Microplastics (MPs) have received a lot of attention and have been detected in multiple environmental matrices as a new environmental hazard, but studies on human internal exposure to MPs are limited. Here, we collected lung tissue samples from 12 nonsmoking patients to evaluate the characteristics of MPs in human lung tissues using an Agilent 8700 laser infrared imaging spectrometer and scanning electron microscopy. We detected 108 MPs covering 12 types in the lung tissue samples, with a median concentration of 2.19 particles/g. Most of the MPs (88.89%) were sized between 20 to 100 μm. Polypropylene accounts for 34.26% of the MPs in the lung tissues, followed by polyethylene terephthalate (21.30%) and polystyrene (8.33%). Compared with males and those living far from a major road (≥300 m), females and those living near the main road (<300 m) had higher levels of MPs in lung tissues, which positively correlated with platelet (PLT), thrombocytocrit, fibrinogen (FIB), and negatively related with direct bilirubin (DB). These findings help confirm the presence in the respiratory system and suggest the potential sources and health effects of inhaled MPs.

Tropheryma whipplei is the bacterium associated with Whipple’s disease (WD), a chronic systemic infectious disease primarily involving the gastrointestinal tract. T. whipplei can also be detected in different body site of healthy individuals, including saliva and feces. Traditionally, Tropheryma whipplei has a higher prevalence in bronchoalveolar lavage fluid (BALF) of immunocompromised individuals. Few studies have explored the significance of the detection of T. whipplei in BALF. Herein, we retrospectively reviewed 1725 BALF samples which detected for metagenomic next-generation sequencing (mNGS) from March 2019 to April 2022 in Zhuhai, China. Seventy BALs (70/1725, 4.0%) from 70 patients were positive for T. whipplei. Forty-four patients were male with an average age of 50 years. The main symptoms included cough (23/70), expectoration (13/70), weight loss (9/70), and/or dyspnea (8/70), but gastrointestinal symptoms were rare. Chronic liver diseases were the most common comorbidity (n=15, 21.4%), followed by diabetes mellitus (n=13, 18.6%). Only nine patients (12.9%) were immunocompromised. Twenty-four patients (34.3%) were finally diagnosed with reactivation tuberculosis and 15 patients (21.4%) were diagnosed with lung tumors, including 13 primary lung adenocarcinoma and two lung metastases. Fifteen patients (21.4%) had pneumonia. Among the 20 samples, T. whipplei was the sole agent, and Mycobacterium tuberculosis complex was the most common detected other pathogens. Among the non-tuberculosis patients, 31 (31/46, 67.4%) had ground glass nodules or solid nodules on chest CT. Our study indicates that T. whipplei should be considered as a potential contributing factor in some lung diseases. For non-immunocompromised patients, the detection of T. whipplei also needs attention. The mNGS technology improves the detection and attention of rare pathogens. In the future, the infection, colonization, and prognosis of T. whipplei in lung still need to be studied.

Background: COVID-19 is a new and highly contagious respiratory disease that has caused global spread, high case fatality rate in severe patients, and a huge medical burden due to invasive mechanical ventilation. The current diagnosis and treatment guidelines are still need to be improved, and more excellent clinical experience is needed to provide reference. Methods: We analyzed and summarized clinical data of 97 confirmed COVID-19 adult patients (including 26 severe cases) admitted to the Fifth Affiliated Hospital of Sun Yat-sen University from January 17, 2020 to March 10, 2020, included laboratory examination results, imaging findings, treatment effect, prognosis, etc, in order to put forward prediction index of severe COVID-19 patients, principles of early intervention and methylprednisolone usages in COVID-19 patients. Results: Hypoxemia, hyperlactic acid, hypoproteinemia, and hypokalemia were prevalent in COVID-19 patients. The significant low lymphocyte count, hypoproteinemia, hypokalemia, the persistent or worsen high CRP, high D-dimer, and high BNP, and the occurrence of hemoptysis and novel coronavirus (SARS-CoV-2) viremia were important indicators for early diagnosis and prediction of severe disease progression. Characteristic images of lung CT had a clear change in COVID-19, Ground-glass opacity (GGO) and high-density linear combinations may indicate different pathological changes. Rapid lobular progression of GGO suggests the possibility of severe disease. Basic principles of early intervention treatment of COVID-19: on the premise of no effective antiviral drugs, treatment is based on supportive and symptomatic therapy (albumin supplementation, supplement of potassium, supplement blood plasma, etc.) in order to maintain the stability of the intracellular environment and adequately reactivate body immunity to clean up SARS-CoV-2. According to severity, oxygenation index, body weight, age, underlying diseases, appropriate amount methylprednisolone application on severe/critical COVID-19 patients on demand, improved blood oxygen and reduced the utilization rate of invasive mechanical ventilation, case fatality rate and medical burden significantly. The most common indications for invasive mechanical ventilation should be strictly control in critical COVID-19 patients. Conclusions: Accurate and timely identification of clinical features in severe risks, and early and appropriate intervention can block disease progression. 2. Appropriate dose of methylprednisolone can effectively avoid invasive mechanical ventilation and reduce case fatality rate in critical COVID-19 patients.

Objective: As an opportunistic pathogen, Nocardia often occurring in the immunocompromised hosts. As the unspecifc clinical presentation and low identification rate of the culture dependent methods, Nocardia infection may be under-diagnosis. Recent study have reported physicians could benefit from metagenomic next-generation sequencing (mNGS) in Nocardia diagnosis. Herein, we present patients with a positive detection of nocardiosis in mNGS, aiming to provide useful information for an differential diagnosis and patients management. Methods: A total of 3756 samples detected for mNGS from March 2019 to April 2022 at the Fifth Affifiliated Hospital of Sun Yat-sen University, were screened. Clinical records, laboratory finding, CT images and mNGS results were reviewed for 19 patients who were positive for Nocardia genus. Results: Samples from low respiratory tract obtained by bronchoscope took the major part of the positive (15/19). 12 of 19 cases were diagnosis as Nocardiosis Disease (ND) and over half of the ND individuals (7/12) were geriatric. Nearly all of them (10/12) were immunocompetent and 2 patients in ND group were impressively asymptomatic. Cough was the most common symptom. Nocardia cyriacigeorgica (4/12) was more frequently occurring in ND, followed by Nocardia abscessus (3/12). There are 3 individuals detected more than one kind of Nocardia species (Supplementary table 1). Except one with renal failure and one allergic to sulfamethoxazole, all of them received co-sulfonamide treatment and relieved eventually. Conclusion: Our study deciphered the clinical features of patients with positive nocardiosis detected by mNGS. Greater attention should be paid to the ND that occurred in the immunocompetent host and the geriatric. Due to the difficulties in establishing diagnosis of Nocardiosis disease, mNGS should play a much more essential role for a better assessment in those intractable cases. Co-sulfonamide treatment should still be the first choice of Nocardiosis disease.

Background: Few studies have explored the correlation between asthma medication and features on HRCT images. We aim to analyse the differences and temporal changes of lung function and airway resistance in asthma with diverse HRCT phenotypes in a short period after inhalation of budesonide/formoterol. Method: This observational study recruited 55 adult patients with varying severities of asthma. We performed detailed airway metrics measurements of chest CT scans, such as airway wall thickness (WT), wall area percentage (WA%), wall thickness percentage (T/OR), and airways with an inner perimeter of 10 mm (Pi10). The effect of lung structural features on asthma medication response was explored according to the WA% and T/OR twelve hours post-drug administration. Using multivariable regression models, we then assessed the influence of WA% on lung function. Results: WA% (p < 0.001) and T/OR (p < 0.001) significantly increased in asthma than in healthy control subjects. Compared to mild asthma, airway walls were further thickened (WA%, p = 0.023; T/OR: p = 0.029) and associated with lumen narrowing (Pi10, p = 0.055) in moderate to severe asthma. WA% and T/OR correlated well with lung function (FEV1, FVC, MMEF, and PEF) and airway resistance (R5, R20, Rp, and Fres). Regression analysis showed that MEF25 decreased with increasing age and WA% (R² = 0.58, p < 0.001). Patients with thickened airway walls experienced a maximal increase in FVC, FEV1, and PEF at 2 h (p < 0.001) and a maximal decrease of R5, Z5, and Rp at 2 h (p < 0.001) in those with a thickened airway pattern. Conclusions: Asthma patients with different bronchial wall thicknesses exhibited variable lung function changes. Specifically, patients with thick airway wall patterns were more sensitive to inhaled budesonide in the short term.

Background: Coronavirus disease 2019 (COVID-19) is a worldwide public health pandemic with a high mortality rate, among severe cases. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. It is important to ensure early detection of the virus to curb disease progression to severe COVID-19. This study aims to establish a clinical-nomogram model to predict the progression to severe COVID-19 in a timely and efficient manner. Methods: This retrospective study included 202 patients with COVID-19 who were admitted to the Fifth Affiliated Hospital of Sun Yat-sen University and Shiyan Taihe Hospital from January 17 to April 30, 2020. The patients were randomly assigned to the training dataset (n = 163, with 43 progressing to severe COVID-19) or the validation dataset (n = 39, with 10 progressing to severe COVID-19) at a ratio of 8:2. The optimal subset algorithm was applied to filter for the clinical factors most relevant to the disease progression. Based on these factors, the logistic regression model was fit to distinguish severe (including severe and critical cases) from non-severe (including mild and moderate cases) COVID-19. Sensitivity, specificity, and area under the curve (AUC) were calculated using the R software package to evaluate prediction performance. A clinical nomogram was established and performance assessed using the discrimination curve. Results: Risk factors, including demographic data, symptoms, laboratory and image findings, were recorded for the 202 patients. Eight of the 53 variables that were entered into the selection process were selected via the best subset algorithm to establish the predictive model; they included gender, age, BMI, CRP, D-dimer, TP, ALB, and involved-lobe. AUC, sensitivity, and specificity were 0.91, 0.84 and 0.86 for the training dataset, and 0.87, 0.66, and 0.80 for the validation dataset. Conclusion: We established an efficient and reliable clinical nomogram model which showed that gender, age, and initial indexes including BMI, CRP, D-dimer, involved-lobe, TP, and ALB could predict the risk of progression to severe COVID-19.