Genotypic diversity and antifungal susceptibility of Cryptococcus neoformans species complex from China, including the diploid VNIII isolates from HIV-infected patients in Chongqing region.

Although previous studies on the genotypic diversity and antifungal susceptibility of the Cryptococcus neoformans species complex (CNSC) isolates from China revealed ST5 genotype isolates being dominant, the information about the CNSC isolates from Chinese HIV-infected patients is limited. In this study, 171 CNSC isolates from HIV-infected patients in the Chongqing region of Southwest China were genotyped using the International Society for Human and Animal Mycology-multilocus sequence typing consensus scheme, and their antifungal drug susceptibilities were determined following CLSI M27-A3 guidelines. Among 171 isolates, six sequence types (STs) were identified, including the dominant ST5 isolates, the newly reported ST15, and four diploid VNIII isolates (ST632/ST636). Moreover, a total of 1019 CNSC isolates with STs and HIV-status information were collected and analyzed from Mainland China in the present study. A minimum spanning analysis grouped these 1019 isolates into three main subgroups, which were dominated by the ST5 clonal complex (CC5), followed by the ST31 clonal complex (CC31) and ST93 clonal complex (CC93). The trend of resistance or decreasing susceptibility of clinical CNSC isolates to azole agents within HIV-infected patients from the Chongqing region is increasing, especially resistance to fluconazole.

In this paper, novel ST15 and four diploid VNIII isolates (ST632/ST636) were found in 171 CNSC isolates in Southwest China, including evidence for resistance to fluconazole. Moreover, we clustered the 1019 clinical CNSC isolates reported so far from Mainland China into three major subgroups.

Association between AMPKα1 gene polymorphisms and gestational diabetes in the Chinese population: A case-control study.

AIM: The aim is to examine the association between seven candidate single nucleotide polymorphisms in AMPKα1 and gestational diabetes in Chinese people. METHOD: We used a matched nested case-control study design, individuals including 334 participants with gestational diabetes and 334 healthy pregnant women. Confirmed 334 gestational diabetes cases and maternal age and district of residence matched controls (1:1) were enrolled. We examined seven candidate single nucleotide polymorphisms in AMPKα1 gene and the risk of gestational diabetes. The associations were estimated in Co-dominant, Dominant, Recessive, and Alleles models. The odds ratios (ORs) and their 95% confidence intervals (95% CI) were estimated by unconditional logistical regression as a measure of the associations between genotypes and gestational diabetes adjusting for maternal age, prepregnancy body mass index (BMI), fetal sex and parity. RESULT: At the gene level, we found that AMPKα1 was associated with gestational diabetes (p = 0.008). After adjusting the covariates and multiple comparison correction, AMPKα1 (rsc1002424, rs10053664, rs13361707) polymorphisms were associated with the risk of gestational diabetes. In addition, gestational diabetes was related to the AAGGA haplotype comprising rs1002424, rs2570091, rs10053664, rs13361707 and rs3805486 in the haplotype models (p = 0.011). CONCLUSIONS: This study provides evidence that the AMPKα1 genotypes (rs1002424 G/A, rs10053664 A/G, rs13361707 A/G) and the haplotype (AAGGA) are relevant genetic factors in a Chinese population with gestational diabetes.

Polymorphisms in oxidative stress, metabolic detoxification, and immune function genes, maternal exposure to ambient air pollution, and risk of preterm birth in Taiyuan, China.

Exposure to air pollutants may be associated with preterm birth (PB) through oxidative stress, metabolic detoxification, and immune system processes. However, no study has investigated the interactive effects of maternal air pollution and genetic polymorphisms in these pathways on risk of PB. The study included 126 PB and 310 term births. A total of 177 single nucleotide polymorphisms (SNPs) in oxidative stress, immune function, and metabolic detoxification-related genes were examined and analyzed. The China air quality index (AQI) was used as an overall estimation of ambient air pollutants. Among 177 SNPs, four SNPs (GPX4-rs376102, GLRX-rs889224, VEGFA-rs3025039, and IL1A-rs3783550) were found to have significant interactions with AQI on the risk of PB (Pinteraction were 0.001, 0.003, 0.03, and 0.04, respectively). After being stratified by the maternal genotypes in these four SNPs, 1.38 to 1.76 times of the risk of PB were observed as per interquartile range increase in maternal AQI among women who carried the GPX4-rs376102 AC/CC genotypes, the GLRX-rs889224 TT genotype, the VEGFA-rs3025039 CC genotype, or the IL1A-rs3783550 GT/TT genotypes. After adjustment for multiple comparisons, only GPX4-rs376102 and AQI interaction remained statistically significant (false discovery rate (FDR)=0.17). After additional stratification by preeclampsia (PE) status, a strongest association was observed in women who carried the GPX4-rs376102 AC/CC genotypes (OR, 2.26; 95% CI, 1.41-3.65, Pinteraction=0.0002, FDR=0.035) in the PE group. Our study provided the first evidence that association between maternal air pollution and PB risk may be modified by the genetic polymorphisms in oxidative stress and immune function genes. Future large studies are necessary to replicate and confirm the observed associations.

Association of CPT1A gene polymorphism with the risk of gestational diabetes mellitus: a case-control study.

PURPOSE: Gestational diabetes mellitus (GDM) is a growing public health problem worldwide and its etiology remains unclear. The pathophysiology of GDM is similar to that of type 2 diabetes (T2DM) and insulin resistance (IR) is the main reason for the development of GDM. Carnitine palmitoyltransferase 1A (CPT1A) is a candidate gene for metabolic disorders; however, the association of the CPT1A gene and GDM has not yet been studied. We aimed to explore whether single-nucleotide polymorphisms (SNPs) of the CPT1A gene could influence the risk of GDM. METHODS: We examined 18 single-nucleotide polymorphisms (SNPs) in the CPT1A gene and the risk of GDM in a nested case-control study of 334 GDM patients and 334 controls. The controls who had no GDM were randomly selected through matching to cases by age and residence. RESULTS: After adjusting the family history of diabetes, pre-pregnancy body mass index, and multiple comparison correction, the CPT1A rs2846194 and rs2602814 were associated with reduced GDM risk while rs59506005 was associated with elevated GDM risk. Moreover, the GGAC haplotype in the CPT1A gene (rs17399246 rs1016873 rs11228450 rs10896396) was associated with a reduced risk of GDM. CONCLUSION: Our study provides evidence for an association between genetic polymorphisms in the CPT1A and the risk of GDM.

Evaluation Model of Autonomous Vehicles' Speed Suitability Based on Overtaking Frequency.

Speed judgment is a vital component of autonomous driving perception systems. Automobile drivers were able to evaluate their speed as a result of their driving experience. However, driverless automobiles cannot autonomously evaluate their speed suitability through external environmental factors such as the surrounding conditions and traffic flows. This study introduced the parameter of overtaking frequency (OTF) based on the state of the traffic flow on both sides of the lane to reflect the difference between the speed of a driverless automobile and its surrounding traffic to solve the above problem. In addition, a speed evaluation algorithm was proposed based on the long short-term memory (LSTM) model. To train the LSTM model, we extracted OTF as the first observation variable, and the characteristic parameters of the vehicle's longitudinal motion and the comparison parameters with the leading vehicle were used as the second observation variables. The algorithm judged the velocity using a hierarchical method. We conducted a road test by using real vehicles and the algorithms verified the data, which showed the accuracy rate of the model is 93%. As a result, OTF is introduced as one of the observed variables that can support the accuracy of the algorithm used to judge speed.

The Effects of Dynamic Complexity on Drivers' Secondary Task Scanning Behavior under a Car-Following Scenario.

The user interface of vehicle interaction systems has become increasingly complex in recent years, which makes these devices important factors that contribute to accidents. Therefore, it is necessary to study the impact of dynamic complexity on the carrying capacity of secondary tasks under different traffic scenarios. First, we selected vehicle speed and vehicle spacing as influencing factors in carrying out secondary tasks. Then, the average single scanning time, total scanning time, and scanning times were selected as evaluation criteria, based on the theories of cognitive psychology. Lastly, we used a driving simulator to conduct an experiment under a car-following scenario and collect data on scanning behavior by an eye tracker, to evaluate the performance of the secondary task. The results show that the relationship between the total scanning time, scanning times, and the vehicle speed can be expressed by an exponential model, the relationship between the above two indicators and the vehicle spacing can be expressed by a logarithmic model, and the relationship with the total number of icons can be expressed by a linear model. Combined with the above relationships and the evaluation criteria for driving secondary tasks, the maximum number of icons at different vehicle speeds and vehicle spacings can be calculated to reduce the likelihood of accidents caused by attention overload.

lncRNA NR2F2-AS1 inhibits the methylation of miR-494 to regulate oral squamous cell carcinoma cell proliferation.

OBJECTIVE: This study aimed to investigate the role of lncRNA NR2F2-AS1 in oral squamous cell carcinoma cells (OSCC). MATERIALS AND METHODS: The TCGA datasets were used to explore the differential expression of NR2F2-AS1 in OSCC. To further explore the potential interaction between NR2F2-AS1 and miR-494, SCC090 cells were transfected with the NR2F2-AS1 expression vector, NR2F2-AS1 siRNA, and a miR-494 mimic. The effect of NR2F2-AS1 on miR-494 methylation was evaluated by performing methylation-specific PCR (MSP). Cell Counting Kit-8 (CCK-8) assay was used to assess the effects of NR2F2-AS1 silencing and miR-494 and NR2F2-AS1 overexpression on OSCC cell proliferation. RESULTS: NR2F2-AS1 expression was downregulated in OSCC and positively correlated with miR-494 expression. In OSCC cells, NR2F2-AS1 overexpression upregulated miR-494 level, while NR2F2-AS1 silencing decreased miR-494 expression. MSP results showed that NR2F2-AS1 overexpression decreased miR-494 methylation while NR2F2-AS1 silencing increased miR-494 methylation. In addition, NR2F2-AS1 silencing increased OSCC cell proliferation rate while overexpression of miR-494 and NR2F2-AS1 decreased OSCC cell proliferation. Furthermore, miR-494 overexpression attenuated the effects of NR2F2-AS1 silencing on cell proliferation. CONCLUSION: NR2F2-AS1 may inhibit miR-494 methylation to regulate cell proliferation in OSCC. AVAILABILITY OF DATA AND MATERIALS: The analyzed data sets generated during the study are available from the corresponding author upon reasonable request.

Oolong Tea Consumption and the Risk of Oral Squamous Cell Carcinoma: A Propensity Score-Based Analysis in Southeast China.

Oolong tea is one of the world's most popular non-alcoholic beverages, particularly in coastal Southeast China. Hitherto, epidemiological studies on the association between oolong tea consumption and the risk of patients with oral squamous cell carcinoma (OSCC) are very limited. This study aimed to evaluate the potential effect of oolong tea consumption on OSCC risk in Southeast China. From January 2010 to October 2020, face-to-face interviews were conducted for 744 newly diagnosed OSCC patients and 1,029 healthy controls to collect information on demographics, oolong tea consumption behaviors, and other lifestyle factors. Propensity score matching (PSM), inverse probability of treatment weight (IPTW), and stabilized inverse probability of treatment weight (SIPTW) were utilized to minimize confounding effects. Multivariate, conditional, and weighted logistic regression was used to evaluate the associations of oolong tea consumption behaviors with OSCC risk. Participants who drank oolong tea showed a lower risk of OSCC when compared to their non-drink counterparts [PSM population, OR (95%CI): 0.69 (0.49-0.97); SIPTW population, OR (95%CI): 0.74 (0.58-0.94)]. Moreover, the reduced risk was found to be significantly associated with certain tea-drinking habits (consumed amount over 500 mL per day, a duration of <20 years, age at initiation older than 30 years, and warm and moderately concentrated tea). Similar results were yielded in the sensitivity analyses (Multivariate adjustment and the IPTW analysis). Furthermore, subgroup analysis revealed that the negative association of oolong tea drinking with OSCC risk was more evident among those with poor oral hygiene. This study provides supportive evidence that oolong tea consumption may have a potentially beneficial effect in preventing OSCC, especially for those with poor oral hygiene.

LncRNA-IUR Sponges miR-24 to Upregulate P53 in Laryngeal Squamous Cell Carcinoma.

OBJECTIVE: The functions of lncRNA-IUR in laryngeal squamous cell carcinoma (LSCC) were investigated in this study. METHODS: RT-qPCR and paired t-test were used to measure and compare expression levels of IUR, miR-24 and p53 in LSCC and non-tumor tissues. Human LSCC cell line UM-SCC-17A was used and transfected by pcDNA3.1 vector to overexpress IUR and miR-24. The transwell assay and wound healing assay illustrated the effect of overexpression of IUR or miR-24 in the cell invasion and migration of LSCC. Subcutaneous tumor model in nude mice was carried out to demonstrate the mechanism between IUR and miR-24 in regulating tumor growth. RESULTS: We found that IUR was downregulated in LSCC. Low expression levels of IUR were correlated with the poor survival of LSCC patients. Overexpression experiments showed that overexpression of IUR led to increased, while overexpression of miR-24 led to decreased expression levels of p53 in LSCC cells. And bioinformatics analysis showed that IUR may sponge miR-24. Cell proliferation assay showed that overexpression of IUR and p53 led to decreased proliferation rate of LSCC cells, while overexpression of miR-24 led to increased proliferation rate of LSCC cells. We also illustrated that overexpression of IUR promoted cell migration and invasion while miR-24 had opposite effects. In addition, subcutaneous tumor model in nude mice showed that overexpression of miR-24 attenuated the effects of overexpression of IUR on the expression of p53 and cancer cell proliferation. CONCLUSION: IUR sponges miR-24 to upregulate p53 in LSCC, thereby inhibiting cancer cell proliferation.

Comparison of the expression of TGF-ß1, E-cadherin, N-cadherin, TP53, RB1CC1 and HIF-1α in oral squamous cell carcinoma and lymph node metastases of humans and mice.

The aim of the present study was to prove that a mouse model closely simulates human oral cancer progression by comparing the expression levels of transforming growth factor (TGF)-ß1, E-cadherin, N-cadherin, tumor protein (TP)53, RB1 inducible coiled-coil (RB1CC)1 and hypoxia inducible factor (HIF)-1α at different stages of oral squamous cell carcinoma (OSCC) in humans and mice. The expression levels of TGF-ß1, E-cadherin, N-cadherin, TP53, RB1CC1, and HIF-1α were detected by immunohistochemical staining in normal oral mucosa, oral mucosa dysplasia, OSCC primary tumor and carcinoma tissues from lymph node metastases. Tissue samples were obtained from human specimens and the Balb/c mouse model of lymphatic metastases oral carcinoma, induced by 4-nitroquinoline-1-oxide in drinking water. The results indicated no significant differences in the expression levels of TGF-ß1, E-cadherin, N-cadherin, TP53, RB1CC1 and HIF-1α between humans and mice, at any stage of OSCC examined (P>0.05). The expression of TGF-ß1, N-cadherin, TP53 and RB1CC1 increased in different stages of OSCC in both humans and mice. The expression of E-cadherin decreased from normal oral mucosa to OSCC, and increased in lymph node metastases in both human and mouse samples. The expression of HIF-1α increased from normal oral mucosa to OSCC, and decreased in lymph node metastases in both human and mouse samples. Additionally, the expression of p53 was positively correlated with that of RB1CC1 in human and mouse samples (r=0.971, P=0.029; r=0.97, P=0.03). Overall, the similar expression of multiple molecules in both human and mouse carcinoma prove that the mouse model of lymphatic metastases from oral carcinoma established in the present study may closely mimic human oral cancer.

Research on the Relationship between Reaction Ability and Mental State for Online Assessment of Driving Fatigue.

Background: Driving fatigue affects the reaction ability of a driver. The aim of this research is to analyze the relationship between driving fatigue, physiological signals and driver's reaction time. Methods: Twenty subjects were tested during driving. Data pertaining to reaction time and physiological signals including electroencephalograph (EEG) were collected from twenty simulation experiments. Grey correlation analysis was used to select the input variable of the classification model. A support vector machine was used to divide the mental state into three levels. The penalty factor for the model was optimized using a genetic algorithm. Results: The results show that α/ß has the greatest correlation to reaction time. The classification results show an accuracy of 86%, a sensitivity of 87.5% and a specificity of 85.53%. The average increase of reaction time is 16.72% from alert state to fatigued state. Females have a faster decrease in reaction ability than males as driving fatigue accumulates. Elderly drivers have longer reaction times than the young. Conclusions: A grey correlation analysis can be used to improve the classification accuracy of the support vector machine (SVM) model. This paper provides basic research that online detection of fatigue can be performed using only a simple device, which is more comfortable for users.