LPS-induced monocarboxylate transporter-1 inhibition facilitates lactate accumulation triggering epithelial-mesenchymal transformation and pulmonary fibrosis.

The epithelial-mesenchymal transformation (EMT) process of alveolar epithelial cells is recognized as involved in the development of pulmonary fibrosis. Recent evidence has shown that lipopolysaccharide (LPS)-induced aerobic glycolysis of lung tissue and elevated lactate concentration are associated with the pathogenesis of sepsis-associated pulmonary fibrosis. However, it is uncertain whether LPS promotes the development of sepsis-associated pulmonary fibrosis by promoting lactate accumulation in lung tissue, thereby initiating EMT process. We hypothesized that monocarboxylate transporter-1 (MCT1), as the main protein for lactate transport, may be crucial in the pathogenic process of sepsis-associated pulmonary fibrosis. We found that high concentrations of lactate induced EMT while moderate concentrations did not. Besides, we demonstrated that MCT1 inhibition enhanced EMT process in MLE-12 cells, while MCT1 upregulation could reverse lactate-induced EMT. LPS could promote EMT in MLE-12 cells through MCT1 inhibition and lactate accumulation, while this could be alleviated by upregulating the expression of MCT1. In addition, the overexpression of MCT1 prevented LPS-induced EMT and pulmonary fibrosis in vivo. Altogether, this study revealed that LPS could inhibit the expression of MCT1 in mouse alveolar epithelial cells and cause lactate transport disorder, which leads to lactate accumulation, and ultimately promotes the process of EMT and lung fibrosis.

Retinol and retinol binding protein 4 levels and COVID-19: a Mendelian randomization study.

BACKGROUND: The Corona Virus Disease 2019 (COVID-19) pandemic has struck globally. Whether the related proteins of retinoic acid (RA) signaling pathway are causally associated with the risk of COVID-19 remains unestablished. We conducted a two-sample Mendelian randomization (MR) study to assess the associations of retinol, retinol binding protein 4 (RBP4), retinol dehydrogenase 16 (RDH16) and cellular retinoic acid binding protein 1 (CRABP1) with COVID-19 in European population. METHODS: The outcome utilized the summary statistics of COVID-19 from the COVID-19 Host Genetics Initiative. The exposure data were obtained from public genome wide association study (GWAS) database. We extracted SNPs from exposure data and outcome data. The inverse variance weighted (IVW), MR-Egger and Wald ratio methods were employed to assess the causal relationship between exposure and outcome. Sensitivity analyses were performed to ensure the validity of the results. RESULTS: The MR estimates showed that retinol was associated with lower COVID-19 susceptibility using IVW (OR: 0.69, 95% CI: 0.53-0.90, P: 0.0065), whereas the associations between retinol and COVID-19 hospitalization or severity were not significant. RBP4 was associated with lower COVID-19 susceptibility using the Wald ratio (OR: 0.83, 95% CI: 0.72-0.95, P: 0.0072). IVW analysis showed RDH16 was associated with increased COVID-19 hospitalization (OR: 1.10, 95% CI: 1.01-1.18, P: 0.0199). CRABP1 was association with lower COVID-19 susceptibility (OR: 0.95, 95% CI: 0.91-0.99, P: 0.0290) using the IVW. CONCLUSIONS: We found evidence of possible causal association of retinol, RBP4, RDH16 and CRABP1 with the susceptibility, hospitalization and severity of COVID-19. Our study defines that retinol is significantly associated with lower COVID-19 susceptibility, which provides a reference for the prevention of COVID-19 with vitamin A supplementation.

Pharmacological inhibition of the ACE/Ang-2/AT1 axis alleviates mechanical ventilation-induced pulmonary fibrosis.

Mechanical ventilation (MV) is an essential therapy for acute respiratory distress syndrome (ARDS) and pulmonary fibrosis. However, it can also induce mechanical ventilation-induced pulmonary fibrosis (MVPF) and the underlying mechanism remains unknown. Based on a mouse model of MVPF, the present study aimed to explore the role of the angiotensin-converting enzyme/angiotensin II/angiotensin type 1 receptor (ACE/Ang-2/AT1R) axis in the process of MVPF. In addition, recombinant angiotensin-converting enzyme 2(rACE2), AT1R inhibitor valsartan, AGTR1-directed shRNA and ACE inhibitor perindopril were applied to verify the effect of inhibiting ACE/Ang-2/AT1R axis in the treatment of MVPF. Our study found MV induced an inflammatory reaction and collagen deposition in mouse lung tissue accompanied by the activation of ACE in lung tissue, increased concentration of Ang-2 in bronchoalveolar lavage fluid (BALF), and upregulation of AT1R in alveolar epithelial cells. The process of pulmonary fibrosis could be alleviated by the application of the ACE inhibitor perindopril, ATIR inhibitor valsartan and AGTR1-directed shRNA. Meanwhile, rACE2 could also alleviate MVPF through the degradation of Ang-2. Our finding indicated the ACE/Ang-2/AT1R axis played an essential role in the pathogenesis of MVPF. Pharmacological inhibition of the ACE/Ang-2/AT1R axis might be a promising strategy for the treatment of MVPF.

METFORMIN MITIGATES SEPSIS-ASSOCIATED PULMONARY FIBROSIS BY PROMOTING AMPK ACTIVATION AND INHIBITING HIF-1α-INDUCED AEROBIC GLYCOLYSIS.

ABSTRACT: Recent research has revealed that aerobic glycolysis has a strong correlation with sepsis-associated pulmonary fibrosis (PF). However, at present, the mechanism and pathogenesis remain unclear. We aimed to test the hypothesis that the adenosine monophosphate-activated protein kinase (AMPK) activation and suppression of hypoxia-inducible factor 1α (HIF-1α)-induced aerobic glycolysis play a central role in septic pulmonary fibrogenesis. Cellular experiments demonstrated that lipopolysaccharide increased fibroblast activation through AMPK inactivation, HIF-1α induction, alongside an augmentation of aerobic glycolysis. By contrast, the effects were reversed by AMPK activation or HIF-1α inhibition. In addition, pretreatment with metformin, which is an AMPK activator, suppresses HIF-1α expression and alleviates PF associated with sepsis, which is caused by aerobic glycolysis, in mice. Hypoxia-inducible factor 1α knockdown demonstrated similar protective effects in vivo . Our research implies that targeting AMPK activation and HIF-1α-induced aerobic glycolysis with metformin might be a practical and useful therapeutic alternative for sepsis-associated PF.

[Research on the mechanism of mechanical ventilation induced endoplasmic reticulum stress promoting mechanical ventilation-induced pulmonary fibrosis].

OBJECTIVE: To demonstrate the mechanism of mechanical ventilation (MV) induced endoplasmic reticulum stress (ERS) promoting mechanical ventilation-induced pulmonary fibrosis (MVPF), and to clarify the role of angiotensin receptor 1 (AT1R) during the process. METHODS: The C57BL/6 mice were randomly divided into four groups: Sham group, MV group, AT1R-shRNA group and MV+AT1R-shRNA group, with 6 mice in each group. The MV group and MV+AT1R-shRNA group mechanically ventilated for 2 hours after endotracheal intubation to establish MVPF animal model (parameter settings: respiratory rate 70 times/minutes, tidal volume 20 mL/kg, inhated oxygen concentration 0.21). The Sham group and AT1R-shRNA group only underwent intubation after anesthesia and maintained spontaneous breathing. AT1R-shRNA group and MV+AT1R-shRNA group were airway injected with the adeno-associated virus one month before modeling to inhibit AT1R gene expression in lung tissue. The expressions of AT1R, ERS signature proteins [immunoglobulin heavy chain-binding protein (BIP), protein disulfide isomerase (PDI)], fibrosis signature proteins [collagen I (COL1A1), α-smooth muscle actin (α-SMA)] in lung tissues were detected by immunofluorescence and Western blotting. Hematoxylin-eosin (HE) staining was used to evaluate lung injury and Masson staining was used to evaluate pulmonary fibrosis. RESULTS: Compared with the Sham group, the degree of pulmonary fibrosis and lung injury were more significant in the MV group. In the MV group, the protein expressions of AT1R, BIP, PDI, COL1A1 and α-SMA were increased (AT1R/ß-actin: 1.40±0.02 vs. 1, BIP/ß-actin: 2.79±0.07 vs. 1, PDI/ß-actin: 2.07±0.02 vs. 1, COL1A1/α-Tubulin: 2.60±0.15 vs. 1, α-SMA/α-Tubulin: 2.80±0.25 vs. 1, all P < 0.01). The number of E-cad+/AT1R+ and E-cad+/BIP+ cells in lung tissue increased, and the fluorescence intensity of COL1A1 and α-SMA increased. Compared with the MV group, the degree of pulmonary fibrosis and lung injury were significantly relieved in the MV+AT1R-shRNA group. In the MV+AT1R-shRNA group, the protein expressions of AT1R, BIP, PDI, COL1A1 and α-SMA were decreased (AT1R/ß-actin: 0.53±0.03 vs. 1.40±0.02, BIP/ß-actin: 1.73±0.15 vs. 2.79±0.07, PDI/ß-actin: 1.04±0.07 vs. 2.07±0.02, COL1A1/α-Tubulin: 1.29±0.11 vs. 2.60±0.15, α-SMA/α-Tubulin: 1.27±0.10 vs. 2.80±0.25, all P < 0.01). The number of E-cad+/AT1R+ and E-cad+/BIP+ cells in lung tissue decreased, and the fluorescence intensity of COL1A1 and α-SMA decreased. There was no statistically significant difference in the indicators between AT1R-shRNA group and Sham group. CONCLUSIONS: MV up-regulate the expression of AT1R in alveolar epithelial cells, activate the AT1R pathway, induce ERS and promote the progression of MVPF.

Fibrotic extracellular vesicles contribute to mechanical ventilation-induced pulmonary fibrosis development by activating lung fibroblasts via JNK signalling pathway: an experimental study.

Recent research has revealed that mechanical ventilation (MV) could initiate ventilator-induced lung injury along with the initiation of the process of pulmonary fibrosis (PF), leading to MV-induced PF (MVPF). However, the underlying mechanism remains unclear. This study aimed to explore the role of MV-induced extracellular vesicles (MV-EVs) and the c-Jun N-terminal kinase (JNK) signalling pathway in the pathogenesis of MVPF in vivo and in vitro. The process of MV is accompanied by the secretion of MV-EVs, which could induce lung fibroblast activation. Furthermore, single-cell RNA-sequencing analysis revealed that the JNK pathway in lung fibroblasts was activated after MV initiation. Inhibiting the JNK pathway could both restrain MV-EV-induced lung fibroblast activation in vitro or reduce the severity of MVPF in vivo. In conclusion, this study demonstrated that MV-EVs contribute to MVPF progression by activating lung fibroblasts via the JNK signalling pathway and that inhibiting the secretion of EV and the activation of the JNK signalling pathway is a promising strategy for treating MVPF.

A deep learning model for predicting COVID-19 ARDS in critically ill patients.

Background: The coronavirus disease 2019 (COVID-19) is an acute infectious pneumonia caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection previously unknown to humans. However, predictive studies of acute respiratory distress syndrome (ARDS) in patients with COVID-19 are limited. In this study, we attempted to establish predictive models to predict ARDS caused by COVID-19 via a thorough analysis of patients' clinical data and CT images. Method: The data of included patients were retrospectively collected from the intensive care unit in our hospital from April 2022 to June 2022. The primary outcome was the development of ARDS after ICU admission. We first established two individual predictive models based on extreme gradient boosting (XGBoost) and convolutional neural network (CNN), respectively; then, an integrated model was developed by combining the two individual models. The performance of all the predictive models was evaluated using the area under receiver operating characteristic curve (AUC), confusion matrix, and calibration plot. Results: A total of 103 critically ill COVID-19 patients were included in this research, of which 23 patients (22.3%) developed ARDS after admission; five predictive variables were selected and further used to establish the machine learning models, and the XGBoost model yielded the most accurate predictions with the highest AUC (0.94, 95% CI: 0.91-0.96). The AUC of the CT-based convolutional neural network predictive model and the integrated model was 0.96 (95% CI: 0.93-0.98) and 0.97 (95% CI: 0.95-0.99), respectively. Conclusion: An integrated deep learning model could be used to predict COVID-19 ARDS in critically ill patients.

Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit.

BACKGROUND: There are no universally accepted indications to initiate renal replacement therapy (RRT) among patients with acute kidney injury (AKI). This study aimed to develop a nomogram to predict the risk of RRT among AKI patients in intensive care unit (ICU). METHODS: In this retrospective cohort study, we extracted AKI patients from Medical Information Mart for Intensive Care III (MIMIC-III) database. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%). Multivariable logistic regression based on Akaike information criterion was used to establish the nomogram. The discrimination and calibration of the nomogram were evaluated by Harrell's concordance index (C-index) and Hosmer-Lemeshow (HL) test. Decision curve analysis (DCA) was performed to evaluate clinical application. RESULTS: A total of 7413 critically ill patients with AKI were finally enrolled. 514 (6.9%) patients received RRT after ICU admission. 5194 (70%) patients were in the training cohort and 2219 (30%) patients were in the validation cohort. Nine variables, namely, age, hemoglobin, creatinine, blood urea nitrogen and lactate at AKI detection, comorbidity of congestive heart failure, AKI stage, and vasopressor use were included in the nomogram. The predictive model demonstrated satisfying discrimination and calibration with C-index of 0.938 (95% CI, 0.927-0.949; HL test, P = 0.430) in training set and 0.935 (95% CI, 0.919-0.951; HL test, P = 0.392) in validation set. DCA showed a positive net benefit of our nomogram. CONCLUSION: The nomogram developed in this study was highly accurate for RRT prediction with potential application value.

Association of geriatric nutritional risk index with all-cause hospital mortality among elderly patients in intensive care unit.

Background: Malnutrition is associated with poor outcomes for geriatric patients in intensive care unit (ICU). It is important to identify patients at risk of malnutrition and provide individual nutrition support. The assessment of malnutrition risk is not easy for these patients due to their cognitive impairment. Geriatric nutrition risk index (GNRI) is a simple and objective scoring tool to evaluate the risk of malnutrition in elderly patients. In this study, we aimed to see whether GNRI score was appropriate to predict clinical outcomes among geriatric patients in the setting of ICU. Materials and methods: Elderly patients with age ≥ 65 years were extracted from Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Categories based on GNRI were classified as major risk (GNRI <82), moderate risk (GNRI 82 to <92), low risk (GNRI 92 to ≤98), and no risk (GNRI >98). The primary outcome was all-cause hospital mortality. Multivariable Cox proportional hazards regression models and restricted cubic spline were used to investigate associations of GNRI with hospital mortality, respectively. A two-piecewise linear regression model was applied to examine the inflection point of GNRI on hospital mortality. To reduce selection bias, propensity score matching (PSM) was used in a 1:1 ratio. Results: A total of 3,696 geriatric patients were finally included with median age 75 (69, 81) years. The prevalence of major risk was 28.6%. In the fully adjusted model, GNRI categories featured a negative trend with hospital mortality (p for trend = 0.037). Restricted cubic spline analysis demonstrated an L-shaped relationship between GNRI and hospital mortality before and after matching. The inflection point was 78.7. At the left side of inflection point, GNRI levels were significantly negatively associated with hospital mortality (HR = 0.96, 95% CI: 0.94-0.98; p < 0.001) and featured no significant relations at the right side. Multiple linear regression also showed that GNRI was negatively associated with length of stay in hospital. Conclusion: The major risk of malnutrition defined by GNRI was able to predict poor prognosis for geriatric patients admitted to ICU.

Non-coding RNA alterations in extracellular vesicles from bronchoalveolar lavage fluid contribute to mechanical ventilation-induced pulmonary fibrosis.

Objective: For respiratory failure patients, mechanical ventilation (MV) is a life-saving therapy to maintain respiratory function. However, MV could also cause damage to pulmonary structures, result in ventilator-induced lung injury (VILI) and eventually progress to mechanical ventilation-induced pulmonary fibrosis (MVPF). Mechanically ventilated patients with MVPF are closely related to increased mortality and poor quality of life in long-term survival. Thus, a thorough understanding of the involved mechanism is necessary. Methods: We used next-generation sequencing to identify differentially expressed non-coding RNAs (ncRNAs) in BALF EVs which were isolated from Sham and MV mice. Bioinformatics analysis was conducted to identify the engaged ncRNAs and related signaling pathways in the process of MVPF. Results: We found 1801 messenger RNAs (mRNA), 53 micro RNAs (miRNA), 273 circular RNAs (circRNA) and 552 long non-coding RNAs (lncRNA) in mice BALF EVs of two groups, which showed significant differential expression. TargetScan predicted that 53 differentially expressed miRNAs targeted 3105 mRNAs. MiRanda revealed that 273 differentially expressed circRNAs were associated with 241 mRNAs while 552 differentially expressed lncRNAs were predicated to target 20528 mRNAs. GO, KEGG pathway analysis and KOG classification showed that these differentially expressed ncRNA-targeted mRNAs were enriched in fibrosis related signaling pathways and biological processes. By taking the intersection of miRNAs target genes, circRNAs target genes and lncRNAs target genes, we found 24 common key genes and 6 downregulated genes were confirmed by qRT-PCR. Conclusions: Changes in BALF-EV ncRNAs may contribute to MVPF. Identification of key target genes involved in the pathogenesis of MVPF could lead to interventions that slow or reverse fibrosis progression.

Integrin ß3 Mediates Sepsis and Mechanical Ventilation-Associated Pulmonary Fibrosis Through Glycometabolic Reprogramming.

Mechanical ventilation (MV) has become a clinical first-line treatment option for patients with respiratory failure. However, it was unclear whether MV further aggravates the process of sepsis-associated pulmonary fibrosis and eventually leads to sepsis and mechanical ventilation-associated pulmonary fibrosis (S-MVPF). This study aimed to explore the mechanism of S-MVPF concerning integrin ß3 activation in glycometabolic reprogramming of lung fibroblasts. We found that MV exacerbated sepsis-associated pulmonary fibrosis induced by lipopolysaccharide, which was accompanied by proliferation of lung fibroblasts, increased deposition of collagen in lung tissue, and increased procollagen type I carboxy-terminal propeptide in the bronchoalveolar lavage fluid. A large number of integrin ß3- and pyruvate kinase M2-positive fibroblasts were detected in lung tissue after stimulation with lipopolysaccharide and MV, with an increase in lactate dehydrogenase A expression and lactate levels. S-MVPF was primarily attenuated in integrin ß3-knockout mice, which also resulted in a decrease in the levels of pyruvate kinase M2, lactate dehydrogenase A, and lactate. In conclusion, MV aggravated sepsis-associated pulmonary fibrosis, with glycometabolic reprogramming mediated by integrin ß3 activation. Thus, integrin ß3-mediated glycometabolic reprogramming might be a potential therapeutic target for S-MVPF.

MACHINE LEARNING MODELS FOR PREDICTING ACUTE KIDNEY INJURY IN PATIENTS WITH SEPSIS-ASSOCIATED ACUTE RESPIRATORY DISTRESS SYNDROME.

ABSTRACT: Background: Acute kidney injury (AKI) is a prevalent and serious complication among patients with sepsis-associated acute respiratory distress syndrome (ARDS). Prompt and accurate prediction of AKI has an important role in timely intervention, ultimately improving the patients' survival rate. This study aimed to establish machine learning models to predict AKI via thorough analysis of data derived from electronic medical records. Method: The data of eligible patients were retrospectively collected from the Medical Information Mart for Intensive Care III database from 2001 to 2012. The primary outcome was the development of AKI within 48 hours after intensive care unit admission. Four different machine learning models were established based on logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The performance of all predictive models was evaluated using the area under receiver operating characteristic curve, precision-recall curve, confusion matrix, and calibration plot. Moreover, the discrimination ability of the machine learning models was compared with that of the Sequential Organ Failure Assessment (SOFA) model. Results; Among 1,085 sepsis-associated ARDS patients included in this research, 375 patients (34.6%) developed AKI within 48 hours after intensive care unit admission. Twelve predictive variables were selected and further used to establish the machine learning models. The XGBoost model yielded the most accurate predictions with the highest area under receiver operating characteristic curve (0.86) and accuracy (0.81). In addition, a novel shiny application based on the XGBoost model was established to predict the probability of developing AKI among patients with sepsis-associated ARDS. Conclusions: Machine learning models could be used for predicting AKI in patients with sepsis-associated ARDS. Accordingly, a user-friendly shiny application based on the XGBoost model with reliable predictive performance was released online to predict the probability of developing AKI among patients with sepsis-associated ARDS.

ASK1-ER stress pathway-mediated fibrotic-EV release contributes to the interaction of alveolar epithelial cells and lung fibroblasts to promote mechanical ventilation-induced pulmonary fibrosis.

Recent clinical research has revealed that mechanical ventilation (MV) can initiate pulmonary fibrosis and induce mechanical ventilation-induced pulmonary fibrosis (MVPF). However, the underlying mechanism remains largely uncharacterized. Based on a mouse model of MVPF and an alveolar epithelial cell cyclic strain model, the present study explores the possible mechanism of MVPF. Single-cell RNA-sequencing and EV RNA-sequencing analysis revealed that MV promoted apoptosis signal-regulating kinase 1 (ASK1)-mediated endoplasmic reticulum (ER) stress pathway activation and extracellular vesicle (EV) release from alveolar epithelial cells. Furthermore, the ASK1-ER stress pathway was shown to mediate mechanical stretch (MS)- or MV-induced EV release and lung fibroblast activation in vivo and in vitro. These processes were suppressed by ER stress inhibitors or by silencing ASK1 with ASK1- short hairpin RNA (shRNA). In addition, MVPF was suppressed by inhibiting ASK1 and ER stress in vivo. Therefore, the present study demonstrates that ASK1-ER stress pathway-mediated fibrotic-EV release from alveolar epithelial cells contributes to fibroblast activation and the initiation of pulmonary fibrosis during MV. The inhibited release of EVs targeting the ASK1-ER stress pathway might be a promising treatment strategy for MVPF.

Scars of COVID-19: A bibliometric analysis of post-COVID-19 fibrosis.

Background: The coronavirus disease 2019 (COVID-19) becomes a worldwide public health threat. Increasing evidence proves that COVID-19-induced acute injuries could be reversed by a couple of therapies. After that, post-COVID-19 fibrosis (PCF), a sequela of "Long COVID," earns rapidly emerging concerns. PCF is associated with deteriorative lung function and worse quality of life. But the process of PCF remains speculative. Therefore, we aim to conduct a bibliometric analysis to explore the overall structure, hotspots, and trend topics of PCF. Materials and methods: A comprehensive search was performed in the Web of Science core database to collect literature on PCF. Search syntax included COVID-19 relevant terms: "COVID 19," "COVID-19 Virus Disease," "COVID-19 Virus Infection," "Coronavirus Disease-19," "2019 Novel Coronavirus Disease," "2019 Novel Coronavirus Infection," "SARS Coronavirus 2 Infection," "COVID-19 Pandemic," "Coronavirus," "2019-nCoV," and "SARS-CoV-2"; and fibrosis relevant terms: "Fibrosis," "Fibroses," and "Cirrhosis." Articles in English were included. Totally 1,088 publications were enrolled. Searching results were subsequentially exported and collected for the bibliometric analysis. National, organizational, and individual level data were analyzed and visualized through biblioshiny package in the R, VOSviewer software, the CiteSpace software, and the Graphical Clustering Toolkit (gCLUTO) software, respectively. Results: The intrinsic structure and development in the field of PCF were investigated in the present bibliometric analysis. The topmost keywords were "COVID-19" (occurrences, 636) surrounded by "SARS-CoV-2" (occurrences, 242), "coronavirus" (occurrences, 123), "fibrosis" (occurrences, 120), and "pneumonia" (occurrences, 94). The epidemiology, physiopathology, diagnosis, and therapy of PCF were extensively studied. After this, based on dynamic analysis of keywords, hot topics sharply changed from "Wuhan," "inflammation," and "cytokine storm" to "quality of life" and "infection" through burst detection; from "acute respiratory syndrome," "cystic-fibrosis" and "fibrosis" to "infection," "COVID-19," "quality-of-life" through thematic evolution; from "enzyme" to "post COVID." Similarly, co-cited references analysis showed that topics of references with most citations shift from "pulmonary pathology" (cluster 0) to "COVID-19 vaccination" (cluster 6). Additionally, the overview of contributors, impact, and collaboration was revealed. Summarily, the USA stood out as the most prolific, influential, and collaborative country. The Udice French Research University, Imperial College London, Harvard University, and the University of Washington represented the largest volume of publications, citations, H-index, and co-authorships, respectively. Dana Albon was the most productive and cited author with the strongest co-authorship link strength. Journal of Cystic Fibrosis topped the list of prolific and influential journals. Conclusion: Outcomes gained from this study assisted professionals in better realizing PCF and would guide future practices. Epidemiology, pathogenesis, and therapeutics were study hotspots in the early phase of PCF research. As the spread of the COVID-19 pandemic and progress in this field, recent attention shifted to the quality of life of patients and post-COVID comorbidities. Nevertheless, COVID-19 relevant infection and vaccination were speculated to be research trends with current and future interest. International cooperation as well as in-depth laboratory experiments were encouraged to promote further explorations in the field of PCF.

Characteristics and topic trends on electrical impedance tomography hardware publications.

Objective: Electrical impedance tomography (EIT) is a technique to measure electrical properties of tissue. With the progress of modern integrated circuits and microchips, EIT instrumentation becomes an active research area to improve all aspects of device performance. Plenty of studies on EIT hardware have been presented in prestigious journals. This study explores publications on EIT hardware to identify the developing hotspots and trends. Method: Publications covering EIT hardware on the Web of Science Core Collection (WoSCC) database from 1989 to 2021 were collected for bibliometric analysis. CiteSpace and VOS viewer were used to study the characteristics of the publications. Main results: A total of 592 publications were analyzed, showing that the number of annual publications steadily increased. China, England, and South Korea were the most prolific countries on EIT hardware publications with productive native institutions and authors. Research topics spread out in "bio-electrical impedance imaging", "hardware optimization", "algorithms" and "clinical applications" (e.g., tissue, lung, brain, and oncology). Hardware research in "pulmonary" and "hemodynamic" applications focused on monitoring and were represented by silhouette recognition and dynamic imaging while research in "tumor and tissue" and "brain" applications focused on diagnosis and were represented by optimization of precision. Electrode development was a research focus through the years. Imaging precision and bioavailability of hardware optimization may be the future trend. Conclusion: Overall, system performance, particularly in the areas of system bandwidth and precision in applications may be the future directions of hardware research.

Integrin ß3-PKM2 pathway-mediated aerobic glycolysis contributes to mechanical ventilation-induced pulmonary fibrosis.

Background: Mechanical ventilation (MV) can induce pulmonary fibrosis. This study aims to investigate whether MV-induced pulmonary fibrosis is associated with aerobic glycolysis and seeks to uncover the underlying mechanisms mediated by integrin ß3-pyruvate kinase M2 (PKM2) pathway. Methods: PKM2 knockdown or inhibition, integrin ß3 knockout or inhibition and wild-type mice were exposed to MV (20 mL/kg) for 2 h. Results: Mice exposed to MV exhibited increased expression of collagen deposition, and upregulation of α-smooth muscle actin and collagen I in lung tissues. Single cells analysis showed that MV-induced pulmonary fibrosis was associated with increased gene expression of integrin and glycolysis in pulmonary fibroblasts, as well as upregulation of glycolytic products tested by metabolomics. Meanwhile, increased protein level of integrin ß3 and PKM2 was confirmed by western blot and immunohistochemistry. Double immunofluorescence staining and flow cytometric analysis showed increased number of fibronectin+/integrin ß3+ and fibronectin+/PKM2+ fibroblasts in lung tissues. Furthermore, MV-induced aerobic glycolysis and pulmonary fibrosis were ameliorated after treatment with PKM2 knockdown-AAV and inhibition, or in integrin ß3 knockout and inhibition mice. Conclusions: Integrin ß3-PKM2 pathway-mediated aerobic glycolysis contributes to MV-induced pulmonary fibrosis. The inhibition of aerobic glycolysis targeting integrin ß3-PKM2 pathway may be a promising treatment for MV-induced pulmonary fibrosis.

Prediction of high-flow nasal cannula outcomes at the early phase using the modified respiratory rate oxygenation index.

BACKGROUND: This study was designed to explore the early predictive value of the respiratory rate oxygenation (ROX) index modified by PaO2 (mROX) in high-flow nasal cannula (HFNC) therapy in patients with acute hypoxemia respiratory failure (AHRF). METHOD: Seventy-five patients with AHRF treated with HFNC were retrospectively reviewed. Respiratory parameters at baseline and 2 h after HFNC initiation were analyzed. The predictive value of the ROX (ratio of pulse oximetry/FIO2 to respiratory rate) and mROX (ratio of arterial oxygen /FIO2 to respiratory rate) indices with two variations by adding heart rate to each index (ROX-HR and mROX-HR) was evaluated. RESULTS: HFNC therapy failed in 24 patients, who had significantly higher intensive care unit (ICU) mortality and longer ICU stay. Both the ROX and mROX indices at 2 h after HFNC initiation can predict the risk of intubation after HFNC. Two hours after HFNC initiation, the mROX index had a higher area under the receiver operating characteristic curve (AUROC) for predicting HFNC success than the ROX index. Besides, baseline mROX index of greater than 7.1 showed a specificity of 100% for HFNC success. CONCLUSION: The mROX index may be a suitable predictor of HFNC therapy outcomes at the early phase in patients with AHRF.

The role of macrophage-fibroblast interaction in lipopolysaccharide-induced pulmonary fibrosis: an acceleration in lung fibroblast aerobic glycolysis.

Recent evidence has shown that lipopolysaccharide (LPS)-induced aerobic glycolysis of lung fibroblasts is closely associated with the pathogenesis of septic pulmonary fibrosis. Nevertheless, the underlying mechanism remains poorly defined. In this study, we demonstrate that LPS promotes c-Jun N-terminal kinase (JNK) signaling pathway activation and endogenous tumor necrosis factor-α (TNF-α) secretion in pulmonary macrophages. This, in turn, could significantly promote aerobic glycolysis and increase lactate production in lung fibroblasts through 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 (PFKFB3) activation. Culturing human lung fibroblast MRC-5 cell line with TNF-α or endogenous TNF-α (cell supernatants of macrophages after LPS stimulation) both enhanced the aerobic glycolysis and increased lactate production. These effects could be prevented by treating macrophages with JNK pathway inhibitor, by administering TNF-α receptor 1 (TNFR1) siRNA, PFKFB3 inhibitor, or by silencing PFKFB3 with fibroblasts-specific shRNA. In addition, the inhibition of TNF-α secretion and PFKFB3 expression prevented LPS-induced pulmonary fibrosis in vivo. In conclusion, this study revealed that LPS-induced macrophage secretion of TNF-α could initiate fibroblast aerobic glycolysis and lactate production, implying that inflammation-metabolism interactions between lung macrophages and fibroblasts might play an essential role in LPS-induced pulmonary fibrosis.

Single-cell analysis reveals urothelial cell heterogeneity and regenerative cues following cyclophosphamide-induced bladder injury.

Cyclophosphamide is a commonly used chemotherapeutic drug to treat cancer with side effects that trigger bladder injury and hemorrhagic cystitis. Although previous studies have demonstrated that certain cell subsets and communications are activated to drive the repair and regeneration of bladder, it is not well understood how distinct bladder cell subsets function synergistically in this process. Here, we used droplet-based single-cell RNA sequencing (scRNA-seq) to profile the cell types within the murine bladder mucous layer under normal and injured conditions. Our analysis showed that superficial cells are directly repaired by cycling intermediate cells. We further identified two resident mesenchymal lineages (Acta2+ myofibroblasts and Cd34+ fibroblasts). The delineation of cell-cell communications revealed that Acta2+ myofibroblasts upregulated Fgf7 expression during acute injury, which activated Fgfr signaling in progenitor cells within the basal/intermediate layers to promote urothelial cell growth and repair. Overall, our study contributes to a more comprehensive understanding of the cellular dynamics during cyclophosphamide-induced bladder injury and may help identify important niche factors contributing to the regeneration of injured bladders.