BACKGROUND: Dental Unit Water Line (DUWL) deliver water to different handpieces in a dental unit. The water in DUWL circulates in a closed system, where it is taken from a container. The quality of dental water is of considerable importance since patients and dental staff are regularly exposed to water and aerosols generated from dental equipment. Output water from DUWLs may be a potential source of infection for both dental health care personnel and patients.
OBJECTIVE: To assess the microbial contamination in the DUWL among dental clinics in Chennai.
METHODS: An in vitro study was conducted on 60 water samples from 20 dental clinics in Chennai in December 2019. Water samples were collected from three different sources of the Dental unit according to ADA guidelines. The collected samples were assessed for the presence of Aspergillus, Acinetobacter, Pseudomonas aeruginosa, and Legionella by agar plate method. The data were analysed using SPSS software version 20.
RESULTS: Legionella was the most prevalent microorganism with 70% prevalence in a three-way syringe and 50% in scaler and airotor, followed by Pseudomonas aeruginosa and Acinetobacter with 10% prevalence in scaler and airotor and Aspergillus with a prevalence of 10% in the three-way syringe.
CONCLUSIONS: Most of the dental units were contaminated with Aspergillus, Legionella, Pseudomonas aeruginosa and Acinetobacter which pose a serious threat to the patients as well as the dentists.

Pleural empyema is a serious complication of pneumonia in children. Negative bacterial cultures commonly impede optimal antibiotic therapy. To improve bacterial identification, we developed a molecular assay and evaluated its performance compared with bacterial culture. Our multiplex-quantitative PCR to detect Streptococcus pneumoniae, Streptococcus pyogenes, Staphylococcus aureus and Haemophilus influenzae was assessed using bacterial genomic DNA and laboratory-prepared samples (n = 267). To evaluate clinical performance, we conducted the Molecular Assessment of Thoracic Empyema (MATE) observational study, enrolling children hospitalised with empyema. Pleural fluids were tested by bacterial culture and multiplex-qPCR, and performance determined using a study gold standard. We determined clinical sensitivity and time-to-organism-identification to assess the potential of the multiplex-qPCR to reduce the duration of empiric untargeted antibiotic therapy. Using spiked samples, the multiplex-qPCR demonstrated 213/215 (99.1%) sensitivity and 52/52 (100%) specificity for all organisms. During May 2019-March 2023, 100 children were enrolled in the MATE study; median age was 3.9 years (IQR 2-5.6). A bacterial pathogen was identified in 90/100 (90%) specimens by multiplex-qPCR, and 24/100 (24%) by bacterial culture (P <0.001). Multiplex-qPCR identified a bacterial cause in 68/76 (90%) culture-negative specimens. S. pneumoniae was the most common pathogen, identified in 67/100 (67%) specimens. We estimate our multiplex-qPCR would have reduced the duration of untargeted antibiotic therapy in 61% of cases by a median 20 days (IQR 17.5-23, range 1-55). Multiplex-qPCR significantly increased pathogen detection compared with culture and may allow for reducing the duration of untargeted antibiotic therapy.

BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires\' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be prone to errors. We aimed to train a deep learning computer vision model to automatically detect cooling towers that are aerially visible.
METHODS: Between Jan 1 and 31, 2021, we extracted satellite view images of Philadelphia (PN, USA) and New York state (NY, USA) from Google Maps and annotated cooling towers to create training datasets. We augmented training data with synthetic data and model-assisted labelling of additional cities. Using 2051 images containing 7292 cooling towers, we trained a two-stage model using YOLOv5, a model that detects objects in images, and EfficientNet-b5, a model that classifies images. We assessed the primary outcomes of sensitivity and positive predictive value (PPV) of the model against manual labelling on test datasets of 548 images, including from two cities not seen in training (Boston [MA, USA] and Athens [GA, USA]). We compared the search speed of the model with that of manual searching by four epidemiologists.
RESULTS: The model identified visible cooling towers with 95·1% sensitivity (95% CI 94·0-96·1) and a PPV of 90·1% (95% CI 90·0-90·2) in New York City and Philadelphia. In Boston, sensitivity was 91·6% (89·2-93·7) and PPV was 80·8% (80·5-81·2). In Athens, sensitivity was 86·9% (75·8-94·2) and PPV was 85·5% (84·2-86·7). For an area of New York City encompassing 45 blocks (0·26 square miles), the model searched more than 600 times faster (7·6 s; 351 potential cooling towers identified) than did human investigators (mean 83·75 min [SD 29·5]; mean 310·8 cooling towers [42·2]).
CONCLUSIONS: The model could be used to accelerate investigation and source control during outbreaks of Legionnaires\' disease through the identification of cooling towers from aerial imagery, potentially preventing additional disease spread. The model has already been used by public health teams for outbreak investigations and to initialise cooling tower registries, which are considered best practice for preventing and responding to outbreaks of Legionnaires\' disease.
BACKGROUND: None.

This study aimed to develop a novel Gelatin silver oxide material for releasing nitric oxide bionanocomposite wound dressing with enhanced mechanical, chemical, and antibacterial properties for the treatment of diabetic wounds. The gelatin- silver oxide nanoparticles (Ag2O-NP) bio nanocomposite was prepared using chitosan and gelatin polymers incorporated with silver oxide nanoparticles through the freeze-drying method. The samples were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Results showed that the Ag2O-NP nanoparticles increased porosity, decreased pore size, and improved elastic modulus. The Ag2O-NP wound dressing exhibited the most effective antibacterial properties against Staphylococcus aureus and Escherichia coli. Among the samples, the wound dressing containing silver oxide nanoparticles demonstrated superior physical and mechanical properties, with 48% porosity, a tensile strength of 3.2 MPa, and an elastic modulus of 51.7 MPa. The fabricated wound dressings had a volume ratio of empty space to total volume ranging from 40% to 60%. In parallel, considering the complications of diabetes and its impact on the vascular system, another aspect of the research focused on developing a per2mediated wound dressing capable of releasing nitric oxide gas to regenerate damaged vessels and accelerate diabetic wound healing. Chitosan, a biocompatible and biodegradable polymer, was selected as the substrate for the wound dressing, and beta-glycerophosphate (GPβ), tripolyphosphate (TPP), and per2mediated alginate (AL) were used as crosslinkers. The chitosan-alginate (CS-AL) wound dressing exhibited optimal characteristics in terms of hole count and uniformity in the scanning electron microscope test. It also demonstrated superior water absorption (3854%) and minimal air permeability. Furthermore, the CS-AL sample exhibited an 80% degradation rate after 14 days, indicating its suitability as a wound dressing. The wound dressing was loaded with S-nitrosoglutathione (GSNO) powder, and the successful release of nitric oxide gas was confirmed through the grease test, showing a peak at a wavelength of 540 nm. Subsequent investigations revealed that the treatment of human umbilical vein endothelial cells (HUVECs) with high glucose led to a decrease in the expression of PER2 and SIRT1, while the expression of PER2 increased, which may subsequently enhance the expression of SIRT1 and promote cell proliferation activity. However, upon treatment of the cells with the modified materials, an increase in the expression of PER2 and SIRT1 was observed, resulting in a partial restoration of cell proliferative activity. This comprehensive study successfully developed per2-mediated bio-nanocomposite wound dressings with improved physical, mechanical, chemical, and antibacterial properties. The incorporation of silver oxide nanoparticles enhanced the antimicrobial activity, while the released nitric oxide gas from the dressing demonstrated the ability to mitigate vascular endothelial cell damage induced by high glucose levels. These advancements show promising potential for facilitating the healing process of diabetic wounds by addressing complications associated with diabetes and enhancing overall wound healing.

OBJECTIVE: Catheter removal is recommended in adults with S. aureus central line-associated bloodstream infection (CLABSI) but is controversial in children with long-term central venous catheters (LTCVC). We evaluated the occurrence of catheter salvage strategy (CSS) in children with S. aureus LTCVC-associated CLABSI and assessed determinants of CSS failure.
METHODS: We retrospectively included children (<18 years) with an LTCVC and hospitalized with S. aureus CLABSI in 8 French tertiary care hospitals (2010-2018). CSS was defined as an LTCVC left in place ≥ 72 hours after initiating empiric antibiotic treatment for suspected bacteremia. Characteristics of patients were reviewed, and multivariable logistic regression was performed to identify factors associated with CSS failure (i.e., persistence, recurrence, or complications of bacteremia).
RESULTS: We included 273 episodes of S. aureus LTCVC-associated CLABSI. CSS was chosen in 194 out of 273 (71%) cases and failed in 74 of them (38%). The main type of CSS failure was the persistence of bacteremia (39 out of 74 cases, 53%). Factors independently associated with CSS failure were: history of catheter infection (adjusted odds ratio [aOR] 3.18, 95% confidence interval [95%CI] 1.38-7.36), CLABSI occurring on an implantable venous access device (aOR 7.61, 95%CI 1.98-29.20) when compared with tunneled-cuffed CVC, polymicrobial CLABSI (aOR 3.45, 95%CI 1.25-9.50), and severe sepsis at the initial stage of infection (aOR 4.46, 95%CI 1.18-16.82).
CONCLUSIONS: CSS was frequently chosen in children with S. aureus LTCVC-associated CLABSI, and failure occurred in one-third of cases. The identified risk factors may help clinicians identify children at risk for CSS failure.

BACKGROUND: Infective endocarditis (IE) caused by MRSA (methicillin-resistant Staphylococcus aureus) is associated with a high mortality rate. This study aimed to elucidate the characteristics of patients with MRSA-IE in Japan and identify the factors associated with prognosis.
METHODS: This retrospective study included patients with a confirmed diagnosis of IE caused by MRSA, between January 2015 and April 2019.
RESULTS: A total of 65 patients from 19 centers were included, with a mean age of 67 years and 26 % were female. Fifty percent of the patients with IE were had nosocomial infections and 25 % had prosthetic valve involvement. The most common comorbidities were hemodialysis (20 %) and diabetes (20 %). Congestive heart failure was present in 86 % of patients (NYHA class I, II: 48 %; III, IV: 38 %). The 30-day and in-hospital mortality rates were 29 % and 46 %, respectively. Multi-organ failure was the primary cause of death, accounting for 43 % of all causes of death. Prognostic factors for in-hospital mortality were age, disseminated intravascular coagulation, daptomycin and/or linezolid as initial antibiotic therapy, and surgery. Surgical treatment was associated with a lower mortality rate (odds ratio [OR], 0.026; 95 % confidence interval [CI], 0.002-0.382; p = 0.008 for 30-day mortality and OR, 0.130; 95 % CI; 0.029-0.584; p = 0.008 for in-hospital mortality).
CONCLUSIONS: Mortality due to MRSA-IE remains high. Surgical treatment is a significant prognostic predictor of MRSA-IE.

BACKGROUND: Health care-associated infections due to multidrug-resistant organisms (MDROs), such as methicillin-resistant Staphylococcus aureus (MRSA) and Clostridioides difficile (CDI), place a significant burden on our health care infrastructure.
OBJECTIVE: Screening for MDROs is an important mechanism for preventing spread but is resource intensive. The objective of this study was to develop automated tools that can predict colonization or infection risk using electronic health record (EHR) data, provide useful information to aid infection control, and guide empiric antibiotic coverage.
METHODS: We retrospectively developed a machine learning model to detect MRSA colonization and infection in undifferentiated patients at the time of sample collection from hospitalized patients at the University of Virginia Hospital. We used clinical and nonclinical features derived from on-admission and throughout-stay information from the patient\'s EHR data to build the model. In addition, we used a class of features derived from contact networks in EHR data; these network features can capture patients\' contacts with providers and other patients, improving model interpretability and accuracy for predicting the outcome of surveillance tests for MRSA. Finally, we explored heterogeneous models for different patient subpopulations, for example, those admitted to an intensive care unit or emergency department or those with specific testing histories, which perform better.
RESULTS: We found that the penalized logistic regression performs better than other methods, and this model\'s performance measured in terms of its receiver operating characteristics-area under the curve score improves by nearly 11% when we use polynomial (second-degree) transformation of the features. Some significant features in predicting MDRO risk include antibiotic use, surgery, use of devices, dialysis, patient\'s comorbidity conditions, and network features. Among these, network features add the most value and improve the model\'s performance by at least 15%. The penalized logistic regression model with the same transformation of features also performs better than other models for specific patient subpopulations.
CONCLUSIONS: Our study shows that MRSA risk prediction can be conducted quite effectively by machine learning methods using clinical and nonclinical features derived from EHR data. Network features are the most predictive and provide significant improvement over prior methods. Furthermore, heterogeneous prediction models for different patient subpopulations enhance the model\'s performance.

We aimed to assess salivary and seroprevalence of Toxoplasma immunoglobulins in risky populations and evaluate drug docking targeting TgERP. A cross-sectional study was conducted in Alexandria University hospitals\' outpatient clinics. 192 participants were enrolled from September 2022 to November 2023. Anti-Toxoplasma IgG and IgM were determined in serum and saliva by ELISA. An in-Silico study examined TgERP\'s protein-protein interactions (PPIs) with pro-inflammatory cytokine receptors, anti-inflammatory cytokine, cell cycle progression regulatory proteins, a proliferation marker, and nuclear envelope integrity-related protein Lamin B1. Our findings revealed that anti-T. gondii IgG were detected in serum (66.1%) and saliva (54.7%), with 2.1% of both samples were positive for IgM. Salivary IgG had 75.59% sensitivity, 86.15% specificity, 91.40% PPV, 64.40% NPP, 79.17% accuracy and fair agreement with serum IgG. On the other hand, the sensitivity, specificity, PPV, NPV, and accuracy in detecting salivary IgM were 75.0%, 99.47%, 75.0%, 99.47%, and 98.96%. AUC 0.859 indicates good discriminatory power. Examined synthetic drugs and natural products can target specific amino acids residues of TgERP that lie at the same binding interface with LB1 and Ki67, subsequently, hindering their interaction. Hence, salivary samples can be a promising diagnostic approach. The studied drugs can counteract the pro-inflammatory action of TgERP.

BACKGROUND: Toxoplasma gondii is an intracellular protozoan parasite that is widely distributed in humans and warm-blooded animals. T. gondii chronic infections can cause toxoplasmic encephalopathy, adverse pregnancy, and male reproductive disorders. In male reproduction, the main function of the testis is to provide a stable place for spermatogenesis and immunological protection. The disorders affecting testis tissue encompass abnormalities in the germ cell cycle, spermatogenic retardation, or complete cessation of sperm development. However, the mechanisms of interaction between T. gondii and the reproductive system is unclear. The aims were to study the expression levels of genes related to spermatogenesis, following T. gondii infection, in mouse testicular tissue.
METHODS: RNA-seq sequencing was carried out on mouse testicular tissues from mice infected or uninfected with the T. gondii type II Prugniaud (PRU) strain and validated in combination with real-time quantitative PCR and immunofluorescence assays.
RESULTS: The results showed that there were 250 significant differentially expressed genes (DEGs) (P < 0.05, |log2fold change| ≧ 1). Bioinformatics analysis showed that 101 DEGs were annotated to the 1696 gene ontology (GO) term. While there was a higher number of DEGs in the biological process classification as a whole, the GO enrichment revealed a significant presence of DEGs in the cellular component classification. The Arhgap18 and Syne1 genes undergo regulatory changes following T. gondii infection, and both were involved in shaping the cytoskeleton of the blood-testis barrier (BTB). The number of DEGs enriched in the MAPK signaling pathway, the ERK1/2 signaling pathway, and the JNK signaling pathway were significant. The PTGDS gene is located in the Arachidonic acid metabolism pathway, which plays an important role in the formation and maintenance of BTB in the testis. The expression of PTGDS is downregulated subsequent to T. gondii infection, potentially exerting deleterious effects on the integrity of the BTB and the spermatogenic microenvironment within the testes.
CONCLUSIONS: Overall, our research provides in-depth insights into how chronic T. gondii infection might affect testicular tissue and potentially impact male fertility. These findings offer a new perspective on the impact of T. gondii infection on the male reproductive system.

OBJECTIVE: Immunity alterations have been observed in bipolar disorder (BD). However, whether serum positivity of antibodies to Toxoplasma gondii (T gondii), rubella, and cytomegalovirus (CMV) shared clinical relevance with BD, remains controversial. This study aimed to investigate this association.
METHODS: Antibody seropositivity of IgM and IgG to T gondii, rubella virus, and CMV of females with BD and controls was extracted based on medical records from January 2018 to January 2023. Family history, type of BD, onset age, and psychotic symptom history were also collected.
RESULTS: 585 individuals with BD and 800 healthy controls were involved. Individuals with BD revealed a lower positive rate of T gondii IgG in the 10-20 aged group (OR = 0.10), and a higher positive rate of rubella IgG in the 10-20 (OR = 5.44) and 20-30 aged group (OR = 3.15). BD with family history preferred a higher positive rate of T gondii IgG (OR = 24.00). Type-I BD owned a decreased positive rate of rubella IgG (OR = 0.37) and an elevated positive rate of CMV IgG (OR = 2.12) compared to type-II BD, while BD with early onset showed contrast results compared to BD without early onset (Rubella IgG, OR = 2.54; CMV IgG, OR = 0.26). BD with psychotic symptom history displayed a lower positive rate of rubella IgG (OR = 0.50).
CONCLUSIONS: Absence of male evidence and control of socioeconomic status and environmental exposure.
CONCLUSIONS: Differential antibody seropositive rates of T gondii, rubella, and cytomegalovirus in BD were observed.