Purpose: More and more patients with community-acquired pneumonia have been detected with Chlamydia psittaci (C. psittaci) infected using metagenomic next-generation sequencing (mNGS). Previously, this was unheard of, and several patients presented with severe pneumonia and even required ECMO. We aimed to clarify the clinical characteristics of C. psittaci pneumonia and find out if there are any possible predictors of severe C. psittaci pneumonia.Methods: In this retrospective study, we included all confirmed cases of C. psittaci pneumonia in Wuxi. Epidemiological, clinical, and radiological features, as well as laboratory data, were collected and analyzed.Results: We enrolled 55 patients with C. psittaci pneumonia, with 30 (54.5%) having a history of exposure to birds or their internal organs. 50 (90.9%) patients were diagnosed by mNGS. Patients with C. psittaci pneumonia had many complications, among which, that deserve sufficient attention from clinicians were vascular embolic events (3, 5.5%). High fever was the most common clinical manifestation (41, 74.5%). The majority of patients had a significant increase in neutrophils ratio, neutrophils to lymphocytes ratio (NLR), rapid c-reactive protein, creatine kinase (CK), and lactate dehydrogenase (LDH), as well as a decrease in lymphocytes ratio, albumin, serum sodium, serum potassium, and serum phosphorus. Chest computed tomography scans revealed unilateral pneumonia (70.9%), consolidation (87.3%), air bronchogram (76.4%), and ground-glass opacity (69.1%). The neutrophil ratio, NLR, LDH, and CK were all factors that could identify severe pneumonia. Both AUCs exceeded 0.8; the respective 95% CIs were 0.715–0.944, 0.710–0.963, 0.677–0.937, and 0.718–0.950; all p < 0.05 (0.01, 0.001, 0.007, 0.007 respectively). The ORs were 10.057, 9.750, 10.057, and 9.667, respectively; the 95% CIs were 2.643–38.276, 2.339–40.649, and 2.643–38.276, respectively; all p-values were less than 0.05 (0.001, 0.002, 0.001, 0.001 respectively).Conclusion: C. psittaci pneumonia is a very complex disease that changes all the time. Some patients showed severe pneumonia. Patients will have a poor prognosis if they are not treated promptly and effectively. We discovered that many clinical indicators were typical. Meanwhile, significant increases in neutrophil ratio, NLR, LDH, and CK predicted severe pneumonia. Timely detection of mNGS provided substantial help for clinical diagnosis and early treatment.

Acute lung injury (ALI) is a life-threatening condition characterized by excessive pulmonary inflammation, yet its precise pathophysiology remains elusive. Pyroptosis, a programmed cell death mechanism controlled by gasdermin D (GSDMD), has been linked to the etiology of ALI. This study investigated the regulatory functions of the transcription factor E-twenty-six variant gene 5 (ETV5) and GSDMD in ALI. Lipopolysaccharide (LPS) was used to treat BEAS-2B cells (50 mmol/mL) and establish an LPS-induced mouse model of ALI (by intratracheal administration, 3 mg/kg). Protein-protein docking, immunofluorescence analysis, western blotting, real-time quantitative polymerase chain reaction, and dual-luciferase reporter gene assay were used to examine ETV5-mediated negative feedback regulation of GSDMD and its effects on pyroptosis and ALI. Our results showed that the physiological function of ETV5 was reduced by its downregulated expression, which impeded its nuclear translocation in ALI mice. Increased pyroptosis and enhanced production of inflammatory cytokines were associated with LPS-induced ALI. ETV5 overexpression in LPS-treated BEAS-2B cells decreased the expression of total and membrane-bound GSDMD, negatively regulated GSDMD, and prevented pyroptosis. The expression of inflammatory cytokines was subsequently reduced due to this inhibition, which, in turn, reduced ALI. Molecular docking analysis and dual-luciferase reporter gene assay results indicated a direct interaction between ETV5 and GSDMD, which inhibited GSDMD production. Our results indicate that ETV5 inhibits pyroptosis, decreases the expression of inflammatory cytokines, and negatively regulates GSDMD expression to ameliorate ALI symptoms.

Acute lung injury (ALI) is a common complication after hemorrhagic shock (HS), which is associated with HS-induced inflammatory response, oxidative stress, and cell apoptosis. This study aimed to investigate the therapeutic efficacy of 8-Gingerol, a constituent extracted from ginger, on ALI after HS in rats. We established a fixed press hemorrhage model in SD rats, in which the HS rats were administered 15 or 30 mg/kg of 8-Gingerol by intraperitoneal injection before fluid resuscitation. H&E staining and TUNEL staining were performed to evaluate histopathological changes and cell apoptosis in lung tissues, respectively. Quantitative reverse transcription PCR and Western blot were used to measure gene and protein expression. Pro-inflammatory cytokines were detected by ELISA kits. Immunofluorescence of myeloperoxidase was used to evaluate neutrophil infiltration. 8-Gingerol reduced pulmonary edema, alveolar wall thickness, and cell apoptosis in lung tissues of HS rats. Regarding inflammatory responses, 8-Gingerol attenuated neutrophil infiltration in lung tissues, reduced pro-inflammatory cytokines in lung tissues and bronchoalveolar lavage fluid, and decreased the levels of NLRP3, ASC, and cleaved caspase 1 in lung tissues. Additionally, 8-Gingerol ameliorated oxidative stress in lung tissues as evidenced by increased antioxidant indicators (SOD and GSH) and decreased production of MDA and ROS. The therapeutic effects of 8-Gingerol were associated with the regulation of MAPK and Nrf2/HO-1 pathways. These results support 8-Gingerol as a promising drug for the treatment of HS-induced ALI.

Background: Metagenomic next-generation sequencing (mNGS) is a promising tool for pathogen detection. However, its clinical utility in detecting opportunistic pulmonary infections of immunocompromised patients remains controversial. Methods: This multicenter retrospective study involving 162 immunocompromised patients with opportunistic pulmonary infections was conducted across four respiratory centers. The enrolled patients were divided into the conventional microbiological tests (CMT) group and the mNGS group based on whether mNGS of BALF was performed after admission. Propensity score-matching (PSM) was adopted to minimize selection bias, and sensitivity analysis confirmed the robustness. The primary outcomes were >30% improvement in oxygenation index (OI) at 7 days post-admission and clinical improvement by day 14 as assessed with the WHO 7-category ordinal scale. Secondary outcomes included 21-day mortality, incidence of septic shock during hospitalization, and pathogen detection rate. Results: Among the 110 patients who underwent mNGS, the results prompted modifications to the antibiotic therapy in 89 patients (80.9%), encompassing both escalation and de-escalation of therapy. The remaining 52 patients received only CMT. After the PSM, 41 matched pairs were further analyzed. Compared to the CMT group, OI improvement >30% on day 7 was more frequent in the mNGS group (41.5% vs. 9.8%, P = 0.001). Clinical improvement on day 14 in the mNGS group was higher than in the CMT group (36.6% vs. 9.8%, P = 0.004). Additionally, BALF mNGS was associated with decreased 21-day mortality (7.3% vs. 34.1%; P = 0.003) in patients with opportunistic pulmonary infections, while showing no significant association with reduced incidence of septic shock during hospitalization. Moreover, the causative pathogen detection rate was significantly higher in the mNGS group compared to the CMT group (97.6% vs. 22.0%, P<0.001), demonstrating the superior diagnostic yield of mNGS. Conclusion: Our study indicated that early BALF mNGS testing upon admission was associated with improved OI up to day 7, clinical improvement on day 14, and decreased 21-day mortality. These benefits are likely facilitated by the higher diagnostic yield of mNGS and its direct impact on guiding targeted antibiotic therapy.

Allergic asthma (AA) is a lung disease characterized by impaired respiratory function and significant infiltration of inflammatory cells. Human Protein-Mimicking Peptide-2 (SHLP2) is a recently discovered mitochondria-encoded peptide that plays a crucial role in mitochondrial retrograde signaling pathways. However, its potential utility in mitigating AA remains unexplored. Our study investigates the therapeutic potential of SHLP2 in AA. We found that SHLP2 expression was significantly lower in the serum of patients with AA and correlated with key AA biomarkers. Exogenous SHLP2 supplementation alleviated house dust mites (HDM)-induced lung inflammation and airway barrier damage in mice. Additionally, SHLP2 ameliorated mitochondrial damage and inhibited pyroptosis in bronchial epithelial cells. At the mechanistic level, we identified a binding site between SHLP2 and the promoter region of the ETS Variant Transcription Factor 5 (ETV5) using a luciferase reporter assay. SHLP2 inhibited the transcription of downstream GSDMD, thereby suppressing pyroptosis. Overexpression of ETV5 improved mitochondrial function and reduced pyroptosis in bronchial epithelial cells. However, exogenous SHLP2 supplementation failed to reverse the exacerbation of HDM-induced lung inflammation and airway barrier damage caused by ETV5 knockout in mice. These findings highlight SHLP2 as a key ETV5/GSDMD signaling pathway regulator, inhibiting pyroptosis and mitigating AA progression.

Radiation pneumonitis (RP), one of the most common and severe complications in locally advanced non-small cell lung cancer (LA-NSCLC) patients following thoracic radiotherapy, presents significant challenges in prediction due to the complexity of clinical risk factors, incomplete multimodal data, and unavailable slice-level annotations in pre-radiotherapy CT images. To address these challenges, we propose a multimodal fusion framework based on Dual-Layer Attention-Based Adaptive Bag Embedding Multiple-Instance Learning (DAAE-MIL) for accurate RP prediction. This study retrospectively collected data from 995 LA-NSCLC patients who received thoracic radiotherapy between November 2018 and April 2025. After screening, Subject datasets (n = 670) were allocated for training (n = 535), and the remaining samples (n = 135) were reserved for an independent test set. The proposed framework first extracts pre-radiotherapy CT image features using a fine-tuned C3D network, followed by the DAAE-MIL module to screen critical instances and generate bag-level representations, thereby enhancing the accuracy of deep feature extraction. Subsequently, clinical data, radiomics features, and CT-derived deep features are integrated to construct a multimodal prediction model. The proposed model demonstrates promising RP prediction performance across multiple evaluation metrics, outperforming both state-of-the-art and unimodal RP prediction approaches. On the test set, it achieves an accuracy (ACC) of 0.93 and an area under the curve (AUC) of 0.97. This study validates that the proposed method effectively addresses the limitations of single-modal prediction and the unknown key features in pre-radiotherapy CT images while providing significant clinical value for RP risk assessment.