Cohort records study of 19,655 women who received postabortion care in a tertiary hospital 2010–2013 in China : what trends can be observed?

The retrospective cohort epidemiological study was to investigate the characteristics of women who underwent induced abortion. Data were retrospectively collected from women who underwent induced abortions () at the Xiamen Maternity and Child Health Care Hospital (2010–2013). The characteristics of women who underwent induced abortions included mean age, unmarried status, no previous deliveries, first pregnancy, ≥2 abortions including the current one, and a history of caesarian section. From 2010 to 2013, mean age increased and declines were observed in the ratio of induced abortions to live births, the proportion of induced abortions among women of 15–24 years, those who were unmarried, had their first pregnancy, or had no history of delivery. However, the rates of induced abortions increased among women who were lactating, had a history of caesarian section, or had an interpregnancy interval of <6 months. This snapshot of induced abortions in China might suggest that the numbers are increasing but the ratio to live births has fallen. Methods should be improved to prevent unwanted pregnancies and reduce the number of induced abortions in China. It must be emphasized that differences in mentality and culture between countries might limit the representativeness of these results

Modulating Linker Composition of Haptens Resulted in Improved Immunoassay for Histamine.

Histamine (HA) is an important food contaminant generated during food fermentation or spoilage. However, an immunoassay for direct (derivatization free) determination of HA has rarely been reported due to its small size to induce the desired antibodies by its current hapten-protein conjugates. In this work, despite violating the classical hapten design criteria which recommend introducing a linear aliphatic (phenyl free) linker into the immunizing hapten, a novel haptens, HA-245 designed and synthesized with a phenyl-contained linker, exhibited significantly enhanced immunological properties. Thus, a quality-improved monoclonal antibody (Mab) against HA was elicited by its hapten-carrier conjugates. Then, as the linear aliphatic linker contained haptens, Hapten B was used as linker-heterologous coating haptens to eliminate the recognition of linker antibodies. Indirect competitive ELISA (ic-ELISA) was developed with a 50% inhibition concentration (IC50) of 0.21 mg/L and a limit of detection (LOD) of 0.06 mg/L in buffer solution. The average recoveries of HA from spiked food samples for this ic-ELISA ranged from 84.1% and 108.5%, and the analysis results agreed well with those of referenced LC-MS/MS. This investigation not only realized derivatization-free immunoassay for HA, but also provided a valuable guidance for hapten design and development of immunoassay for small molecules

Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning

Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about their environments, they are more likely to achieve better cooperation. Meanwhile, only cognitive consistency within a neighborhood matters because humans only interact directly with their neighbors. Inspired by these observations, we take the first step to introduce \emph{neighborhood cognitive consistency} (NCC) into multi-agent reinforcement learning (MARL). Our NCC design is quite general and can be easily combined with existing MARL methods. As examples, we propose neighborhood cognition consistent deep Q-learning and Actor-Critic to facilitate large-scale multi-agent cooperations. Extensive experiments on several challenging tasks (i.e., packet routing, wifi configuration, and Google football player control) justify the superior performance of our methods compared with state-of-the-art MARL approaches.Comment: Accepted by AAAI2020 with oral presentation (https://aaai.org/Conferences/AAAI-20/wp-content/uploads/2020/01/AAAI-20-Accepted-Paper-List.pdf). Since AAAI2020 has started, I have the right to distribute this paper on arXi

Elevated expression of CDK4 in lung cancer

<p/> <p>Background</p> <p>The aim of the present study was to analyze the expression of Cyclin-dependent kinase 4 (<it>CDK4</it>) in lung cancer and its correlation with clinicopathologic features. Furthermore, the involvement of <it>CDK4</it>-mediated cell cycle progression and its molecular basis were investigated in the pathogenesis of lung cancer.</p> <p>Methods</p> <p>Using immunohistochemistry analysis, we analyzed <it>CDK4 </it>protein expression in 89 clinicopathologically characterized lung cancer patients (59 males and 30 females) with ages ranging from 36 to 78 years and compared them to 23 normal lung tissues. Cases with cytoplasmic and nuclear <it>CDK4 </it>immunostaining score values greater than or equal to 7 were regarded as high expression while scores less than 7 were considered low expression. The correlation between the expression level of <it>CDK4 </it>and clinical features was analyzed. Furthermore, we used lentiviral-mediated shRNA to suppress the expression of CDK4 and investigate its function and molecular mechanism for mediating cell cycle progression.</p> <p>Results</p> <p>The expression level of <it>CDK4 </it>protein was significantly increased in lung cancer tissues compared to normal tissues (<it>P </it>< 0.001). In addition, high levels of <it>CDK4 </it>protein were positively correlated with the status of pathology classification (<it>P </it>= 0.047), lymph node metastasis (<it>P </it>= 0.007), and clinical stage (<it>P </it>= 0.004) of lung cancer patients. Patients with higher <it>CDK4 </it>expression had a markedly shorter overall survival time than patients with low <it>CDK4 </it>expression. Multivariate analysis suggested the level of <it>CDK4 </it>expression was an independent prognostic indicator (<it>P </it>< 0.001) for the survival of patients with lung cancer. Use of lentiviral-mediated shRNA to inhibit the expression of <it>CDK4 </it>in lung cancer cell line A549 not only inhibited cell cycle progression, but also dramatically suppressed cell proliferation, colony formation, and migration. Furthermore, suppressing <it>CDK4 </it>expression also significantly elevated the expression of cell cycle regulator <it>p21</it></p> <p>Conclusion</p> <p>Overexpressed <it>CDK4 </it>is a potential unfavorable prognostic factor and mediates cell cycle progression by regulating the expression of <it>p21 </it>in lung cancer</p

TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer

We present TransNormerLLM, the first linear attention-based Large Language Model (LLM) that outperforms conventional softmax attention-based models in terms of both accuracy and efficiency. TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization. Specifically, we use LRPE together with an exponential decay to avoid attention dilution issues while allowing the model to retain global interactions between tokens. Additionally, we propose Lightning Attention, a cutting-edge technique that accelerates linear attention by more than twice in runtime and reduces memory usage by a remarkable four times. To further enhance the performance of TransNormer, we leverage a gating mechanism for smooth training and a new tensor normalization scheme to accelerate the model, resulting in an impressive acceleration of over $20\%$. Furthermore, we develop a robust inference algorithm that ensures numerical stability and consistent inference speed, regardless of the sequence length, showcasing superior efficiency during both training and inference stages. We also implement an efficient model parallel schema for TransNormerLLM, enabling seamless deployment on large-scale clusters and facilitating expansion to even more extensive models, i.e., LLMs with 175B parameters. We validate our model design through a series of ablations and train models with sizes of 385M, 1B, and 7B on our self-collected corpus. Benchmark results demonstrate that our models not only match the performance of state-of-the-art LLMs with Transformer but are also significantly faster. Code is released at: https://github.com/OpenNLPLab/TransnormerLLM.Comment: Technical Report. Yiran Zhong is the corresponding author. Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen contribute equally to this paper. Code is released at: https://github.com/OpenNLPLab/TransnormerLL

Integrated application of uniform design and least-squares support vector machines to transfection optimization

<p>Abstract</p> <p>Background</p> <p>Transfection in mammalian cells based on liposome presents great challenge for biological professionals. To protect themselves from exogenous insults, mammalian cells tend to manifest poor transfection efficiency. In order to gain high efficiency, we have to optimize several conditions of transfection, such as amount of liposome, amount of plasmid, and cell density at transfection. However, this process may be time-consuming and energy-consuming. Fortunately, several mathematical methods, developed in the past decades, may facilitate the resolution of this issue. This study investigates the possibility of optimizing transfection efficiency by using a method referred to as least-squares support vector machine, which requires only a few experiments and maintains fairly high accuracy.</p> <p>Results</p> <p>A protocol consists of 15 experiments was performed according to the principle of uniform design. In this protocol, amount of liposome, amount of plasmid, and the number of seeded cells 24 h before transfection were set as independent variables and transfection efficiency was set as dependent variable. A model was deduced from independent variables and their respective dependent variable. Another protocol made up by 10 experiments was performed to test the accuracy of the model. The model manifested a high accuracy. Compared to traditional method, the integrated application of uniform design and least-squares support vector machine greatly reduced the number of required experiments. What's more, higher transfection efficiency was achieved.</p> <p>Conclusion</p> <p>The integrated application of uniform design and least-squares support vector machine is a simple technique for obtaining high transfection efficiency. Using this novel method, the number of required experiments would be greatly cut down while higher efficiency would be gained. Least-squares support vector machine may be applicable to many other problems that need to be optimized.</p