.9 versus 17.1 months, P = 0.383).

CONCLUSIONS

TD is an important prognostic factor for recurrence and survival in patients undergoing resection for PDAC. We suggest that patients presenting TDs be classified into the stage III category in the next edition of the staging system.

A new approach: Evaluation of necroptosis and immune status enables prediction of the tumor microenvironment and treatment targets in pancreatic cancer

Growing evidence indicates a potential correlation between necroptosis and pancreatic cancer, and the relationship between necroptosis, immune infiltration and the microenvironment in pancreatic cancer has drawn increasing attention. However, two-dimensional phenotype and prognostic assessment systems based on a combination of necroptosis and immunity have not been explored. In our present study, we explored the pancancer genomics signature of necroptosis-related molecules, identifying necroptosis-related molecule mutation profiles, expression profiles, and correlations between expression levels and methylation/CNV levels. We identified distinct necroptotic as well as immune statuses in pancreatic cancer, and a high necroptosis phenotype and high immunity phenotype both indicated better prognosis than a low necroptosis phenotype and low immunity phenotype. The two-dimensional phenotype we constructed has ideal discriminative effects on pancreatic cancer prognosis, inflammation, and the immune microenvironment. The "high-necroptosis and high-immunity (HNHI)" group exhibited the best prognosis and the highest proportion of infiltrating immune cells. The NI score can be used to predict patient prognosis and is correlated with the immune microenvironment score, chemotherapeutic drug IC50, and tumor mutational burden. In addition, it may be useful for predicting the effect of individualized chemotherapy and immunotherapy. Our study also revealed that SLC2A1 is associated with both necroptosis and immunity and acts as a potential oncogene in pancreatic cancer. In conclusion, the two-dimensional phenotype and NI score we developed are promising tools for clinical multiomics applications and prediction of chemotherapy and immunotherapy response and present benefits in terms of precision medicine and individualized treatment decision-making for pancreatic cancer patients.

A diagnostic model for distinguishing between active tuberculosis and latent tuberculosis infection based on the blood expression profiles of autophagy-related genes

BACKGROUND

Autophagy is closely involved in the control of mycobacterial infection.

OBJECTIVES

Here, a diagnostic model was developed using the levels of autophagy-related genes (ARGs) in the blood to differentiate active tuberculosis (ATB) and latent tuberculosis infection (LTBI).

DESIGN

Secondary data analysis of three prospective cohorts.

METHODS

The expression of ARGs in patients with ATB and LTBI were analyzed using the GSE37250, GSE19491, and GSE28623 datasets from the GEO database.

RESULTS

Twenty-two differentially expressed ARGs were identified in the training dataset GSE37250. Using least absolute shrinkage and selection operator and multivariate logistic regression, three ARGs (FOXO1, CCL2, and ITGA3) were found that were positively associated with adaptive immune-related lymphocytes and negatively associated with myeloid and inflammatory cells. A nomogram was constructed using the three ARGs. The accuracy, consistency, and clinical relevance of the nomogram were evaluated using receiver operating characteristic curves, the C-index, calibration curves, and validation in the datasets GSE19491 and GSE28623. The nomogram showed good predictive performance.

CONCLUSION

The nomogram was able to accurately differentiate between ATB and LTBI patients. These findings provide evidence for future study on the pathology of autophagy in tuberculosis infection.

Visual analysis of social events and stock market volatility in China and the USA during the pandemic

The COVID-19 pandemic is one of the most severe infectious diseases in recent decades, and has had a significant impact on the global economy, and the stock market. Most existing studies on stock market volatility during the pandemic have been conducted from a data science perspective, with statistical analysis and mathematical models often revealing the superficial relationship between Covid and the stock market at the data level. In contrast, few studies have explored the relationship between more specialised aspects of the pandemic. Specifically, the relationship found between major social events and the stock market. In this work, a multi-source, data-based relationship analysis method is proposed, that collects historical data on significant social events and related stock data in China and the USA, to further explore the potential correlation between stock market index fluctuations and the impact of social events by analysing cross-timeline data. The results suggest and offer more evidence that social events do indeed impact equity markets, and that the indices in both China and the USA were also affected more by the epidemic in 2020 than in 2021, and these indices became less affected by the epidemic as it became the world adapted. Moreover, these relationships may also be influenced by a variety of other factors not covered in this study. This research, so far, is in its initial stage, and the methodology is not rigorous and cannot be applied as an individual tool for decision; however, it could potentially serve as a supplementary tool and provide a multi-dimensional basis for stock investors and policymakers to make decisions.

Metabolic reprogramming of cancer-associated fibroblasts in pancreatic cancer contributes to the intratumor heterogeneity of PET-CT

Intratumor heterogeneity of positron emission tomography-computed tomography (PET-CT) is reflected by variable ¹⁸F-fluorodeoxyglucose (FDG) uptake. Increasing evidence has shown that neoplastic and non-neoplastic components can affect the total ¹⁸F-FDG uptake in tumors. Cancer-associated fibroblasts (CAFs) is considered as the main non-neoplastic components in tumor microenvironment (TME) of pancreatic cancer. Our study aims to explore the impact of metabolic changes in CAFs on heterogeneity of PET-CT. A total of 126 patients with pancreatic cancer underwent PET-CT and endoscopic ultrasound elastography (EUS-EG) before treatment. High maximum standardized uptake value (SUVmax) from the PET-CT was positively correlated with the EUS-derived strain ratio (SR) and indicated poor prognosis of patients. In addition, single-cell RNA analysis showed that CAV1 affected glycolytic activity and correlated with glycolytic enzyme expression in fibroblasts in pancreatic cancer. We also observed the negative correlation between CAV1 and glycolytic enzyme expression in the tumor stroma by using immunohistochemistry (IHC) assay in the SUVmax-high and SUVmax-low groups of pancreatic cancer patients. Additionally, CAFs with high glycolytic activity contributed to pancreatic cancer cell migration, and blocking CAF glycolysis reversed this process, suggesting that glycolytic CAFs promote malignant biological behavior in pancreatic cancer. In summary, our research demonstrated that the metabolic reprogramming of CAFs affects total ¹⁸F-FDG uptake in tumors. Thus, an increase in glycolytic CAFs with decreased CAV1 expression promotes tumor progression, and high SUVmax may be a marker for therapy targeting the neoplastic stroma. Further studies should clarify the underlying mechanisms.

Signaling pathways in cancer-associated fibroblasts: recent advances and future perspectives

As a critical component of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) play important roles in cancer initiation and progression. Well-known signaling pathways, including the transforming growth factor-β (TGF-β), Hedgehog (Hh), Notch, Wnt, Hippo, nuclear factor kappa-B (NF-κB), Janus kinase (JAK)/signal transducer and activator of transcription (STAT), mitogen-activated protein kinase (MAPK), and phosphoinositide 3-kinase (PI3K)/AKT pathways, as well as transcription factors, including hypoxia-inducible factor (HIF), heat shock transcription factor 1 (HSF1), P53, Snail, and Twist, constitute complex regulatory networks in the TME to modulate the formation, activation, heterogeneity, metabolic characteristics and malignant phenotype of CAFs. Activated CAFs remodel the TME and influence the malignant biological processes of cancer cells by altering the transcriptional and secretory characteristics, and this modulation partially depends on the regulation of signaling cascades. The results of preclinical and clinical trials indicated that therapies targeting signaling pathways in CAFs demonstrated promising efficacy but were also accompanied by some failures (e.g., NCT01130142 and NCT01064622). Hence, a comprehensive understanding of the signaling cascades in CAFs might help us better understand the roles of CAFs and the TME in cancer progression and may facilitate the development of more efficient and safer stroma-targeted cancer therapies. Here, we review recent advances in studies of signaling pathways in CAFs and briefly discuss some future perspectives on CAF research.

A Novel Metaphor Graph Drawing Method for Multidimensional Data Visualisation and Its Case Study on COVID-19 Vaccination Analysis

Visualisation techniques have been one of the best data processing and analysis methods in recent decades, and they have assisted in data understanding efforts in various fields. Visualisation techniques for low-dimensional data are well developed and applied in multiple sectors; however, multidimensional data visualisation techniques still present some limitations, such as inaccurate data comparison and perception, exaggerated visual differences, label occlusion, and overlap. This study addresses the pros and cons and proposes a novel graphical drawing method, the multidimensional rose chart. It adopts the design idea of the Nightingale rose chart, but overcomes relevant limitations. The main challenges of this area include the incomplete presentation of multidimensional data, the neglect of the linkage of multiple attributes, the inefficient use of space, and the lack of simplicity of the interface. Contributions include enriching the representations of multidimensional data through the use of colour shades, area, and height sizes to represent values; straightforward data attribute comparisons via graph nesting; and detailed attributes showing the use of specific value labels. To verify the preliminary validity of this method, we imported COVID-19 data into experiments and further compared the final layouts with traditional methods, such as the line chart, bar chart, tree, parallel coordinate chart, and Nightingale rose chart, as well as their structures, functionalities, clear advantages, and disadvantages. The experimental results show that multidimensional rose diagrams perform effectively in presenting multidimensional data when comparing other graph drawing methods in our case, and the outcomes match existing works' conclusions in related COVID-19 research sectors. This work has the potential to provide a suitable supplemental approach to the multidimensional data analysis.

Turning up the heat on non-immunoreactive tumors: autophagy influences the immune microenvironment in pancreatic cancer

Background

Autophagy regulators play important roles in the occurrence and development of a variety of tumors and are involved in immune regulation and drug resistance. However, the modulatory roles and prognostic value of autophagy regulators in pancreatic cancer have not been identified.

Methods

Transcriptomic data and survival information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to construct a risk score model. Important clinical features were analyzed to generate a nomogram. In addition, we used various algorithms, including ssGSEA, CIBERSORT, XCELL, EPIC, TIMER, and QUANTISEQ, to evaluate the roles of autophagy regulators in the pancreatic cancer immune microenvironment. Furthermore, the mutation landscape was compared between different risk groups.

Results

Pan cancer analysis indicated that most of the autophagy regulators were upregulated in pancreatic cancer and were correlated with methylation and CNV level. MET, TSC1, and ITGA6 were identified as the prognostic autophagy regulators and used to construct a risk score model. Some critical clinical indicators, such as age, American Joint Committee on Cancer (AJCC) T stage, AJCC N stage, alcohol and sex, were combined with the risk model to establish the nomogram, which may offer clinical guidance. In addition, our study demonstrated that the low score groups exhibited high immune activity and high abundances of various immune cells, including T cells, B cells, and NK cells. Patients with high risk scores exhibited lower half inhibitory concentration (IC50) values for paclitaxel and had downregulated expression profiles of PD1, CTLA4, and LAG3. Mutation investigation indicated that the high risk groups exhibited a higher mutation burden and higher mutation number compared to the low risk groups. additionally, we verified our risk stratification method using cytology and histology data from our center, and the results are satisfactory.

Conclusion

We speculated that autophagy regulators have large effects on the prognosis, immune landscape and drug sensitivity of pancreatic cancer. Our model, which combines critical autophagy regulators and clinical indicators, will provide guidance for clinical treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01371-0.

Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation

BACKGROUND

Influenza is a contagious disease that affects people of all ages and is linked to considerable mortality during epidemics and occasional outbreaks. Moreover, effective immunological biomarkers are needed for elucidating aetiology and preventing and treating severe influenza. Herein, we aimed to evaluate the key genes linked with the disease severity in influenza patients needing invasive mechanical ventilation (IMV). Three gene microarray data sets (GSE101702, GSE21802, and GSE111368) from blood samples of influenza patients were made available by the Gene Expression Omnibus (GEO) database. The GSE101702 and GSE21802 data sets were combined to create the training set. Hub indicators for IMV patients with severe influenza were determined using differential expression analysis and Weighted correlation network analysis (WGCNA) from the training set. The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy. Different immune cells' infiltration levels in the expression profile and their correlation with hub gene markers were examined using single-sample gene set enrichment analysis (ssGSEA).

RESULTS

In the present study, we evaluated a total of 447 differential genes. WGCNA identified eight co-expression modules, with the red module having the strongest correlation with IMV patients. Differential genes were combined to obtain 3 hub genes (HLA-DPA1, HLA-DRB3, and CECR1). The identified genes were investigated as potential indicators for patients with severe influenza who required IMV using the least absolute shrinkage and selection operator (LASSO) approach. The ROC showed the diagnostic value of the three hub genes in determining the severity of influenza. Using ssGSEA, it has been revealed that the expression of key genes was negatively correlated with neutrophil activation and positively associated with adaptive cellular immune response.

CONCLUSION

We evaluated three novel hub genes that could be linked to the immunopathological mechanism of severe influenza patients who require IMV treatment and could be used as potential biomarkers for severe influenza prevention and treatment.

Pyroptosis-related lncRNA pairs to estimate the molecular features and prognostic outcomes of pancreatic ductal adenocarcinoma

Pyroptosis is a form of programmed cell death associated with inflammatory alterations. However, the intrinsic mechanisms and underlying correlation of pyroptosis-related lncRNAs (PRLs) in pancreatic ductal adenocarcinoma (PDAC) remain unclear. The objective of the current research was to identify pyroptosis-related lncRNAs and a prognostic model to predict the prognosis of patients. We extracted pyroptosis-related lncRNAs to construct a risk model and validated them at Fudan University Shanghai Cancer Center. Crosstalk between lncRNA SNHG10 and GSDMD was found to regulate pyroptosis levels. A new algorithm was used to establish a 0 or 1 PRL pair matrix and prognostic model. Six pyroptosis-related lncRNA pairs were identified and utilized to construct a risk model. The low-risk groups exhibited better prognoses than the high-risk groups. The area under the curve (AUC) indicated extremely high accuracy, reaching 0.810 at 1 year, 0.850 at 2 years, and 0.850 at 3 years in the training set. Patients with different risk scores exhibited distinct metabolic, inflammatory, and immune microenvironments as well as tumor mutation landscapes. Additionally, 9 commonly used chemotherapeutic drugs exhibited different sensitivities between the high- and low-risk groups. To conclude, we propose that pyroptosis exhibits a close correlation with PDAC. Our risk model based on PRL pairs may be beneficial for the accurate estimation of prognostic outcomes, the immune microenvironment, and drug sensitivity, bringing therapeutic hope for patients with PDAC.

High efficiency and low operating voltage yellow phosphorescent organic light-emitting diodes with a simple doping-free structure

Yellow phosphorescent organic light-emitting diodes (PhOLEDs) with high efficiency and a low operating voltage were reported through using a simple doping-free structure. The structure of the PhOLEDs was ITO/C₆₀/MoO₃/mCP/PO-01-TB/PO-T2T/Liq/Al. The np-type C₆₀/MoO₃ heterojunction acted as hole injection layer, and the ultrathin PO-01-TB layer (0.1 nm) was inserted at the interface between mCP and PO-T2T to serve as yellow phosphorescent emitter. Detailed investigation suggested that the complete energy transfer occurred from the mCP/PO-T2T interfacial exciplex to yellow PO-01-TB. Furthermore, the np-type C₆₀/MoO₃ heterojunction could supply more free charge carriers, giving rise to further enhanced PhOLED efficiency. By adjusting the thickness of the C₆₀/MoO₃ heterojunction, a yellow PhOLED with a power efficiency of 71.6 lm W⁻¹ was demonstrated with an extremely low operating voltage of 3.79 V at 1000 cd m⁻².

A PhOLED with lower operating voltage and power efficiency was demonstrated by combining an np-type C₆₀/MoO₃ hole-injecting layer with a doping-free ultrathin phosphorescent emitter based on an interfacial exciplex strategy.