Epidemiological characteristics of syphilis in mainland China, 2004 to 2019.

OBJECTIVES: Syphilis is a globally prevalent sexually transmitted infection. This study aimed to elucidate the epidemiological characteristics of syphilis in China from 2004 to 2019. METHODS: Incidence data for syphilis across 31 provinces in mainland China were obtained from the Data Center of China Public Health Science for the period from 2004 to 2019. Epidemiological methods and the Chi-squared test were used to analyze the temporal, regional, and disease stage distributions of syphilis. RESULTS: In total, 5,527,399 syphilis cases were reported in China from 2004 to 2019, with an average annual prevalence of 25.7063 per 100,000 population and overall increasing trend. In terms of regional distribution, high-incidence provinces included Shanghai, Zhejiang, Fujian, Guangxi, Guangdong, Xinjiang, Ningxia, and Qinghai. The proportion of latent syphilis increased from 20.41% in 2004 to 82.95% in 2019, with an upward trend each year. CONCLUSIONS: Syphilis incidence exhibited an overall increasing trend in China, and latent syphilis was predominant. Syphilis incidences considerably varied among regions, and syphilis was detected from coastal to inland provinces. Thus, syphilis prevention and control programs should be tailored according to the specific epidemiological characteristics of each region.

Pathogenesis and preventions of denture stomatitis. / ä¹‰é½¿æ€§å£è ”ç‚Žçš„å‘ç— æœºåˆ¶å’Œé˜²æ²».

Denture stomatitis (DS) is one of the frequent oral diseases caused by multiple factors among denture wearers and is an erythematous lesion of the mucosa in the denture-bearing area, which is a limited and non-specific damage that seriously endangers the oral health of denture wearers. Traditional drug treatment for DS is effective, but it is prone to the development of drug-resistant strains. Therefore, it is important to find new treating options. For the prevention and treatment of DS, there are various methods such as direct administration of azole and polyene antibiotics to the mucosal lesions, extra-oral cleaning of the denture by cleansers and physical disinfection, and modification of denture materials. Natural ingredient preparations that have emerged in recent years are safe, convenient, inexpensive, and less likely to produce drug-resistant strains, and are seen as new sources of drugs for DS treatment. Photodynamic therapy has shown superior antibacterial properties and is also considered promising due to the convenience and safety of the treatment process and the ease of developing drug resistance. Antibacterial agents endow dentures with new characteristics, and denture modification will be a new way to treat DS. In addition, combining different prevention and control methods has shown better antibacterial activity against Candida albicans, which also provides new ideas for prevention and treatment of DS in the future.

Early Triage of Critically Ill Adult Patients With Mushroom Poisoning: Machine Learning Approach.

BACKGROUND: Early triage of patients with mushroom poisoning is essential for administering precise treatment and reducing mortality. To our knowledge, there has been no established method to triage patients with mushroom poisoning based on clinical data. OBJECTIVE: The purpose of this work was to construct a triage system to identify patients with mushroom poisoning based on clinical indicators using several machine learning approaches and to assess the prediction accuracy of these strategies. METHODS: In all, 567 patients were collected from 5 primary care hospitals and facilities in Enshi, Hubei Province, China, and divided into 2 groups; 322 patients from 2 hospitals were used as the training cohort, and 245 patients from 3 hospitals were used as the test cohort. Four machine learning algorithms were used to construct the triage model for patients with mushroom poisoning. Performance was assessed using the area under the receiver operating characteristic curve (AUC), decision curve, sensitivity, specificity, and other representative statistics. Feature contributions were evaluated using Shapley additive explanations. RESULTS: Among several machine learning algorithms, extreme gradient boosting (XGBoost) showed the best discriminative ability in 5-fold cross-validation (AUC=0.83, 95% CI 0.77-0.90) and the test set (AUC=0.90, 95% CI 0.83-0.96). In the test set, the XGBoost model had a sensitivity of 0.93 (95% CI 0.81-0.99) and a specificity of 0.79 (95% CI 0.73-0.85), whereas the physicians' assessment had a sensitivity of 0.86 (95% CI 0.72-0.95) and a specificity of 0.66 (95% CI 0.59-0.73). CONCLUSIONS: The 14-factor XGBoost model for the early triage of mushroom poisoning can rapidly and accurately identify critically ill patients and will possibly serve as an important basis for the selection of treatment options and referral of patients, potentially reducing patient mortality and improving clinical outcomes.

A path recorder algorithm for Multiple Longest Common Subsequences (MLCS) problems.

MOTIVATION: Searching the Longest Common Subsequences of many sequences is called a Multiple Longest Common Subsequence (MLCS) problem which is a very fundamental and challenging problem in many fields of data mining. The existing algorithms cannot be applicable to problems with long and large-scale sequences due to their huge time and space consumption. To efficiently handle large-scale MLCS problems, a Path Recorder Directed Acyclic Graph (PRDAG) model and a novel Path Recorder Algorithm (PRA) are proposed. RESULTS: In PRDAG, we transform the MLCS problem into searching the longest path from the Directed Acyclic Graph (DAG), where each longest path in DAG corresponds to an MLCS. To tackle the problem efficiently, we eliminate all redundant and repeated nodes during the construction of DAG, and for each node, we only maintain the longest paths from the source node to it but ignore all non-longest paths. As a result, the size of the DAG becomes very small, and the memory space and search time will be greatly saved. Empirical experiments have been performed on a standard benchmark set of both DNA sequences and protein sequences. The experimental results demonstrate that our model and algorithm outperform the related leading algorithms, especially for large-scale MLCS problems. AVAILABILITY AND IMPLEMENTATION: This program code is written by the first author and can be available at https://www.ncbi.nlm.nih.gov/nuccore and https://blog.csdn.net/wswguilin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Automated Piston Gauge Calibration System.

Piston gauges or pressure balances are important primary standards for the realization of the SI unit of pressure, the pascal. Because of their long-term stability, they are also used as secondary or working standards in the dissemination of the pressure scale. The National Institute of Standards and Technology (NIST) operates and maintains a calibration service for these devices, and has recently undertaken a modernization effort. Following a preliminary investigation into the feasibility of using transducers as instantaneous in-situ transfer standards, we now present the results of a near fully automated calibration system. This effort includes the design, building, and validation of an automated gas-handling manifold, and the development of a new software suite. The new system demonstrates an expanded uncertainty on the order of 1 in 105, comparable to the traditional system, but offers a five-fold decrease in calibration turnaround time.

[Screening of plant pathogenic fungi by ginsenoside compound K production].

OBJECTIVE: To screen a new strain which can transform panaxadiol saponins into the rare ginsenoside compound K. METHOD: The total saponins in stems and leaves of Panax notoginseng was used as a substrate in the liquid state fermentation process, and the results were detected by TLC and HPLC-ELSD to screen a strain from twelve plant pathogenic fungi which can produce ginsenoside compound K. RESULT: Fusarium moniliforme was found to transform the total saponins to ginsenoside compound K efficiently in the all twelve fungal strains. In the fermentation process, ginsenoside Rb1 was transformed almost completely, and the content of ginsenoside Rd was decreasing evidently. CONCLUSION: F. moniliforme is selected as a new high-yield strain. It is expected to be used to produce the high activity infrequent ginsenoside compound K and to improve the content of active principles in medicinal plants.

Prognostic significance of urokinase-type plasminogen activator and its receptor in patients with systemic inflammatory response syndrome.

BACKGROUND: This study aimed to determine the plasma levels of urokinase-type plasminogen activator (uPA), urokinase-type plasminogen activator receptor (uPAR), D-dimer, IL-6 and TNF-α and observe the relations among uPA, uPAR, D-dimer, IL-6 and TNF-α in patients with systemic inflammatory response syndrome (SIRS). METHODS: A prospective, clinical case-control study was conducted in patients with SIRS at age of more than 55 years old treated during 2008-2010 at Wuhan Central Hospital. Venous blood samples were collected by routine venipuncture. Eighty-five patients were divided into two groups according to diagnostic criteria of SIRS: SIRS patients from intensive care units (n=50), and non-SIRS patients from medical wards (n=35). Thirty healthy blood donors who visited the General Health Check-up Division at Wuhan Central Hospital served as controls. Excluded from the study were (1) those patients with pregnancy; (2) those with cancer; (3) those died after admission into the ICU in 7 days; (4) those received cardiopulmonary resuscitation; (5) those who had previous blood system diseases; and (6) those with SIRS before admission into the ICU. The levels of uPA, uPAR, D-D, IL-6 and TNF-α in blood were detected by commercial enzyme-linked immunosorbent assay (ELISA) kit. The data were analyzed using SPSS version 17.0 and expressed as mean ± standard. Student's t test and the Mann-Whitney U test were used in the analysis. The relations of uPA, uPAR and D-dimer, IL-6 TNF-α levels were analyzed using Spearman's rank-order correlation coefficient test. RESULTS: The plasma levels of uPA, uPAR, D-dimer,IL-6 and TNF-α in the patients with SIRS were obviously higher than those in the non-SIRS patients and controls (P<0.001). Correlation analysis showed a positive correlation between uPAR and IL-6 levels (r=0.395, P=0.004) and between uPAR and TNF-α levels (r=0.606, P<0.001), but no correlation between uPAR and D-dimer levels (r=0.069, P=0.632). No correlation was observed between uPA, D-dimer, IL-6 and TNF-α levels (P>0.05). The establishment of ROC curve was based on the levels of uPAR, D-dimer, IL-6 and TNF-α in 24 hours for the diagnosis of multiple organ dysfunction syndrome (MODS), and the ROC areas under the curve were 0.76, 0.58, 0.86 and 0.83, respectively. CONCLUSIONS: uPA and uPAR play a major role in patients with SIRS in the process of coagulation disorder, but the mechanism of SIRS is not the same. uPAR may play a central role in the development of SIRS to MODS.