Analysis of noncanonical calciumdependent protein kinases in Toxoplasma gondii by targeted gene deletion using CRISPR/Cas9

Calcium-dependent protein kinases (CDPKs) are expanded in apicomplexan parasites, especially in Toxoplasma gondii where 14 separate genes encoding these enzymes are found. Although previous studies have shown that several CDPKs play a role in controlling invasion, egress, and cell division in T. gondii, the roles of most of these genes are unexplored. Here we developed a more efficient method for gene disruption using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9) that was modified to completely delete large, multiexonic genes from the genome and to allow serial replacement by recycling of the selectable marker using Cre-loxP. Using this system, we generated a total of 24 mutants in type 1 and 2 genetic backgrounds to ascertain the functions of noncanonical CDPKs. Remarkably, although we were able to confirm the essentiality of CDPK1 and CDPK7, the majority of CDPKs had no discernible phenotype for growth in vitro or infection in the mouse model. The exception to this was CDPK6, loss of which leads to reduced plaquing, fitness defect in a competition assay, and reduced tissue cyst formation in chronically infected mice. Our findings highlight the utility of CRISPR/Cas9 for rapid serial gene deletion and also suggest that additional models are needed to reveal the functions of many genes in T. gondii

Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks

Predicting the future health information of patients from the historical Electronic Health Records (EHR) is a core research task in the development of personalized healthcare. Patient EHR data consist of sequences of visits over time, where each visit contains multiple medical codes, including diagnosis, medication, and procedure codes. The most important challenges for this task are to model the temporality and high dimensionality of sequential EHR data and to interpret the prediction results. Existing work solves this problem by employing recurrent neural networks (RNNs) to model EHR data and utilizing simple attention mechanism to interpret the results. However, RNN-based approaches suffer from the problem that the performance of RNNs drops when the length of sequences is large, and the relationships between subsequent visits are ignored by current RNN-based approaches. To address these issues, we propose {\sf Dipole}, an end-to-end, simple and robust model for predicting patients' future health information. Dipole employs bidirectional recurrent neural networks to remember all the information of both the past visits and the future visits, and it introduces three attention mechanisms to measure the relationships of different visits for the prediction. With the attention mechanisms, Dipole can interpret the prediction results effectively. Dipole also allows us to interpret the learned medical code representations which are confirmed positively by medical experts. Experimental results on two real world EHR datasets show that the proposed Dipole can significantly improve the prediction accuracy compared with the state-of-the-art diagnosis prediction approaches and provide clinically meaningful interpretation

Influence of surface coating on structure and properties of metallic lithium anode for rechargeable Li-O2 battery

Abstract Amorphous lithium phosphorous oxynitride film was coated directly on pre-treated lithium metal as anode of lithium air battery by radio-frequency sputtering technique from a Li 3 PO 4 target. The structure and composition of modified anode was analyzed before and after charge/discharge test in a lithium-air battery, which comprises 0.5 M LiNO 3 /TEGDME as the electrolyte and super P carbon as cathode. Batteries were galvanostatically discharged by an Arbin BT-2000 battery tester between open current voltage and 2.15 V vs. Li + /Li at various current regimes ranging from 0.1–0.4 mA/cm 2 . Compared with fresh lithium, LIPON-coated anode exhibited better electrochemical performance. Good charging efficiency of 90% at a narrower voltage gap with high ionic conductivity of 9.4 × 10 −5 S/cm was achieved through optimizing lithium pre-treated conditions, sputtering N 2 flows and suitable solute for electrolyte

Synergy effect of talent policies on corporate innovation—Evidence from China

The talent policy is a powerful tool for the government to implement and the talent is the key resources attributed to corporate innovation. Different types of talent policy instruments need to be synergistically combined to promote corporate innovation. By using the sample of China’s listed companies during the period 2007–2020, this paper applies the multidimensional fixed-effect OLS method to explore the impact of different types of talent policies and talent policy mixes on corporate innovation, and adopts threshold regression model to detect the threshold effect of talent gathering in the framework of government-enterprise interaction. The results are shown as follows: The supply-side talent policy (STP), demand-side talent policy (DTP), and environmental-side talent policy (ETP) all positively affect corporate innovation. Talent policy mixes have a significant synergy on corporate innovation. And the effect of STP- DTP-ETP mixes is greater than that of any two types of talent policy mixes. Talent gathering has a threshold effect on the relationship between STP-DTP-ETP mixes and corporate innovation. Our study provides empirical evidence of the positive impact of different types of talent policy and their mixes on corporate innovation and enriches the literature related to talent gathering

The effectiveness of modified, group-based CBT for dementia worry among Chinese elders

Objectives Dementias are highly prevalent among Chinese elders. This study examined the effectiveness of a modified group cognitive behavioral therapy (CBT) on dementia worry among Chinese older adults. Methods Eighty-two older adults recruited from four elder group homes were randomly assigned to either intervention or control group. The intervention group (n= 44) received eight weekly 60-minute face-to-face CBT, while the control group (n=38) received treatment-as-usual. Results Outcomes indicated that the modified group CBT has significantly reduced dementia worry and culturally biased beliefs about dementia (p<.001). Study findings supported both statistically and clinically significant effect of modified group CBT on dementia worry [g=-1.52, 95% CI (-2.01, -1.03)] and biased beliefs about dementia [g=-.95, 95% CI (-1.40, -.49)]. Discussion The culturally adapted CBT is promising in alleviating worries and anxiety over dementia among Chinese older adults. Future research needs to include larger samples and participants from different regions to replicate findings.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167612/1/An et al., 2020.pdfSEL