Coexistence of Histologically Confirmed Hashimoto's Thyroiditis with Different Stages of Papillary Thyroid Carcinoma in a Consecutive Chinese Cohort

Purpose. To determine the relationship between Hashimoto's thyroiditis (HT) and all stages of papillary thyroid carcinoma (PTC) with or without local lymph node metastasis (LNM). Methods:. We conducted a retrospective study of thyroidectomies from 2008–2013 in First Affiliated Hospital of Nanjing Medical University. We categorized patients according to the presence of histopathologically proven HT. The prevalence of mPTC (maximum diameter ≤ 10 mm) and crPTC (clinical relevant PTC) and local LNM rates were compared. Results:. We evaluated 6,432 consecutive thyroidectomies. In total, 1,328 specimens were confirmed as HT. The prevalence of PTC in this HT cohort was 43.8%, significantly higher than non-HT group. After adjustment of gender and age, the prevalence of PTC was still higher in HT group. HT was a risk factor for PTC in multivariate analysis with odds ratio 2.725 (95% CI, 2.390–3.109) (P < 0.001). However, no correlation was found between HT and LNM of PTC. Conclusion:. HT was associated with an increased prevalence of all stages of PTC, independent of tumor size, gender, and age. In contrast, locally advanced disease defined by LNM was unrelated to HT. These data suggest an association of HT with low risk PTC and a potential protective immunologic effect from further disease progression

Genome Physical Mapping of Polyploids: A BIBAC Physical Map of Cultivated Tetraploid Cotton, Gossypium hirsutum L

Polyploids account for approximately 70% of flowering plants, including many field, horticulture and forage crops. Cottons are a world-leading fiber and important oilseed crop, and a model species for study of plant polyploidization, cellulose biosynthesis and cell wall biogenesis. This study has addressed the concerns of physical mapping of polyploids with BACs and/or BIBACs by constructing a physical map of the tetraploid cotton, Gossypium hirsutum L. The physical map consists of 3,450 BIBAC contigs with an N50 contig size of 863 kb, collectively spanning 2,244 Mb. We sorted the map contigs according to their origin of subgenome, showing that we assembled physical maps for the A- and D-subgenomes of the tetraploid cotton, separately. We also identified the BIBACs in the map minimal tilling path, which consists of 15,277 clones. Moreover, we have marked the physical map with nearly 10,000 BIBAC ends (BESs), making one BES in approximately 250 kb. This physical map provides a line of evidence and a strategy for physical mapping of polyploids, and a platform for advanced research of the tetraploid cotton genome, particularly fine mapping and cloning the cotton agronomic genes and QTLs, and sequencing and assembling the cotton genome using the modern next-generation sequencing technology

PORF-DDPG: Learning Personalized Autonomous Driving Behavior with Progressively Optimized Reward Function

Autonomous driving with artificial intelligence technology has been viewed as promising for autonomous vehicles hitting the road in the near future. In recent years, considerable progress has been made with Deep Reinforcement Learnings (DRLs) for realizing end-to-end autonomous driving. Still, driving safely and comfortably in real dynamic scenarios with DRL is nontrivial due to the reward functions being typically pre-defined with expertise. This paper proposes a human-in-the-loop DRL algorithm for learning personalized autonomous driving behavior in a progressive learning way. Specifically, a progressively optimized reward function (PORF) learning model is built and integrated into the Deep Deterministic Policy Gradient (DDPG) framework, which is called PORF-DDPG in this paper. PORF consists of two parts: the first part of the PORF is a pre-defined typical reward function on the system state, the second part is modeled as a Deep Neural Network (DNN) for representing driving adjusting intention by the human observer, which is the main contribution of this paper. The DNN-based reward model is progressively learned using the front-view images as the input and via active human supervision and intervention. The proposed approach is potentially useful for driving in dynamic constrained scenarios when dangerous collision events might occur frequently with classic DRLs. The experimental results show that the proposed autonomous driving behavior learning method exhibits online learning capability and environmental adaptability

Rate-Gyro-Integral Constraint for Ambiguity Resolution in GNSS Attitude Determination Applications

sensor

The Inertial Attitude Augmentation for Ambiguity Resolution in SF/SE-GNSS Attitude Determination

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation

Ratiometric Fluorescent Biosensing of Hydrogen Peroxide and Hydroxyl Radical in Living Cells with Lysozyme–Silver Nanoclusters: Lysozyme as Stabilizing Ligand and Fluorescence Signal Unit

Construction of facile ratiometric fluorescent probes which possess sensitive and selective sensing ability for bioactive small molecules is highly desirable and challenging. Herein, silver nanoclusters capped with denatured lysozyme (dLys-AgNCs) were synthesized and proved to be dual emissive. The facility of the dLys-AgNCs ratiometric probe was attributed to the finding that the lysozyme acted not only as stabilizing ligand but also as fluorescence signal unit. In the presence of Fenton reagents, the emission of dLys-AgNCs at 640 nm was quenched by ^•OH, whereas the emission at 450 was enhanced due to ^•OH-induced oxidation of tyrosine in the lysozyme. This probe could be used for highly sensitive detection of H₂O₂. The fluorescence changes of <i>F</i>₄₅₀<i>/F</i>₆₄₀ had fantastic linearity to H₂O₂ concentrations in the range of 0.8–200 μmol/L (<i>R</i>² = 0.9993), with a limit of detection (LOD) as low as 0.2 μmol/L. Additionally, this probe was also applied to H₂O₂-generated oxidase-based biosensing. As a proof-of-concept, glucose and acetylcholine chloride were detected with benefical LOD values of 0.6 μmol/L and 0.8 μmol/L, respectively. Furthermore, fluorescence confocal imaging demonstrated dLys-AgNCs had a sensitive response to fluctuation of ^•OH levels in living cells, which might have promising application in study of ^•OH-induced oxidative damage to proteins

Is body mass index associated with outcomes of mechanically ventilated adult patients in intensive critical units? A systematic review and meta-analysis

<div><p>Background</p><p>Obesity paradox refers to lower mortality in subjects with higher body mass index (BMI), and has been documented under a variety of condition. However, whether obesity paradox exists in adults requiring mechanical ventilation in intensive critical units (ICU) remains controversial.</p><p>Methods</p><p>MEDLINE, EMBASE, China Biology Medicine disc (CBM) and CINAHL electronic databases were searched from the earliest available date to July 2017, using the following search terms: “body weight”, “body mass index”, “overweight” or “obesity” and “ventilator”, “mechanically ventilated”, “mechanical ventilation”, without language restriction. Subjects were divided into the following categories based on BMI (kg/m²): underweight, < 18.5 kg/m²; normal, 18.5–24.9 kg/m²; overweight, BMI 25–29.9 kg/m²; obese, 30–39.9 kg/m²; and severely obese > 40 kg/m². The primary outcome was mortality, and included ICU mortality, hospital mortality, short-term mortality (<6 months), and long-term mortality (6 months or beyond). Secondary outcomes included duration of mechanical ventilation, length of stay (LOS) in ICU and hospital. A random-effects model was used for data analyses. Risk of bias was assessed using the Newcastle-Ottawa quality assessment scale.</p><p>Results</p><p>A total of 15,729 articles were screened. The final analysis included 23 articles (199,421 subjects). In comparison to non-obese patients, obese patients had lower ICU mortality (odds ratio (OR) 0.88, 95% CI 0.0.84–0.92, I² = 0%), hospital mortality (OR 0.83, 95% CI 0.74–0.93, I² = 52%), short-term mortality (OR 0.81, 95% CI 0.74–0.88, I² = 0%) as well as long-term mortality (OR 0.69, 95% CI 0.60–0.79, I² = 0%). In comparison to subjects with normal BMI, obese patients had lower ICU mortality (OR 0.88, 95% CI 0.82–0.93, I² = 5%). Hospital mortality was lower in severely obese and obese subjects (OR 0.71, 95% CI 0.53–0.94, I² = 74%, and OR 0.80, 95% CI 0.73–0.89, I² = 30%). Short-term mortality was lower in overweight and obese subjects (OR 0.82, 95% CI 0.75–0.90, I² = 0%, and, OR 0.75, 95% CI 0.66–0.84, I² = 8%, respectively). Long-term mortality was lower in severely obese, obese and overweight subjects (OR 0.39, 95% CI 0.18–0.83, and OR 0.63, 95% CI 0.46–0.86, I² = 56%, and OR 0.66, 95% CI 0.57–0.77, I² = 0%). All 4 mortality measures were higher in underweight subjects than in subjects with normal BMI. Obese subjects had significantly longer duration on mechanical ventilation than non-obese group (mean difference (MD) 0.48, 95% CI 0.16–0.80, I² = 37%), In comparison to subjects with normal BMI, severely obese BMI had significantly longer time in mechanical ventilation (MD 1.10, 95% CI 0.38–1.83, I² = 47%). Hospital LOS did not differ between obese and non-obese patients (MD 0.05, 95% CI -0.52 to 0.50, I² = 80%). Obese patients had longer ICU LOS than non-obese patients (MD 0.38, 95% CI 0.17–0.59, I² = 70%). Hospital LOS and ICU LOS did not differ significantly in subjects with different BMI status.</p><p>Conclusions</p><p>In ICU patients receiving mechanical ventilation, higher BMI is associated with lower mortality and longer duration on mechanical ventilation.</p></div

2-Deoxy-D-glucose ameliorates inflammation and fibrosis in a silicosis mouse model by inhibiting hypoxia-inducible factor-1α in alveolar macrophages

Inhaling silica causes the occupational illness silicosis, which mostly results in the gradual fibrosis of lung tissue. Previous research has demonstrated that hypoxia-inducible factor-1α (HIF-1α) and glycolysis-related genes are up-regulated in silicosis. The role of 2-deoxy-D-glucose (2-DG) as an inhibitor of glycolysis in silicosis mouse models and its molecular mechanisms remain unclear. Therefore, we used 2-DG to observe its effect on pulmonary inflammation and fibrosis in a silicosis mouse model. Furthermore, in vitro cell experiments were conducted to explore the specific mechanisms of HIF-1α. Our study found that 2-DG down-regulated HIF-1α levels in alveolar macrophages induced by silica exposure and reduced the interleukin-1β (IL-1β) level in pulmonary inflammation. Additionally, 2-DG reduced silica-induced pulmonary fibrosis. From these findings, we hypothesize that 2-DG reduced glucose transporter 1 (GLUT1) expression by inhibiting glycolysis, which inhibits the expression of HIF-1α and ultimately reduces transcription of the inflammatory cytokine, IL-1β, thus alleviating lung damage. Therefore, we elucidated the important regulatory role of HIF-1α in an experimental silicosis model and the potential defense mechanisms of 2-DG. These results provide a possible effective strategy for 2-DG in the treatment of silicosis

Flow diagram of study selection process.

<p>Flow diagram of study selection process.</p