Yanfan Chen

Hypoxic pulmonary hypertension (HPH) is a life‐threatening disease that occurs due to a lack of oxygen in the lungs, leading to an increase in pulmonary vascular resistance, right ventricular failure, and ultimately death. HPH is a multifactorial disorder that involves multiple molecular pathways, making it a challenge for clinicians to identify effective therapies. Pulmonary artery smooth muscle cells (PASMCs) play a crucial role in HPH pathogenesis by proliferating, resisting apoptosis, and promoting vascular remodelling. Curcumin, a natural polyphenolic compound, has shown potential as a therapeutic agent for HPH by reducing pulmonary vascular resistance, inhibiting vascular remodelling, and promoting apoptosis of PASMCs. Regulation of PASMCs could significantly inhibits HPH. However, curcumin has the disadvantages of poor solubility and low bioavailability, and its derivative WZ35 has better biosafety. Here, Cu‐based metal organic frameworks (MOF _Cu ) was fabricated to encapsulate the curcumin analogue WZ35 (MOF _Cu @WZ35) for the inhibition of PASMCs proliferation. The authors found that the MOF _Cu @WZ35 could promote the death of PASMCs. Furthermore, the authors believed that this drug delivery system will effectively alleviate the HPH.

Background: The burden of chronic respiratory diseases has changed over the three decades. This study aims to describe the spatiotemporal trends of prevalence, mortality, and disability-adjusted life years (DALY) due to chronic respiratory diseases (CRDs) worldwide during 1990–2019 using data from the Global Burden of Disease Study 2019 (GBD 2019).Methods: The prevalence, mortality, and DALY attributable to CRDs and risk factors from 1990 to 2019 were estimated. We also assessed the driving factors and potentiality for improvement with decomposition and frontier analyses, respectively.Results: In 2019, 454.56 [95% uncertainty interval (UI): 417.35–499.14] million individuals worldwide had a CRD, showing a 39·8% increase compared with 1990. Deaths due to CRDs were 3.97 (95%UI: 3.58–4.30) million, and DALY in 2019 was 103.53 (95%UI: 94.79–112.27) million. Declines by average annual percent change (AAPC) were observed in age-standardized prevalence rates (ASPR) (0.64% decrease), age-standardized mortality rates (ASMR) (1.92%), and age-standardized DALY rates (ASDR) (1.72%) globally and in 5 socio-demographic index (SDI) regions. Decomposition analyses represented that the increase in overall CRDs DALY was driven by aging and population growth. However, chronic obstructive pulmonary disease (COPD) was the leading driver of increased DALY worldwide. Frontier analyses witnessed significant improvement opportunities at all levels of the development spectrum. Smoking remained a leading risk factor (RF) for mortality and DALY, although it showed a downward trend. Air pollution, a growing factor especially in relatively low SDI regions, deserves our attention.Conclusion: Our study clarified that CRDs remain the leading causes of prevalence, mortality, and DALY worldwide, with growth in absolute numbers but declines in several age-standardized estimators since 1990. The estimated contribution of risk factors to mortality and DALY demands the need for urgent measures to improve them.Systematic review registration: http://ghdx.healthdata.org/gbd-results-tool.

Introduction: Pulmonary embolism (PE) is a common thrombotic disease and potentially deadly cardiovascular disorder. The ratio of clinical misdiagnosis and missed diagnosis of PE is very large because patients with PE are asymptomatic or non-specific.Methods: Using the clinical data from the First Affiliated Hospital of Wenzhou Medical University (Wenzhou, China), we proposed a swarm intelligence algorithm-based kernel extreme learning machine model (SSACS-KELM) to recognize and discriminate the severity of the PE by patient’s basic information and serum biomarkers. First, an enhanced method (SSACS) is presented by combining the salp swarm algorithm (SSA) with the cuckoo search (CS). Then, the SSACS algorithm is introduced into the KELM classifier to propose the SSACS-KELM model to improve the accuracy and stability of the traditional classifier.Results: In the experiments, the benchmark optimization performance of SSACS is confirmed by comparing SSACS with five original classical methods and five high-performance improved algorithms through benchmark function experiments. Then, the overall adaptability and accuracy of the SSACS-KELM model are tested using eight public data sets. Further, to highlight the superiority of SSACS-KELM on PE datasets, this paper conducts comparison experiments with other classical classifiers, swarm intelligence algorithms, and feature selection approaches.Discussion: The experimental results show that high D-dimer concentration, hypoalbuminemia, and other indicators are important for the diagnosis of PE. The classification results showed that the accuracy of the prediction model was 99.33%. It is expected to be a new and accurate method to distinguish the severity of PE.

Introduction: Pulmonary embolism (PE) is a cardiopulmonary condition that can be fatal. PE can lead to sudden cardiovascular collapse and is potentially life-threatening, necessitating risk classification to modify therapy following the diagnosis of PE. We collected clinical characteristics, routine blood data, and arterial blood gas analysis data from all 139 patients.Methods: Combining these data, this paper proposes a PE risk stratified prediction framework based on machine learning technology. An improved algorithm is proposed by adding sobol sequence and black hole mechanism to the cuckoo search algorithm (CS), called SBCS. Based on the coupling of the enhanced algorithm and the kernel extreme learning machine (KELM), a prediction framework is also proposed.Results: To confirm the overall performance of SBCS, we run benchmark function experiments in this work. The results demonstrate that SBCS has great convergence accuracy and speed. Then, tests based on seven open data sets are carried out in this study to verify the performance of SBCS on the feature selection problem. To further demonstrate the usefulness and applicability of the SBCS-KELM framework, this paper conducts aided diagnosis experiments on PE data collected from the hospital.Discussion: The experiment findings show that the indicators chosen, such as syncope, systolic blood pressure (SBP), oxygen saturation (SaO2%), white blood cell (WBC), neutrophil percentage (NEUT%), and others, are crucial for the feature selection approach presented in this study to assess the severity of PE. The classification results reveal that the prediction model’s accuracy is 99.26% and its sensitivity is 98.57%. It is expected to become a new and accurate method to distinguish the severity of PE.

Background The burden of chronic respiratory diseases has changed over three decades.To describe the spatiotemporal trends of prevalence, mortality and disability adjusted life years (DALY) due to chronic respiratory diseases(CRDs), across the globe during 1990–2019 using data from the Global Burden of Disease Study 2019(GBD 2019). Methods The prevalence, mortality and DALY attributable to CRDs, and risk factors from 1990 to 2019 were estimated. We also assessed the driving factors and potentiality for improvement by decomposition analyses and frontier analyses. Results In 2019, 454.56 (95% uncertainty interval(UI): 417.35-499.14) million individuals worldwide had a CRD, showing a 39·8% increase compared with 1990. Deaths due to CRDs numbered 3.97(95% UI: 3.58–4.30) million, and DALY in 2019 was 103.53 (95% UI:94.79-112.27) million. Declines by average annual percent change(AAPC) were observed in age-standardized prevalence rates(ASPR) (0.64% decrease), age-standardized mortality rates(ASMR) (1.92%), and age-standardized DALY rates(ASDR) (1.72%) globally and in 5 socio-demographic index (SDI) regions. Decomposition analyses represented that the increase in overall CRDs DALY was driven by aging and population growth. Chronic obstructive pulmonary disease (COPD) was the leading drivers globally. Frontier analyses witnessed significant improvement opportunities at all levels of the development spectrum. Smoking remained a leading risk factor(RF) for the mortality and DALY, although, it showed a downward trend. Air pollution, a growing factor especially in relatively low SDI regions, deserves our attention. Conclusion Our study clarified that CRDs remain a leading cause of prevalence, mortality and DALY worldwide, with growth in absolute numbers but declines in several age-standardized estimators since 1990. The estimated contribution of risk factors to mortality and DALY supports the need for urgent measures to improve them.

Talaromyces marneffei (T. marneffei) is a thermal dimorphic pathogenic fungus that often causes fatal opportunistic infections in human immunodeficiency virus (HIV)-infected patients. Although T. marneffei-infected cases have been increasingly reported among non-HIV-infected patients in recent years, no cases of T. marneffei infection have been reported in pulmonary sarcoidosis patients. In this case, we describe a T. marneffei infection in an HIV-negative patient diagnosed with pulmonary sarcoidosis. A 41-year-old Chinese man who had pre-existing pulmonary sarcoidosis presented with daily hyperpyrexia and cough. Following a fungal culture from bronchoalveolar lavage (BAL), the patient was diagnosed with T. marneffei infection. A high-resolution computed tomography (HRCT) chest scan revealed bilateral lung diffuse miliary nodules, multiple patchy exudative shadows in the bilateral superior lobes and right inferior lobes, air bronchogram in the consolidation of the right superior lobe, multiple hilar and mediastinal lymphadenopathies and local pleural thickening. After 3 mos of antifungal therapy, the patient’s pulmonary symptoms rapidly disappeared, and the physical condition improved markedly. A subsequent CT re-examination demonstrated that foci were absorbed remarkably after treatment. The patient is receiving follow-up therapy and assessment for a cure. This case suggested that clinicians should pay more attention to non-HIV-related lung infections in patients with pulmonary sarcoidosis. Early diagnosis and treatment with antifungal therapy can improve the prognosis of T. marneffei infection.