BACKGROUND: Legionella pneumonia is one of the most severe types of atypical pneumonia, impairing multiple organ systems, posing a threat to life. Diagnosing Legionella pneumonia is challenging due to difficulties in culturing the bacteria and limitations in immunoassay sensitivity and specificity.
METHODS: This paper reports a rare case of sepsis caused by combined infection with Legionella pneumophila and Fusobacterium necrophorum, leading to respiratory failure, acute kidney injury, acute liver injury, myocardial damage, and electrolyte disorders. In addition, we systematically reviewed literature on patients with combined Legionella infections, analyzing their clinical features, laboratory results and diagnosis.
CONCLUSIONS: For pathogens that require prolonged incubation periods and are less sensitive to conventional culturing methods, metagenomic next-generation sequencing (mNGS) can be a powerful supplement to pathogen screening and plays a significant role in the auxiliary diagnosis of complex infectious diseases.

BACKGROUND: Q fever, a zoonotic disease caused by Coxiella burnetii (C. burnetii), presents diagnostic challenges due to its clinical and radiological nonspecificity, which often mimics community-acquired pneumonia, coupled with the limitations of traditional diagnostic methods. Metagenomic next-generation sequencing (mNGS) has become an indispensable tool in clinical diagnostics for its high-throughput pathogen identification capabilities. Herein, we detail a case of acute Q fever pneumonia diagnosed with mNGS.
METHODS: The patient exhibited symptoms of fever, cough, expectoration, and diarrhea for three days, with the pathogen undetected in initial laboratory assessments. Bronchoscopy and bronchoalveolar lavage (BAL) were conducted, leading to the identification of C. burnetii in the lavage fluid via mNGS. Consequently, the patient was promptly initiated on a treatment regimen of 100 mg doxycycline, administered orally every 12 hours.
RESULTS: Post-treatment, the patient\'s temperature normalized, and a full recovery was observed. The follow-up chest CT scan revealed complete resolution of the right lower lobe consolidation.
CONCLUSIONS: The clinical presentation of Q fever pneumonia lacks specificity, making diagnosis based solely on symptoms and imaging challenging. mNGS offers a superior alternative for identifying elusive or rarely cultured pathogens.

UNASSIGNED: Pneumonia is a common infection in the intensive care unit (ICU), and gram-negative bacilli are the most common bacterial cause. The purpose of the study was to investigate the risk factors for 30-day mortality in patients with gram-negative bacillary pneumonia in the ICU, construct a predictive model, and stratify patients based on risk to assess their short-term survival.
UNASSIGNED: Patients admitted to the ICU with gram-negative bacillary pneumonia at Fujian Medical University Affiliated First Hospital between January 2018 and September 2020 were selected. Patients were divided into deceased and survivor groups based on whether death occurred within 30 days. Multifactorial logistic regression analysis was used to identify independent risk factors for 30-day mortality in these patients, and a predictive nomogram model was constructed based on these factors. Patients were categorized into low-, medium-, and high-risk groups according to the model\'s predicted probability, and Kaplan-Meier survival curves were plotted to assess short-term survival.
UNASSIGNED: The study included 305 patients. Lactic acid (odds ratio [OR], 1.524, 95% CI: 1.057-2.197), tracheal intubation (OR: 4.202, 95% CI: 1.092-16.169), and acute kidney injury (OR:4.776, 95% CI: 1.632-13.978) were identified as independent risk factors for 30-day mortality. A nomogram prediction model was established based on these three factors. Internal validation of the model showed a Hosmer-Lemeshow test result of X2=5.770, P=0.834, and an area under the ROC curve of 0.791 (95% CI: 0.688-0.893). Bootstrap resampling of the original data 1000 times yielded a C-index of 0.791, and a decision curve analysis indicated a high net benefit when the threshold probability was between 15%-90%. The survival time for low-, medium-, and high-risk patients was 30 (30, 30), 30 (16.5, 30), and 17 (11, 27) days, respectively, which were significantly different.
UNASSIGNED: Lactic acid, tracheal intubation, and acute kidney injury were independent risk factors for 30-day mortality in patients in the ICU with gram-negative bacillary pneumonia. The predictive model constructed based on these factors showed good predictive performance and helped assess short-term survival, facilitating early intervention and treatment.

BACKGROUND: A. baumannii is an important and common clinical pathogen, especially in the intensive care unit (ICU). This study aimed to characterize one hypervirulent A. baumannii strain in a patient with community-acquired pneumonia and herpes simplex type 1 virus infection.
METHODS: Minimum inhibitory concentrations (MICs) were determined using the Kirby-Bauer (K-B) and broth microdilution methods. Galleria mellonella infection model experiment was conducted. Whole-genome sequencing (WGS) was performed using the Illumina and Nanopore platforms. The resistance and virulence determinants were identified using the ABRicate program with ResFinder and the VFDB database. The capsular polysaccharide locus (K locus) and lipooligosaccharide outer core locus (OC locus) were identified using Kleborate with Kaptive. Phylogenetic analyses were conducted using the BacWGSTdb server.
RESULTS: A. baumannii XH2146 strain belongs to ST10Pas and ST447Oxf. The strain was resistant to cefazolin, ciprofloxacin, and trimethoprim/sulfamethoxazole (TMP-SMX). Bautype and Kaptive analyses showed that XH2146 contains OCL2 and KL49. WGS analysis revealed that the strain harbored blaADC-76, blaOXA-68, ant(3\'\')-IIa, tet(B), and sul2. Notably, tet(B) and sul2, both were located within a 114,700-bp plasmid (designated pXH2146-1). Virulence assay revealed A. baumannii XH2146 possessed higher virulence than A. baumannii AB5075 at 12 h. Comparative genomic analysis showed that A. baumannii ST447 strains were mainly isolated from the USA and exhibited a relatively close genetic relationship. Importantly, 11 strains were observed to carry blaOXA-58; blaOXA-23 was identified in 11 isolates and three ST447 A. baumannii strains harbored blaNDM-1.
CONCLUSIONS: Early detection of community-acquired hypervirulent Acinetobacter baumannii strains is recommended to prevent their extensive spread in hospitals.

BACKGROUND: Community-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis.
METHODS: We conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced.
RESULTS: The sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections.
CONCLUSIONS: Collectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

Cold-inducible RNA-binding protein (CIRP) is a damage-associated molecular pattern that plays a critical role in triggering inflammatory responses. It remains unknown whether CIRP is strongly associated with bacterial load, inflammatory response, and mortality in sepsis model. Pneumonia was induced in specific pathogen-free 8-9-week old male rats by injecting bacteria via puncture of the tracheal cartilage. The expressions of CIRP and proinflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and IL-1β] in lung tissues, alveolar macrophages (AMs), plasma, and bronchoalveolar lavage fluid (BALF) were determined by reverse transcription-polymerase chain reaction, western blotting, and enzyme-linked immunosorbent assay. The numbers of bacteria recovered from the lungs were correlated with the bacterial loads injected and mortality. The expressions of CIRP increased sharply as the bacterial loads increased in the lung tissues and AMs. The amounts of TNF-α, IL-6 and IL-1β proteins synthesized were dependent on the bacterial load in the lung tissues. Releases of CIRP, TNF-α, IL-6, and IL-1β increased with the bacterial load in the blood plasma. The proteins confirmed similar patterns in the BALF. CIRP was strongly associated with the releases of TNF-α, IL-6, and IL-1β in the lung tissues, blood plasma, and BALF, and showed a close correlation with mortality. CIRP demonstrated a strong association with bacterial load, which is new evidence, and close correlations with proinflammatory cytokines and mortality of pneumonia in rats, suggesting that it might be an interesting pneumonic biomarker for monitoring host response and predicting mortality, and a promising target for immunotherapy.

The immune dysregulation associated with carbapenem-resistant Klebsiella pneumoniae (CRKP) severity was investigated through single-cell RNA sequencing (scRNA-seq) of 5 peripheral blood samples from 3 patients with moderate and severe CRKP pneumonia. Additionally, scRNA-seq datasets from two individuals with COVID-19 were included for comparative analysis. The dynamic characterization and functional properties of each immune cell type were examined by delineating the transcriptional profiles of immune cells throughout the transition from moderate to severe conditions. Overall, most immune cells in CRKP patients exhibited a robust interferon-α response and inflammatory reaction compared to healthy controls, mirroring observations in COVID-19 patients. Furthermore, cell signatures associated with NK cells, macrophages, and monocytes were identified in CRKP progression including PTPRCAP for NK cells, C1QB for macrophages, and S100A12 for both macrophages and monocytes. In summary, this study offers a comprehensive scRNA-seq resource for illustrating the dynamic immune response patterns during CRKP progression, thereby shedding light on the associations between CRKP and COVID-19.

This study aimed to investigate the expression and significance of serum procalcitonin (PCT), leukotriene B4 (LTB4), Serum amyloid A (SAA), and C-reactive protein (CRP) in children with different types of pneumonia caused by different pathogenic infections. One hundred and one children with pneumonia admitted to The Fifth People Hospital of Zhuhai from July 2019 to June 2020 were enrolled and divided into 38 cases in the bacterial group, 30 cases in the mycoplasma group, and 33 cases in the virus group according to the different types of pathogens. The patients were divided into 42 cases in the noncritical group, 33 cases in the critical group, and 26 cases in the very critical group according to the pediatric clinical illness score (PCIS), and 30 healthy children were selected as the control group during the same period. Comparison of serum PCT, SAA: bacterial group > mycoplasma group > viral group > control group with significant differences (P < .05). Receiver operator characteristic (ROC) analysis showed that the area under the curves (AUCs) of serum PCT, LTB4, SAA, and CRP for the diagnosis of bacterial pneumonia were 1.000, 0.531, 0.969, and 0.833, respectively, and the AUCs for the diagnosis of mycoplasma pneumonia were 0.653, 0.609, 0.547, and 0.652, respectively, and the AUCs for the diagnosis of viral pneumonia were 0.888, 0.570, 0.955, and 1.000, respectively. Comparison of serum PCT, LTB4, SAA: very critical group > critical group > noncritical group > control group, with significant differences (P < .05). Serum PCT, LTB4, and SAA were negatively correlated with PCIS score by Pearson analysis (P < .05). Serum PCT and SAA showed diagnostic value for bacterial pneumonia, and serum SAA and CRP showed diagnostic value for viral pneumonia; serum PCT, LTB4, and SAA correlate with severity of disease and show higher expression with worsening of the condition.

BACKGROUND: The connections between fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) and daily mortality of viral pneumonia and bacterial pneumonia were unclear.
OBJECTIVE: To distinguish the connections between PM2.5 and PM2.5-10 and daily mortality due to viral pneumonia and bacterial pneumonia.
METHODS: Using a comprehensive national death registry encompassing all areas of mainland China, we conducted a case-crossover investigation from 2013 to 2019 at an individual level. Residential daily particle concentrations were evaluated using satellite-based models with a spatial resolution of 1 km. To analyze the data, we employed the conditional logistic regression model in conjunction with polynomial distributed lag models.
RESULTS: We included 221,507 pneumonia deaths in China. Every interquartile range (IQR) elevation in concentrations of PM2.5 (lag 0-2 d, 37.6 μg/m3) was associated with higher magnitude of mortality for viral pneumonia (3.03%) than bacterial pneumonia (2.14%), whereas the difference was not significant (p-value for difference = 0.38). An IQR increase in concentrations of PM2.5-10 (lag 0-2 d, 28.4 μg/m3) was also linked to higher magnitude of mortality from viral pneumonia (3.06%) compared to bacterial pneumonia (2.31%), whereas the difference was not significant (p-value for difference = 0.52). After controlling for gaseous pollutants, their effects were all stable; however, with mutual adjustment, the associations of PM2.5 remained, and those of PM2.5-10 were no longer statistically significant. Greater magnitude of associations was noted in individuals aged 75 years and above, as well as during the cold season.
CONCLUSIONS: This nationwide study presents compelling evidence that both PM2.5 and PM2.5-10 exposures could increase pneumonia mortality of viral and bacterial causes, highlighting the more robust effects of PM2.5 and somewhat higher sensitivity of viral pneumonia.

OBJECTIVE: To study the etiological characteristics of community-acquired pneumonia (CAP) combined with type 2 diabetes (T2D), providing a reference for early clinical diagnosis and treatment of the disease.
METHODS: We selected a total of 93 patients with CAP and analyzed their metagenomics nextgeneration sequencing (mNGS) data. The case group comprised 46 patients with combined CAP/T2D, and the control group comprised 47 patients without diabetes. We analyzed the pathogenic findings of the two groups.
RESULTS: There were statistically significant differences in age between the two groups (P = 0.001). Leukocytes (P = 0.012), blood platelets (P = 0.034), fibrinogen (P = 0.037), D-dimer (P = 0.000), calcitonin ogen (P = 0.015), ultrasensitive C-reactive protein or C-reactive protein (CRP) (P = 0.000), serum amyloid A (P = 0.000), and erythrocyte sedimentation rate (P = 0.003) were higher in the case group than in the control group. Albumin was lower in the case group than in the control group. All differences were statistically significant. The infection rates of Klebsiella pneumoniae (P = 0.030), Pseudomonas aeruginosa (P = 0.043), and Candida albicans (P = 0.032) were significantly different between the two groups.
CONCLUSIONS: Compared with those without diabetes, the infection rates of Klebsiella pneumoniae, Pseudomonas aeruginosa, and Candida albicans were higher in patients with combined CAP/T2D.