Programmable base editing of zebrafish genome using a modified CRISPR-Cas9 system.

Precise genetic modifications in model animals are essential for biomedical research. Here, we report a programmable "base editing" system to induce precise base conversion with high efficiency in zebrafish. Using cytidine deaminase fused to Cas9 nickase, up to 28% of site-specific single-base mutations are achieved in multiple gene loci. In addition, an engineered Cas9-VQR variant with 5'-NGA PAM specificities is used to induce base conversion in zebrafish. This shows that Cas9 variants can be used to expand the utility of this technology. Collectively, the targeted base editing system represents a strategy for precise and effective genome editing in zebrafish.The use of base editing enables precise genetic modifications in model animals. Here the authors show high efficient single-base editing in zebrafish using modified Cas9 and its VQR variant with an altered PAM specificity

Cometary implications of recent laboratory experiments on the photochemistry of the C2H and C3H2 radicals

Recent laboratory results on the photodissociation of the C2H and C3H2 radicals are described. These studies show that the C2 and C3 radicals are produced by the 193 nm photolysis of the C2H and C3H2 radicals, respectively. The quantum state distributions that were determined for the C2 radicals put certain constraints on the initial conditions for any models of the observed C2 cometary spectra. Experimental observations of C2 formed by the 212.8 nm photolysis of C2H are used to calculate a range of photochemical lifetimes for the C2H radical

miR-221/222 promotes S-phase entry and cellular migration in control of basal-like breast cancer.

The miR-221/222 cluster has been demonstrated to function as oncomiR in human cancers. miR-221/222 promotes epithelial-to-mesenchymal transition (EMT) and confers tamoxifen resistance in breast cancer. However, the effects and mechanisms by which miR-221/222 regulates breast cancer aggressiveness remain unclear. Here we detected a much higher expression of miR-221/222 in highly invasive basal-like breast cancer (BLBC) cells than that in non-invasive luminal cells. A microRNA dataset from breast cancer patients indicated an elevated expression of miR-221/222 in BLBC subtype. S-phase entry of the cell cycle was associated with the induction of miR-221/222 expression. miRNA inhibitors specially targeting miR-221 or miR-222 both significantly suppressed cellular migration, invasion and G1/S transition of the cell cycle in BLBC cell types. Proteomic analysis demonstrated the down-regulation of two tumor suppressor genes, suppressor of cytokine signaling 1 (SOCS1) and cyclin-dependent kinase inhibit 1B (CDKN1B), by miR-221/222. This is the first report to reveal miR-221/222 regulation of G1/S transition of the cell cycle. These findings demonstrate that miR-221/222 contribute to the aggressiveness in control of BLBC

SUIT: Learning Significance-guided Information for 3D Temporal Detection

3D object detection from LiDAR point cloud is of critical importance for autonomous driving and robotics. While sequential point cloud has the potential to enhance 3D perception through temporal information, utilizing these temporal features effectively and efficiently remains a challenging problem. Based on the observation that the foreground information is sparsely distributed in LiDAR scenes, we believe sufficient knowledge can be provided by sparse format rather than dense maps. To this end, we propose to learn Significance-gUided Information for 3D Temporal detection (SUIT), which simplifies temporal information as sparse features for information fusion across frames. Specifically, we first introduce a significant sampling mechanism that extracts information-rich yet sparse features based on predicted object centroids. On top of that, we present an explicit geometric transformation learning technique, which learns the object-centric transformations among sparse features across frames. We evaluate our method on large-scale nuScenes and Waymo dataset, where our SUIT not only significantly reduces the memory and computation cost of temporal fusion, but also performs well over the state-of-the-art baselines.Comment: Accepted to IROS 202

Hepatitis E virus infection in swine workers: A meta‐analysis

Hepatitis E virus (HEV) infects both humans and animals. Swine has been confirmed to be the principal natural reservoir, which raises a concern that HEV infection would be substantially increasing among swine workers. The present study calculated the pooled prevalence of IgG antibodies against HEV among swine workers and the general population in previous cross‐sectional studies. We conducted a meta‐analysis comparing the prevalence of HEV infection between swine workers and the general population, including local residents, blood donors and non‐swine workers. Through searches in three databases (PubMed and OVID in English, and CNKI in Chinese) and after study selection, a total of 32 studies from 16 countries (from 1999 through 2018) were included in the meta‐analysis. A random‐effect model was employed in the study; an I 2 statistic assessed heterogeneity, and the Egger’s test detected publication bias. The comparative prevalence of anti‐HEV IgG was pooled from the studies. Compared to the general population, the prevalence ratio (PR) for swine workers was estimated to be 1.52 (95% CI 1.38–1.76) with the I 2 being 71%. No publication bias was detected (p = 0.40). A subgroup analysis further indicated increased prevalence of anti‐HEV IgG in the swine workers in Asia (PR = 1.49, 95% CI: 1.35–1.64), in Europe (PR = 1.93, 95% CI: 1.49–2.50) and in all five swine‐related occupations, including swine farmers, butchers, meat processors, pork retailers and veterinarians (PR ranged between 1.19 and 1.75). In summary, swine workers have a relatively higher prevalence of past HEV infection, and this finding is true across swine‐related occupations, which confirms zoonotic transmission between swine and swine workers.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147857/1/zph12548_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147857/2/zph12548.pd

Consecutive Inertia Drift of Autonomous RC Car via Primitive-based Planning and Data-driven Control

Inertia drift is an aggressive transitional driving maneuver, which is challenging due to the high nonlinearity of the system and the stringent requirement on control and planning performance. This paper presents a solution for the consecutive inertia drift of an autonomous RC car based on primitive-based planning and data-driven control. The planner generates complex paths via the concatenation of path segments called primitives, and the controller eases the burden on feedback by interpolating between multiple real trajectories with different initial conditions into one near-feasible reference trajectory. The proposed strategy is capable of drifting through various paths containing consecutive turns, which is validated in both simulation and reality.Comment: 9 pages, 10 figures, to appear to IROS 202

InsightLens: Discovering and Exploring Insights from Conversational Contexts in Large-Language-Model-Powered Data Analysis

The proliferation of large language models (LLMs) has revolutionized the capabilities of natural language interfaces (NLIs) for data analysis. LLMs can perform multi-step and complex reasoning to generate data insights based on users' analytic intents. However, these insights often entangle with an abundance of contexts in analytic conversations such as code, visualizations, and natural language explanations. This hinders efficient identification, verification, and interpretation of insights within the current chat-based interfaces of LLMs. In this paper, we first conduct a formative study with eight experienced data analysts to understand their general workflow and pain points during LLM-powered data analysis. Then, we propose an LLM-based multi-agent framework to automatically extract, associate, and organize insights along with the analysis process. Based on this, we introduce InsightLens, an interactive system that visualizes the intricate conversational contexts from multiple aspects to facilitate insight discovery and exploration. A user study with twelve data analysts demonstrates the effectiveness of InsightLens, showing that it significantly reduces users' manual and cognitive effort without disrupting their conversational data analysis workflow, leading to a more efficient analysis experience

Should chronic hepatitis B mothers breastfeed? a meta analysis

<p>Abstract</p> <p>Background</p> <p>Hepatitis B virus (HBV) exists in the breast milk of chronic hepatitis B (CHB) mothers. The authors use a meta-analytic technique to quantify the evidence of an association between breastfeeding and risk of CHB infection among the infants vaccinated against HBV.</p> <p>Methods</p> <p>Literature search is performed up to 2010 on the relationship between infantile CHB infection within one-year follow up after immunization with the third-dose hepatitis B vaccine and breastfeeding. Two reviewers independently extract the data and evaluate the methodological quality. A random-effects model is employed to systematically combine the results of all included studies.</p> <p>Results</p> <p>Based on data from 32 studies, 4.32% (244/5650) of infants born of CHB mothers develop CHB infection. The difference in risk of the infection between breastfed and formula-fed infants (RD) is -0.8%, (95% confidence interval [CI]: -1.6%, 0.1%). Analysis of the data from 16 of the studies finds that RD for mothers who are positive for the HBeAg and/or the HBV DNA, 0.7% (95%CI: -2.0%, 3.5%), is similar to that for those who are negative for these infectivity markers, -0.5% (95%CI: -1.7%, 0.6%).</p> <p>Conclusions</p> <p>Breast milk is infectious; yet, breastfeeding, even by mothers with high infectivity, is not associated with demonstrable risk of infantile CHB infection, provided that the infants have been vaccinated against HBV at birth.</p

Metagenomic surveillance and comparative genomic analysis of Chlamydia psittaci in patients with pneumonia

Chlamydia psittaci, a strictly intracellular bacterium, is an underestimated etiologic agent leading to infections in a broad range of animals and mild illness or pneumonia in humans. In this study, the metagenomes of bronchoalveolar lavage fluids from the patients with pneumonia were sequenced and highly abundant C. psittaci was found. The target-enriched metagenomic reads were recruited to reconstruct draft genomes with more than 99% completeness. Two C. psittaci strains from novel sequence types were detected and these were closely related to the animal-borne isolates derived from the lineages of ST43 and ST28, indicating the zoonotic transmissions of C. psittaci would benefit its prevalence worldwide. Comparative genomic analysis combined with public isolate genomes revealed that the pan-genome of C. psittaci possessed a more stable gene repertoire than those of other extracellular bacteria, with ~90% of the genes per genome being conserved core genes. Furthermore, the evidence for significantly positive selection was identified in 20 virulence-associated gene products, particularly bacterial membrane-embedded proteins and type three secretion machines, which may play important roles in the pathogen-host interactions. This survey uncovered novel strains of C. psittaci causing pneumonia and the evolutionary analysis characterized prominent gene candidates involved in bacterial adaptation to immune pressures. The metagenomic approach is of significance to the surveillance of difficult-to-culture intracellular pathogens and the research into molecular epidemiology and evolutionary biology of C. psittaci