[System analysis of the ecological distribution of bacteriophages in hospital wastewater]

Phage therapy is one of the most important tools for the treatment of infections with multi-drug resistant bacteria. Such phages are usually isolated from hospital effluents, however, no systematic study on the distribution of phages in hospital effluents has been conducted so far. The aim of this study was to isolate the corresponding phages of common pathogenic bacteria isolated in the clinic as hosts, so as to assess the ecological distribution of phages in hospital wastewater and to provide a reference for the isolation and application of phages of drug-resistant bacteria in the clinic. A cross-sectional study design was used in this study. The 125 pathogenic bacteria (belonging to 16 different strains) isolated from the clinical microbiology laboratory of Qilu Hospital of Shandong University from May to June 2023 were selected as the target strains, and the phages corresponding to these strains were isolated and purified from the hospital wastewater by using the double-layer plate sandwich method. At the same time, the distribution of pathogenic bacteria in the same batch of wastewater was analyzed with the help of mNGS sequencing technology, so as to preliminarily investigate the abundance correspondence between pathogenic bacteria and phages in wastewater. The results showed that a total of 56 phage strains were isolated from 125 clinical pathogens as hosts, corresponding to six pathogens, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. All six pathogenic bacteria contained strains with different degrees of drug resistance, with a higher percentage of multi-drug resistant strains in A. baumannii, Escherichia coli and P. aeruginosa. The phage acquisition rates of these six pathogens were, in descending order, Escherichia coli (80%), Stenotrophomonas maltophilia (75%), Pseudomonas aeruginosa (70%), Klebsiella pneumoniae (66.67%), Acinetobacter baumannii (36.36%) and Staphylococcus aureus (12.5%). Preliminary mNGS sequencing results showed that the pathogenic bacteria with higher abundance in the batch of effluent were Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Klebsiella aerogenes, Klebsiella michiganensis and Pseudomonas aeruginosa. In conclusion, phages of most common clinical Gram-negative pathogens were isolated from hospital wastewater with high isolation rates; however, phages of Gram-positive pathogens were isolated at lower rates, and only phages corresponding to Staphylococcus aureus were isolated in this study. The corresponding mNGS sequencing results showed that the distribution of Gram-negative pathogens in sewage may had a positive correlation with the ecological distribution of phages.

[Establishment and validation of a new predictive equation with multiple risk factors for the development of cardiorenal syndrome type 1 in patients with acute myocardial infarction]

Objective: To investigate the independent risk factors of cardiorenal syndrome type 1 (CRS1) in patients with acute myocardial infarction (AMI) and to build a predictive equation for the development of CRS1 in these patients. Method: Consecutive inpatients with AMI, who hospitalized from January 2017 to December 2018 in the Hunan Provincial People's Hospital, were enrolled in this case-control study. Patients were divided into CRS1 group and non-CRS1 group according to the presence or absence of CRS1.The clinical data were collected through the electronic medical record system of Hunan Provincial People's Hospital. The matching process was conducted with a minimum-distance scoring method and a 1∶1 match between the CRS1 group and the no-CRS1 group, the propensity score was calculated through the logistic regression model. Factors with statistically significant differences in univariate analysis were included in the multivariate logistic regression model to analyze the risk factors of AMI patients with CRS1, then the independent risk factors were used to establish a predicting equation for CRS1 by logistic regression function for model building. Area under the curve (AUC) value and the best cut-off value of the combined predictors was determined according to the ROC curve. Python 3.8 software was used to perform 10-fold cross-validation on modeling samples. Results: A total of 942 patients were included, there were 113 cases in CRS1 group and 829 cases in non-CRS1 group. Ultimately, 99 CRS1 patients were successfully matched to 99 non-CRS1 patient using 1∶1 matching. After propensity score matching, the baseline age and sex along with heart rate, mean arterial pressure, percentage of people with a history of diabetes, hypertension, ST-segment elevation myocardial infarction, myocardial ischemia time, angiotensin converting enzyme inhibitors or angiotensin Ⅱ receptor blockers use, and β receptor blocker use were similar between the two groups(all P>0.05). The contrast agent dosage was also similar between the two groups (P=0.266). The peak cardiac troponin I (cTnI), N-terminal pro-brain natriuretic peptide(NT-proBNP), white blood cell count, base estimated glomerular filtration rate (eGFR), albumin and hemoglobin levels were statistically significant between the two groups (all P<0.05). Multivariate logistic regression analysis showed that decreased baseline eGFR, increased NT-proBNP, peak cTnI concentrations and white blood cell count were independent risk factors of CRS1 in AMI patients (all P<0.01).The predicting equation of the combined predictor was established by transforming the logistic model equation, L=0.031×cTnI+0.000 2×NT-proBNP-0.024×eGFR+0.254×white blood cell count, where L represented the combined predictor. ROC curve analysis indicated that the AUC of the peak cTnI, NT-proBNP, baseline eGFR, white blood cell count, and combined predictor were 0.76, 0.85, 0.79, 0.81, and 0.92 respectively (all P<0.05), and the cutoff value of combined predictor was 2.6. The AUC of ROC curve after the model's ten-fold cross validation was 0.89. Conclusions: Decreased baseline eGFR, increased NT-proBNP, peak cTnI concentrations and white blood cell count are the independent risk factors for CRS1 in AMI patients. The combined predictor equation based on the above 4 biomarkers presents a good predictive value for CRS1 in AMI patients.

[Association between dust exposure and the risk of hypertension of male coal miners in Henan Province]

Objective: To explore the association between dust exposure and the incidence of hypertension in male coal miners. Methods: Using the method of retrospective cohort study,a hypertension cohort of colliery in Henan Province was established in January 2006. From 2006 to 2017,all the male coal miners in a colliery who were exposed to dust were selected into the exposure group including tunneling, mining,auxiliary and combining workers, and workers from administrative logistics departments who were not exposed to dust were selected into the control group. The eligible participants should satisfy following conditions: working more than one year, with clear and complete record of occupation change, and with complete archives and reliable diagnosis of occupational health surveillance. The exclusion criteria of participants were with hypertension at the baseline of study or with heart,liver,kidney diseases and malignant tumors. A total of 12 647 participants were enrolled in this study (11 663 in the exposure group and 984 in the control group). The follow-up period was from January 2006 to December 2017,with a total follow-up of 89 259.75 person-years. Questionnaires and physical measurements were used to collect general demographic characteristics, occupational exposure history and occupational health surveillance data of all participants. The Cox proportional hazards regression model was used to estimate the association between the dust exposure and the incidence of hypertension. Results: During the follow-up period, 2 549 new-onset hypertension patients were identified with an incidence density of hypertension about 2 855.71 per 100 000 person-years. The incidence density of hypertension was 2 967.58 per 100 000 person-years in the exposure group, and 1 643.85 per 100 000 person-years in the control group. The results of multivariate Cox proportional hazards regression model showed that after the adjustment of marriage, age, smoking, alcohol drinking and body mass index,the risk of hypertension was higher in the exposure group compared with the control group (HR=1.692, 95%CI: 1.410-2.032). Further analysis showed that compared with workers from administrative logistics departments,the risk of hypertension in tunneling,mining and auxiliary working was 1.629(1.345-1.973),1.677(1.374-2.046) and 1.782(1.475-2.151),respectively. Conclusion: Dust exposure may increase the risk of hypertension in male coal miners.

C-reactive protein predicts systolic blood pressure and pulse pressure but not diastolic blood pressure: the Cardiovascular Disease Risk Factors Two-Township Study

OBJECTIVE

Inflammation has been associated with cardiovascular events and mortality, using C-reactive protein (CRP) as a marker. We examined whether the baseline serum concentration of CRP can independently predict the development of hypertension or future systolic or diastolic blood pressure (BP) in a community-based population in Taiwan.

METHODS

A study population sample was recruited in cycle 2 (1990-1993) of the CardioVascular Disease risk FACtors Two-township Study (CVDFACTS) and was followed to 1994-1997. A total of 2,113 nondiabetic adults with normal BP were enrolled for the study of incident hypertension. Hypertension was defined as a systolic blood pressure (SBP) ≥ 140 mm Hg, a diastolic blood pressure (DBP) ≥ 90 mm Hg, or the use of antihypertensive drugs. Cox regression and linear regression analyses were used to evaluate the association between baseline serum concentrations of CRP measured with a high-sensitivity assay and the development of hypertension and future SBP/DBP and pulse pressure (PP).

RESULTS

During the follow-up period of a median of 3.27 years, 145 participants developed incident hypertension. The incidence rates of hypertension by tertile of increasing CRP were 9.3, 19.0, and 33.0 per 1,000 person-years (P for trend < 0.01). In the multivariate model adjusted for age, gender, and prehypertension, baseline CRP remained significantly predictive of incident hypertension. The concentration of CRP was associated with SBP and PP, but not with DBP.

CONCLUSION

Inflammation is associated with future SBP in the Taiwanese population.

Common polymorphism near the MC4R gene is associated with type 2 diabetes: data from a meta-analysis of 123,373 individuals

AIMS/HYPOTHESIS

Genome-wide association studies have shown that variants near the melanocortin 4 receptor gene (MC4R) (rs17782313 and rs12970134) are associated with risk of obesity in Europeans. As obesity is associated with an increased risk of type 2 diabetes, many studies have investigated the association between polymorphisms near the MC4R gene and type 2 diabetes risk across different ethnic populations, with inconsistent results. In this study, we performed a meta-analysis to clarify the association of variants near MC4R with type 2 diabetes risk.

METHODS

Published literature from PubMed and Embase was retrieved. All studies that evaluated the association of at least one of the two MC4R polymorphism(s) with type 2 diabetes were included in the study. Pooled ORs with 95% CIs were calculated using the fixed-effects model.

RESULTS

A total of 19 studies (comprising 34,195 cases and 89,178 controls) of the rs17782313 polymorphism (or its proxy rs12970134) were included in the meta-analysis. The results indicated that the rs17782313 polymorphism was significantly associated with type 2 diabetes risk among the overall study population (OR 1.10, 95% CI 1.07, 1.13, p = 2.83 × 10(-12) [Z test], I(2) = 9.1%, p = 0.345 [heterogeneity]). The association remained significant even after adjustment for body mass index (BMI) (OR 1.06, 95% CI 1.03, 1.09, p = 2.14 × 10(-5) [Z test], I(2) = 4.9%, p = 0.397 [heterogeneity]). Further sensitivity analysis confirmed the statistically significant association of rs17782313 polymorphism with type 2 diabetes, and no publication bias was detected.

CONCLUSIONS/INTERPRETATION

The present meta-analysis confirmed the significant association of the rs17782313 polymorphism near the MC4R gene with type 2 diabetes risk, which was independent of BMI.