The Prospects for Immigration Amendments

Obg proteins are a family of P-loop GTPases, conserved from bacteria to human. The Obg protein in Escherichia coli (ObgE) has been implicated in many diverse cellular functions, with proposed molecular roles in two global processes, ribosome assembly and stringent response. Here, using pre-steady state fast kinetics we demonstrate that ObgE is an anti-association factor, which prevents ribosomal subunit association and downstream steps in translation by binding to the 50S subunit. ObgE is a ribosome dependent GTPase; however, upon binding to guanosine tetraphosphate (ppGpp), the global regulator of stringent response, ObgE exhibits an enhanced interaction with the 50S subunit, resulting in increased equilibrium dissociation of the 70S ribosome into subunits. Furthermore, our cryo-electron microscopy (cryo-EM) structure of the 50S? ObgE? GMPPNP complex indicates that the evolutionarily conserved N-terminal domain (NTD) of ObgE is a tRNA structural mimic, with specific interactions with peptidyl-transferase center, displaying a marked resemblance to Class I release factors. These structural data might define ObgE as a specialized translation factor related to stress responses, and provide a framework towards future elucidation of functional interplay between ObgE and ribosome-associated (p) ppGpp regulators. Together with published data, our results suggest that ObgE might act as a checkpoint in final stages of the 50S subunit assembly under normal growth conditions. And more importantly, ObgE, as a (p) ppGpp effector, might also have a regulatory role in the production of the 50S subunit and its participation in translation under certain stressed conditions. Thus, our findings might have uncovered an under-recognized mechanism of translation control by environmental cues

Applications of New Technologies and New Methods in ZHENG Differentiation

With the hope to provide an effective approach for personalized diagnosis and treatment clinically, Traditional Chinese Medicine (TCM) is being paid increasing attention as a complementary and alternative medicine. It performs treatment based on ZHENG (TCM syndrome) differentiation, which could be identified as clinical special phenotypes by symptoms and signs of patients. However, it caused skepticism and criticism because ZHENG classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which is lack of objectivity and repeatability. Scientists have done fruitful researches for its objectivity and standardization. Compared with traditional four diagnostic methods (looking, listening and smelling, asking, and touching), in this paper, the applications of new technologies and new methods on the ZHENG differentiation were systemically reviewed, including acquisition, analysis, and integration of clinical data or information. Furthermore, the characteristics and application range of these technologies and methods were summarized. It will provide reference for further researches

FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation

Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit negative user behaviors (e.g., dislikes) or simply treat non-clicks as negative feedback, failing to learn negative user interests comprehensively. In such situations, users may experience fatigue because of seeing too many similar recommendations. In this paper, we propose Fatigue-Aware Network (FAN), a novel CTR model that directly perceives user fatigue from non-clicks. Specifically, we first apply Fourier Transformation to the time series generated from non-clicks, obtaining its frequency spectrum which contains comprehensive information about user fatigue. Then the frequency spectrum is modulated by category information of the target item to model the bias that both the upper bound of fatigue and users' patience is different for different categories. Moreover, a gating network is adopted to model the confidence of user fatigue and an auxiliary task is designed to guide the learning of user fatigue, so we can obtain a well-learned fatigue representation and combine it with user interests for the final CTR prediction. Experimental results on real-world datasets validate the superiority of FAN and online A/B tests also show FAN outperforms representative CTR models significantly

Sjögren’s Syndrome Complicated by Myeloid/Natural Killer Cell Precursor Acute Leukemia: Case Report and Review of the Literature

We report a case of Sjögren’s syndrome (SS) complicated by myeloid/natural killer (NK) cell precursor acute leukemia (M/NKPAL). A 75-year-old woman with a previous SS history for 2 years was routinely treated. Peripheral blood progenitor cells were increased, and subsequent bone marrow cell morphology examination showed the presence of acute myeloid leukemia type M4. However, flow cytometry analysis revealed that CD7/CD56/CD33/CD34/HLA-DR/cCD3 were all positive and myeloperoxidase- (MPO-) specific staining, other T cells, NK cells, and myeloid markers were all negative. Clonal T-cell receptor (TCR)β/TCRγ/TCRδ gene rearrangements and Epstein-Barr virus (EBV) were negative. The diagnosis of M/NKPAL was therefore confirmed. Unfortunately, this patient did not receive chemotherapy and later died of acute left heart failure and respiratory failure. SS complication with M/NKPAL is relatively rare. Combined with the relevant literatures, our study offers new insights into the clinical characteristics, pathological features, possible pathogenesis, and differential diagnosis of this rare disease

Exploration of Macro-Micro Biomarkers for Dampness-Heat Syndrome Differentiation in Different Diseases

Increased attention is being paid to traditional Chinese medicine (TCM) as a complementary and alternative medicine to provide an effective approach for personalized diagnosis and clinical treatment. TMC performs treatment based on differentiation of TCM syndrome (ZHENG), which may identify special phenotypes by symptoms and signs of patients even if they are in different diseases. There has, however, been skepticism and criticism because syndrome classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. In order to transform syndrome classification into mainstream medicine, we introduce a macro-micro approach that combines symptoms, clinical indicators, and metabolites. The present paper explores the macro-micro biomarkers of dampness-heat syndrome in chronic hepatitis B and nonalcoholic fatty liver patients, which could provide the basis for developing a possible population-screening tool for selecting target individuals and creating an evaluation index for personalized treatment

Similar Connotation in Chronic Hepatitis B and Nonalcoholic Fatty Liver Patients with Dampness-Heat Syndrome

The phenomenon that the same syndrome turns up in different diseases appears in the sight of people around the world, which raises the thought for possibility of “Same Treatment for Different Diseases.” Actually, treatment based on ZHENG classification in Traditional Chinese Medicine could bring revelation for the former finding. The dampness-heat syndrome in chronic hepatitis B and nonalcoholic fatty liver is regarded as the breakthrough point. We discussed the molecular mechanism of similar connotation that exists in chronic hepatitis B and nonalcoholic fatty liver by metabonomics to give the modern understanding of dampness-heat syndrome. Both urine and serum metabolic profiling revealed that obvious differences existed between dampness-heat syndrome and non-dampness-heat syndrome but the commonality was proved to appear in chronic hepatitis B and nonalcoholic fatty liver patients with dampness-heat syndrome. Furthermore, disorder of body fluid metabolism, decline in digestive capacity, and imbalance of intestinal flora were found to be the new guiding for treatment, with the hope to provide the basis for Chinese personalized medicine

ZHENG-Omics Application in ZHENG Classification and Treatment: Chinese Personalized Medicine

With the hope to provide an effective approach for personalized diagnosis and treatment clinically, traditional chinese medicine (TCM) is being paid increasing attention as a complementary and alternative medicine. It performs treatment based on ZHENG (TCM syndrome) classification, which could be identified clinical special phenotypes by symptoms and signs of patients even if they have a different disease. However, it caused controversy because ZHENG classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. Although researchers and scientists of TCM have done some work with a lot of beneficial methods, the results could not reach satisfactory with the shortcomings of generalizing the entire state of the body or ignoring the patients' feelings. By total summary, mining, and integration of existing researches, the present paper attempts to introduce a novel macro-microconcept of ZHENG-omics, with the prospect of bright future in providing an objective and repeatable approach for Chinese personalized medicine in an effective way. In this paper, we give the brief introduction and preliminary validation, and discuss strategies and system-oriented technologies for achieving this goal