Detection and analysis of human papillomavirus (HPV) DNA in breast cancer patients by an effective method of HPV capture

Despite an increase in the number of molecular epidemiological studies conducted in recent years to evaluate the association between human papillomavirus (HPV) and the risk of breast carcinoma, these studies remain inconclusive. Here we aim to detect HPV DNA in various tissues from patients with breast carcinoma using the method of HPV capture combined with massive paralleled sequencing (MPS). To validate the confidence of our methods, 15 cervical cancer samples were tested by PCR and the new method. Results showed that there was 100% consistence between the two methods.DNA from peripheral blood, tumor tissue, adjacent lymph nodes and adjacent normal tissue were collected from seven malignant breast cancer patients, and HPV type 16(HPV16) was detected in 1/7, 1/7, 1/7and 1/7 of patients respectively. Peripheral blood, tumor tissue and adjacent normal tissue were also collected from two patients with benign breast tumor, and 1/2, 2/2 and 2/2 was detected to have HPV16 DNA respectively. MPS metrics including mapping ratio, coverage, depth and SNVs were provided to characterize HPV in samples. The average coverage was 69% and 61.2% for malignant and benign samples respectively. 126 SNVs were identified in all 9 samples. The maximum number of SNVs was located in the gene of E2 and E4 among all samples. Our study not only provided an efficient method to capture HPV DNA, but detected the SNVS, coverage, SNV type and depth. The finding has provided further clue of association between HPV16 and breast cancer

Associations between anthropometric indicators and refraction in school-age children during the post-COVID-19 era

PurposeTo explore the associations between anthropometric indicators and refraction in school-aged children in the post-COVID-19 era.MethodsData were collected from 25,644 children aged 7 to 12 years in 48 elementary schools in Tianjin. The comprehensive examination included height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), refraction, and calculation of BMI, with a follow-up visit after 6 months. Myopia was defined as spherical equivalent refraction (SER) ≤-0.50 diopter (D). Bivariate correlation coefficients and multiple linear regression models were used to explore the cross-sectional and longitudinal associations between anthropometric indicators (height, weight, BMI, SBP, and DBP) and refraction.ResultsThe mean changes in height, weight, BMI, SBP, DBP, and SER of the participants were 4.03 ± 2.18 cm, 3.10 ± 2.39 kg, 0.45 ± 1.16 kg/m2, 2.26 ± 14.74 mmHg, 2.18 ± 11.79 mmHg and −0.17 ± 0.51 D, respectively. Overall, height, weight, BMI, SBP, and DBP were all correlated with SER (r = −0.324, r = −0.234, r = −0.121, r = −0.112, r = −0.066, both p < 0.001), and changes in height and weight were correlated with changes in SER (r = −0.034, −0.031, both p < 0.001). Furthermore, multiple linear regression analysis revealed that the association of BMI, SBP, and DBP with SER was significant in myopic children but not in non-myopic children. The association between changes in weight and changes in SER was only present in non-myopic children but not in myopic children.ConclusionHeight and weight were negatively correlated with SER in both cross-sectional analysis and longitudinal changes, indicating that children's height, weight and growth rate may be used as a reference indicator for myopia risk prediction and myopia progression monitoring

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

ADDITIVITY OF MAPS ON TRIANGULAR ALGEBRAS ∗

Abstract. In this paper, it is proven that every multiplicative bijective map, Jordan bijective map, Jordan triple bijective map, and elementary surjective map on triangular algebras is automatically additive

An integrated dependability guarantee provisioning for cluster‐based IoV networks with slicing

Abstract High‐dependability Internet of Vehicle (IoV) is essential for urban transit, since it contributes to the safe operation of vehicles, and even to the safety of the entire city. This paper introduces the IoV cluster model with network slicing. Based on this model, an integrated vehicles clustering and network slicing scheme for IoV networks is introduced to guarantee the dependability of different traffics in IoV. The network slicing scheme is proposed to divide the wireless frequency resource of the IoV network into separate logical networks. A ChristmasTree analysis model, based on age of information, is utilized as an integrated indicator for evaluating the dependability of the IoV system in urban transit. Asynchronous reinforcement learning with advantage actor‐critic is employed to optimize the integrated dependability of IoV. It is demonstrated in simulations that the proposed IoV cluster incorporating the network slicing scheme can guarantee the integrated dependability of the IoV system. Moreover, by the application of reinforcement learning, the system dependability can be further improved

The minimum effective concentration (MEC90) of ropivacaine for ultrasound-guided quadratus lumborum block for analgesia after cesarean delivery: a dose finding study

Abstract Background Quadratus lumborum block was recently proposed as an alternative technique for post-cesarean delivery analgesia. However, there is not a definite optimum concentration of local anesthetics. A biased coin design up-and-down method was used to explore the minimum effective concentration of ropivacaine in quadratus lumborum block for satisfactory analgesia after cesarean delivery. Methods Fifty-six patients weighing 60–80 kg after cesarean section and with ages between 18 and 40 years were recruited. For the posterior quadratus lumborum block, a volume of 25 ml of the assigned concentration of ropivacaine was injected bilaterally. The concentration administered to each patient depended on the response to the previous dose. The first patient received 0.25%. If a successful block was observed, the next patient was randomized to receive the same ropivacaine concentration (with a probability of 0.89) or 0.025% less (with a probability of 0.11). After any block failure, the concentration was always increased by 0.025% for the next. The study ended when 45 successful blocks were obtained. We defined effective quadratus lumborum block as a resting visual analog score ≤ 3 and the absence of a need for rescue anesthetics. Results The 90% minimum effective concentration of ropivacaine was 0.335% (95% CI 0.306 to 0.375%), and the 99% minimum effective concentration was 0.371% (95% CI 0.355 to 0.375%). The sufentanil consumption was 11 (11,13) and 24 (22,27) μg at 12 and 24 hours after quadratus lumborum block, respectively. Conclusions The optimum dosage of ropivacaine is a 25 ml volume of 0.335% for quadratus lumborum block after cesarean delivery. Trial registration The study was registered in the Chinese Clinical Trial Registry (No. ChiCTR2000040415 )

A novel combinational evaluation method of voltage and reactive power in regional power grid containing renewable energy

The output of renewable energy is strongly uncertain and random, and the distribution of voltage and reactive power in regional power grids is changed with the access to large-scale renewable energy. In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a novel combinational evaluation method of voltage and reactive power in regional power grids containing renewable energy is proposed. Firstly, the actual operation data of renewable energy and load demand are clustered based on the K-means algorithm, and several typical scenarios are divided. Then, the entropy weight method (EWM) and the analytic hierarchy process (AHP) are combined to evaluate the voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve in typical scenarios. Besides, the evaluation results are used as the training samples for back-propagation (BP) neural networks. The proposed combinational evaluation method can calculate the weight coefficient of the indexes adaptively with the change of samples, which simplifies the calculation process of the indexes’ weight. At last, the case simulation of an actual regional power grid is provided, and the historical data of one year is taken as the sample for training, evaluating and analyzing. And finally, the effectiveness of the proposed method is verified based on the comparison with the existing method. The evaluated results could provide reference and guidance to the operation analysis and planning of renewable energy

Modeling and analyzing land use and land cover change in metropolitan Birmingham area using landsat TM, OLI data

The Birmingham Metropolitan Area experienced land use land cover (LULC) change over the last three decades, such as the development of urban area, the development of transportation system, deforestation, and rise of population. The main purpose of the thesis is to model and analyze the LULC change through last three decades in Birmingham area, and also simulate the LULC in next three decades. Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from U.S. Geological Survey (USGS) is used for investigating the LULC in Birmingham area. Supervised Classification is used; the maximum overall accuracy is 86.33%. Drivers such as transportation, topographic measures, population and income, location measures are analyzed. Remote sensing indices are also derived from Landsat data, such as NDVI, NDBI, MNDWI, and LST. Pearson's Correlation test is run among the LULC proportion, drivers within counties and census tracts. Finally, the cellular automation model SLEUTH is used to simulate the future pattern of LULC. The results shows the Birmingham experienced a significant LULC change in last three decades. Transportation and slope are two main factors in terms of LULC change. In summary, the thesis completes a systematic LULC classification in Birmingham area in last three decades, and uses different methods to model and analyze LULC and eventually simulate the LULC pattern in next three decades. (Published By University of Alabama Libraries