Investigation of the mechanism of poly (ADP-ribose) polymerase (PARP) in elderly mouse myocardial ischemia-reperfusion injury.

This study investigated the role of Poly (ADP-ribose) Polymerase (PARP) in myocardial ischemia-reperfusion injury (MIRI) in elderly mice. It involves 30 elderly male KM mice divided into three groups: Sham, MIRI, and DPQ, where the MIRI and DPQ groups undergo myocardial ischemia-reperfusion with the DPQ group also receiving DPQ for PARP-1 inhibition. Over three weeks, assessments include histological analysis of myocardial lesions, left ventricular ejection fraction (LVEF) measurements, and evaluations of serum cardiac enzymes and inflammatory markers. This approach aims to understand the protective effects of DPQ in MIRI, focusing on its impact on cardiac health and inflammation via the JAK2/STAT3 pathway. The findings suggest that PARP activation exacerbates cardiac dysfunction and inflammation in MIRI by possibly modulating the JAK2/STAT3 signaling pathway. Inhibition of PARP-1 with DPQ mitigates these effects, as indicated by reduced myocardial lesions and inflammatory infiltration, improved LVEF, and altered levels of inflammatory markers and signaling molecules. However, the differences in STAT3 and p-STAT3 protein expression between the DPQ and MIRI groups were not statistically significant, suggesting that while PARP inhibition affects many aspects of MIRI pathology, its impact on the JAK2/STAT3 pathway may not fully explain the observed benefits. This study contributes to our understanding of the complex mechanisms underlying myocardial ischemia-reperfusion injury, particularly in the context of aging. It highlights the potential of PARP inhibition as a therapeutic strategy to attenuate cardiac dysfunction and inflammation in MIRI, though further research is necessary to fully elucidate the underlying molecular pathways and to explore the clinical relevance of these findings in humans.

HGF Facilitates the Repair of Spinal Cord Injuries by Driving the Chemotactic Migration of MSCs Through the ß-Catenin/TCF4/Nedd9 Signaling Pathway.

Transplanted mesenchymal stem cells (MSCs) can significantly aid in repairing spinal cord injuries (SCI) by migrating to and settling at the injury site. However, this process is typically inefficient, as only a small fraction of MSCs successfully reach the target lesion area. During SCI, the increased expression and secretion of hepatocyte growth factor (HGF) act as a chemoattractant that guides MSC migration. Nonetheless, the precise mechanisms by which HGF influences MSC migration are not fully understood. This study focused on unraveling the molecular pathways that drive MSC migration towards the SCI site in response to HGF. It was found that HGF can activate ß-catenin signaling in MSCs either by phosphorylating LRP6 or by suppressing GSK3ß phosphorylation through the AKT and ERK1/2 pathways, or by enhancing the expression and nuclear translocation of TCF4. This activation leads to elevated Nedd9 expression, which promotes focal adhesion formation and F-actin polymerization, facilitating chemotactic migration. Transplanting MSCs during peak HGF expression in injured tissues substantially improves nerve regeneration, reduces scarring, and enhances hind limb mobility. Additionally, prolonging HGF release can further boost MSC migration and engraftment, thereby amplifying regenerative outcomes. However, inhibiting HGF/Met or interfering with ß-catenin or Nedd9 signaling significantly impairs MSC engraftment, obstructing tissue repair and functional recovery. Together, these findings provide a theoretical basis and practical strategy for MSC transplantation therapy in SCI, highlighting the specific molecular mechanisms by which HGF regulates ß-catenin signaling in MSCs, ultimately triggering their chemotactic migration.

Exploring soil multi-parameter stacking measurement through Raman and NIR dual-spectroscopy.

The excessive use of fertilizers can lead to increased production costs, degraded soil quality, diminished product excellence, and environmental contamination. To address this issue, a solution involving soil testing and customizing fertilizer application has been proposed. The current standard methodology for soil parameter assessment relies on chemical analysis performed by trained laboratory technicians, which only allows for the measurement of one indicator at a time. Hence, a novel approach utilizing the fusion of near-infrared (NIR) and Raman dual-spectral features has been suggested to simultaneously determine five crucial indicators (hydrolyzed N, available P, quick-release K, OM, and pH) in soil with a single scan. In this research, seven preprocessing techniques and four feature extraction methods were initially explored to optimize the composite NIR and Raman feature variables. Subsequently, a regressor with a two-layer network structure (RF, LR, SVR; ELM, and PLS) was developed using the stacking algorithm. This methodology synergizes the strengths of the five base learners, minimizes the risk of overfitting, and demonstrates high computational efficiency for linear data correlations and robust fitting capabilities for nonlinear data correlations. Additionally, it showcases strong generalization capabilities, noise resilience, and robustness. The model produced relevant results for hydrolyzed N, available P, quick release K, OM, and pH measurements, with Rp2 values of 0.9966, 0.9722, 0.9855, 0.9557, and 0.9951, RMSEP values of 2.9547, 2.9972, 7.6550, 0.0765, and 0.0313, and RPD values of 6.0855, 2.4655, 3.0511, 8.3084, and 10.6977. This work delivers a twofold contribution by presenting a swift method for simultaneous measurement of multiple soil parameters, enabling concurrent ploughing, soil surveying, and fertilizer application. Furthermore, it introduces a stacking measurement model based on dual fusion features, showcasing detailed model parameters. The stacking model outperformed mono-spectral models (NIR and Raman) and the dual PLS model in terms of Rp2, RPD, and RMSEP values, and fluctuation ranges, demonstrating enhanced stability, predictive prowess, and reliable observations. Overall, the stacking model offers a cost-effective, rapid, and precise solution for online evaluation of soil physicochemical conditions, catering to the requirements of modern agricultural production well. This innovative approach signifies a significant leap forward and provides a solid theoretical foundation for the enhancement of associated online monitoring systems and tools.

Rosuvastatin inhibit ox-LDL-induced platelet activation by the p38/MAPK pathway.

OBJECTIVE: This study intends to explore the effects of Rosuvastatin on ox-LDL induced platelet activation and its molecular mechanism. METHODS: Platelet aggregation rate was detected by aggregometer. ELISA kit was used to detect the levels of cAMP. Immunofluorescence staining was used to detect the platelet adhesion. The expression levels of platelet surface markers CD62p and PAC-1 were detected by flow cytometry. The protein levels of p-p38, p-IKKa and p-IKKB in platelets were detected by western blot. RESULTS: We found that rosuvastatin significantly inhibited platelet aggregation and increased the level of cAMP in a dose-dependent manner. Immunofluorescence staining results showed that rosuvastatin could inhibit platelet adhesion. Flow cytometry results showed that rosuvastatin could reduce the expression of platelet activation markers. Western blot results showed that rosuvastatin could down-regulate the expression levels of p-p38, p-IKKa and p-IKKb. CONCLUSION: Our study revealed the rosuvastatin could inhibit the aggregation, adhesion and activation of platelet induced by ox-LDL, its mechanism may be related to inhibition of p38/MAPK signal pathway.

Reduction of circulating IgE and allergens by a pH-sensitive antibody with enhanced FcγRIIb binding.

Allergen-crosslinked IgE triggers allergy by interacting with its receptor on basophils and mast cells. The anti-IgE monoclonal antibody omalizumab can alleviate allergy by competing with the receptor for IgE binding. However, along with neutralization, omalizumab also inhibits IgE degradation, which is clinically associated with high dose and total IgE accumulation problems. In this study, we have developed an IgE-eliminating antibody on the basis of omalizumab, which has pH-dependent Fabs and an Fc with high affinity for FcγRIIb. In mice, the antibody rapidly eliminated total serum IgE to baseline levels and caused lower free IgE levels than omalizumab. At low dosages, the antibody also exhibited favorable IgE elimination effects. In addition, the antibody can degrade the corresponding allergen with the removal of IgE, addressing the allergy from its source. Introduction of the M252Y/S254T/T256E (YTE) mutation into this antibody prolongs its serum half-life without reducing potency. Thus, this engineered antibody holds a promising therapeutic option for allergy patients. Mechanistic insights are also included in this study.

In vitro co-culture models for studying organoids-macrophages interaction: the golden technology of cancer immunotherapy.

Macrophages, as the largest immune cell group in tumour tissues, play a crucial role in influencing various malignant behaviours of tumour cells and tumour immune evasion. As the research on macrophages and cancer immunotherapy develops, the importance of appropriate research models becomes increasingly evident. The development of organoids has bridged the gap between traditional two-dimensional (2D) cultures and animal experiments. Recent studies have demonstrated that organoids exhibit similar physiological characteristics to the source tissue and closely resemble the in vivo genome and molecular markers of the source tissue or organ. However, organoids still lack an immune component. Developing a co-culture model of organoids and macrophages is crucial for studying the interaction and mechanisms between tumour cells and macrophages. This paper presents an overview of the establishment of co-culture models, the current research status of organoid macrophage interactions, and the current status of immunotherapy. In addition, the application prospects and shortcomings of the model are explained. Ultimately, it is hoped that the co-culture model will offer a preclinical testing platform for maximising a precise cancer immunotherapy strategy.

Reduction in polycyclic aromatic hydrocarbon exposure in Beijing following China's clean air actions.

Exposure to polycyclic aromatic hydrocarbons (PAHs) in the Chinese population was among the highest globally and associated with various adverse effects. This study examines the impact of China's two-phase clean air initiatives, namely the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013-2017 and the Blue-Sky Defense War (BSDW) in 2018-2020, on PAH levels and human exposures in Beijing. To evaluate the effects of APPCAP, we measured 16 PAHs in 287 PM2.5 samples collected in Beijing and 9 PAH metabolites in 358 urine samples obtained from 54 individuals who traveled from Los Angeles to Beijing between 2014 and 2018. The concentration of PM2.5-bound benzo[a]pyrene equivalents (BaPeq) decreased by 88.5% in 2014-2018 due to reduced traffic, coal, and biomass emissions. PAH metabolite concentrations in travelers' urine decreased by 52.3% in Beijing, correlated with changes in PM2.5 and NO2 levels. In contrast, no significant changes were observed in Los Angeles. To evaluate BSDW's effects, we collected 123 additional PM2.5 samples for PAH measurements in 2019-2021. We observed sustained reductions in BaPeq concentrations attributable to reductions in coal and biomass emissions during the BSDW phase, but those from traffic sources remained unchanged. After accounting for meteorological factors, China's two-phase clean air initiatives jointly reduced Beijing's PM2.5-bound BaPeq concentrations by 96.6% from 2014 to 2021. These findings provide compelling evidence for the effectiveness of China's clean air actions in mitigating population exposure to PAHs in Beijing.

Identification and quantitative detection of illegal additives in wheat flour based on near-infrared spectroscopy combined with chemometrics.

As a common food raw material in daily life, the quality and safety of wheat flour are directly related to people's health. In this study, a model was developed for the rapid identification and detection of three illegal additives in flour, namely azodicarbonamide (ADA), talcum powder, and gypsum powder. This model utilized a combination of near-infrared spectroscopy with chemometric methods. A one-dimensional convolutional neural network was used to reduce data dimensionality, while a support vector machine was applied for non-linear classification to identify illegal additives in flour. The model achieved a calibration set F1 score of 99.38% and accuracy of 99.63%, with a validation set F1 score of 98.81% and accuracy of 98.89%. Two cascaded wavelength selection methods were introduced: The first method involved backward interval partial least squares (BiPLS) combined with an improved binary particle swarm optimization algorithm (IBPSO). The second method utilized the CARS-IBPSO algorithm, which integrated competitive adaptive reweighted sampling (CARS) with IBPSO. The two cascade wavelength selection methods were used to select feature wavelengths associated with additives and construct partial least squares quantitative detection models. The models constructed using CARS-IBPSO selected feature wavelengths for detecting ADA, talcum powder, and gypsum powder exhibited the highest overall performance. The model achieved validation set determination coefficients of 0.9786, 0.9102, and 0.9226, with corresponding to root mean square errors of 0.0024%, 1.3693%, and 1.6506% and residual predictive deviations of 6.8368, 3.5852, and 3.9253, respectively. Near-infrared spectroscopy in combination with convolutional neural network dimensionality reduction and support vector machine classification enabled rapid identification of various illegal additives. The combination of CARS-IBPSO feature wavelength selection and partial least squares regression models facilitated rapid quantitative detection of these additives. This study introduces a new approach for rapidly and accurately identifying and detecting illegal additives in flour.

Identification of Noncoding Functional Regulatory Variants of STIM1 Gene in Idiopathic Pulmonary Arterial Hypertension.

BACKGROUND: STIM1 (stromal interaction molecule 1) regulates store-operated calcium entry and is involved in pulmonary artery vasoconstriction and pulmonary artery smooth muscle cell proliferation, leading to pulmonary arterial hypertension (PAH). METHODS: Bioinformatics analysis and a 2-stage matched case-control study were conducted to screen for noncoding variants that may potentially affect STIM1 transcriptional regulation in 242 patients with idiopathic PAH and 414 healthy controls. Luciferase reporter assay, real-time quantitative polymerase chain reaction, western blot, 5-ethynyl-2'-deoxyuridine (EdU) assay, and intracellular Ca2+ measurement were performed to study the mechanistic roles of those STIM1 noncoding variants in PAH. RESULTS: Five noncoding variants (rs3794050, rs7934581, rs3750996, rs1561876, and rs3750994) were identified and genotyped using Sanger sequencing. Rs3794050, rs7934581, and rs1561876 were associated with idiopathic PAH (recessive model, all P<0.05). Bioinformatics analysis showed that these 3 noncoding variants possibly affect the enhancer function of STIM1 or the microRNA (miRNA) binding to STIM1. Functional validation performed in HEK293 and pulmonary artery smooth muscle cells demonstrated that the noncoding variant rs1561876-G (STIM1 mutant) had significantly stronger transcriptional activity than the wild-type counterpart, rs1561876-A, by affecting the transcriptional regulatory function of both hsa-miRNA-3140-5p and hsa-miRNA-4766-5p. rs1561876-G enhanced intracellular Ca2+ signaling in human pulmonary artery smooth muscle cells secondary to calcium-sensing receptor activation and promoted proliferation of pulmonary artery smooth muscle cells under both normoxia and hypoxia conditions, suggesting a possible contribution to PAH development. CONCLUSIONS: The potential clinical implications of the 3 noncoding variants of STIM1, rs3794050, rs7934581, and rs1561876, are 2-fold, as they may help predict the risk and prognosis of idiopathic PAH and guide investigations on novel therapeutic pathway(s).

Near-infrared spectral expansion method based on active semi-supervised regression.

BACKGROUND: The utilization of near-infrared (NIR) spectroscopy, in conjunction with chemometric techniques, has been widely used in a variety of sectors, including agricultural production and pharmaceutical production. Nevertheless, the laborious and arduous procedure of gathering samples and evaluating their physicochemical properties leads to relatively limited training set sizes for modeling. This problem severely limits the optimization and practical application of NIR spectrum analysis models. The Safer Active Semi-Supervised Sample Augmentation Learning Model (Safer-AS3A) proposed in this paper tries to address the problem by incorporating active learning (AL) and semi-supervised learning (SSL) techniques. RESULTS: Experiments were conducted on two sets of publicly available NIR spectral datasets, and the Safer-AS3A model was compared to other models with similar characteristics. The experimental results indicate that the Safer-AS3A model proposed in our study outperforms comparable models in terms of accuracy and robustness when dealing with scenarios having a limited number of labeled samples. Furthermore, after the training set was expanded with the Safer-AS3A model, the Partial least squares regression (PLSR), Bayesian ridge regression (BRR), and Support vector regression (SVR) models on the Diesel dataset improved their R2 on the test set by 5.923 %, 3.018 %, and 7.331 %, respectively, compared to the models using only the labeled sample set. On the other hand, the Ridge regression (RR), BRR, and SVR models on the test set on the Shoot dataset improved the R2 by 4.169 %, 4.449 %, and 11.597 %, respectively. Overall, the Safer-AS3A model can effectively expand the NIR spectral dataset and considerably improve the performance of the NIR spectral analysis model. SIGNIFICANCE AND NOVELTY: Using the AL method, the SSL method, and the co-training method together, a novel and effective method is presented for generating high-quality pseudo-labels. This method opens up new avenues for enhancing the efficiency and precision of NIR spectrum analysis. It also provides novel perspectives on sample diversification and prospective applications in other disciplines.

Upconverting Ultra-Thin Bi2O2CO3 Nanosheets for Synergistic Photodynamic Therapy and Radiotherapy.

Synergistic therapy has become the major therapeutic method for malignant tumors in clinical. Photodynamic therapy (PDT) and radiotherapy (RT) always combine together because of their identical anti-tumor mechanisms, that is reactive oxygen species are generated by the use of radiosensitizers after irradiation by X-ray to efficiently kill cancer cells, PDT also follows similar mechanism. Full exposure of energy-absorbing species in nanomaterials to X-ray or near-infrared light irradiation makes the energy interchange between nanomaterials and surrounding H2O or dissolved oxygen easier, however, it remains challenging. Herein, an ultrathin two-dimensional (2D) nanosheet (NS) is developed, Bi2O2CO3, doped with lanthanide ions to give out upconversion luminescence, where the high Z elements Bi, Yb, and Er promote the radio-sensitizing effect. To the surprise, lanthanide activator ions gave out completely different luminescence properties compared with traditional upconversion nanoparticles. Less dopant of Er ions in nanosheets lattice resulted in brighter red emission, which provides more efficient PDT. Under RT/PDT combined treatment, NS shows a good tumor growth-inhibiting effect. In addition, synergistic therapy requires lower radiation dose than conventional radiotherapy and lower light power than single photodynamic therapy, thus greatly reducing radiation damage caused by RT and thermal damage caused by PDT.

A cryptic homotypic interaction motif of insect STING is required for its antiviral signaling.

Stimulator of interferon genes (STING) mediates innate immune response upon binding to cyclic GMP-AMP (cGAMP). It recruits tank-binding kinase 1 (TBK1) and transcription factor interferon regulatory factor 3 (IRF3) through its C-terminal tail and facilitates TBK1-dependent phosphorylation of IRF3 via forming STING polymers in mammalian cells. However, the mechanism behind STING-mediated activation of NF-κB transcription factor, Relish, in insect cells is unknown. Our study revealed that insect STING formed oligomers and the cryptic RIP homotypic interaction motif (cRHIM) was required for its oligomerization and its anti-viral functions. Cells expressing cRHIM-deficient mutants exhibited lower levels of anti-viral molecules, higher viral load after viral infection and weak activation of Relish. Moreover, we observed that under cGAMP stimulation, insect STING interacted with IMD, and deletion of the cRHIM motif on either protein prevented this interaction. Finally, we demonstrated that cGAMP enhanced the amyloid-like property of insect STING aggregates by ThT staining. In summary, our research showed that insect STING employed a homotypic motif to form intermolecular interactions that are essential for its antiviral signaling.

miR-9-5p and miR-221-3p Promote Human Mesenchymal Stem Cells to Alleviate Carbon Tetrachloride-Induced Liver Injury by Enhancing Human Mesenchymal Stem Cell Engraftment and Inhibiting Hepatic Stellate Cell Activation.

Mesenchymal stem cells (MSCs) have shown great potential for the treatment of liver injuries, and the therapeutic efficacy greatly depends on their homing to the site of injury. In the present study, we detected significant upregulation of hepatocyte growth factor (HGF) in the serum and liver in mice with acute or chronic liver injury. In vitro study revealed that upregulation of miR-9-5p or miR-221-3p promoted the migration of human MSCs (hMSCs) toward HGF. Moreover, overexpression of miR-9-5p or miR-221-3p promoted hMSC homing to the injured liver and resulted in significantly higher engraftment upon peripheral infusion. hMSCs reduced hepatic necrosis and inflammatory infiltration but showed little effect on extracellular matrix (ECM) deposition. By contrast, hMSCs overexpressing miR-9-5p or miR-221-3p resulted in not only less centrilobular necrosis and venous congestion but also a significant reduction of ECM deposition, leading to obvious improvement of hepatocyte morphology and alleviation of fibrosis around central vein and portal triads. Further studies showed that hMSCs inhibited the activation of hepatic stellate cells (HSCs) but could not decrease the expression of TIMP-1 upon acute injury and the expression of MCP-1 and TIMP-1 upon chronic injury, while hMSCs overexpressing miR-9-5p or miR-221-3p led to further inactivation of HSCs and downregulation of all three fibrogenic and proinflammatory factors TGF-ß, MCP-1, and TIMP-1 upon both acute and chronic injuries. Overexpression of miR-9-5p or miR-221-3p significantly downregulated the expression of α-SMA and Col-1α1 in activated human hepatic stellate cell line LX-2, suggesting that miR-9-5p and miR-221-3p may partially contribute to the alleviation of liver injury by preventing HSC activation and collagen expression, shedding light on improving the therapeutic efficacy of hMSCs via microRNA modification.

Quantum gate control of polar molecules with machine learning.

We propose a scheme for achieving basic quantum gates using ultracold polar molecules in pendular states. The qubits are encoded in the YbF molecules trapped in an electric field with a certain gradient and coupled by the dipole-dipole interaction. The time-dependent control sequences consisting of multiple pulses are considered to interact with the pendular qubits. To achieve high-fidelity quantum gates, we map the control problem for the coupled molecular system into a Markov decision process and deal with it using the techniques of deep reinforcement learning (DRL). By training the agents over multiple episodes, the optimal control pulse sequences for the two-qubit gates of NOT, controlled NOT, and Hadamard are discovered with high fidelities. Moreover, the population dynamics of YbF molecules driven by the discovered gate sequences are analyzed in detail. Furthermore, by combining the optimal gate sequences, we successfully simulate the quantum circuit for entanglement. Our findings could offer new insights into efficiently controlling molecular systems for practical molecule-based quantum computing using DRL.

Alteration of the health effects of bioaerosols by chemical modification in the atmosphere: A review.

Bioaerosols are a subset of important airborne particulates that present a substantial human health hazard due to their allergenicity and infectivity. Chemical reactions in atmospheric processes can significantly influence the health hazard presented by bioaerosols; however, few studies have summarized such alterations to bioaerosols and the mechanisms involved. In this paper, we systematically review the chemical modifications of bioaerosols and the impact on their health effects, mainly focusing on the exacerbation of allergic diseases such as asthma, rhinitis, and bronchitis. Oxidation, nitration, and oligomerization induced by hydroxyl radicals, ozone, and nitrogen dioxide are the major chemical modifications affecting bioaerosols, all of which can aggravate allergenicity mainly through immunoglobulin E pathways. Such processes can even interact with climate change including the greenhouse effect, suggesting the importance of bioaerosols in the future implementation of carbon neutralization strategies. In summary, the chemical modification of bioaerosols and the subsequent impact on health hazards indicate that the combined management of both chemical and biological components is required to mitigate the health hazards of particulate air pollution.

Evaluating the clinical utility of small airway function assessment for early diagnosis of GOLD stage 0 chronic obstructive pulmonary disease.

OBJECTIVE: To investigate the clinical utility of small airway function indices for early identification of GOLD stage 0 chronic obstructive pulmonary disease (COPD). METHODS: This retrospective study enrolled 137 participants at our institution between January 2017 and December 2018, comprising 40 healthy controls, 46 individuals with GOLD stage 0 COPD, and 51 patients with established COPD. Pulmonary function was assessed using the PowerCube spirometry system (GANSHORN, Germany). Parameters evaluated included forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), FEV1/FVC ratio, and small airway function indicators. RESULTS: The COPD cohort exhibited significantly lower values across all lung function measures compared to the other two groups, particularly for dynamic lung volume parameters such as FEV1%predicted and FEV1/FVC%. Small airway function indices, including FEV3%predicted, FEF75%predicted, FEF50%predicted, FEF25%predicted, and MMEF%predicted, were markedly decreased in the COPD group (all p-values <0.001). Receiver operating characteristic (ROC) curve analysis demonstrated that MMEF/FVC% and FEV3/FVC% had high diagnostic accuracy for COPD, with MMEF/FVC% exhibiting the optimal sensitivity and specificity. CONCLUSION: Small airway function indices, especially MMEF/FVC%, can serve as effective tools for early identification of GOLD stage 0 COPD. Incorporation of these findings into clinical practice may facilitate early diagnosis and intervention, thereby improving treatment outcomes and patient quality of life.

Pulmonary vascular resistance predicts the mortality in patients with bronchiectasis-associated pulmonary hypertension.

OBJECTIVE: Pulmonary hypertension is a severe complication of bronchiectasis, characterized by elevated pulmonary vascular resistance (PVR) and subsequent right heart failure. The association between PVR and mortality in bronchiectasis-associated pulmonary hypertension has not been investigated previously. METHODS: In the present study, a retrospective analysis was conducted on 139 consecutive patients diagnosed with bronchiectasis-associated pulmonary hypertension based on right heart catheterization, enrolled between January 2010 and June 2023. Baseline clinical characteristics and hemodynamic assessment were analyzed. The survival time for each patient was calculated in months from the date of diagnosis until the date of death or, if the patient was still alive, until their last visit. RESULTS: Patients with bronchiectasis-associated pulmonary hypertension exhibited estimated survival rates of 89.5, 70, and 52.9 at 1-year, 3-year, and 5-year intervals respectively, with a median survival time of 67 months. Multivariable Cox regression analysis revealed that increased age [(adjusted hazard ratio per year 1.042, 95% confidence interval (CI) 1.008-1.076, P  = 0.015] and elevated PVR (adjusted HR per 1 Wood Units 1.115, 95% CI 1.015-1.224, P  = 0.023) were associated with an increased risk of all-cause mortality. In contrast, higher BMI was associated with a decreased risk of all-cause death (adjusted hazard ratio per 1 kg/m 2 0.915, 95% CI 0.856-0.979, P  = 0.009). Receiver-operating characteristic analyses identified a cutoff value for PVR at 4 Wood Units as predictive for all-cause death within 3 years [area under the curve (AUC) = 0.624; specificity= 87.5%; sensitivity= 35.8%; P  < 0.05]. Patients with a PVR greater than 4 Wood Units had a significantly higher risk of all-cause death compared with those with 4 Wood Units or less (adjusted hazard ratio 2.392; 95% CI 1.316-4.349; P  = 0.019). Notably, there were no significant differences in age, sex, BMI, WHO functional class, 6-min walk distance, and NT-proBNP levels at baseline between patients categorized as having 4 Wood Units or less or greater than 4 Wood Units for PVR. CONCLUSION: Based on these data, PVR could serve as a discriminative marker for distinguishing between nonsevere pulmonary hypertension (PVR ≤ 4 Wood Units) and severe pulmonary hypertension (PVR > 4 Wood Units). The utilization of a PVR cutoff value of 4.0 Wood Units provides enhanced prognostic capabilities for predicting mortality.

Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension.

BACKGROUND: Patients with pulmonary hypertension (PH) and chronic obstructive pulmonary disease (COPD) have an increased risk of disease exacerbation and decreased survival. We aimed to develop and validate a non-invasive nomogram for predicting COPD associated with severe PH and a prognostic nomogram for patients with COPD and concurrent PH (COPD-PH). METHODS: This study included 535 patients with COPD-PH from six hospitals. A multivariate logistic regression analysis was used to analyse the risk factors for severe PH in patients with COPD and a multivariate Cox regression was used for the prognostic factors of COPD-PH. Performance was assessed using calibration, the area under the receiver operating characteristic curve and decision analysis curves. Kaplan-Meier curves were used for a survival analysis. The nomograms were developed as online network software. RESULTS: Tricuspid regurgitation velocity, right ventricular diameter, N-terminal pro-brain natriuretic peptide (NT-proBNP), the red blood cell count, New York Heart Association functional class and sex were non-invasive independent variables of severe PH in patients with COPD. These variables were used to construct a risk assessment nomogram with good discrimination. NT-proBNP, mean pulmonary arterial pressure, partial pressure of arterial oxygen, the platelet count and albumin were independent prognostic factors for COPD-PH and were used to create a predictive nomogram of overall survival rates. CONCLUSIONS: The proposed nomograms based on a large sample size of patients with COPD-PH could be used as non-invasive clinical tools to enhance the risk assessment of severe PH in patients with COPD and for the prognosis of COPD-PH. Additionally, the online network has the potential to provide artificial intelligence-assisted diagnosis and treatment. HIGHLIGHTS: A multicentre study with a large sample of chronic obstructive pulmonary disease (COPD) patients diagnosed with PH through right heart catheterisation. A non-invasive online clinical tool for assessing severe pulmonary hypertension (PH) in COPD. The first risk assessment tool was established for Chinese patients with COPD-PH.