Extracellular vesicles (EVs) are nano-sized particles released from cells into the extracellular environment, and are separated from eukaryotic cells, bacteria, and other organisms with cellular structures. EVs alter cell communication by delivering their contents and performing various functions depending on their cargo and release into certain environments or other cells. The cell walls of Gram-positive bacteria have a thick peptidoglycan layer and were previously thought to be unable to produce EVs. However, recent studies have demonstrated that Gram-positive bacterial EVs are crucial for health and disease. In this review, we have summarized the formation, composition, and characteristics of the contents, resistance to external stress, participation in immune regulation, and other functions of Gram-positive bacterial EVs, as well as their application in clinical diagnosis and treatment, to provide a new perspective to further our understanding of Gram-positive bacterial EVs.

Background: High-risk human papillomavirus type 16 (HPV16) is a risk factor for cervical cancer. Previous studies suggest that polymorphisms in the E6 gene or the long control region(LCR)of HPV16 may alter the oncogenic potential of the virus. The aims of this study were to investigate the genetic variations of HPV16 E6 gene and LCR in isolates from Chinese population and correlation of the E6 and LCR polymorphisms with disease status of infected patients. Methods: HPV16 positive endocervical specimens were collected from 304 women living in Northeast of China. Sequences of E6 gene and LCR were analyzed by PCR-sequencing. Results: Two lineages were found in the populations, including EUR lineage and As lineage. Based on the HPV16 prototype, the most frequent variation in the E6 gene was T178A/G (48.7%), followed by mutations of G94A (12.2%) and T350G (9.9%). The rank orders of incidence of E6 variations in amino acid were as follows: D25E (46.3%), L83V (9.9%) and H78Y (4.3%). Nucleotide variations in LCR were found in all the 304 isolates from HPV16 positive cervical samples. The most commonly observed LCR variations were the transition replacement G7193T, 7434CIns, G7521A and 7863ADel (100%). The As lineage was associated with HPV persistent infections and with disease status of ≥CIN2,3. The EUR lineage variants showed a negative trend of association with the severity of ≥CIN2,3. Among 41 variations found in LCR, 25 (61.0%) were located at the binding sites for transcription factors. Occurrence of ≥CIN2,3 was significantly associated with the mutations of R10G/L83V in E6 and the C7294T co-variation in LCR, after adjusting for ages of infected patients. Conclusions: Associations between As lineage and HPV persistent infections, and with disease status of ≥CIN2,3, and an association between the EUR lineage and negative trend of association with the severity of ≥CIN2,3 were found in this study. An association between a co-variation of R10G/L83V in E6 and C7294T in LCR and an increased risk for developing CIN-2,3 was found in a HPV16 infected population of Chinese women. These findings indicate that HPV16 polymorphism influences development of CIN-2,3.

Background: Pneumonia caused by 2019 novel coronavirus (2019-nCoV) was first reported in Wuhan, Hubei Province, China in December 2019. Then it has been reported in more than 20 countries and regions overseas rapidly. More than eighty thousand cases have been infected, resulting in more than three thousand deaths. Due to the limitation of nucleic acid detection, many clinical suspected cases cannot be diagnosed in time. Methods: We used automated chemiluminescent immunoassay to detect serum IgM and IgG antibodies to 2019-nCoV of 736 subjects including confirmed Corona Virus Disease 2019 (COVID-19) patients, non-COVID-19 fever patients, other disease patients and medical staff as well as healthy people. The dynamic process of antibody production in COVID-19 disease progression were analyzed, and the value of antibody detection in the laboratory diagnosis of COVID-19 were evaluated. Results: COVID-19 patients were becoming reactive(positive) for specific anti-2019-nCoV IgM antibodies from 7-12 days after the onset of morbidity, followed closely by the IgG. The levels of specific IgM and IgG antibodies increased with the progression of the disease. The trend of IgM and IgG changes in different cases is not exactly the same. The levels of IgM and IgG and their distributions in different groups were different with that of healthy people. The areas under the ROC curves for IgM and IgG to diagnose COVID-19 were 0.988 and 1.000, respectively. Conclusions: Specific IgM or IgG antibody detection had good sensitivity and specificity for the diagnosis of suspected fever cases. Detection of specific antibodies in patients with fever can be a good distinction between COVID-19 and other diseases in low epidemic area.

Streptococcus pneumoniae is a common pathogen associated with community-acquired bacterial meningitis, characterized by high morbidity and mortality rates. While vaccination reduces the incidence of meningitis, many survivors experience severe brain damage and corresponding sequelae. The pathogenesis of pneumococcal meningitis has not been fully elucidated. Currently, meningitis requires bacterial disruption of the blood - brain barrier, a process that involves the interaction of bacterial surface components with host cells and various inflammatory responses. This review delineates the global prevalence, pathogenesis, and treatment strategies of pneumococcal meningitis. The objective is to enhance the thorough comprehension of the clinical manifestations and biological mechanisms of the disease, thereby enabling more efficient prevention, diagnosis, and therapeutic interventions.

SUMMARY: Streptococcus pneumoniae ( S. pneumoniae ) is a major human pathogen that can cause severe diseases such as meningitis and bacteremia. β-lactam antibiotics are the most essential antimicrobial agents for treating S. pneumoniae infections, but the resistance has become a significant challenge in clinical therapy. Analyses reveal notable regional disparities in the prevalence of β-lactam resistance in S. pneumoniae . The use of pneumococcal conjugate vaccines effectively reduces the spread of highly resistant clones, indirectly improving resistance patterns. Interestingly, resistance is inversely correlated with bacterial invasiveness, suggesting mutual selective pressures. Additionally, the COVID-19 pandemic may have influenced the evolution of S. pneumoniae resistance by altering host immune states and healthcare resource allocation. Immunocompromised patients face a higher risk of invasive pneumococcal disease, driving increased antimicrobial use that fuels the rise of resistance. Beyond the single-molecular mechanism, the resistance gene acquisition order plays a critical role in the successful resistance evolution. Analyzing the dynamic principles and key nodes involved in the evolution of drug resistance could offer novel insights for developing precise antibacterial treatment strategies. Current research efforts focus on the development of novel antibiotics, antimicrobial peptides, lysins, and other innovative therapeutic agents. Artificial intelligence shows immense potential in the screening of antimicrobial drugs and the prediction of resistance mechanisms. This review synthesizes recent advances in the epidemiology, molecular mechanisms, and management of β-lactam resistance in S. pneumoniae , with the aim of informing evidence-based antimicrobial stewardship and accelerating the development of innovative therapeutics to combat this evolving public health threat.