Emergence of multiple fluconazole-resistant Candida parapsilosis sensu stricto clones with persistence and transmission in China.

OBJECTIVES: We explored the epidemiological and molecular characteristics of Candida parapsilosis sensu stricto isolates in China, and their mechanisms of azole resistance. METHODS: Azole susceptibilities of 2318 non-duplicate isolates were determined using CLSI broth microdilution. Isolates were genotyped by a microsatellite typing method. Molecular resistance mechanisms were also studied and functionally validated by CRISPR/Cas9-based genetic alterations. RESULTS: Fluconazole resistance occurred in 2.4% (n = 56) of isolates, and these isolates showed a higher frequency of distribution in ICU inpatients compared with susceptible isolates (48.2%, n = 27/56 versus 27.8%, 613/2208; P = 0.019). Microsatellite-genotyping analysis yielded 29 genotypes among 56 fluconazole-resistant isolates, of which 10 genotypes, including 37 isolates, belonged to clusters, persisting and transmitting in Chinese hospitals for 1-29 months. Clusters harbouring Erg11Y132F (5/10; 50%) were predominant in China. Among these, the second most dominant cluster MT07, including seven isolates, characteristically harbouring Erg11Y132F and Mrr1Q625K, lent its carriage to being one of the strongest associations with cross-resistance and high MICs of fluconazole (>256 mg/L) and voriconazole (2-8 mg/L), causing transmission across two hospitals. Among mutations tested, Mrr1Q625K led to the highest-level increase of fluconazole MIC (32-fold), while mutations located within or near the predicted transcription factor domain of Tac1 (D440Y, T492M and L518F) conferred cross-resistance to azoles. CONCLUSIONS: This study is the first Chinese report of persistence and transmissions of multiple fluconazole-resistant C. parapsilosis sensu stricto clones harbouring Erg11Y132F, and the first demonstration of the mutations Erg11G307A, Mrr1Q625K, Tac1L263S, Tac1D440Y and Tac1T492M as conferring resistance to azoles.

Comparisons of the diagnostic accuracy across prostate health index, prostate health index density, and percentage free prostate-specific antigen for clinically significant prostate cancer: a prospective diagnostic study.

Background: As the novel serum biomarkers, it has not been clearly clarified that the diagnostic accuracy of prostate health index (PHI) and prostate health index density (PHID) are superior to that of percentage free prostate-specific antigen (%fPSA) in detection of clinically significant prostate cancer (csPCa), especially in the gray zone. Therefore, this study aimed to compare the diagnostic value of PHI, PHID, and %fPSA for csPCa in the patients with prostate-specific antigen (PSA) >4 ng/mL and those with PSA within 4-10 ng/mL. Methods: In this study, the serum samples and clinicopathological features were prospectively obtained from the patients who underwent prostate biopsy between September 2019 and December 2020. According to the inclusion criteria, the patients with total PSA (tPSA) >4 ng/mL, prostate magnetic resonance imaging or ultrasound clearly suggesting an occupying lesion were enrolled in this study. The patients with Gleason score ≥7 indicated csPCa. The receiver operating characteristic curves and the area under the curve (AUC) values were used to assess the diagnostic performance. Results: Among the 296 patients (mean age 67.5 years, median tPSA 7.94 ng/mL) included in this study, there were 54 in the csPCa group (mean age 70.4 years, median tPSA 11.0 ng/mL) and 242 in the non-csPCa group (mean age 66.8 years, median tPSA 7.67 ng/mL). Based on the PSA level, there were 198 patients with PSA within the gray zone, which included 40 patients in the csPCa group and 158 in the non-csPCa group. In all patients, the sensitivity of PHID for detecting csPCa was 96.30%, and the specificity was 33.06% with the cut-off value of 0.51. Moreover, both PHID and PHI did better in the diagnosis of csPCa (AUC: 0.880 and 0.867, respectively) compared with other PSA derivative markers. Similarly, in the patients with PSA level in the gray zone, the diagnostic accuracy of PHID and PHI in predicting csPCa (AUC: 0.788 and 0.777, respectively) were better than other PSA derivative markers. Conclusions: PHID presented the better diagnostic accuracy in predicting csPCa in patients with PSA in the gray zone than other PSA derivative markers, which could be a promising biomarker for making the biopsy strategy.

Changes of clinical characteristics of asymptomatic patients with positive SARS-Cov-2 nucleic acid test during treatment cycle and related risk factors.

OBJECTIVE: This study was designed to explore the clinical characteristics, outcomes, and related influencing factors for asymptomatic patients with positive Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-Cov-2) nucleic acid test. METHODS: Clinical data of 1568 patients with positive SARS-Cov-2 nucleic acid test (SNAT) were collected retrospectively. The patients were assigned to an asymptomatic group and a symptomatic group according to the existence of clinical symptoms when they got positive result in nucleic acid test, and the clinical data of the two groups were analyzed and compared. In addition, the data of asymptomatic patients who showed clinical symptoms later and the results of two-week follow-up after cure were analyzed. RESULTS: Among all enrolled patients, there were 1489 patients with positive symptoms and 79 asymptomatic patients, including 34 patients who developed symptoms during treatment. Logistic analysis revealed that age ≤45 years (OR=2.722, P<0.001), history of diabetes mellitus (OR=0.446, P=0.007), and history of cancer (OR=0.259, P=0.008) were independent factors for asymptomatic presentation in patients with positive SNAT, and age ≥46 years (OR=1.562, P=0.012) and history of hypertension (OR=2.077, P<0.001) were risk factors for the occurrence of clinical symptoms in asymptomatic patients with positive SNAT during hospitalization. During the follow-up after cure, 8 patients got reoccurring positive SNAT result. CONCLUSION: Asymptomatic patients with positive SNAT are mostly young and middle-aged people, and old age and hypertension are risk factors for the occurrence of positive clinical characteristics in asymptomatic patients.

Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model.

OBJECTIVE: It aimed to analyze the epidemic situation of new coronary pneumonia (COVID-19) based on the epidemiological Markov model, and to study the clinical risk factors of the patients based on the patient's cardinal data and clinical symptoms. METHODS: A total of 500 patients with COVID-19 diagnosed by nucleic acid testing in the X hospital from January 2020 to May 2020 were collected. According to the severity of the disease, they were classified into general group (200 cases) and acute critical group (300 cases). Markov model to predict the number of COVID-19 infections was constructed. Patient's general information, clinical characteristics, and prevention methods were analyzed. RESULTS: According to Markov model statistics, the developmental expected stay time of patients infected with COVID-19 was 14 days. 2. The two groups of patients had statistically considerable differences in complications such as gender, age, hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia (P < 0.05). 3. Logistic multivariate regression analysis showed that the clinical risk factors for patients with COVID-19 mainly included the patient's gender, age, whether they were associated with hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia. CONCLUSION: Markov model can be utilized to judge the time course of the COVID-19 in various development states. In addition, the COVID-19 spread rapidly and is extremely harmful. Clinically, through active prevention, the treatment effect can be improved, the patient's respiratory function, and the quality of life can also be improved.

Circulating cytokines and lymphocyte subsets in patients who have recovered from COVID-19

To investigate the immune status of people who previously had COVID-19 infections, we recruited patients 2 weeks post-recovery and analyzed circulating cytokines and lymphocyte subsets. We measured levels of total lymphocytes, CD4+ T cells, CD8+ T cells, CD19+ B cells, CD56+ NK cells, and the serum concentrations of interleukin (IL)-1, IL-4, IL-6, IL-8, IL-10, transforming growth factor beta (TGF-{beta}), tumor necrosis factor alpha (TNF-), and interferon gamma (IFN-{gamma}) by flow cytometry. We found that in most post-recovery patients, levels of total lymphocytes (66.67%), CD3+ T cells (54.55%), CD4+ T cells (54.55%), CD8 + T cells (81.82%), CD19+ B cells (69.70%), and CD56+ NK cells(51.52%) remained lower than normal, whereas most patients showed normal levels of IL-2 (100%), IL-4 (80.88%), IL-6 (79.41%), IL-10 (98.53%), TNF- (89.71%), IFN-{gamma} (100%) and IL-17 (97.06%). Compared to healthy controls, 2-week post-recovery patients had significantly lower absolute numbers of total lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD56+ NK cells, along with significantly higher levels of IL-2, IL-4, IL-6, IL-10, TNF-, IFN-{gamma} and IL-17. Among post-recovery patients, T cells, particularly CD4+ T cells, were positively correlated with CD19+ B cell counts. Additionally, CD8+ T cells positively correlated with CD4+ T cells and IL-2 levels, and IL-6 positively correlated with TNF- and IFN-{gamma}. These correlations were not observed in healthy controls. By ROC curve analysis, post-recovery decreases in lymphocyte subsets and increases in cytokines were identified as independent predictors of rehabilitation efficacy. These findings indicate that the immune system has gradually recovered following COVID-19 infection; however, the sustained hyper-inflammatory response for more than 14 days suggests a need to continue medical observation following discharge from the hospital. Longitudinal studies of a larger cohort of recovered patients are needed to fully understand the consequences of the infection.