Active Discriminative Dictionary Learning for Weather Recognition

Weather recognition based on outdoor images is a brand-new and challenging subject, which is widely required in many fields. This paper presents a novel framework for recognizing different weather conditions. Compared with other algorithms, the proposed method possesses the following advantages. Firstly, our method extracts both visual appearance features of the sky region and physical characteristics features of the nonsky region in images. Thus, the extracted features are more comprehensive than some of the existing methods in which only the features of sky region are considered. Secondly, unlike other methods which used the traditional classifiers (e.g., SVM and K-NN), we use discriminative dictionary learning as the classification model for weather, which could address the limitations of previous works. Moreover, the active learning procedure is introduced into dictionary learning to avoid requiring a large number of labeled samples to train the classification model for achieving good performance of weather recognition. Experiments and comparisons are performed on two datasets to verify the effectiveness of the proposed method

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

Interaction between ephrin/Eph and BDNF in modulating hippocampal synaptic transmission and synapse formation

The hippocampus is a brain structure known to be critical for learning and memory consolidation. Abnormal development or damage to this structure is known to play a role in developmental or degenerative neurological disorders such as autism and Alzheimer's disease. In this thesis, I argue that an interaction between ephrin/Eph and BDNF signaling pathways is critical for the development of the selective connection of CA3 neurons to CA1 neurons in hippocampus. This claim was evaluated on the basis of electrophysiology evidence about the ephrin/Eph -- BDNF interaction in synaptic activity, and the effect of the interrupting Eph and BDNF signaling on the hippocampal projection specificity onto CA1 neurons by functional synapse identification via the combination of electrophysiology and immunocytochemistry. First, I confirmed that the primary hippocampal neuronal culture can be a model for studying the specificity of synaptic connection within the hippocampal circuitry. Functional synapses were characterized by recording from pairs of cells which we subsequently identified with immunocytochemical labeling. Most connections were unidirectional, and I found that when one of the cells was a CA1 neuron (identified by labeling with the CA1 marker anti-SCIP) it was predominantly the postsynaptic member of the pair, a result consistent with in vivo connectivity. Second, ephrin-A/EphA signaling was shown to produce a transient increase in synaptic transmission and be able to inhibit the effect of subsequent BDNF application on synaptic activity. These electrophysiological experiments were suggestive of possible interaction between ephrin-A/EphA and BDNF in modulation synapse formation. Third, interruption of the endogenous EphA signaling by the kinase dominant negative EphA constructs significantly changed the natural synaptic connection selectivity in the hippocampal circuitry and dramatically increased the bi-directional connections in the culture as a consequence. The empirical results presented in this thesis provide a valuable mechanism for hippocampal trisynaptic circuitry development and function through balancing opposite influences of various modulating factors at specific developmental phases.Ph.D.Includes bibliographical references (p. 94-112)

Data for vitD - PTH paper

<p>Data for all the figures in the manuscript:</p> <p>PLOS ONE: PONE-D-14-33969R1 - [EMID:a23075f29839dd31]</p

Chem. Lett.

A new process for preparation of magnetic microspheres was investigated. In this process, the formation and the encapsulation of magnetic nanoparticles were accomplished in one step. The magnetic polymer microspheres exhibited superparamagnetic property and had a spherical shape with a smooth surface. This method can be used to prepare inorganic and organic composite particle when the inorganic particles can be prepared by chemical coprecipitation reaction.A new process for preparation of magnetic microspheres was investigated. In this process, the formation and the encapsulation of magnetic nanoparticles were accomplished in one step. The magnetic polymer microspheres exhibited superparamagnetic property and had a spherical shape with a smooth surface. This method can be used to prepare inorganic and organic composite particle when the inorganic particles can be prepared by chemical coprecipitation reaction

Contributions of Glucose and Hemoglobin A1c Measurements in Diabetes Screening.

OBJECTIVES: Given the long-term consequences of untreated diabetes, patients benefit from timely diagnoses. Payer policies often recognize glucose but not hemoglobin A1c (HbA1c) for diabetes screening. This study evaluates the different information that glucose and HbA1c provide for diabetes screening. METHODS: We conducted a retrospective review of national clinical laboratory testing during 2020 when glucose and HbA1c were ordered for routine diabetes screening, excluding patients with known diabetes, out-of-range glucose, or metabolic syndrome. RESULTS: Of 15.47 million glucose and HbA1c tests ordered simultaneously, 672,467 (4.35%) met screening inclusion criteria; 116,585 (17.3%) were excluded because of diabetes-related conditions or the specimen was nonfasting, leaving 555,882 result pairs. More than 1 in 4 patients 60 years of age or older with glucose within range had an elevated HbA1c level. HbA1c claims were denied more often for Medicare beneficiaries (38,918/65,273 [59.6%]) than for other health plans combined (23,234/291,764 [8.0%]). CONCLUSIONS: Although many health plans do not cover HbA1c testing for diabetes screening, more than 1 in 4 glucose screening patients 60 years of age or older with an in-range glucose result had a concurrent elevated HbA1c result. Guideline developers and health plans should explicitly recognize that glucose and HbA1c provide complementary information and together offer improved clinical utility for diabetes screening

Associations of aerobic and strength exercise with clinical laboratory test values.

Physical exercise may affect levels of blood-based biomarkers. However, exercise status is seldom considered in the interpretation of laboratory results. This study reports the associations between habitual exercise participation and clinical laboratory test results.The effects of days per week of aerobic and strength exercise participation on laboratory test results for 26 biomarkers in young adults aged 18 to 34 years (n = 80,111) were evaluated using percentile distribution analyses and multivariate regression.In both men and women, more days per week of either aerobic or strength exercise were significantly associated with lower levels of glucose, hemoglobin A1c, LDL cholesterol, total cholesterol, triglycerides, estimated glomerular filtration rate, globulin, and C-reactive protein, and significantly higher levels of HDL cholesterol, creatinine, iron, and percent saturation (all p < .05). Type of exercise or gender influenced the observed relationships with exercise frequency for total cholesterol, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, uric acid, bilirubin, and iron binding capacity.Physical exercise shifted the distribution of results into the direction suggestive of better health. Reported relationships may help clinicians and patients to better understand and interpret laboratory results in athletic populations and possibly re-evaluate interpretation of reference intervals for physically active populations

Supervised Filter Learning for Representation Based Face Recognition.

Representation based classification methods, such as Sparse Representation Classification (SRC) and Linear Regression Classification (LRC) have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances) in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP) features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm