Polarization of Macrophages in Tumor Microenvironment Using High-Throughput Single-Cell Metabolomics.

Macrophages consist of a heterogeneous population of functionally distinct cells that participate in many physiological and pathological processes. They exhibit prominent plasticity by changing their different functional phenotypes represented by proinflammatory (M1) and anti-inflammatory (M2) in response to different environmental stimuli. Emerging evidence illustrates the importance of intracellular metabolic pathways in macrophage polarizations and functions. In the tumor microenvironment (TME), macrophages tend to M2 polarization, which promotes tumor growth and leads to adverse physiological effects. Due to the lack of highly specific antigens in M1 and M2 macrophages, significant challenges present in isolating these subtypes from clinical samples or in vitro coculture models of tumor-immune cells. In reverse, the single-cell technique provides the possibility to investigate the factors influencing macrophage polarization in the TME. In this research, we employed inertial microfluidic chip-mass spectrometry (IMC-MS) to conduct single-cell metabolomics analysis of macrophages polarized into the two major phenotypes, respectively, and 213 metabolites were identified in total. Subsequently, differential metabolites between macrophage phenotypes were analyzed using volcano plots and binary logistic regression models. Glutamine was pinpointed as a key metabolite for the M1 and M2 phenotypes. Experimental results from both monoculture and coculture cell models demonstrated that M1 polarization is more reliant on the presence of glutamine in the culture environment than M2 polarization. Glutamine deficiency resulted in failed M1 polarization, while its absence had a less pronounced effect on M2 polarization. Replenishing an appropriate amount of glutamine during the intermediate stages of coculture models significantly enhanced the proportion of M1 polarization and suppressed the growth of tumor cells. This research elucidated glutamine as a key factor influencing macrophage polarization in the TME via single-cell metabolomics based on IMC-MS, offering promising insights and targets for tumor therapies.

Impact and implications of national centralized drug procurement in China.

The national centralized drug procurement (NCDP) policy, known as the "4 + 7" policy in China, has transformed pharmaceutical procurement and access by leveraging healthcare institutions' collective buying power to reduce drug prices substantially. This policy has profoundly impacted drug pricing mechanisms, healthcare expenditures, market dynamics, and the quality of available drugs. This commentary evaluates the efficacy, challenges, and broader implications of the NCDP, summarizes the current state of post-marketing monitoring of selected generic drugs for centralized procurement, and presents relevant considerations.

Emodin nanocapsules inhibit acute pancreatitis by regulating lipid metabolic reprogramming in macrophage polarization.

BACKGROUND: Emodin is a chemical compound found in traditional Chinese herbs. It possesses anti-inflammatory and many other pharmacological effects. Our previous study showed that emodin significantly alleviates the inflammation effect of severe acute pancreatitis (SAP). However, its poor solubility, high toxicity and limited pancreas retention time hinder its clinical application. PURPOSE: We aimed to prepare emodin nanocapsules with improved bioavailability to achieve the controlled release of emodin by targeting macrophages. Further, the mechanism of mannose-conjugated chitosan-coated lipid nanocapsules loaded with emodin (M-CS-E-LNC) in the treatment of SAP was explored. METHODS: M-CS-E-LNC were prepared by the phase inversion method with slight modification. The expression of inflammation mediators and the anti-inflammation efficacy of M-CS-E-LNC were examined by ELISA, IHC and IF in macrophage cells and LPS-induced SAP mice. IVIS spectrum imaging and HPLC were applied to explore the controlled release of M-CS-E-LNC in the pancreas. LC-MS/MS was performed for lipidomics analysis of macrophages. Moreover, a vector-based short hairpin RNA (shRNA) method was used to silence CTP1 gene expression in macrophage cells. RESULTS: The levels of inflammatory mediators in macrophages were markedly decreased after treatment with M-CS-E-LNC. The same anti-inflammation effects were detected in SAP mouse through the analysis of serum levels of amylase, TNF-α and IL-6. Importantly, M-CS-E-LNC allowed the emodin to selectively accumulate at pancreas and gastrointestinal tissues, thus exhibiting a targeted release. Mechanistically, the M-CS-E-LNC treatment group showed up-regulated expression of the carnitine palmitoyltransferase 1 (CPT1) protein which promoted intracellular long-chain fatty acid transport, thereby promoting the M2 phenotype polarization of macrophages. CONCLUSION: M-CS-E-LNC exhibited significantly improved bioavailability and water solubility, which translated to greater therapeutic effects on macrophage polarization. Our findings also demonstrate, for the first time, that CPT1 may be a new therapeutic target for SAP treatment.

Investigating the Impact of Gut Microbiota on Gout Through Mendelian Randomization.

Background: The relationship between gout and gut microbiota has attracted significant attention in current research. However, due to the diverse range of gut microbiota, the specific causal effect on gout remains unclear. This study utilizes Mendelian randomization (MR) to investigate the causal relationship between gut microbiota and gout, aiming to elucidate the underlying mechanism of microbiome-mediated gout and provide valuable guidance for clinical prevention and treatment. Materials and Methods: The largest genome-wide association study meta-analysis conducted by the MiBioGen Consortium (n=18,340) was utilized to perform a two-sample Mendelian randomization investigation on aggregate statistics of intestinal microbiota. Summary statistics for gout were utilized from the data released by EBI. Various methods, including inverse variance weighted, weighted median, weighted model, MR-Egger, and Simple-mode, were employed to assess the causal relationship between gut microbiota and gout. Reverse Mendelian randomization analysis revealed a causal association between bacteria and gout in forward Mendelian randomization analysis. Cochran's Q statistic was used to quantify instrumental variable heterogeneity. Results: The inverse variance weighted estimation revealed that Rikenellaceae exhibited a slight protective effect on gout, while the presence of Ruminococcaceae UCG_011 is associated with a marginal increase in the risk of gout. According to the reverse Mendelian Randomization results, no significant causal relationship between gout and gut microbiota was observed. No significant heterogeneity of instrumental variables or level pleiotropy was detected. Conclusion: Our MR analysis revealed a potential causal relationship between the development of gout and specific gut microbiota; however, the causal effect was not robust, and further research is warranted to elucidate its underlying mechanism in gout development. Considering the significant association between diet, gut microbiota, and gout, these findings undoubtedly shed light on the mechanisms of microbiota-mediated gout and provide new insights for translational research on managing and standardizing treatment for this condition.

Clinical efficacy and safety of tigecycline based on therapeutic drug monitoring for carbapenem-resistant Gram-negative bacterium pneumonia in intensive care units.

BACKGROUND: We investigated the associations between the different doses of tigecycline, its efficacy and safety, and the role of tigecycline therapeutic drug monitoring for patients in the intensive care unit. METHODS: This study was a single-center cohort including patients infected with multidrug-resistant Acinetobacter baumannii (MDR-AB) and multidrug-resistant Klebsiella pneumoniae (MDR-KP) causing pulmonary infections. The steady-state plasma concentration after tigecycline administration was determined by High-Performance Liquid Chromatography (HPLC) in patients admitted to the ICU between October 2020 and December 2021. Multivariate analyses of tigecycline's clinical efficacy and safety were performed to control confounding factors. RESULTS: For this study, we included 45 patients and 45 blood samples to determine steady-state trough concentrations of tigecycline. All patients were divided into the High Dose (HD) and Standard Dose (SD) groups. The median trough concentration of tigecycline was 0.56 µg/mL in the HD group, which was higher than in the SD group (0,21 µg/mL), p = 0.000. There was no significant difference between the two groups of patients in terms of bacterial eradication rate, mortality rate, and clinical efficacy. Multiple regression analysis showed that the ICU days were correlated with mortality OR 1.030(1.005-1.056), p = 0.017. APACHE II was significantly associated with clinical efficacy OR 0.870(0.755-1.002), p = 0.045. The level of fibrinogen decline in the HD group was significantly higher than in the SD group (-3.05 ± 1.67 vs -1.75 ± 1.90), p = 0.038. We identified that age and tigecycline treatment duration influenced fibrinogen decline. CONCLUSIONS: Tigecycline plasma concentrations are significantly increased when using a high dose. However, the plasma concentration of tigecycline is not correlated with clinical efficacy and adverse reactions. Fibrinogen decline appears to be related to the patient's age and days of tigecycline. Large sample data are still needed to confirm the clinical guidance significance of tigecycline TDM.

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer.

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

Mstnet: method for glaucoma grading based on multimodal feature fusion of spatial relations.

Objective.The objective of this study is to develop an efficient multimodal learning framework for the classification of glaucoma. Glaucoma is a group of eye diseases that can result in vision loss and blindness, often due to delayed detection and treatment. Fundus images and optical coherence tomography (OCT) images have proven valuable for the diagnosis and management of glaucoma. However, current models that combine features from both modalities often lack efficient spatial relationship modeling.Approach.In this study, we propose an innovative approach to address the classification of glaucoma. We focus on leveraging the features of OCT volumes and harness the capabilities of transformer models to capture long-range spatial relationships. To achieve this, we introduce a 3D transformer model to extract features from OCT volumes, enhancing the model's effectiveness. Additionally, we employ downsampling techniques to enhance model efficiency. We then utilize the spatial feature relationships between OCT volumes and fundus images to fuse the features extracted from both sources.Main results.Our proposed framework has yielded remarkable results, particularly in terms of glaucoma grading performance. We conducted our experiments using the GAMMA dataset, and our approach outperformed traditional feature fusion methods. By effectively modeling spatial relationships and combining OCT volume and fundus map features, our framework achieved outstanding classification results.Significance.This research is of significant importance in the field of glaucoma diagnosis and management. Efficient and accurate glaucoma classification is essential for timely intervention and prevention of vision loss. Our proposed approach, which integrates 3D transformer models, offers a novel way to extract and fuse features from OCT volumes and fundus images, ultimately enhancing the effectiveness of glaucoma classification. This work has the potential to contribute to improved patient care, particularly in the early detection and treatment of glaucoma, thereby reducing the risk of vision impairment and blindness.

Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients.

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients' microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy. Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan-Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment. Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils. Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options.

A prospective prognostic signature for pancreatic adenocarcinoma based on ubiquitination-related mRNA-lncRNA with experimental validation in vitro and vivo.

Ubiquitination-related genes (URGs) exerted a crucial part in a variety of human disease disorders; however, their association with pancreatic adenocarcinoma (PAAD) had yet to be clearly described. We aimed to comprehensively characterize the contributions of URGs in PAAD through in silico analysis and experimental validation, and then identified a robust mRNA-lncRNA-based molecular prognostic panel for patients with PAAD using bulk RNA-sequencing and single-cell RNA-sequencing data. Initially, we collected the multi-omics data from TCGA platform to depict a comprehensive landscape of URGs in pan-cancer. Furthermore, we were accurate to PAAD for in-depth analysis. Significant differences of the activation of ubiquitination pathways and the expression of URGs were detected between normal and malignant cells. Unsupervised hierarchical clustering determined two PAAD subtypes with distinct clinical outcomes, ubiquitination pathway activities, immune microenvironment, and functional annotation characteristics. The expression profiles of ubiquitination-associated mRNAs and lncRNAs in the training and validation datasets were utilized to develop and verify a novel ubiquitination-related mRNA-lncRNA prognostic panel, which had a satisfied prediction efficiency. Our ubiquitination-associated model could function as an effective prognostic index and outperformed four other recognized panels in evaluating PAAD patients' survival status. Tumor immune microenvironment, mutation burden, and chemotherapy response were intensively explored to demonstrate the underlying mechanism of prognostic difference according to our panel. Our findings also revealed that FTI-277, a farnesyltransferase inhibitor, had a better curative effect in high-risk patients, while MK-2206, an Akt allosteric inhibitor, had a superior therapeutic effect in low-risk patients. The real-time PCR results uncovered the RNA expression of AC005062.1 in all the three PAAD cell lines was elevated several thousandfold. In conclusion, our URGs-based classification panel could be triumphantly served as a prediction tool for survival evaluation in patients with PAAD, and the genes in this panel could be developed as a potential target in PAAD therapy.

Enhancing the Electrochemiluminescence of Porphyrin via Crystalline Networks of Metal-Organic Frameworks for Sensitive Detection of Cardiac Troponin I.

Porphyrins easily aggregate due to unfavorable π-π accumulation, causing luminescent quenching in the aqueous phase and subsequently reducing luminescent efficiency. It is a feasible way to immobilize porphyrin molecules through metal-organic framework materials (MOFs). In this study, 5,10,15,20-tetrakis (4-carboxyphenyl) porphyrin (TCPP) was introduced into the metal-organic skeleton (PCN-224) as a ligand. The result showed that the electrochemiluminescence (ECL) and photoluminescence (PL) efficiency of the MOF skeleton was 8.2 and 6.5 times higher than TCPP, respectively. Impressively, the periodic distribution of porphyrin molecules in the MOF framework can overcome the bottleneck of porphyrin aggregation, resulting in the organic ligand TCPP participating in the electron transfer reaction. Herein, based on the PCN-224, a sandwich-type ECL immunosensor was constructed for the determination of cardiac troponin I (cTnI). It provided sensitive detection of cTnI in the range of 1 fg/mL to 10 ng/mL with a detection limit of 0.34 fg/mL. This work not only innovatively exploited a disaggregation ECL (DIECL) strategy via the crystalline framework of MOF to enhance the PL and ECL efficiency of porphyrin but also provided a promising ECL platform for the ultrasensitive monitoring of cTnI.

Interaction between Chinese medicine and digoxin: Clinical and research update.

Background: Digoxin is one of the most widely and commonly used cardiac drug, which plays an irreplaceable role in treating heart failure and arrhythmia. The 2010 Edition of Pharmacopoeia of the People's Republic of China stipulates that the effective range of digoxin plasma concentration is 0.5-2.0 ng/mL and it is toxic at plasma concentration >2 ng/mL. Its effective plasma drug concentration is close to the toxic concentration, and large individual differences in the effects of the drug have been observed. It is often used in combination with other drugs, but drug interactions have a great impact on the plasma concentration of digoxin and lead to adverse reactions (ADRs), such as poisoning. Most of the reported drug interactions are with Western drugs. However, there are many combinations of traditional Chinese medicine (TCM) and Western drugs, TCM interacting with digoxin comprises monomer components, single medicines, and Chinese patent medicines. Aim of the study: We aimed i) to provide an overview of the TCM formulations affecting the pharmacology of digoxin and their mechanisms of action and ii) to provide a theoretical reference for the safe and rational use of digoxin in combination with TCM in clinical practice and to avoid ADRs. Methods: A literature search of electronic databases, including PubMed, MEDLINE, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WANFANG Data, was performed to search for articles published between 1 January 1960, and 1 August 2022. Search terms used included "digoxin," "traditional Chinese medicine," "Chinese patent medicine," and "adverse reactions" and their combinations. Results: A total of 49 articles were obtained, including clinical reports, pharmacological experiments and in vitro experiments. The mechanisms of action affecting the pharmacology of digoxin are complex. TCM formulations may affect the pharmacology of digoxin in vivo by influencing gastrointestinal motility or gastric juice pH, regulating P-glycoprotein levels, exerting cumulative pharmacological effects, and enhancing the sensitivity of the heart to digoxin. Although studies have shown that some TCM formulations interact with digoxin, they may be influenced by the complexity of the composition and the pharmacological effects of the TCM, the sensitivity of digoxin concentration determination methods, etc. The results of existing studies are controversial and further in-depth studies are required. Conclusion: Combinations of digoxin and TCM formulations are commonly used. This article serves as a reference to understand the interactions between TCM formulations and digoxin to avoid the occurrence of ADRs and improve the efficacy and safety of digoxin.

The role of the miR-4306/PAK6 axis in degenerative nucleus pulposus cells in human intervertebral disc degeneration.

Intervertebral disc degeneration (IDD), characterized by degenerative changes that occur in intervertebral discs due to aging or structural injury, is thought to be the most common cause of lower back pain. Recent studies have shown that microRNAs (miRNAs) have a critical role in the etiopathogenesis of IDD. In the current study, we aimed to determine the role of miRNAs in mediating the underlying mechanisms associated with IDD. First, differentially expressed miRNAs (DEmiRNAs) were identified using the GEO database, and subsequently confirmed by RT-qPCR and in situ hybridization. We found that miR-4306 expression was significantly decreased in human nucleus pulposus (NP) tissues compared with healthy controls, and was negatively correlated with the patients' Pfirrmann grade. To determine the mechanism by which miR-4306 was involved in IDD pathogenesis, we examined the effects of overexpressing or silencing miR-4306 on extracellular matrix (ECM) synthesis/degradation, proliferation, autophagy and apoptosis of human degenerated NP cells isolated from IDD patients. Next, we used dual-luciferase reporter assays to demonstrate that miR-4306 interacted with the 3'-untranslated regions of p21-activated kinase 6 (PAK6) mRNA, resulting in significant suppression of PAK6 expression. This effect was abolished by miR-4306 binding site mutations. Using miR-4306/PAK6 gain-of-function and loss-of-function studies in human degenerated NP cells, we demonstrated that miR-4306 promoted NP cell proliferation, ECM synthesis and autophagy, while inhibiting apoptosis and ECM degradation via PAK6. Thus, our findings indicate that miR-4306, acting via PAK6, has an important role in IDD and can be used as a promising therapeutic target for the treatment of patients with IDD.

The Retention-Rate Improvement of Stromal Vascular Fraction Gel in Prefrontal Filling With Botulinum Toxin-A Injection: A Retrospective Analysis.

BACKGROUND: As a derivative of adipose tissues, stromal vascular fraction gel has been widely utilized in facial soft tissue filling, but it still does not achieve the expected effect in forehead filling. The reason may be related to the corrugator muscles movements. OBJECTIVES: The authors aimed to evaluate the effect of botulinum toxin-A (BTX-A) on the retention rate of stromal vascular fraction gel by limiting the corrugator muscles movements and to provide a theoretical basis that short-term inhibition of movement in the affected area could improve the effects of the fat graft. METHODS: From January 2019 to June 2021, patients with stromal vascular fraction gel facial filling (including frontal and temporal parts) were selected. According to whether or not BTX-A treatment was received, patients were divided into injected and the noninjected groups. A questionnaire and the Global Aesthetic Improvement Scale (GAIS) were administered to evaluate 2-dimensional photos. The retention rate and curvature were calculated with 3-dimensional images utilizing Artec Studio 13 Professional and MATLAB software. RESULTS: The graft retention, forehead curvature, and GAIS scores were all higher in the injected group than the noninjected group (P < .01). On the questionnaire, the injected group also showed more satisfaction with the treatment effect and were more willing to recommend the treatment to their friends. CONCLUSIONS: BTX-A injection can improve the retention rate of prefrontal stromal vascular fraction gel filling, with higher patient satisfaction and better postoperative effects.

Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma.

Background: Despite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel. Methods: Single cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel. Results: The malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel. Conclusions: Overall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.

A Review of the Intelligent Optimization and Decision in Plastic Forming.

The plastic forming process involves many influencing factors and has some inevitable disturbance factors, rendering the multi-objective collaborative optimization difficult. With the rapid development of big data and artificial intelligence (AI) technology, intelligent process optimization has become one of the critical technologies for plastic forming. This paper elaborated on the research progress on the intelligent optimization of plastic forming and the data-driven process planning and decision-making system in plastic forming process optimization. The development trend in intelligent optimization of the plastic forming process was researched. This review showed that the intelligent optimization algorithm has great potential in controlling forming quality, microstructure, and performance in plastic forming. It is a general trend to develop an intelligent optimization model of the plastic forming process with high integration, versatility, and high performance. Future research will take the data-driven expert system and digital twin system as the carrier, integrate the optimization algorithm and model, and realize the multi-scale, high-precision, high-efficiency, and real-time optimization of the plastic forming process.

Comprehensive characterization of extracellular matrix-related genes in PAAD identified a novel prognostic panel related to clinical outcomes and immune microenvironment: A silico analysis with in vivo and vitro validation.

The extracellular matrix (ECM) is a vital component of the tumor microenvironment, which interplays with stromal and tumor cells to stimulate the capacity of cancer cells to proliferate, migrate, invade, and undergo angiogenesis. Nevertheless, the crucial functions of ECM-related genes (ECMGs) in pancreatic adenocarcinoma (PAAD) have not been systematically evaluated. Hence, a comprehensive evaluation of the ECMGs is required in pan-cancer, especially in PAAD. First, a pan-cancer overview of ECMGs was explored through the integration of expression profiles, prognostic values, mutation information, methylation levels, and pathway-regulation relationships. Seven ECMGs (i.e. LAMB3, LAMA3, ITGB6, ITGB4, ITGA2, LAMC2, and COL11A1) were identified to be hub genes of PAAD, which were obviously up-regulated in PAAD and considerably linked to tumor stage as well as prognosis. Subsequently, patients with PAAD were divided into 3 clusters premised on ECMG expression and ECM scores. Cluster 2 was the subtype with the best prognosis accompanied by the lowest ECM scores, further verifying ECM's significant contribution to the pathophysiological processes of PAAD. Significant differences were observed for oncogene and tumor suppressor gene expression, immune microenvironment, and chemotherapy sensitivity across three ECM subtypes. After applying a variety of bioinformatics methods, a novel and robust ECM-associated mRNA-lncRNA-based prognostic panel (ECM-APP) was developed and validated for accurately predicting clinical outcomes of patients with PAAD. Patients with PAAD were randomly categorized into the train, internal validation, and external validation cohorts; meanwhile, each patient was allocated into high-risk (unfavorable prognosis) and low-risk (favorable prognosis) populations premised on the expression traits of ECM-related mRNAs and lncRNAs. The discrepancy in the tumor mutation burden and immune microenvironment might be responsible for the difference in prognoses across the high-risk and low-risk populations. Overall, our findings identified and validated seven ECMGs remarkably linked to the onset and progression of PAAD. ECM-based molecular classification and prognostic panel aid in the prognostic assessment and personalized intervention of patients with PAAD.

Clinical Efficacy, Antibiotic Resistance Genes, Virulence Factors and Outcome of Hospital-Acquired Pneumonia Induced by Klebsiella pneumoniae Carbapenemase 2-Producing with Tigecycline Treatment in the ICU.

Purpose: Tigecycline is an agent for carbapenemase-producing Klebsiella pneumonia (KPC-KP), given its penetration into lung tissues. Our study focused on the molecular and clinical efficacy of tigecycline for hospital-acquired pneumonia (HAP) in the ICU. Patients and Methods: A retrospective cohort study of 52 adult KPC-KP HAP patients by searching hospital medical records from January 2018 to December 2020 was established to investigate the epidemiology of KPC-KP infections for tigecycline treatment and the associated clinical efficacy of tigecycline. The KPC-KP isolates underwent multilocus sequence typing. Molecular typing, antimicrobial resistance, and virulence profiling were also analyzed by whole-genome sequencing of KPC-KP. Results: Among 52 patients with KPC-KP, the ICU mortality rate was 14/52 (27%), and there was no significant statistical difference in mortality between the effective group and failure group (p = 0.754). However, the duration of tigecycline was statistically different between the two groups of patients (14.4 vs 10 days, p=0.046). The total bacterial clearance rate was 6/52 (11.5%). There was no significant statistical difference in both groups (p=0.416). Antibiotic resistance genes (aac3iia) and virulence gene (AREO-iutA, Capsule-wzc) were negatively correlated with clinical efficacy (p = 0.011, OR = 1.237). Conclusions: Blakpc was the main carbapenemase in all K. pneumoniae strains. ST11-KL64 KPC-KP was the most common virulence factors in KPC-KP isolates. This study suggested that antibiotic resistance genes (aac3iia) and virulence gene (AREO-iutA, Capsule-wzc) were independent mortality risk factors for patients with Klebsiella pneumoniae carbapenemase-2 producing K. pneumoniae infections, when during the tigecycline treatment. Molecular analysis of K. pneumoniae may provide an option when choosing the antimicrobial treatment.

Characterization of neuroendocrine regulation- and metabolism-associated molecular features and prognostic indicators with aid to clinical chemotherapy and immunotherapy of patients with pancreatic cancer.

The worldwide prevalence of pancreatic cancer has been rising in recent decades, and its prognosis has not improved much. The imbalance of substance and energy metabolism in tumour cells is among the primary causes of tumour formation and occurrence, which is often controlled by the neuroendocrine system. We applied Cox and LASSO regression analysis to develop a neuroendocrine regulation- and metabolism-related prognostic risk score model with three genes (GSK3B, IL18 and VEGFA) for pancreatic cancer. TCGA dataset served as the training and internal validation sets, and GSE28735, GSE62452 and GSE57495 were designated as external validation sets. Patients classified as the low-risk population (category, group) exhibited considerably improved survival duration in contrast with those classified as the high-risk population, as determined by the Kaplan-Meier curve. Then, we combined all the samples, and divided them into three clusters using unsupervised clustering analysis. Unsupervised clustering, t-distributed stochastic neighbor embedding (t-SNE), and principal component analysis (PCA) were further utilized to demonstrate the reliability of the prognostic model. Moreover, the risk score was shown to independently function as a predictor of pancreatic cancer in both univariate and multivariate Cox regression analyses. The results of gene set enrichment analysis (GSEA) illustrated that the low-risk population was predominantly enriched in immune-associated pathways. "ESTIMATE" algorithm, single-sample GSEA (ssGSEA) and the Tumor Immune Estimation Resource (TIMER) database showed immune infiltration ratings were enhanced in the low-risk category in contrast with the high-risk group. Tumour immune dysfunction and exclusion (TIDE) database predicted that immunotherapy for pancreatic cancer may be more successful in the high-risk than in the low-risk population. Mutation analysis illustrated a positive link between the tumour mutation burden and risk score. Drug sensitivity analysis identified 44 sensitive drugs in the high- and low-risk population. GSK3B expression was negatively correlated with Oxaliplatin, and IL18 expression was negatively correlated with Paclitaxel. Lastly, we analyzed and verified gene expression at RNA and protein levels based on GENPIA platform, HPA database and quantitative real-time PCR. In short, we developed a neuroendocrine regulation- and metabolism-associated prognostic model for pancreatic cancer that takes into account the immunological microenvironment and drug sensitivity.

Development and Application of the Placebo Response Model in Clinical Trials for Primary Sjögren's Syndrome.

This study aimed to develop a placebo response model for pharmaceutical clinical trials of primary Sjogren's syndrome,and to quantitatively analyze the distribution and related factors influencing the placebo response to further optimize the design of clinical trials and evaluate the results of single-arm clinical trials. Public databases, including PubMed, Embase, and Cochrane Library were searched for reports on randomized placebo-controlled trials for Sjögren's syndrome which used the change from baseline in ESSDAI score as the primary outcome. The model-based meta-analysis method was used to evaluate the time course and the related influencing factors of the placebo response for ESSDAI in such clinical trials. A virtual placebo control group was constructed based on the final placebo response model to determine the treatment efficacy of belimumab and cyclosporine A for primary Sjögren's syndrome in a single-arm study. A total of 12 studies involving 450 subjects were included in the analysis. The established model described the time-course characteristics of the changes in ESSDAI score from the baseline in the 48 weeks placebo group. We found that the onset time of placebo response was approximately 12 weeks, and its efficacy plateaued at 48 weeks. The baseline ESSDAI score had a significant effect on the maximum value of the placebo response; the maximum value of the placebo response decreased by 0.552 for every 1 score rise in the baseline ESSDAI score. The efficacy of belimumab and cyclosporine A in the single-arm trial was comparable to that of the placebo response at the same baseline; no significant therapeutic advantage was observed. The placebo response model established in this study could provide a basis for designing clinical trials for primary Sjogren's syndrome in the future. It may also provide a reliable external efficacy control standard for single-arm clinical trials.

Bioinformatics study on different gene expression profiles of fibroblasts and vascular endothelial cells in keloids.

ABSTRACT: Keloid is a benign fibroproliferative skin tumor. The respective functions of fibroblasts and vascular endothelial cells in keloid have not been fully studied. The purpose of this study is to identify the respective roles and key genes of fibroblasts and vascular endothelial cells in keloids, which can be used as new targets for diagnosis or treatment.The microarray datasets of keloid fibroblasts and vascular endothelial cells were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis. The search tool for retrieval of interacting genes and Cytoscape were used to construct protein-protein interaction (PPI) networks and analyze gene modules. The hub genes were screened out, and the relevant interaction networks and biological process analysis were carried out.In fibroblasts, the DEGs were significantly enriched in collagen fibril organization, extracellular matrix organization and ECM-receptor interaction. The PPI network was constructed, and the most significant module was selected, which is mainly enriched in ECM-receptor interaction. In vascular endothelial cells, the DEGs were significantly enriched in cytokine activity, growth factor activity and transforming growth factor-ß (TGF-ß) signaling pathway. Module analysis was mainly enriched in TGF-ß signaling pathway. Hub genes were screened out separately.In summary, the DEGs and hub genes discovered in this study may help us understand the molecular mechanisms of keloid, and provide potential targets for diagnosis and treatment.