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Background Early detection and accurate differentiation of malignant ground-glass nodules (GGNs) in lung CT scans are crucial for the effective treatment of lung adenocarcinoma. However, existing imaging diagnostic methods often struggle to distinguish between benign and malignant GGNs in the early stages. This study aims to predict the malignancy risk of GGNs observed in lung CT scans by applying two radiomics methods: topological data analysis and texture analysis. Methods A retrospective analysis was conducted on 3223 patients from two centers between January 2018 and June2023. The dataset was divided into training, testing, and validation sets to ensure robust model development and validation. We developed topological features applied to GGNs using radiomics analysis based on homology. This innovative approach emphasizes the integration of topological information, capturing complex geometric and spatial relationships within GGNs. By combining machine learning and deep learning algorithms, we established a predictive model that integrates clinical parameters, previous radiomics features, and topological radiomics features. Results Incorporating topological radiomics into our model significantly enhanced the ability to distinguish between benign and malignant GGNs. The topological radiomics model achieved areas under the curve (AUC) of 0.85 and 0.862 in two independent validation sets, outperforming previous radiomics models. Furthermore, this model demonstrated higher sensitivity compared to models based solely on clinical parameters, with sensitivities of 80.7% in validation set 1 and 82.3% in validation set 2. The most comprehensive model, which combined clinical parameters, previous radiomics features, and topological radiomics features, achieved the highest AUC value of 0.879 across all datasets. Conclusion This study validates the potential of topological radiomics in improving the predictive performance for distinguishing between benign and malignant GGNs. By integrating topological features with previous radiomics and clinical parameters, our comprehensive model provides a more accurate and reliable basis for developing treatment strategies for patients with GGNs.

Abstract Background Pneumocystis jirovecii pneumonia (PCP) could be fatal to patients without human immunodeficiency virus (HIV) infection. Current diagnostic methods are either invasive or inaccurate. We aimed to establish an accurate and non-invasive radiomics-based way to identify the risk of PCP infection in non-HIV patients with computed tomography (CT) manifestation of pneumonia. Methods This is a retrospective study including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022 in one hospital. The patients were randomized in a 7:3 ratio into training and validation cohorts. Computed tomography (CT)-based radiomics features were extracted automatically and used to construct a radiomics model. A diagnostic model with traditional clinical and CT features was also built. The area under the curve (AUC) were calculated and used to evaluate the diagnostic performance of the models. The combination of the radiomics features and serum β-D-glucan levels was also evaluated for PCP diagnosis. Results A total of 140 patients (PCP: N = 61, non-PCP: N = 79) were randomized into training (N = 97) and validation (N = 43) cohorts. The radiomics model consisting of nine radiomic features performed significantly better (AUC = 0.954; 95% CI: 0.898-1.000) than the traditional model consisting of serum β-D-glucan levels (AUC = 0.752; 95% CI: 0.597–0.908) in identifying PCP (P = 0.002). The combination of radiomics features and serum β-D-glucan levels showed an accuracy of 95.8% for identifying PCP infection (positive predictive value: 95.7%, negative predictive value: 95.8%). Conclusions Radiomics showed good diagnostic performance in differentiating PCP from other types of pneumonia in non-HIV patients. A combined diagnostic method including radiomics and serum β-D-glucan has the potential to provide an accurate and non-invasive way to identify the risk of PCP infection in non-HIV patients with CT manifestation of pneumonia. Trial registration ClinicalTrials.gov (NCT05701631).

Abstract Perioperative adjuvant treatment has become an increasingly important aspect of the management of patients with non‐small cell lung cancer (NSCLC). In particular, the success of immune checkpoint inhibitors, such as antibodies against PD‐1 and PD‐L1, in patients with lung cancer has increased our expectations for the success of these therapeutics as neoadjuvant immunotherapy. Neoadjuvant therapy is widely used in patients with resectable stage IIIA NSCLC and can reduce primary tumor and lymph node stage, improve the complete resection rate, and eliminate microsatellite foci; however, complete pathological response is rare. Moreover, because the clinical benefit of neoadjuvant therapy is not obvious and may complicate surgery, it has not yet entered the mainstream of clinical treatment. Small‐scale clinical studies performed in recent years have shown improvements in the major pathological remission rate after neoadjuvant therapy, suggesting that it will soon become an important part of NSCLC treatment. Nevertheless, neoadjuvant immunotherapy may be accompanied by serious adverse reactions that lead to delay or cancellation of surgery, additional illness, and even death, and have therefore attracted much attention. In this article, we draw on several sources of information, including (i) guidelines on adverse reactions related to immune checkpoint inhibitors, (ii) published data from large‐scale clinical studies in thoracic surgery, and (iii) practical experience and published cases, to provide clinical recommendations on adverse events in NSCLC patients induced by perioperative immunotherapy.

Abstract Background Enterococcus spp. are the common cause of nosocomial bloodstream infections (BSIs) with high morbidity and mortality. The purpose of this study was to characterize the incidence, clinical and microbiological features, and mortality of nosocomial enterococcal BSIs at a large Chinese tertiary-care hospital in Beijing, China. Methods A retrospective cohort study on adult patients with nosocomial BSIs due to Enterococcus spp. was performed between January 1, 2012, and December 31, 2015 at the Chinese People’s Liberation Army General Hospital. Patients’ data were gathered by reviewing electronic medical records. Results A total of 233 episodes of BSI due to Enterococcus spp. occurred among 224 patients during these 4 years. The overall incidence was 3.9 episodes per 10,000 admissions. Enterococcus faecium (E. faecium) was the major pathogen (74%, 95% CI 68–80%), followed by Enterococcus faecalis (E. faecalis) (20%, 95% CI 15–25%). E. faecium showed higher antimicrobial resistance than E. faecalis. The 30-day mortality of nosocomial enterococcal BSI was 24% (95% CI 18–29%). Predictors for mortality included the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Charlson comorbidity index (CCI), impaired renal function, prior use of immunosuppressive agents, and appropriate empirical antimicrobial treatment. Conclusions This study emphasizes that Enterococcus spp. were major pathogens for nosocomial BSIs and associated with high mortality. Appropriate empirical antimicrobial treatment can improve outcomes. Vancomycin is the best choice for patients with E. faecium BSIs. Penicillins, aminoglycosides, fluoroquinolones, and vancomycin can be considered for patients with E. faecalis BSIs.

Background: Healthcare-associated pneumonia (HCAP) is associated with drug-resistant pathogens and high mortality, and there is no clear evidence that this is due to inappropriate antibiotic therapy. This study was to elucidate the clinical features, pathogens, therapy, and outcomes of HCAP, and to clarify the risk factors for drug-resistant pathogens and prognosis. Methods: Retrospective observational study among hospitalized patients with HCAP over 10 years. The primary outcome was 30-day all-cause hospital mortality after admission. Demographics (age, gender, clinical features, and comorbidities), dates of admission, discharge and/or death, hospitalization costs, microbiological results, chest imaging studies, and CURB-65 were analyzed. Antibiotics, admission to Intensive Care Unit (ICU), mechanical ventilation, and pneumonia prognosis were recorded. Patients were dichotomized based on CURB-65 (low- vs. high-risk). Results: Among 612 patients (mean age of 70.7 years), 88.4% had at least one comorbidity. Commonly detected pathogens were Acinetobacter baumannii, Pseudomonas aeruginosa, and coagulase-negative staphylococci. Initial monotherapy with β-lactam antibiotics was the most common initial therapy (50%). Mean age, length of stay, hospitalization expenses, ICU admission, mechanical ventilation use, malignancies, and detection rate for P. aeruginosa, and Staphylococcus aureus were higher in the high-risk group compared with the low-risk group. CURB-65 ≥3, malignancies, and mechanical ventilation were associated with an increased mortality. Logistic regression analysis showed that cerebrovascular diseases and being bedridden were independent risk factors for HCAP. Conclusion: Initial treatment of HCAP with broad-spectrum antibiotics could be an appropriate approach. CURB-65 ≥3, malignancies, and mechanical ventilation may result in an increased mortality.

Interstitial lung disease (ILD) induced by epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib and erlotinib, is a rare but fatal complication of TKI treatment. Transfer to chemotherapy or continuation with TKI of reduced dose are alternative treatment strategies. We report a case of severe ILD in a non-small cell lung cancer patient treated with gefitinib. She experienced partial response with restarted low-dose EGFR-TKI erlotinib and corticosteroid treatment.

Tissue regeneration is a process that recapitulates and restores organ structure and function. Although previous studies have demonstrated wound-induced hair neogenesis (WIHN) in laboratory mice (Mus), the regeneration is limited to the center of the wound unlike those observed in African spiny (Acomys) mice. Tissue mechanics have been implicated as an integral part of tissue morphogenesis. Here, we use the WIHN model to investigate the mechanical and molecular responses of laboratory and African spiny mice, and report these models demonstrate opposing trends in spatiotemporal morphogenetic field formation with association to wound stiffness landscapes. Transcriptome analysis and K14-Cre-Twist1 transgenic mice show the Twist1 pathway acts as a mediator for both epidermal-dermal interactions and a competence factor for periodic patterning, differing from those used in development. We propose a Turing model based on tissue stiffness that supports a two-scale tissue mechanics process: (1) establishing a morphogenetic field within the wound bed (mm scale) and (2) symmetry breaking of the epidermis and forming periodically arranged hair primordia within the morphogenetic field (μm scale). Thus, we delineate distinct chemo-mechanical events in building a Turing morphogenesis-competent field during WIHN of laboratory and African spiny mice and identify its evo-devo advantages with perspectives for regenerative medicine.