Miracle-dz/UniFAR-FTUs huggingface dataset:
A transient reporter for editing enrichment (TREE) in human cells

Abstract Current approaches to identify cell populations that have been modified with deaminase base editing technologies are inefficient and rely on downstream sequencing techniques. In this study, we utilized a blue fluorescent protein (BFP) that converts to green fluorescent protein (GFP) upon a C-to-T substitution as an assay to report directly on base editing activity within a cell. Using this assay, we optimize various base editing transfection parameters and delivery strategies. Moreover, we utilize this assay in conjunction with flow cytometry to develop a transient reporter for editing enrichment (TREE) to efficiently purify base-edited cell populations. Compared to conventional cell enrichment strategies that employ reporters of transfection (RoT), TREE significantly improved the editing efficiency at multiple independent loci, with efficiencies approaching 80%. We also employed the BFP-to-GFP conversion assay to optimize base editor vector design in human pluripotent stem cells (hPSCs), a cell type that is resistant to genome editing and in which modification via base editors has not been previously reported. At last, using these optimized vectors in the context of TREE allowed for the highly efficient editing of hPSCs. We envision TREE as a readily adoptable method to facilitate base editing applications in synthetic biology, disease modeling, and regenerative medicine.
Development of Self-Focusing Piezoelectric Composite Ultrasound Transducer Using Laser Engraving Technology

Based on the Fresnel half-wave band interference and laser engraving, a high-frequency self-focusing piezoelectric composite ultrasound transducer (FPCUT) is presented in this article. The theoretical analysis was performed based on the concept of constructive interference of acoustic waves and the electromechanical response of piezoelectric composites. The calculated and simulation results showed that the FPCUT combined the advantages of the composite transducer and the plate self-focusing transducer and can achieve high electromechanical coupling coefficient (>0.66), low acoustic impedance (~15 MRayl), high intensity, and short focal length. Furthermore, a 30-MHz self-focusing piezoelectric composite transducer prototype was fabricated and tested. It is composed of 11 lead zirconate titanates (PZTs) and ten epoxy annuluses. A UV engraving laser with a linewidth of 10 $\mu \text{m}$ was used in each of the PZTs to form the annuluses, and the kerf among the annuluses was filled with epoxy. The measured center frequency, bandwidth, and focal length were 27 MHz, 50.37%, and 3.7 mm, respectively. A vertical wire phantom was imaged using a fabricated transducer and a contrast flat transducer; the images showed significant improvement in the lateral resolution over a range of 9 mm. Because this self-focusing piezoelectric composite transducer was based on the precise laser engraving systems, the fabrication process was accurate and controllable, which enabled it to have good potential for medical imaging and industrial nondestructive testing applications.
The Blood and Muscle Expression Pattern of the Equine TCAP Gene during the Race Track Training of Arabian Horses

Simple Summary The highly selective breeding of horses results in a variety of fiber type compositions among the breeds. Moreover, fiber type composition is known to differ within and between muscles. Telethonin (TCAP) plays a significant role in myofibril assembly, muscle development, and functional regulation. Analysis performed by qPCR of the gluteus medius muscle and the whole blood of Arabian horses during the training schedule showed that the expression pattern of the TCAP gene differs between skeletal muscles and whole blood. The results of these studies are a base for further research focused on the identification of processes related to adaptation of exertion in horses. Abstract Horse musculature has been shaped through evolution by environmental and human factors, which has resulted in several extraordinary adaptations to physical effort. Skeletal muscle plasticity results from the response to mechanical stimulation causing hypertrophy, where sarcomeres increase the muscle’s cross-sectional area under the influence of contractile forces. The aim of the present study was the evaluation of transcript abundance of the telethonin (TCAP) gene, which is a part of the sarcomere macromolecular mechanosensory complex in the gluteus medius muscle, and the whole blood of Arabian horses during flat race training. The analysis, performed by quantitative PCR, showed an increase of TCAP transcripts in skeletal muscle. However, in whole blood, the transcript abundance decreased after the first stage of training and further increased after the second phase. The obtained results indicate a lack of similarity of TCAP gene expression in both tissues.
Dog Owners’ Knowledge about Rabies and Other Factors That Influence Canine Anti-Rabies Vaccination in the Upper East Region of Ghana

Background: Human rabies, often contracted through dog bites, is a serious but neglected public health problem in the tropics, including Ghana. Due to its high fatality rate, adequate knowledge and vaccination of domestic dogs against the disease are very crucial in reducing its burden. We examined dog owners’ knowledge level on rabies and factors that influenced anti-rabies vaccination of dogs in the Upper East Region of Ghana. Methods: This descriptive cross-sectional study was conducted among 260 randomly sampled dog owners in six communities from six Districts using a multistage sampling technique, in the Upper East Region of Ghana. An interviewer-administered questionnaire was used to collect data from the respondents. Descriptive and inferential analyses were done using STATA 14.1. Results: While knowledge about rabies was 199 (76.5%), that about anti-rabies vaccination was 137 (52.7%). District of residence (χ2 = 112.59, p < 0.001), sex (χ2 = 6.14, p = 0.013), education (χ2 = 20.45, p < 0.001) as well as occupation (χ2 = 11.97, p = 0.007) were significantly associated with rabies knowledge. District of residence (χ2 = 57.61, p < 0.001), Educational level (χ2 = 15.37, p = 0.004), occupation (χ2 = 11.66, p = 0.009), religion (χ2 = 8.25, p = 0.016) and knowledge on rabies (χ2 = 42.13, p < 0.001) were also statistically associated with dog vaccination against rabies. Dog owners with good knowledge on rabies for instance, were more likely to vaccinate their dogs against rabies compared to those with poor knowledge [AOR = 1.99 (95% CI: 0.68, 5.86), p = 0.210]. Dog owners with tertiary level of education were also 76.31 times more likely (95% CI: 6.20, 938.49, p = 0.001) to have good knowledge about rabies compared to those with no formal education. Conclusions: Dog owners in the Upper East Region of Ghana had good knowledge about rabies. This, however, did not translate into correspondingly high levels of dog vaccination against the disease. Rabies awareness and vaccination campaigns should, therefore, be intensified in the region, especially among the least educated and female dog owners.
Experience Report on the Challenges and Opportunities in Securing Smartphones Against Zero-Click Attacks

Zero-click attacks require no user interaction and typically exploit zero-day (i.e., unpatched) vulnerabilities in instant chat applications (such as WhatsApp and iMessage) to gain root access to the victim's smartphone and exfiltrate sensitive data. In this paper, we report our experiences in attempting to secure smartphones against zero-click attacks. We approached the problem by first enumerating several properties we believed were necessary to prevent zero-click attacks against smartphones. Then, we created a security design that satisfies all the identified properties, and attempted to build it using off-the-shelf components. Our key idea was to shift the attack surface from the user's smartphone to a sandboxed virtual smartphone ecosystem where each chat application runs in isolation. Our performance and usability evaluations of the system we built highlighted several shortcomings and the fundamental challenges in securing modern smartphones against zero-click attacks. In this experience report, we discuss the lessons we learned, and share insights on the missing components necessary to achieve foolproof security against zero-click attacks for modern mobile devices.
Vitamin D status among adults (18–65 years old) attending primary healthcare centres in Qatar: a cross-sectional analysis of the Electronic Medical Records for the year 2017

Objectives To investigate the prevalence of vitamin D deficiency among individuals attending primary healthcare facilities in Qatar and to assess the association between vitamin D deficiency and some medical conditions in persons aged 18–65 years old. Setting The study was undertaken in publicly funded primary healthcare services in the State of Qatar. Participants A total of 102 342 participants aged between 18 and 65 years old with a valid serum vitamin D test result during the year 2017. Outcome measures Serum level <10 ng/mL (<25 nmol/L) was defined as severe vitamin D deficiency, a serum level of <20 ng/mL (<50 nmol/L) was defined as vitamin D deficiency and a serum level <30 ng/mL (<75 nmol/L) defined as vitamin D insufficiency. Results The prevalence rate of severe vitamin D deficiency was 14.1% among study participants with no history of vitamin D replacement therapy in the previous months. The prevalence rate of vitamin D deficiency was as high as 71.4% and that of vitamin D insufficiency was up to 92.7%. None of the five chronic conditions explored in the study (diabetes, hypertension, asthma, stroke and cardiovascular disease) had an obvious association with severe vitamin D deficiency status in a bivariate analysis. However, multivariate modelling showed that (adjusting for age, gender, body mass index and nationality and each of the included chronic conditions) hypertension, cardiovascular diseases and stroke placed an individual at a higher risk of having an associated severe vitamin D deficiency status. Conclusion Although not comprehensive and nationally representative, this study is suggestive of a higher prevalence of vitamin D deficiency among young adults, females, Qatari nationality and those with higher body mass index. Multivariate modelling showed that hypertension, cardiovascular diseases and stroke were associated with a higher risk of severe vitamin D deficiency status.
Global prediction of chromatin accessibility using small-cell-number and single-cell RNA-seq

Abstract Conventional high-throughput genomic technologies for mapping regulatory element activities in bulk samples such as ChIP-seq, DNase-seq and FAIRE-seq cannot analyze samples with small numbers of cells. The recently developed low-input and single-cell regulome mapping technologies such as ATAC-seq and single-cell ATAC-seq (scATAC-seq) allow analyses of small-cell-number and single-cell samples, but their signals remain highly discrete or noisy. Compared to these regulome mapping technologies, transcriptome profiling by RNA-seq is more widely used. Transcriptome data in single-cell and small-cell-number samples are more continuous and often less noisy. Here, we show that one can globally predict chromatin accessibility and infer regulatory element activities using RNA-seq. Genome-wide chromatin accessibility predicted by RNA-seq from 30 cells can offer better accuracy than ATAC-seq from 500 cells. Predictions based on single-cell RNA-seq (scRNA-seq) can more accurately reconstruct bulk chromatin accessibility than using scATAC-seq. Integrating ATAC-seq with predictions from RNA-seq increases the power and value of both methods. Thus, transcriptome-based prediction provides a new tool for decoding gene regulatory circuitry in samples with limited cell numbers.
Postinjury Inhibition of miR-181a Promotes Restoration of Hippocampal CA1 Neurons after Transient Forebrain Ischemia in Rats

Abstract The cellular and molecular mechanisms regulating postinjury neurogenesis in the adult hippocampus remain undefined. We have previously demonstrated that preinjury treatment with anti-microRNA (miR)-181a preserved neurons and prevented astrocyte dysfunction in the hippocampal cornu ammonis-1 (CA1) following transient forebrain ischemia. In the present study, we assessed postinjury treatment with anti-miR-181a on recovery of CA1 neurons following transient forebrain ischemia in rats. Stereotactic CA1 injection of miR-181a antagomir at either 2 h or 7 d postinjury resulted in improved restoration of CA1 measured at 28 d postinjury. Treatment with antagomir was associated with overexpression of the mir-181a target cell adhesion-associated, oncogene-related protein and enhanced expression of the neuroprogenitor cell marker doublecortin (DCX) in the CA1. Assessment of GFAP+ cell fate by Cre/Lox-mediated deletion demonstrated that some GFAP+ cells in CA1 exhibited de novo DCX expression in response to injury. In vitro experiments using primary neuronal stem cells confirmed that miR-181a inhibition augmented the expression of DCX and directed cellular differentiation toward a neuronal fate. These results suggest that miR-181a inhibition plays a central role in the restoration of CA1 neurons via augmentation of early latent neurogenic gene activation in neural progenitor cells, including some reactive astrocytes. Therapeutic interventions targeting this restorative process may represent a novel postinjury approach to improve clinical outcomes in survivors of forebrain ischemia.
A Novel Approach for Potential Human LncRNA-Disease Association Prediction Based on Local Random Walk

In recent years, lncRNAs (long non-coding RNAs) have been proved to be closely related to many diseases that are seriously harmful to human health. Although researches on clarifying the relationships between lncRNAs and diseases are developing rapidly, associations between the lncRNAs and diseases are still remaining largely unknown. In this manuscript, a novel Local Random Walk based prediction model called LRWHLDA is proposed for inferring potential associations between human lncRNAs and diseases. In LRWHLDA, a new heterogeneous network is established first, which allows that LRWHLDA can be implemented in the case of lacking known lncRNA-disease associations. And then, an improved local random walk method is designed for prediction of novel lncRNA-disease associations, which can help LRWHLDA achieve high prediction accuracy but with low time complexity. Finally, in order to evaluate the prediction performance of LRWHLDA, different frameworks such as LOOCV, 2-folds CV, and 5-folds CV have been implemented, simulation results indicate that LRWHLDA can achieve reliable AUCs of 0.8037, 0.8354, and 0.8556 under the frameworks of 2-fold CV, 5-fold CV, and LOOCV, respectively. Hence, it is easy to know that LRWHLDA contains the potential to be a representative of emerging methods in the field of research on potential lncRNA-disease associations prediction.
Zero-Shot Classification by Logical Reasoning on Natural Language Explanations

Humans can classify data of an unseen category by reasoning on its language explanations. This ability is owing to the compositional nature of language: we can combine previously seen attributes to describe the new category. For example, we might describe a sage thrasher as"it has a slim straight relatively short bill, yellow eyes and a long tail", so that others can use their knowledge of attributes"slim straight relatively short bill","yellow eyes"and"long tail"to recognize a sage thrasher. Inspired by this observation, in this work we tackle zero-shot classification task by logically parsing and reasoning on natural language expla-nations. To this end, we propose the framework CLORE (Classification by LOgical Reasoning on Explanations). While previous methods usually regard textual information as implicit features, CLORE parses explanations into logical structures and then explicitly reasons along thess structures on the input to produce a classification score. Experimental results on explanation-based zero-shot classification benchmarks demonstrate that CLORE is superior to baselines, which we further show mainly comes from higher scores on tasks requiring more logical reasoning. We also demonstrate that our framework can be extended to zero-shot classification on visual modality. Alongside classification decisions, CLORE can provide the logical parsing and reasoning process as a clear form of rationale. Through empirical analysis we demonstrate that CLORE is also less affected by linguistic biases than baselines.
Artificial intelligence in dermatology: past, present, and future

Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China; Graduate School, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China; Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, Hefei, Anhui 230032, China; Shanghai Wheat Color Intelligent Technology Company, LTD, Shanghai 200051, China; Department of Dermatology, Air Force General Hospital of People’s Liberation Army, Beijing 100142, China; Department of Dermatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
Stochastic Dual Simplex Algorithm: A Novel Heuristic Optimization Algorithm

A new heuristic optimization algorithm is presented to solve the nonlinear optimization problems. The proposed algorithm utilizes a stochastic method to achieve the optimal point based on simplex techniques. A dual simplex is distributed stochastically in the search space to find the best optimal point. Simplexes share the best and worst vertices of one another to move better through search space. The proposed algorithm is applied to 25 well-known benchmarks, and its performance is compared with grey wolf optimizer (GWO), particle swarm optimization (PSO), Nelder–Mead simplex algorithm, hybrid GWO combined with pattern search (hGWO-PS), and hybrid GWO algorithm combined with random exploratory search algorithm (hGWO-RES). The numerical results show that the proposed algorithm, called stochastic dual simplex algorithm (SDSA), has a competitive performance in terms of accuracy and complexity.
The Longitudinal Associations between Physical Health and Mental Health among Older Adults

Abstract Objectives This study examines the lead-lag relationship between physical and mental health among older adults. Method Data are collected from 16,417 older adults aged 50 years and older participating in the biannual Health and Retirement Study (HRS). Participants were assessed on up to 11 measurement points over a 21-year period from 1994 to 2014. Physical health was measured as a composite of chronic diseases, functional limitations, and difficulties in basic and instrumental activities of daily living. Mental health was measured with the modified CES-D. Bivariate latent change score models (BLCSM) were estimated. Results Both physical and mental health declined in the observed years, with slower declining rates over time. A reciprocal relationship emerged, with the prior level of physical health acting as the leading indicator of subsequent change in mental health, and the prior mental health state acting as the leading indicator of subsequent changes in physical health. Additionally, the influence of physical health on mental health changes was larger than the corresponding effect of mental health on subsequent physical health. Conclusion This study demonstrates the reciprocal relationship between physical and mental health in later adulthood and highlights the need to pay attention to the mental health of older people with physical health problems.
Simulation of Ultrasonic Beam Propagation From Phased Arrays in Anisotropic Media Using Linearly Phased Multi-Gaussian Beams

Phased array ultrasonic testing is widely used to test structures for flaws due to its ability to produce steered and focused beams. The inherent anisotropic nature of some materials, however, leads to skewing and distortion of the phased array beam and consequently measurement errors. To overcome this, a quantitative model of phased array beam propagation in such materials is required, so as to accurately model the skew and the distortion. The existing phased array beam models which are based on exact methods or numerical methods are computationally expensive or time consuming. This article proposes a modeling approach based on developing the linear phased multi-Gaussian beam (MGB) approach to model beam steering in anisotropic media. MGBs have the advantages of being computationally inexpensive and remaining non-singular. This article provides a comparison of the beam propagation modeled by the developed ordinary Gaussian beam and linear phased Gaussian beam models through transversely isotropic austenitic steel for different steering angles. It is shown that the linear phased Gaussian beam model outperforms the ordinary one, especially at steering angles higher than 20° in anisotropic solids. The proposed model allows us to model the beam propagation from phased arrays in both isotropic and anisotropic media in a way that is computationally inexpensive. As a further step, the developed model has been validated against a finite element model (FEM) computed using COMSOL Multiphysics.
A high-throughput system to identify inhibitors of Candidatus Liberibacter asiaticus transcription regulators

Significance The insect-disseminated bacterium Candidatus Liberibacter asiaticus causes the destructive, incurable “citrus greening disease,” which is widespread in Asia, Africa, and the Americas, resulting in economic losses in the billions of dollars. One approach to treating infected citrus trees is application of antimicrobial compounds. However, use of broad-spectrum antibiotics in commercial citrus orchards has significant disadvantages, such as emergence of resistance and inhibition of beneficial bacteria. We designed a synthetic system for high-throughput screening of compound libraries in a closely related, culturable, and nonpathogenic bacterium, allowing us to identify small molecule inhibitors of Ca. L. asiaticus transcription activators. Citrus greening disease, also known as huanglongbing (HLB), is the most devastating disease of Citrus worldwide. This incurable disease is caused primarily by the bacterium Candidatus Liberibacter asiaticus and spread by feeding of the Asian Citrus Psyllid, Diaphorina citri. Ca. L. asiaticus cannot be cultured; its growth is restricted to citrus phloem and the psyllid insect. Management of infected trees includes use of broad-spectrum antibiotics, which have disadvantages. Recent work has sought to identify small molecules that inhibit Ca. L. asiaticus transcription regulators, based on a premise that at least some regulators control expression of genes necessary for virulence. We describe a synthetic, high-throughput screening system to identify compounds that inhibit activity of Ca. L. asiaticus transcription activators LdtR, RpoH, and VisNR. Our system uses the closely related model bacterium, Sinorhizobium meliloti, as a heterologous host for expression of a Ca. L. asiaticus transcription activator, the activity of which is detected through expression of an enhanced green fluorescent protein (EGFP) gene fused to a target promoter. We used this system to screen more than 120,000 compounds for compounds that inhibited regulator activity, but not growth. Our screen identified several dozen compounds that inhibit regulator activity in our assay. This work shows that, in addition to providing a means of characterizing Ca. L. asiaticus regulators, an S. meliloti host can be used for preliminary identification of candidate inhibitory molecules.