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BACKGROUND: sTREM-1H and miR-126 play crucial roles in inflammation and immune responses, yet their involvement in patients with pulmonary infection following cranial injury remains understudied. OBJECTIVE: The distribution of pathogens causing infection in patients with pulmonary infection after craniocerebral injury was explored, and the changes in the levels of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) and miR-126 in peripheral blood were analyzed. METHODS: In this study, 60 patients (study group) with postoperative lung infection in craniocerebral injury treated from January 2019 to December 2, 2021, and 60 patients without lung infection were selected as the control group. The study group received anti-infection treatment. The infection pathogen of the study group was tested, and the changes of sTREM-1 and miR-126 levels in the peripheral blood of the study and control groups were recorded to explore the diagnosis and predictive Value of prognostic death. RESULTS: 66 pathogens were detected, including 18 gram-positive bacteria, 42 gram-negative bacteria, and 6 fungi. The sTREM-1 level was higher than the control group, and the miR-126 level was lower than the control group. By ROC curve analysis, the diagnostic AUC values of both patients were 0.907 and 0.848, respectively (P < 0.05). Compared to those in the study group, patients had decreased sTREM-1 levels and increased miR-126 levels after treatment (P < 0.05). Compared with the survival group, patients in the death group had increased sTREM-1 levels and decreased miR-126 levels, and ROC curve analysis, the predicted AUC death values were 0.854 and 0.862, respectively. CONCLUSION: Gram-negative bacteria, with increased peripheral sTREM-1 levels and decreased miR-126 levels. The levels of sTREM-1 and miR-126 have specific diagnostic and prognostic Values for pulmonary infection after craniocerebral injury. However, the study's conclusions are drawn from a limited sample and short-term data, which might limit their broader applicability. Future studies with larger populations and longitudinal designs are required to confirm these findings and determine these biomarkers' robustness across different settings. Further research should also explore how these biomarkers influence patient outcomes in craniocerebral injuries. [ABSTRACT FROM AUTHOR]

Abstract Background Unsaturated fatty acids targeting quorum sensing (QS) system have shown potential application in reducing bacterial virulence. We aim to investigate the effect of palmitoleic acid (PMA) on P. aeruginosa QS activation, and its impact on infection-induced lung injury. Methods The influence of PMA on QS signaling molecule (3OC12-HSL and C4-HSL) concentrations, pyocyanin production, and QS gene transcription levels were examined in wildtype PAO1 culture. The roles of PMA in reducing infection-induced injury were assessed in human bronchial epithelial BEAS-2B cells and mouse lung infection models, respectively. PMA levels and QS signaling molecule concentrations were tested in the bronchoalveolar lavage fluid (BALF) of bronchiectasis patients with first-time detection of P. aeruginosa infection. Results PMA administration dose-dependently suppressed the expression of QS signaling molecules, pyocyanin, and QS genes during the logarithmic stage of bacterial growth. In BEAS-2B cells, PMA-treated PAO1 filtrates significantly reduced cell apoptosis and expression of IL-8 and IL-6. In mouse lung infection models, prophylactically oral administration of PMA significantly downregulated the expression of P. aeruginosa QS signals and QS genes (lasR, rhlR, rhlI, lasB, rhlA, phzA1, phnA) in lungs, and relieved neutrophilic airway inflammation. Finally, PMA levels were negatively correlated with the concentrations of both 3OC12-HSL and C4-HSL in BALF of bronchiectasis patients, and positively correlated with their forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1.0). Conclusion Our findings show that PMA inhibits P. aeruginosa QS activation and protects lungs from injury caused by bacterial virulence. Hence, PMA may serve as a potential anti-QS agent against P. aeruginosa infection and would help to alleviate lung injury in bronchiectasis patients.

The widespread dissemination of bacterial resistance has led to great attention being paid to finding substitutes for traditionally used antibiotics. Plants are rich in various phytochemicals that could be used as antibacterial therapies. Here, we elucidate the phytochemical profile of Euphorbia canariensis ethanol extract (EMEE) and then elucidate the antibacterial potential of ECEE against Pseudomonas aeruginosa clinical isolates. ECEE showed minimum inhibitory concentrations ranging from 128 to 512 µg/mL. The impact of ECEE on the biofilm-forming ability of the tested isolates was elucidated using crystal violet assay and qRT-PCR to study its effect on the gene expression level. ECEE exhibited antibiofilm potential, which resulted in a downregulation of the expression of the biofilm genes (algD, pelF, and pslD) in 39.13% of the tested isolates. The antibacterial potential of ECEE was studied in vivo using a lung infection model in mice. A remarkable improvement was observed in the ECEE-treated group, as revealed by the histological and immunohistochemical studies. Also, ELISA showed a noticeable decrease in the oxidative stress markers (nitric oxide and malondialdehyde). The gene expression of the proinflammatory marker (interleukin-6) was downregulated, while the anti-inflammatory biomarker was upregulated (interleukin-10). Thus, clinical trials should be performed soon to explore the potential antibacterial activity of ECEE, which could help in our battle against resistant pathogenic bacteria.

BACKGROUND: Establishing a nomogram prediction model for postoperative pulmonary infection in hip fractures and taking early intervention measures is crucial for improving patients’ quality of life and reducing medical costs. OBJECTIVE: To construct a nomogram risk prediction model of postoperative pulmonary infection in elderly patients with hip fracture, and provide theoretical basis for feasible prevention and early intervention. METHODS: Case data of 305 elderly patients with hip fractures who underwent surgical treatment at Wuxi Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine between January and October 2020 (training set) were retrospectively analyzed. Using univariate and multivariate logistic regression analysis and Hosmer-Lemeshow goodness of fit test, receiver operating characteristic curve was utilized to analyze the diagnostic predictive efficacy of independent risk factors and joint models for postoperative pulmonary infections. Tools glmnet, pROC, and rms in R Studio software were applied to construct a nomogram model for predicting the risk of postoperative pulmonary infection in elderly patients with hip fractures, and calibration curves were further drawn to verify the predictive ability of the nomogram model. Receiver operating characteristic curves, calibration curves, and decision curves were analyzed for 133 elderly patients with hip fractures (validation set) receiving surgery at the same hospital from November 2022 to March 2023 to further predict the predictive ability of the nomogram model. RESULTS AND CONCLUSION: (1) The postoperative pulmonary infection rate in elderly patients with hip fractures in this group was 9.18% (28/305). (2) Single factor and multivariate analysis, as well as forest plots, showed that preoperative hospitalization days, leukocyte count, hypersensitive C-reactive protein, and serum sodium levels were independent risk factors (P < 0.05). The Hosmer-Leme show goodness of fit test showed good fit (χ² =4.57, P=0.803). Receiver operating characteristic curve analysis was conducted on the independent risk factors and their joint models mentioned above, and the differentiation of each independent risk factor and joint model was good, with statistical significance (P < 0.05). (3) The graphical calibration method, C-index, and decision curve were used to validate the nomogram prediction model. The predicted calibration curve was located between the standard curve and the acceptable line, and the predicted risk of the nomogram model was consistent with the actual risk. (4) The validation set used receiver operating characteristic curve, graphic calibration method, and decision curve to validate the prediction model. The results showed good consistency with clinical practice, indicating that the model had a good fit. The nomogram risk prediction model constructed for postoperative pulmonary infection in elderly patients with hip fractures has good predictive performance. The use of the nomogram risk prediction model can screen high-risk populations and provide a theoretical basis for early intervention. [ABSTRACT FROM AUTHOR]

Objective To analyze the risk factors of pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction heart failure, and establish a risk predicting model of pulmonary infection in those patients by decision tree CART algorithm. Methods 320 elderly patients with heart failure with reduced left ventricular ejection fraction admitted from January 2020 to December 2022 were retrospectively selected as study objects, and were divided into an infection group and a non-infection group according to whether the patients were complicated with pulmonary infection. Logistic regression model and decision tree CART model were used to construct a prediction model of heart failure with reduced left ventricular ejection fraction complicated with pulmonary infection, and 5-fold cross-validation method was used for internal verification. The prediction efficiency of the models was compared. Results In the 320 patients, the incidence of pulmonary infection was 30.94%. The data on age, smoking history, diabetes mellitus, cardiac function grades, COPD, invasive procedures, length of hospital stay were compared between the infection and non-infection groups (P < 0.05). logistic regression analysis showed that age of ≥ 75 years smoking history, complications with diabetes or/and COPD, cardiac function grade Ⅲ/Ⅳ, invasive procedures, and hospital stay of ≥14 days were independent risk factors for pulmonary infection in the patients (P < 0.05). Probability forecasting model P = 1[/ 1 + e (-3.368+0.763*X1+0.814*X2+0.652*X3+1.085*X4+0.865*X5+1.027*X6+0.652*X7)], with an overall accurate rate of prediction of 80.9%. The Omnibus test showed P < 0.001. The accuracy of prediction was 73.6% after the cross-validation of 5 fold. The decision tree model showed that invasive procedures were the most important influencing factors for pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction, with an information gain of 0.280. The ROC showed that the AUC value of logistic regression model was slightly higher than that of the decision tree (Z = 2.850, P = 0.004), and the prediction efficiency of both models was medium. Conclusions Age, smoking history, complications with diabetes mellitus or/and COPD, cardiac function grades, invasive procedures, and length of hospital stay are all influencing factors for pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction. The decision tree model constructed in this study has a better efficiency for risk prediction, and it can provide reference for early clinical screening and intervention of heart failure with reduced left ventricular ejection fraction. [ABSTRACT FROM AUTHOR]

Deep learning-powered AI tools offer significant potential to improve COVID-19 lung infection diagnosis. This study proposes a novel AI-based image analysis method for multiclass classification. We analyzed publicly available datasets from Italian Society of Medical and Interventional Radiology (SIRM), Kaggle, and Radiopaedia. However, the relevance, strength, and relationships of static features extracted from these images require further investigation. Bayesian inference approaches have recently emerged as powerful tools for analyzing static features. These approaches can reveal hidden dynamics and relationships between features. Using Analysis of variance (ANOVA) based ranking techniques, we extracted gray level co-occurrence matrix (GLCM) features from images belonging to three classes such as COVID-19, bacterial pneumonia, and normal. To delve deeper into the dynamic behavior and optimize its diagnostic potential, Homogeneity (identified as the most significant feature) was chosen for further analysis using dynamic profiling and optimization methods. This focused investigation aimed to decipher the intricate, non-linear dynamics within GLCM features across all three classes. Our method offers a two-fold benefit. First, it deepens our understanding of the intricate relationships between features extracted from chest X-rays using gray level co-occurrence matrix analysis. Second, it provides a comprehensive examination of these features themselves. This combined analysis sheds light on the hidden dynamics that are crucial for accurate diagnosis and prognosis of various infectious diseases. In addition to the above, we have developed a novel AI-powered imaging analysis method for multiclass classification. This innovative approach has the potential to significantly improve diagnostic accuracy and prognosis of infectious diseases, particularly COVID-19. [ABSTRACT FROM AUTHOR]

Suppurative lung diseases leading to end‐stage respiratory failure are typical indications for bilateral lung transplantation (LuTx). Some cases may present severe chest asymmetry because of recurrent infections or previous surgical procedures, and the most used surgical options are single LuTx and contralateral pneumonectomy or bilateral transplantation with graft downsizing. Our purpose is to evaluate our treatment protocols for these patients and review surgical strategies reported by others. We prospectively collected clinical data of patients with significant pleural cavity asymmetry who underwent bilateral LuTx at our center from 2017 to 2022. Clinical reports of all patients who underwent LuTx for end‐stage suppurative disease in the same period were reviewed as the control group. During the study period, 74 patients underwent bilateral LuTx for suppurative disease; seven of them presented with severe thoracic asymmetry, and all of them were extubated by the second postoperative day. The mean intensive care unit stay was 4 days. The postoperative radiological evaluation did not show clustering or atelectasis of the graft implanted in the smaller hemithorax. No perioperative major complications were recorded, and the average length of stay was 23 days. The perioperative course appeared remarkably good, and both the short‐ and long‐term follow‐up were similar to that of the control group. [ABSTRACT FROM AUTHOR]

Background and Objectives: Airway fungal infection is a severe clinical problem, especially in patients with compromised immune functions. Here, we examined the distribution and antifungal susceptibility profiles of fungal agents isolated from respiratory tract of symptomatic patients hospitalized in pulmonary units. Materials and Methods: This descriptive cross-sectional study took place from 2023 to 2024, involving 360 patients. Bronchoalveolar lavage (BAL) or sputum specimens were collected and analyzed using mycological and molecular methods for this study. Antifungal susceptibility testing (AFST) was carried out using the broth micro dilution method. Results: Of a total of 360 respiratory specimens, 114 (31.6%) were positive. The male-to-female ratio was 63:51 (1.3%). Candida albicans and Aspergillus flavus were the most common yeast and mold species. Chronic obstructive pulmonary disease (COPD) had the highest rate of colonization with fungal agents (47/114, 41%). The isolates associated with COPD in this study included Aspergillus species (4/12, 3.5%), Candida species (41/96, 36%), and other fungal species (2/6, 1.5%). Coughing (87%) was the predominant symptom, and malignancy (52%) was the predominant comorbidity factor. The result of AFST for antifungal agents showed that 9 (22.5%) Candida isolates were resistant, and the highest rate of resistance was related to voriconazole agent (5/9, 55.5%). Resistance to antifungal agents was not observed among Aspergillus isolates. Conclusion: This study showed a significant relationship between the frequency of Aspergillus and Candida species in patients with underlying lung diseases. In addition, voriconazole was more effective than itraconazole, especially against Aspergillus flavus. [ABSTRACT FROM AUTHOR]

On 11 February 2020, the prevalent outbreak of COVID-19, a coronavirus illness, was declared a global pandemic. Since then, nearly seven million people have died and over 765 million confirmed cases of COVID-19 have been reported. The goal of this study is to develop a diagnostic tool for detecting COVID-19 infections more efficiently. Currently, the most widely used method is Reverse Transcription Polymerase Chain Reaction (RT-PCR), a clinical technique for infection identification. However, RT-PCR is expensive, has limited sensitivity, and requires specialized medical expertise. One of the major challenges in the rapid diagnosis of COVID-19 is the need for reliable imaging, particularly X-ray imaging. This work takes advantage of artificial intelligence (AI) techniques to enhance diagnostic accuracy by automating the detection of COVID-19 infections from chest X-ray (CXR) images. We obtained and analyzed CXR images from the Kaggle public database (4035 images in total), including cases of COVID-19, viral pneumonia, pulmonary opacity, and healthy controls. By integrating advanced techniques with transfer learning from pre-trained convolutional neural networks (CNNs), specifically InceptionV3, ResNet50, and Xception, we achieved an accuracy of 95%, significantly higher than the 85.5% achieved with ResNet50 alone. Additionally, our proposed method, CXR-DNNs, can accurately distinguish between three different types of chest X-ray images for the first time. This computer-assisted diagnostic tool has the potential to significantly enhance the speed and accuracy of COVID-19 diagnoses. [ABSTRACT FROM AUTHOR]

Background: Unsaturated fatty acids targeting quorum sensing (QS) system have shown potential application in reducing bacterial virulence. We aim to investigate the effect of palmitoleic acid (PMA) on P. aeruginosa QS activation, and its impact on infection-induced lung injury. Methods: The influence of PMA on QS signaling molecule (3OC12-HSL and C4-HSL) concentrations, pyocyanin production, and QS gene transcription levels were examined in wildtype PAO1 culture. The roles of PMA in reducing infection-induced injury were assessed in human bronchial epithelial BEAS-2B cells and mouse lung infection models, respectively. PMA levels and QS signaling molecule concentrations were tested in the bronchoalveolar lavage fluid (BALF) of bronchiectasis patients with first-time detection of P. aeruginosa infection. Results: PMA administration dose-dependently suppressed the expression of QS signaling molecules, pyocyanin, and QS genes during the logarithmic stage of bacterial growth. In BEAS-2B cells, PMA-treated PAO1 filtrates significantly reduced cell apoptosis and expression of IL-8 and IL-6. In mouse lung infection models, prophylactically oral administration of PMA significantly downregulated the expression of P. aeruginosa QS signals and QS genes (lasR, rhlR, rhlI, lasB, rhlA, phzA1, phnA) in lungs, and relieved neutrophilic airway inflammation. Finally, PMA levels were negatively correlated with the concentrations of both 3OC12-HSL and C4-HSL in BALF of bronchiectasis patients, and positively correlated with their forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1.0). Conclusion: Our findings show that PMA inhibits P. aeruginosa QS activation and protects lungs from injury caused by bacterial virulence. Hence, PMA may serve as a potential anti-QS agent against P. aeruginosa infection and would help to alleviate lung injury in bronchiectasis patients. [ABSTRACT FROM AUTHOR]

The widespread dissemination of bacterial resistance has led to great attention being paid to finding substitutes for traditionally used antibiotics. Plants are rich in various phytochemicals that could be used as antibacterial therapies. Here, we elucidate the phytochemical profile of Euphorbia canariensis ethanol extract (EMEE) and then elucidate the antibacterial potential of ECEE against Pseudomonas aeruginosa clinical isolates. ECEE showed minimum inhibitory concentrations ranging from 128 to 512 µg/mL. The impact of ECEE on the biofilm-forming ability of the tested isolates was elucidated using crystal violet assay and qRT-PCR to study its effect on the gene expression level. ECEE exhibited antibiofilm potential, which resulted in a downregulation of the expression of the biofilm genes (algD, pelF, and pslD) in 39.13% of the tested isolates. The antibacterial potential of ECEE was studied in vivo using a lung infection model in mice. A remarkable improvement was observed in the ECEE-treated group, as revealed by the histological and immunohistochemical studies. Also, ELISA showed a noticeable decrease in the oxidative stress markers (nitric oxide and malondialdehyde). The gene expression of the proinflammatory marker (interleukin-6) was downregulated, while the anti-inflammatory biomarker was upregulated (interleukin-10). Thus, clinical trials should be performed soon to explore the potential antibacterial activity of ECEE, which could help in our battle against resistant pathogenic bacteria. [ABSTRACT FROM AUTHOR]

A physical examination and diagnostic imaging techniques including lung biopsies, ultrasounds, and chest X-rays are typically used to make the diagnosis of pneumonia infection, an infectious disease that has the potential to be life-threatening. The objective of this research is to categorize the stages of pneumonia through image processing methods. Before that, an ensemble model for diagnosing pneumonia infections is created utilizing the transfer learning algorithms ResNet50V2 and DenseNet201. The 5,857 images were taken from the PAUL MOONEY dataset for this research. The proposed ensemble averaging model recognizes lung infection appropriately and accurately. By applying a contour detection approach, the left and right chests are separated and the affected pixels from there to analyze the stage of pneumonia. It is very crucial to identify the stage for treatment purposes. [ABSTRACT FROM AUTHOR]

• This study confirm the overwhelming occurrence of VBNC forms of different pathogens (PA, MSSA, MRSA, AXE, SM) in the CF clinical settings. • In particular Pseudomonas aeruginosa VBNC impact on the lung infection progression in patients with CF. • In patients with chronic or intermittent infection our results suggest that highly effective modulator therapy cannot eradicate the bacteria, underlining both the weaknesses of the routine cultural methods and the doubtful efficacy of the adopted therapeutic treatments to achieve infection eradication. Lung infections antibiotic treatment in Cystic Fibrosis patients (pwCF) is often complicated by bacterial persisters, including the so-called Viable but Non Culturable (VBNC) forms, live cells undetected by the routine cultural microbiological methods. This study investigated the occurrence of VBNC cells of five CF bacterial pathogens in 94 pwCF over one year and the possible associations with the patients' clinical features. Sputum samples, recovered at routine visits and during exacerbation episodes, were analyzed for the presence of the five pathogens by both routine culture-based assays and species-specific qPCR. VBNC cells were estimated as the difference between molecular and cultural counts and their presence was matched with the clinical data in particular the therapeutic regimens. All but ten pwCF showed the presence of VBNC cells at least once during the study. Pseudomonas aeruginosa and methicillin-susceptible Staphylococcus aureus were the species most frequently found in the VBNC state. Only the former showed a significant association between chronic infection and VBNC cells presence; VBNC-MSSA positive patients significantly increased overtime. The presence of non culturable bacteria was generally concurrent with poor lung functionality and more frequent pulmonary exacerbations. No significant association with modulator treatment was evidenced. The obtained data demonstrated the overwhelming occurrence of bacterial VBNC cells in CF lung infections, warranting a constant monitoring of pwCF and underlining the need of implementing the routine culture-based assays with culture-independent techniques. This is pivotal to understand the CF bacterial population dynamics and to efficiently contrast the lung infection progression and worsening. [ABSTRACT FROM AUTHOR]

Simvastatin had minimum inhibitory concentrations of 32 to 128 µg/mL against Klebsiella pneumoniae isolates and hindered the biofilm-formation ability of 58.54% of the isolates. It considerably diminished the bacterial cell counts in the biofilms as revealed by scanning electron microscope. Also, qRT-PCR revealed a downregulation of the biofilm genes (bcsA, wza, and luxS) by simvastatin in 48.78% of the isolates. Moreover, simvastatin has significantly improved the survival of mice and decreased the burden of bacteria in the infected lungs. Also, the histological architecture was substantially improved in the simvastatin-treated group, as the alveolar sacs and bronchioles appeared normal with minimal collagen fiber deposition. The immunohistochemical studies exposed that the TNF-α, NF-kβ, and COX-2 immunostaining considerably declined in the simvastatin-treated group. Furthermore, ELISA exposed that both IL-1β and IL-6 were considerably diminished in the lungs of the simvastatin-treated group. [ABSTRACT FROM AUTHOR]

Bacteria exposed to bactericidal treatment, such as antibiotics or bacteriophages (phages), often develop resistance. While phage therapy is proposed as a solution to the antibiotic resistance crisis, the bacterial resistance emerging during phage therapy remains poorly characterized. In this study, we examined a large population of phage-resistant extra-intestinal pathogenic Escherichia coli 536 clones that emerged from both in vitro (non-limited liquid medium) and in vivo (murine pneumonia) conditions. Genome sequencing uncovered a convergent mutational pattern in phage resistance mechanisms under both conditions, particularly targeting two cell-wall components, the K15 capsule and the lipopolysaccharide (LPS). This suggests that their identification in vivo could be predicted from in vitro assays. Phage-resistant clones exhibited a wide range of fitness according to in vitro tests, growth rate, and resistance to amoeba grazing, which could not distinguish between the K15 capsule and LPS mutants. In contrast, K15 capsule mutants retained virulence comparable to the wild-type strain, whereas LPS mutants showed significant attenuation in the murine pneumonia model. Additionally, we observed that resistance to the therapeutic phage through an onspecific mechanism, such as capsule overproduction, did not systematically lead to co-resistance to other phages that were initially capable or incapable of infecting the wild-type strain. Our findings highlight the importance of incorporating a diverse range of phages in the design of therapeutic cocktails to target potential future phage-resistant clones effectively. [ABSTRACT FROM AUTHOR]

Cystic fibrosis-related diabetes (CFRD), the most common comorbidity in cystic fibrosis (CF), leads to increased mortality by accelerating the decline in lung function. Scnn1b-Tg transgenic mice overexpressing the epithelial sodium channel β subunit exhibit spontaneous CF-like lung disease, including airway mucus obstruction and chronic inflammation. Here, we established a chronic CFRD-like model using Scnn1b-Tg mice made diabetic by injection of streptozotocin (STZ). In Ussing chamber recordings of the trachea, Scnn1b-Tg mice exhibited larger amiloride-sensitive currents and forskolin-activated currents, without a difference in adenosine triphosphate (ATP)-activated currents compared with wild-type (WT) littermates. Both diabetic WT (WT-D) and diabetic Scnn1b-Tg (Scnn1b-Tg-D) mice on the same genetic background exhibited substantially elevated blood glucose at 8 wk; glucose levels also were elevated in bronchoalveolar lavage fluid (BALF). Bulk lung RNA-seq data showed significant differences between WT-D and Scnn1b-Tg-D mice. Neutrophil counts in BALF were substantially increased in Scnn1b-Tg-D lungs compared with controls (Scnn1b-Tg-con) and compared with WT-D lungs. Lung histology data showed enhanced parenchymal destruction, alveolar wall thickening, and neutrophilic infiltration in Scnn1b-Tg-D mice compared with WT-D mice, consistent with the development of a spontaneous lung infection. We intranasally administered Pseudomonas aeruginosa to induce lung infection in these mice for 24 h, which led to severe lung leukocytic infiltration and an increase in pro-inflammatory cytokine levels in the BALF. In summary, we established a chronic CFRD-like lung mouse model using the Scnn1b-Tg mice. The model can be used for future studies toward understanding the mechanisms underlying the lung pathophysiology associated with CFRD and developing novel therapeutics. NEW & NOTEWORTHY: We established a chronic CFRD-like mouse model using the Scnn1b-Tg transgenic mice overexpressing the epithelial sodium channel β subunit made diabetic by injection of streptozotocin. The results underscore the urgent need to develop novel therapeutics for CF lung disease. [ABSTRACT FROM AUTHOR]

Invasive pulmonary mucormycosis (IPM) is a deadly opportunistic mold infection in patients with hematological malignancies (HM). Radiologic imaging is essential for its timely diagnosis. Here, we compared IPM lesions visualized by chest computed tomography (CCT) and chest X-ray (CXR) and determined the prognostic significance of discordant imaging. Therefore, we reviewed 44 consecutive HM patients with probable/proven IPM at MD Anderson Cancer Center in 2000–2020 who had concurrent CCT and CXR studies performed. All 44 patients had abnormal CCTs and 39 (89%) had anormal CXR findings at IPM diagnosis. However, only 26 patients (59%) showed CCT-matching IPM-suspicious lesions on CXR. Acute Physiology and Chronic Health Evaluation II score > 18 at IPM diagnosis and breakthrough infection to Mucorales-active antifungals were the only independent risk factors for 42-day and/or 84-day mortality. Absence of neutropenia at IPM diagnosis, neutrophil recovery in neutropenic patients, and surgical revision of mucormycosis lesions were protective factors. Although not reaching significance on multivariable analysis, visualization of CCT-matching lesions on CXR was associated with significantly increased 84-day mortality (log-rank test, p = 0.033), possibly as a surrogate of extensive lesions and tissue necrosis. This observation supports the exploration of radiologic lesion kinetics as a prognostic staging tool in IPM patients. [ABSTRACT FROM AUTHOR]

Purpose: Differentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT classification models rely on 2D slices, lacking comprehensive information and requiring manual selection. 3D models that involve chunking compromise image information and struggle with parameter reduction, limiting performance. These limitations must be addressed to improve accuracy and practicality. Methods: We propose a transformer sequential feature encoding structure to integrate multi-level information from complete CT images, inspired by the clinical practice of using a sequence of cross-sectional slices for diagnosis. We incorporate position encoding and cross-level long-range information fusion modules into the feature extraction CNN network for cross-sectional slices, ensuring high-precision feature extraction. Results: We conducted comprehensive experiments on a dataset of 124 patients, with respective sizes of 64, 20 and 40 for training, validation and testing. The results of ablation experiments and comparative experiments demonstrated the effectiveness of our approach. Our method outperforms existing state-of-the-art methods in the 3D CT image classification problem of distinguishing between lung infections and pulmonary lymphoma, achieving an accuracy of 0.875, AUC of 0.953 and F1 score of 0.889. Conclusion: The experiments verified that our proposed position-enhanced transformer-based sequential feature encoding model is capable of effectively performing high-precision feature extraction and contextual feature fusion in the lungs. It enhances the ability of a standalone CNN network or transformer to extract features, thereby improving the classification performance. The source code is accessible at https://github.com/imchuyu/PTSFE. [ABSTRACT FROM AUTHOR]

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In this article, we propose an AI-based low-risk visualization framework for lung health monitoring using low-resolution ultra-low-dose CT (LR-ULDCT). We present a novel deep cascade processing workflow to achieve diagnostic visualization on LR-ULDCT (<0.3 mSv) at par high-resolution CT (HRCT) of 100 mSV radiation technology. To this end, we build a low-risk and affordable deep cascade network comprising three sequential deep processes: restoration, super-resolution (SR), and segmentation. Given degraded LR-ULDCT, the first novel network unsupervisedly learns restoration function from augmenting patch-based dictionaries and residuals. The restored version is then super-resolved (SR) for target (sensor) resolution. Here, we combine perceptual and adversarial losses in novel GAN to establish the closeness between probability distributions of generated SR-ULDCT and restored LR-ULDCT. Thus SR-ULDCT is presented to the segmentation network that first separates the chest portion from SR-ULDCT followed by lobe-wise colorization. Finally, we extract five lobes to account for the presence of ground glass opacity (GGO) in the lung. Hence, our AI-based system provides low-risk visualization of input degraded LR-ULDCT to various stages, i.e., restored LR-ULDCT, restored SR-ULDCT, and segmented SR-ULDCT, and achieves diagnostic power of HRCT. We perform case studies by experimenting on real datasets of COVID-19, pneumonia, and pulmonary edema/congestion while comparing our results with state-of-the-art. Ablation experiments are conducted for better visualizing different operating pipelines. Finally, we present a verification report by fourteen (14) experienced radiologists and pulmonologists. [ABSTRACT FROM AUTHOR]

The frequency of lung infection induced by multi-drug resistant strains of Pseudomonas aeruginosa has significantly risen, primarily due to the inadequate effectiveness of powerful chemotherapeutic methods. This study demonstrates that the Ocimum basilicum aqueous extract and copper nanoparticles (CuNPs) exhibited significant antioxidant and anti-infectious properties under in vivo conditions. To analyze the characteristics of the CuNPs synthesized from the reaction between copper nitrate solution and the aqueous O. basilicum extract, various techniques such as energy dispersive X-ray analysis, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction analysis, and transmission electron microscopy were employed. The in vivo study encompasses the assessment of P. aeruginosa lethal dose in mice and the disease manifestation analysis, which comprises reduction in body weight, hypothermia, bacteremia, and other parameters, over a 48 h infection period. The infected mice exhibited a notable decrease in body temperature, measuring at 25°C after 48 h, compared to the initial temperature of 39°C. Additionally, a 30% reduction in weight was seen at the conclusion of the study. To assess the effectiveness of CuNPs on lung infection caused by the calculated lethal dose and bacteremia, histopathology analysis was employed. The bacterial load in the CuNPs group was determined to be 0.5 Log10CFU/mL on Day 8, indicating a notable decrease from the initial measurement of 1.5 Log10CFU/mL on Day 1. The histopathological findings revealed a widespread and sporadic buildup of alveolar space inflammatory cells, with infiltrates observed throughout all lung sections in infected mice. Enhanced lung histology was observed in the group of animal treated with reduced exudates noted at 200 µg/kg. CuNPs demonstrated inhibitory effects on the growth of P. aeruginosa at 8 µg/mL, while at 16 µg/mL, they effectively eradicated P. aeruginosa. The research unequivocally demonstrates the efficacy of CuNPs extract in combating lung infections induced by P. aeruginosa at 200 µg/kg. The recent survey aims to further explore the biomedical characteristics of these CuNPs in order to develop a powerful treatment against this dangerous pathogen.

The problem of antimicrobial resistance (AMR) caused by the abuse of antibiotics is becoming serious. The development of antibacterial materials with synergistic efficiency and treatment of deep tissue/organ infections is imminent. Herein, synergistic antibacterial nanoparticles (MPH NPs) are prepared by loading antibacterial peptide polymyxin B (PMB) on Fe‐based MOF (MIL‐100) with hyaluronic acid (HA) modification. MPH NPs exerts antibacterial effects by chemodynamic therapy (CDT) and the release of PMB. MPH NPs have broad‐spectrum antibacterial properties on Gram‐negative bacteria (E. coli, 100%), Gram‐positive bacteria (S. aureus, 98.5 %), and MRSA (98.4%). Importantly, MPH NPs not only promote the healing of infected wounds but also target lungs to accomplish organ infection therapy. Therefore, this study provides a new strategy for designing a synergetic anti‐AMR bacteria system and the function for deep tissue/organ infection therapy in the future. [ABSTRACT FROM AUTHOR]

Respiratory infections are a major health burden worldwide. Respiratory syncytial virus (RSV) is among the leading causes of hospitalization in both young children and older adults. The onset of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and the public health response had a profound impact on the normal seasonal outbreaks of other respiratory viruses. However, little is known about how a prior respiratory virus infection impacts SARS-CoV-2 disease outcomes. In this study, we examine the impact of a previous RSV infection on the disease severity of a subsequent SARS-CoV-2 challenge in BALB/c mice. Mice infected with RSV, followed by a SARS-CoV-2 challenge, 30 days later, exhibited decreased weight loss and increased survival as compared to control groups. Our results suggest a prior RSV infection can provide protection against a subsequent SARS-CoV-2 infection. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 and respiratory syncytial virus are respiratory viruses that are a major health burden worldwide. Severe acute respiratory syndrome coronavirus 2 and respiratory syncytial virus frequently have peak seasonal outbreaks during the winter months, and are capable of causing severe respiratory disease, often leading to hospitalization. The 2019 pandemic brought attention to the importance of understanding how co-circulating viruses can impact the disease severity of other respiratory viruses. It is known that many hospitalized patients are undergoing multiple viral infections at once, yet not much has been studied to understand the impact this has on other respiratory viruses or patients. How co-circulating viruses impact one another can provide critical knowledge for future interventions of hospitalized patients and potential vaccination strategies. [ABSTRACT FROM AUTHOR]

The inhaled delivery of lactic acid bacteria (LAB) probiotics has been demonstrated to exert therapeutic benefits to the lungs due to LAB's immunomodulatory activities. The development of inhaled probiotics formulation, however, is in its nascent stage limited to nebulized LAB. We developed a dry powder inhaler (DPI) formulation of lactobacillus rhamnosus GG (LGG) intended for bronchiectasis maintenance therapy by spray freeze drying (SFD). The optimal DPI formulation (i.e., LGG: mannitol: lactose: leucine = 35: 45: 15: 5 wt.%) was determined based on the aerosolization efficiency (86% emitted dose and 26% respirable fraction) and LGG cell viability post-SFD (7 log CFU/mL per mg powder). The optimal DPI formulation was evaluated and compared to lyophilized naked LGG by its (1) adhesion capacity and cytotoxicity to human lung epithelium cells (i.e., A549 and 16HBE14o- cells) as well as its (2) effectiveness in inhibiting the growth and adhesion of Pseudomonas aeruginosa to lung cells. The optimal DPI of LGG exhibited similar non-cytotoxicity and adhesion capacity to lung cells to naked LGG. The DPI of LGG also inhibited the growth and adhesion of P. aeruginosa to the lung cells as effectively as the naked LGG. The present work established the feasibility of delivering the LAB probiotic by the DPI platform without adversely affecting LGG's anti-pseudomonal activities. [ABSTRACT FROM AUTHOR]

Pneumonia continues to be a serious health risk for young children, particularly in developing areas. This study examined 100 mothers in a rural Philippine community to explore how socio-demographic factors, knowledge, attitudes, and health-seeking practices influence pneumonia prevention. Results showed that most mothers had moderate knowledge, generally positive attitudes, and only occasionally pursued healthcare for pneumonia prevention. There were notable correlations between higher knowledge and more frequent healthcare-seeking behavior, as well as between positive attitudes and proactive health actions. These findings highlight the need for targeted efforts to enhance mothers' knowledge and preventive practices to reduce pneumonia risks in children. [ABSTRACT FROM AUTHOR]

Iron plays a critical role in lung infections due to its function in the inflammatory immune response but also as an important factor for bacterial growth. Iron chelation represents a potential therapeutic approach to inhibit bacterial growth and pathologically increased pro-inflammatory mediator production. The present study was designed to investigate the impact of the iron chelator DIBI in murine lung infection induced by intratracheal Pseudomonas aeruginosa (strain PA14) administration. DIBI is a polymer with a polyvinylpyrrolidone backbone containing nine 3-hydroxy-1-(methacrylamidoethyl)-2-methyl-4(1H) pyridinone (MAHMP) residues per molecule and was given by intraperitoneal injection either as a single dose (80 mg/kg) immediately after PA14 administration or a double dose (second dose 4 h after PA14 administration). The results showed that lung NF-κBp65 levels, as well as levels of various inflammatory cytokines (TNFα, IL-1β, IL-6) both in lung tissue and bronchoalveolar lavage fluid (BALF), were significantly increased 24 h after PA14 administration. Single-dose DIBI did not affect the bacterial load or inflammatory response in the lungs or BALF. However, two doses of DIBI significantly decreased bacterial load, attenuated NF-κBp65 upregulation, reduced inflammatory cytokines production, and relieved lung tissue damage. Our findings support the conclusion that the iron chelator, DIBI, can reduce lung injury induced by P. aeruginosa, via its anti-bacterial and anti-inflammatory effects. [ABSTRACT FROM AUTHOR]

Background and Objectives: Airway fungal infection is a severe clinical problem, especially in patients with compromised immune functions. Here, we examined the distribution and antifungal susceptibility profiles of fungal agents isolated from respiratory tract of symptomatic patients hospitalized in pulmonary units. Materials and Methods: This descriptive cross-sectional study took place from 2023 to 2024, involving 360 patients. Bronchoalveolar lavage (BAL) or sputum specimens were collected and analyzed using mycological and molecular methods for this study. Antifungal susceptibility testing (AFST) was carried out using the broth micro dilution method. Results: Of a total of 360 respiratory specimens, 114 (31.6%) were positive. The male-to-female ratio was 63:51 (1.3%). Candida albicans and Aspergillus flavus were the most common yeast and mold species. Chronic obstructive pulmonary disease (COPD) had the highest rate of colonization with fungal agents (47/114, 41%). The isolates associated with COPD in this study included Aspergillus species (4/12, 3.5%), Candida species (41/96, 36%), and other fungal species (2/6, 1.5%). Coughing (87%) was the predominant symptom, and malignancy (52%) was the predominant comorbidity factor. The result of AFST for antifungal agents showed that 9 (22.5%) Candida isolates were resistant, and the highest rate of resistance was related to voriconazole agent (5/9, 55.5%). Resistance to antifungal agents was not observed among Aspergillus isolates. Conclusion: This study showed a significant relationship between the frequency of Aspergillus and Candida species in patients with underlying lung diseases. In addition, voriconazole was more effective than itraconazole, especially against Aspergillus flavus.

ABSTRACT The polysaccharide hyaluronan (HA) is an important component of lung extracellular matrix that increases following infection with influenza or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hellman et al. (U. Hellman, E. Rosendal, J. Lehrstrand, J. Henriksson, et al., mBio 15:e01303-24, https://doi.org/10.1128/mbio.01303-24) show that fragmented HA accumulates in the lungs of coronavirus disease 2019 (COVID-19) patients, with systemic levels of HA being associated with reduced lung function 3–6 months after infection. This study provides novel insights into HA’s role in COVID-19 pathology and its potential utility as a biomarker for disease severity. However, much remains to be understood about the lung HA matrix in COVID-19 and how it compares to other lung conditions. In particular, the role of HA-binding proteins in organizing HA into a crosslinked network is yet to be fully determined at a molecular level. This knowledge is crucial in understanding the inter-relationships between the structure of the HA matrix and the regulation of the immune response, and thus our ability to target HA therapeutically for improved outcomes in COVID-19.

ABSTRACT Infections caused by multidrug resistant (MDR) pathogenic bacteria are a global health threat. Bacteriophages (“phage”) are increasingly used as alternative or last-resort therapeutics to treat patients infected by MDR bacteria. However, the therapeutic outcomes of phage therapy may be limited by the emergence of phage resistance during treatment and/or by physical constraints that impede phage–bacteria interactions in vivo. In this work, we evaluate the role of lung spatial structure on the efficacy of phage therapy for Pseudomonas aeruginosa infections. To do so, we developed a spatially structured metapopulation network model based on the geometry of the bronchial tree, including host innate immune responses and the emergence of phage-resistant bacterial mutants. We model the ecological interactions between bacteria, phage, and the host innate immune system at the airway (node) level. The model predicts the synergistic elimination of a P. aeruginosa infection due to the combined effects of phage and neutrophils, given the sufficient innate immune activity and efficient phage-induced lysis. The metapopulation model simulations also predict that MDR bacteria are cleared faster at distal nodes of the bronchial tree. Notably, image analysis of lung tissue time series from wild-type and lymphocyte-depleted mice revealed a concordant, statistically significant pattern: infection intensity cleared in the bottom before the top of the lungs. Overall, the combined use of simulations and image analysis of in vivo experiments further supports the use of phage therapy for treating acute lung infections caused by P. aeruginosa, while highlighting potential limits to therapy in a spatially structured environment given impaired innate immune responses and/or inefficient phage-induced lysis.IMPORTANCEPhage therapy is increasingly employed as a compassionate treatment for severe infections caused by multidrug-resistant (MDR) bacteria. However, the mixed outcomes observed in larger clinical studies highlight a gap in understanding when phage therapy succeeds or fails. Previous research from our team, using in vivo experiments and single-compartment mathematical models, demonstrated the synergistic clearance of acute P. aeruginosa pneumonia by phage and neutrophils despite the emergence of phage-resistant bacteria. In fact, the lung environment is highly structured, prompting the question of whether immunophage synergy explains the curative treatment of P. aeruginosa when incorporating realistic physical connectivity. To address this, we developed a metapopulation network model mimicking the lung branching structure to assess phage therapy efficacy for MDR P. aeruginosa pneumonia. The model predicts the synergistic elimination of P. aeruginosa by phage and neutrophils but emphasizes potential challenges in spatially structured environments, suggesting that higher innate immune levels may be required for successful bacterial clearance. Model simulations reveal a spatial pattern in pathogen clearance where P. aeruginosa are cleared faster at distal nodes of the bronchial tree than in primary nodes. Interestingly, image analysis of infected mice reveals a concordant and statistically significant pattern: infection intensity clears in the bottom before the top of the lungs. The combined use of modeling and image analysis supports the application of phage therapy for acute P. aeruginosa pneumonia while emphasizing potential challenges to curative success in spatially structured in vivo environments, including impaired innate immune responses and reduced phage efficacy.

Accidental fish bone ingestion is a common manifestation at emergency departments. In most cases, ingested foreign bodies usually pass uneventfully through the gastrointestinal tract and complications only present in less than 5% of all patients. In this report, we present the first documented case of pulmonary artery injury due to a fish bone in a 63-year-old male patient hospitalized with hemoptysis after accidentally swallowing a fish bone 30 days ago. This patient subsequently had surgery and endoscopy to safely remove the foreign body and then recovered well on a follow-up examination. For cases of fish bone ingestion, contrast-enhanced chest computed tomography is one of the most essential tools to assess vascular problems and associated mediastinal infections-risk factors for life-threatening and long-term recurrent inflammation. Reconstructing planes along the foreign body axis and changing windows when analyzing CT scans is necessary to avoid missing lesions and dilemmas.

Abstract The production of alternative and effective medicines is crucial given that antibiotic resistance is currently a global health concern. Several biochemical identification tests were used to screen for Staphylococcus aureus isolates. Analysis of Artemisia annua extract was performed using a trace GC‒mass spectrometer, which revealed that the A. annua extract contains numerous compounds, such as artemisinins, palmitic acid and other vital essential compounds that have antioxidant and anti-inflammatory properties. The isolate st.8 was resistant to cefoxitin, oxacillin, and cephalosporins; furthermore, MALDI-TOF/MS Biotyper® identified it as methicillin-resistant S. aureus with confidence value 99.9% of mass spectrum compared with reference spectra. The synthesis of green silver nanoparticles based on A. annua as a reducing agent was confirmed via partial characterizations: (HR-TEM), (XRD), (SEM), (EDX) and (FTIR) analysis. The significant of antibacterial activity of the new green material (AgNPs) was achieved by determining the agar well diffusion assay. Furthermore, compared with those in the Staphylococcus-infected group, a significant decrease in hematological parameters was observed, with an increase in antioxidant biomarkers, a decrease in interstitial tissue thickening by inflammatory cells, and a weak positive immune reaction in a few cells (TNF-α and iNOS) in rats. Overall, this study is a promising step toward the development of new and effective strategies for combating MRSA infections.

Influenza viruses are deadly respiratory pathogens of special importance due to their long history of global pandemics. During influenza virus infections, the host responds by producing interferons, which activate interferon-stimulated genes (ISGs) inside target cells. One of these ISGs is inducible nitric oxide synthase (iNOS). iNOS produces nitric oxide (NO) from arginine and molecular oxygen inside the cell. NO can react with superoxide radicals to form reactive nitrogen species, principally peroxynitrite. While much work has been done studying the many roles of nitric oxide in influenza virus infections, the direct effect of peroxynitrite on influenza virus proteins has not been determined. Manipulations of NO, either by knocking out iNOS or chemically inhibiting NO, produced no change in virus titers in mouse models of influenza infection. However, peroxynitrite has a known antimicrobial effect on various bacteria and parasites, and the reason for its lack of antimicrobial effect on influenza virus titers in vivo remains unclear. Therefore, we wished to test the direct effect of nitration of influenza virus proteins. We examined the impact of nitration on virus infectivity, replication, and immunogenicity. We observed that the nitration of influenza A virus proteins decreased virus infectivity and replication ex vivo. We also determined that the nitration of influenza virus hemagglutinin protein can reduce antibody responses to native virus protein. However, our study also suggests that nitration of influenza virus proteins in vivo is likely not extensive enough to inhibit virus functions substantially. These findings will help clarify the role of peroxynitrite during influenza virus infections. IMPORTANCE Nitric oxide and peroxynitrite produced during microbial infections have diverse and seemingly paradoxical functions. While nitration of lung tissue during influenza virus infection has been observed in both mice and humans, the direct effect of protein nitration on influenza viruses has remained elusive. We addressed the impact of nitration of influenza virus proteins on virus infectivity, replication, and immunogenicity. We observed that ex vivo nitration of influenza virus proteins reduced virus infectivity and immunogenicity. However, we did not detect nitration of influenza virus hemagglutinin protein in vivo. These results contribute to our understanding of the roles of nitric oxide and peroxynitrite in influenza virus infections.

With the increasing resistance of Acinetobacter baumannii (A. baumannii) to antibiotics, researchers have turned their attention to the development of new antimicrobial agents. Among them, coumarin-based heterocycles have attracted much attention due to their unique biological activities, especially in the field of antibacterial infection. In this study, a series of coumarin derivatives were synthesized and screened for their bactericidal activities (Ren et al. 2018; Salehian et al. 2021). The inhibitory activities of these compounds on bacterial strains were evaluated, and the related mechanism of the new compounds was explored. Firstly, the MIC values and bacterial growth curves were measured after compound treatment to evaluate the antibacterial activity in vitro. Then, the in vivo antibacterial activities of the new compounds were assessed on A. baumannii-infected mice by determining the mice survival rates, counting bacterial CFU numbers, measuring inflammatory cytokine levels, and histopathology analysis. In addition, the ROS levels in the bacterial cells were measured with DCFH-DA detection kit. Furthermore, the potential target and detailed mechanism of the new compounds during infection disease therapy were predicted and evidenced with molecular docking. After that, ADMET characteristic prediction was completed, and novel, synthesizable, drug-effective molecules were optimized with reinforcement learning study based on the probed compound as a training template. The interaction between the selected structures and target proteins was further evidenced with molecular docking. This series of innovative studies provides important theoretical and experimental data for the development of new anti-A. baumannii infection drugs. [ABSTRACT FROM AUTHOR]

Objectives: Slow-growing nontuberculous mycobacteria (NTMs) are highly prevalent and routinely cause opportunistic intracellular infectious disease in immunocompromised hosts. Methods: The activity of the triple combination of antibiotics, clarithromycin (CLR), rifabutin (RFB), and clofazimine (CFZ), was evaluated and compared with the activity of single antibiotics as well as with double combinations in an in vitro biofilm assay and an in vivo murine model of Mycobacterium avium subsp. hominissuis (M. avium) lung infection. Results: Treatment of 1-week-old biofilms with the triple combination exerted the strongest effect of all (0.12 ± 0.5 × 107 CFU/mL) in reducing bacterial growth as compared to the untreated (5.20 ± 0.5 × 107/mL) or any other combination (≥0.75 ± 0.6 × 107/mL) by 7 days. The treatment of mice intranasally infected with M. avium with either CLR and CFZ or the triple combination provided the greatest reduction in CLR-sensitive M. avium bacterial counts in both the lung and spleen compared to any single antibiotic or remaining double combination by 4 weeks posttreatment. After 4 weeks of treatment with the triple combination, there were no resistant colonies detected in mice infected with a CLR-resistant strain. No clear relationships between treatment and spleen or lung organ weights were apparent after triple combination treatment. Conclusions: The biofilm assay data and mouse disease model efficacy results support the further investigation of the triple-antibiotic combination. [ABSTRACT FROM AUTHOR]

Human and animal infections due to multidrug-resistant bacterial pathogens are currently a global health threat. The design and development of antibacterial agents and alternative treatment strategies remain challenges in therapeutic and clinical applications. Herein, we loaded the flavone rutin onto carbon dots (R-CDs) using a one-step hydrothermal/self-assembly method. The minimum inhibitory concentration (MIC) of R-CDs against a methicillin-resistant Staphylococcus aureus (MRSA) strain was 32 μg/mL. MRSA exposed to R-CDs in vitro displayed evidence of cell membrane destruction and increased permeability, leading to a bactericidal effect. Efficient antibacterial effects were further demonstrated in vivo using a mouse model of pulmonary infection with MRSA. The R-CDs were also biocompatibility in vitro and in vivo. Therefore, the R-CDs have potential applications in the treatment of bacterial infections and are an alternative candidate to traditional antibiotic treatment. The present formulation is suitable for testing against MRSA infections in the lung. [ABSTRACT FROM AUTHOR]

Background: Kartagener syndrome (KS) is recognized as an inherited, autosomal recessive disorder characterized by a combination of chronic sinusitis, bronchiectasis, and situs inversus. It affects one in 12,500–50,000 live births worldwide. Aim: This paper aims to discuss the dental management of patients diagnosed with KS. Case Report: A 31‐year‐old male with KS manifests by impaired cilia motility which increases the risk of a frequent lung infection. The dental examination revealed that the patient required comprehensive oral hygiene care which included patient education and nonsurgical periodontal therapy under local anesthesia. Conclusions: Dental care providers should ask affected patients with KS about their signs and symptoms of cardiac and pulmonary disease and seek consultation with their attending physician regarding these health concerns before the initiation of general anesthesia and perhaps conscious sedation administration. Patients with KS with emerging cardiac and/or respiratory impairment should be referred promptly for medical assessment. [ABSTRACT FROM AUTHOR]

The production of alternative and effective medicines is crucial given that antibiotic resistance is currently a global health concern. Several biochemical identification tests were used to screen for Staphylococcus aureus isolates. Analysis of Artemisia annua extract was performed using a trace GC--mass spectrometer, which revealed that the A. annua extract contains numerous compounds, such as artemisinins, palmitic acid and other vital essential compounds that have antioxidant and anti-inflammatory properties. The isolate st.8 was resistant to cefoxitin, oxacillin, and cephalosporins; furthermore, MALDI-TOF/MS Biotyper® identified it as methicillin-resistant S. aureus with confidence value 99.9% of mass spectrum compared with reference spectra. The synthesis of green silver nanoparticles based on A. annua as a reducing agent was confirmed via partial characterizations: (HR-TEM), (XRD), (SEM), (EDX) and (FTIR) analysis. The significant of antibacterial activity of the new green material (AgNPs) was achieved by determining the agar well diffusion assay. Furthermore, compared with those in the Staphylococcus-infected group, a significant decrease in hematological parameters was observed, with an increase in antioxidant biomarkers, a decrease in interstitial tissue thickening by inflammatory cells, and a weak positive immune reaction in a few cells (TNF-α and iNOS) in rats. Overall, this study is a promising step toward the development of new and effective strategies for combating MRSA infections. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the antibacterial effect of Tanreqing (TRQ) against K. pneumoniae and its inhibition activity on bacterial biofilm formation in vitro and in vivo, and to explore the mechanism of the inhibitory effects of TRQ on K. pneumoniae biofilm formation. Methods: An in vitro biofilm model of K. pneumoniae was established, and the impact of TRQ on biofilm formation was evaluated using crystal violet staining and scanning electron microscopy (SEM). Furthermore, the clearance effect of TRQ against K. pneumoniae in the biofilm was assessed using the viable plate counting method; q-RT PCR was used to evaluate the inhibitory effect of different concentrations of TRQ on the expression of biofilm-related genes in Klebsiella pneumoniae; The activity of quorum sensing signal molecule AI-2 was detected by Vibrio harveyi bioluminescence assay; Meanwhile, a guinea pig lung infection model of Klebsiella pneumoniae was constructed, and after treated with drugs, pathological analysis of lung tissue and determination of bacterial load in lung tissue were performed. The treatment groups included TRQ group, imipenem(IPM) group, TRQ+IPM group, and sterile saline group as the control. Results: The formation of K. pneumoniae biofilm was significantly inhibited by TRQ in vitro experiments. Furthermore, when combined with IPM, the clearance of K. pneumoniae in the biofilm was notably increased compared to the TRQ group and IPM group alone. q-RT PCR analysis revealed that TRQ downregulated the expression of genes related to biofilm formation in K. pneumoniae, specifically luxS, wbbm, wzm, and lsrK, and also inhibited the activity of AI-2 molecules in the bacterium. In vivo experiments demonstrated that TRQ effectively treated guinea pig lung infections, resulting in reduced lung inflammation. Additionally, when combined with IPM, there was a significant reduction in the bacterial load in lung tissue. Conclusion: TRQ as a potential therapeutic agent plays a great role in the treatment of K. pneumoniae infections, particularly in combination with conventional antibiotics. And TRQ can enhanced the clearance effect on the bacterium by inhibiting the K. pneumoniae biofilm formation, which provided experimental evidence in support of clinical treatment of TRQ against K. pneumoniae infections. [ABSTRACT FROM AUTHOR]

Respiratory infection by Lophomonas blattarum is a rare opportunistic pathology, however, immunocompromised individuals are susceptible to contract this infection. The following is a case of Lophomonas blattarum pneumonia in a 44-year-old patient with Human Immunodeficiency Virus (HIV), who was admitted to the Regional Military Hospital of Puebla with respiratory distress, nonproductive cough, chest pain and fever; during his initial approach a presumptive positive HIV 1-2 Ac. test was detected. Imaging studies showed findings characteristic of pneumonia caused by atypical microorganisms, so empirical treatment with cephalosporin, macrolide, triazoles and sulfonamide was decided. The bronchial secretion culture revealed a multiflagellate protozoan parasite (L. blattarum), so pharmacological management was started with metronidazole with an impregnation dose of 1500 milligrams, continuing with 500 milligrams every 8 hours for 2 weeks, which resulted in improvement of symptoms and respiratory function. She concluded her stay at the Regional Hospital of Puebla, for follow-up and confirmation of HIV at the third level of care. Finally, despite antibiotic treatment, immunosuppressed patients, together with any opportunistic infection, mortality is present in more than 80%. [ABSTRACT FROM AUTHOR]

A major disease affecting individuals irrespective of the different ages is lung disease and this problem is a result of different causes. The recent spread of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected a huge community worldwide and has impacted the respiratory system adversely. The infection severity can be determined by inspecting the using X-ray images of the lung. In this work, a multilevel classification approach is presented, wherein the lung severity and COVID-19 prediction are executed based on Deep Learning (DL) technique. The contribution of this research is three-fold: (1) a novel Political Golden Search Algorithm (PGSA) was devised for routing the data accumulated from the nodes over the Internet of Things (IoT), (2) first-level classification was performed using the developed SqueezeNet-based technique, and it is optimized by the devised Taylor Political Golden Search Optimization (TPGSO) algorithm, to detect if COVID-19 is present or not, (3) second-level classification is accomplished using the TPGSO-deep convolutional neural network (DCNN) to categorize lung infection severity. The presented TPGSO-DCNN for second-level classification is examined for its performance based on testing accuracy, test negative rate (TNR), and test positive rate (TPR), and is established to have obtained values of 0.922, 0.926, and 0.909, respectively. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the impact of intraoperative infusion of recombinant human-activated coagulation factor VII (rFVIIa) on postoperative outcomes in patients with acute aortic dissection (AAD). Methods: This study involved 120 individuals who underwent aortic coarctation surgery between January 1, 2020, and December 31, 2022 in the First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China. The participants were divided into control (receiving only conventional treatment) and study (receiving rFVIIa infusion in addition to conventional treatment) groups. Various parameters, including patient status, postoperative measures, and complications were evaluated. Results: There was no significant difference in age, gender distribution, duration of myocardial block, onset time, or surgery duration (p > 0.05) between both groups. However, the study group exhibited longer extracorporeal circulation duration (p < 0.05). The study group also demonstrated lower levels of chest drainage compared to the control group 12 and 24 h after surgery (p < 0.05). Moreover, fewer concentrated red blood cells and fresh frozen plasma transfusions were administered to study group (p < 0.05). Despite having longer stays in the ICU (p < 0.05), the study group required less postoperative mechanical ventilation (p < 0.05). There was a significant difference in the incidence of postoperative thrombosis cases, positive gram-negative bacilli sputum culture results, and deaths within the study group (p < 0.05). Conclusion: Intraoperative rFVIIa infusion in AAD patients enhances short-term prognosis, with elevated risk of chest complications. However, further studies with larger sample sizes is essential to comprehensively assess clinical advantages and drawbacks. [ABSTRACT FROM AUTHOR]

Invasive fungal infection is a life-threatening complication of chemotherapy and neutropaenia in the haematology population. Trichoderma species rarely cause human disease but have been reported to cause invasive infection in the immunosuppressed. We present a case of invasive Trichoderma longibrachiatum pulmonary infection with fatal outcome in a neutropaenic patient with acute myeloid leukaemia. 2012 Elsevier Ltd. All rights reserved.

PurposeThe objective of this study was to create and validate a machine learning (ML)-based model for predicting the likelihood of lung infections following chemotherapy in patients with lung cancer.MethodsA retrospective study was conducted on a cohort of 502 lung cancer patients undergoing chemotherapy. Data on age, Body Mass Index (BMI), underlying disease, chemotherapy cycle, number of hospitalizations, and various blood test results were collected from medical records. We used the Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. Feature screening was performed using the Boruta algorithm and The Least Absolute Shrinkage and Selection Operator (LASSO). Subsequently, six ML algorithms, namely Logistic Regression (LR), Random Forest (RF), Gaussian Naive Bayes (GNB), Multi-layer Perceptron (MLP), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) were employed to train and develop an ML model using a 10-fold cross-validation methodology. The model’s performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (ROC), accuracy, sensitivity, specificity, F1 score, calibration curve, decision curves, clinical impact curve, and confusion matrix. In addition, model interpretation was performed by the Shapley Additive Explanations (SHAP) analysis to clarify the importance of each feature of the model and its decision basis. Finally, we constructed nomograms to make the predictive model results more readable.ResultsThe integration of Boruta and LASSO methodologies identified Gender, Smoke, Drink, Chemotherapy cycles, pleural effusion (PE), Neutrophil-lymphocyte count ratio (NLR), Neutrophil-monocyte count ratio (NMR), Lymphocytes (LYM) and Neutrophil (NEUT) as significant predictors. The LR model demonstrated superior performance compared to alternative ML algorithms, achieving an accuracy of 81.80%, a sensitivity of 81.1%, a specificity of 82.5%, an F1 score of 81.6%, and an AUC of 0.888(95%CI(0.863-0.911)). Furthermore, the SHAP method identified Chemotherapy cycles and Smoke as the primary decision factors influencing the ML model’s predictions. Finally, this study successfully constructed interactive nomograms and dynamic nomograms.ConclusionThe ML algorithm, combining demographic and clinical factors, accurately predicted post-chemotherapy lung infections in cancer patients. The LR model performed well, potentially improving early detection and treatment in clinical practice.